Simulating Climate Change and Livelihood Security: A Western Himalayan Experience, India (Advances in Geographical and Environmental Sciences) 9811646473, 9789811646478

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Advances in Geographical and Environmental Sciences

Swarnima Singh R. B. Singh

Simulating Climate Change and Livelihood Security A Western Himalayan Experience, India

Advances in Geographical and Environmental Sciences Series Editor R. B. Singh, University of Delhi, Delhi, India

Advances in Geographical and Environmental Sciences synthesizes series diagnostigation and prognostication of earth environment, incorporating challenging interactive areas within ecological envelope of geosphere, biosphere, hydrosphere, atmosphere and cryosphere. It deals with land use land cover change (LUCC), urbanization, energy flux, land-ocean fluxes, climate, food security, ecohydrology, biodiversity, natural hazards and disasters, human health and their mutual interaction and feedback mechanism in order to contribute towards sustainable future. The geosciences methods range from traditional field techniques and conventional data collection, use of remote sensing and geographical information system, computer aided technique to advance geostatistical and dynamic modeling. The series integrate past, present and future of geospheric attributes incorporating biophysical and human dimensions in spatio-temporal perspectives. The geosciences, encompassing land-ocean-atmosphere interaction is considered as a vital component in the context of environmental issues, especially in observation and prediction of air and water pollution, global warming and urban heat islands. It is important to communicate the advances in geosciences to increase resilience of society through capacity building for mitigating the impact of natural hazards and disasters. Sustainability of human society depends strongly on the earth environment, and thus the development of geosciences is critical for a better understanding of our living environment, and its sustainable development. Geoscience also has the responsibility to not confine itself to addressing current problems but it is also developing a framework to address future issues. In order to build a ‘Future Earth Model’ for understanding and predicting the functioning of the whole climatic system, collaboration of experts in the traditional earth disciplines as well as in ecology, information technology, instrumentation and complex system is essential, through initiatives from human geoscientists. Thus human geosceince is emerging as key policy science for contributing towards sustainability/survivality science together with future earth initiative. Advances in Geographical and Environmental Sciences series publishes books that contain novel approaches in tackling issues of human geoscience in its broadest sense — books in the series should focus on true progress in a particular area or region. The series includes monographs and edited volumes without any limitations in the page numbers.

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Swarnima Singh · R. B. Singh

Simulating Climate Change and Livelihood Security A Western Himalayan Experience, India

Swarnima Singh Department of Geography Deen Dayal Upadhyaya Gorakhpur University Gorakhpur, Uttar Pradesh, India

R. B. Singh Department of Geography University of Delhi New Delhi, Delhi, India

ISSN 2198-3542 ISSN 2198-3550 (electronic) Advances in Geographical and Environmental Sciences ISBN 978-981-16-4647-8 ISBN 978-981-16-4648-5 (eBook) https://doi.org/10.1007/978-981-16-4648-5 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

Preface

Change is the law of nature, and the fragile Himalaya is no exception to this, where changing climate and its feedback mechanisms have become inescapable because its unconceivable impacts are experienced almost in all realms of existence and will continue to affect in the future as well. These high altitudinal areas have been undergoing through the transitional phase not only in terms of natural changes but also in terms of socio-economic. The extent and frequency of extreme climate-related events are not new, and it has been happening since the origin of this planet and is on the continuous rise throughout. The continuous and persistent impact of climatic variability on the flora, fauna and crops is much evident; therefore, it could not be called a myth. Consequently, it has awakened even the non-believers through the amplified vulnerability and their outcomes on livelihoods and food security. Subsequently, it has become one of the chief concerns to monitor and analyze the changing climate and its impact with the help of several calibrations/simulation models and ground observations. In its Fourth Assessment Report (AR4), IPCC has provided irrefutable observations regarding an increase in surface air temperatures (SATs) and surface skin temperatures (SSTs) triggering an extensive yet slow and steady rise in temperature leading to a modification of human lives and livelihoods, especially in the agrarian economy. The thermally induced change in the length of growing period of plants and crops is gradually altering agro-ecological zones (AEZs), pushing incessant pressure on the marginal and small farming communities, where current trends in GHGs emissions and potential agricultural losses have induced alarm on livelihood sustainability. While knowledge on the effects of climate change on livelihood is increasing, there is still a dearth of micro-level studies that can provide a better understanding. This work is an attempt to analyze the impact of changing climate on livelihood security by creating a baseline scenario of temperature and rainfall records through the regional circulation model from both ground stations and satellite data to investigate existing and projected livelihood security in the Western Himalayan district of Himachal Pradesh, India. It is one of the largest districts of Himachal Pradesh, in terms of its population, agricultural production and the resource richness where climate change impact on this agrarian village’s livelihood is likely to be very alarming. No sector or society is untouched by the impact of climate change; therefore, this book is an attempt to present the inception of climatic variability v

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and livelihood security. It is a quite unique and inclusive study because substantial work has been piloted on regional climate change modeling and simulated results on livelihood security that has not been attempted before. The research work in the book has been penned down into eleven chapters; Chap. 1 presents the conceptual evolution of climate change, its relation to livelihood, the probable indicators to study livelihood security and an argument on of physical, socio-economic, ecological and equity interface approach to analyze livelihood security. Further, an overview of the changing climate in India is discussed. Chapter 2 conceptualizes the research problem, detailed literature review on the state of changing global climate, GHGs emissions, climate change modeling, sustainable livelihood, adaptation and mitigation strategies in climate impacted livelihoods. All related concepts to study have been significantly defined. Further, it deals with a brief description of the study area, research questions, objectives and a concise account of the methodology of each objective. Chapter 3 dispenses with a detailed description of the study area. It discusses the geographical location, physiography including elevation and slope, soil zones, water resources, kuhl irrigation, climatic conditions, status of forests and vegetation cover, sanctum sanctorum, brief description of land use, socio-economic and demographic characteristics, occupational structure, operational landholding size, infrastructure characteristics, social empowerment, work participation, etc. Chapter 4 discusses climate and climate change scenario modeling of Kangra district where the investigation thrusts upon the causes of climatic variability, climatic zonation of the study region to determine the baseline data required to create a methodology for baseline and simulated spatiotemporal precipitation and temperature trend for impact analysis. The regional climate has been scaled down for regional adaptive responses on the WRF model, where several databases including IMD, AIRS and TRMM have been used and interpolated. The gridded data have been overlaid on the ArcGIS map to generate climate change scenarios for 2020, 2050 and 2080 for temperature and precipitation, shaped by GHGs emissions preceded from Intergovernmental Panel on Climate Change-Special Emission Scenario (IPCC-SRES) Change Modeling Mechanism. Chapter 5 deals with the dynamics of livelihood capitals security, where all livelihood capital variabilities have been calibrated from Pearson’s product–moment correlation coefficient ®) multiple regression analysis, cellular automation analysis to analyze poverty gap ratio (PGR), head count indices, etc., to illustrate in the form of capital assets pentagon (spider diagram). Therefore, to study a micro-level livelihood, a new framework has been constructed for this particular study, wherein a micro-level sustainable livelihood security index (MSLSI) has been constructed over a period of several months regress analysis based on the Department for International Development’s (DFID) sustainable livelihoods framework (SLF) because it was realized that SLF does not enable accord among different supporting groups and it needs regional responses embedded within them. Therefore, the capital assets/endowments (human, social, natural, financial and physical capital) for livelihood security have been prepared for all 27 villages. Chapter 6 is an extension of the previous Chap. 5, where sustainable livelihood analysis (SLA) has been depicted through the SLF core. The SLF core is called the capital pentagon; here, it has been comprehended, assessed and

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applied in the study area. The differential pentagon diagrams have been prepared to analyze capital security gaps between 27 different villages in the district. The conventional approach to secure livelihood was not able to solve the problem because it disregarded several micro-level livelihood aspects to which assets were meticulously knotted. Therefore, this chapter surpasses this limitation. Chapter 7 provides reasoning on the computed methodology for climate dynamics and livelihood vulnerability indices assessment. It deals with the two separate methodologies to analyze livelihood security in the district, with and without climate change analysis where the observed climatic changes for almost 44 years (1970–2014) from Landsat, MODIS and IRS-P3 have been done to prepare composite livelihood vulnerability index (LVI) without climate change and CCLVI with climate change impact. To varify the results further 12 core climate indices; length of growing period (LGP), frost days, annual count when daily minimum temperature is . . . Climate change modeling mechanism GCMs downscaling to regional adaptive responses. Source By authors . . . . . . . . . . . . Locations of weather stations across Kangra District 2012. Source By authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Methodological framework for preparing spatio-temporal baseline and simulation maps. Source By authors . . . . . . . . . . . . Comparative status of average monthly decadal rainfall (cm), maximum and minimum temperature (°C) of Kangra district for 1970–1990 and 1990–2014. Source By authors computation based on gauge data . . . . . . . . . . . . . . . . . . . . . . . . . a Spatio-temporal change in January isotherm and b Change in the June isotherm for the years 1970 and 2014. Source By authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Fig. 4.6

Fig. 4.7

Fig. 4.8

Fig. 4.9

Fig. 4.10

Fig. 4.11

Fig. 4.12 Fig. 4.13

Fig. 4.14

Fig. 5.1

List of Figures

Mean seasonal temperature pattern in Kangra district over the period of 1970–2014 and T max and T min graph of mean monthly change in climatological records (percent) during 44 years. Source By authors based on Mann-Kendal and Sen slope geospatial analysis . . . . . . . . . . . The cleaning outlier data for geophysical flows data and parallel algorithm analysis in MATLAB for temperature and precipitation on longitudes in the study region. Source By authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Longitudinal distribution of mean annual seasonal temperature trend, a June, b July and c August months. Source Downscaled and computed from raw TRMM data from NASA by authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Simulated trend lines for differential decadal (a–c) and Annual (a –c ) variation during 1970, 2000, 2019, 2050 and 2080 for a Nurpur, b Bada Bhangal and c Kangra blocks. Source By authors, computation based on raw data processing, downscaling and simulation of IMD and AIRS. Note Bada Bhangal is having downward negative differential decadal and annual trend in thermal climate exhibit inconsistent signals of cooling in the high altitude north-eastern blocks, in the district as compared to other parts in the region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Spatial patterns of mean annual rainfall isohyets in Kangra, 1970–2014. Source Calculated from IMD and TRMM-NASA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . a Mean monthly rainfall pattern for two time period between 1970–1990 and 1990–2014. Source By authors based on TRMM and IMD raw data processing. b Decreasing annual rainfall trend Source By authors based on TRMM and IMD raw data processing through IDW and Kriging technique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Seasonal temperature and precipitation trends for RCP 4.5 and RCP 8.5. Source By authors . . . . . . . . . . . . . . . . . . . . . . . . . . Observed change scenario in rainfall pattern for the months of June (a), July (b), August (c) and September (d) respectively from 1970–2014. Source Downscaled and computed by the authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Simulated climate change in a,b and c (observed); a , b and c (RCP 4.5); a , b and c (for RCP 8.5) Scenario Rainfall pattern for the months of June, July, and August respectively for the year 2020, 2050 and 2080. Source Simulated by the authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Purpose of environmentally sustainable development. Source By authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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List of Figures

Fig. 5.2 Fig. 5.3

Fig. 5.4 Fig. 5.5

Fig. 5.6

Fig. 5.7

Fig. 5.8

Fig. 5.9

Fig. 5.10

Fig. 5.11

Fig. 6.1

Fig. 6.2

Sustainable livelihood indicators in the SLSI framework. Source By authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Flow diagram of the process of data collection, analysis and tabulation of results for understanding livelihoods framework. Source By authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . Schematic diagram showing composite livelihood indices through its data type and linkages . . . . . . . . . . . . . . . . . . . . . . . . . a–d Showing number of land holders (LHs) having irrigation facility (a), percent LHs for multiple cropping (b), percent LHs ready for crop diversification (c) together with percent LHs having farming (crop and livestock) diversification (d), in sampled villages. Source Primary survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Marginal, small and medium size land holders combined percent of Z scores in sampled villages. Source Based on primary data acquisition and their respective Z-score values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The Z score average value for marginal, small and medium-size landholders (LHs) in Kanals for SCI across sampled villages. Source Based on primary data acquisition and their respective Z-Score values for each . . . . . . . Social capital based on the share of agricultural products, case of crop disease incidences, help/support from relatives/friends, organizational membership, and organizational involvement. Source Primary survey . . . . . . . Village wise percent status of households share their view on whether they get help/support during crop diseases incidences. Source Primary survey . . . . . . . . . . . . . . . . . . . . . . . . Village wise percent status of households observation on help/support of family or friends, entire village or none other than individual help during crop diseases incidences. Source Primary survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Village wise status of livestock population in percent including small ruminants (Sheep and Goat), cow and other mammals. Source Primary survey . . . . . . . . . . . . . . . . . . . . . . . . . Livelihood assets pentagon. Source DFID (2005). Note NC—natural capital (land, water, etc.), HC—human capital, SC—social capital, FC—financial capital, PC—physical capital (all types of infrastructures) . . . . . . . . . . . . The livelihood pentagons summary of the combined five capital assets in Sidhpur, Gabli, Uparli Barol, Chogan, Aweri, Baijnath, Munla, Jhalot, and Ulharli of the Kangra district. Source Results based on primary survey and combined Z-scores . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Fig. 6.3

Fig. 6.4

Fig. 7.1

Fig. 7.2 Fig. 7.3

Fig. 7.4

Fig. 7.5 Fig. 7.6

Fig. 7.7

Fig. 7.8

Fig. 7.9 Fig. 7.10

Fig. 7.11

List of Figures

The livelihood pentagons summary of the combined five capital assets in Poling, Tarmehr, Bada Bahngal, Hara Rekhas, Samkar, Pong Dam, Ghan Ban, and Ghiyori of the Kangra district. Source Results based on primary survey and combined Z-scores . . . . . . . . . . . . . . . . . . . . . . . . . . . . Summary of livelihood pentagons depicting the combined five capital assets in Garh, Sansar Pur, Nangal Chowk, Gangath, Indora, Raja Khas, Sohara, Zamana Bad, and Abdulla Pur villages of the Kangra district. Source Results based on primary survey and combined Z-scores . . . . . . Methodological flow chart for LVI computation and indexing without climate change scenario. Source By authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Vulnerability radar diagram of HCVI for selected villages of Kangra. Source Primary survey, 2013–14 . . . . . . . . . . . . . . . . . Vulnerability radar diagram of NCVI, SCVI, and FCVI for selected villages of Kangra. Source Primary survey, 2012–14 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Spatial pattern of mean maximum and minimum temperature (1970–2014). Source Calculated from AIRS and IMD data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Average temperature pattern of 44 years (1970–2014). Source Calculated from AIRS and IMD data . . . . . . . . . . . . . . . . a Maximum and minimum temperature pattern of 44 years (1970–2014). Source By authors. b Current annual rainfall trend in Kangra from 2000 to 2014. Source By authors . . . . . . . . a Struggling between inaccessibility and firewood demand. b Inaccessibility is a biggest question here: four days trek to reach Bada Bhangal. c Remoteness and traditional livelihood options. d Creating alternative livelihood possibilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . a Effect of elevated CO2 on the growth yield of wheat crop. Source Simulated by authors. b Effect of elevated temperature on the growth yield of wheat crop. Source Simulated by authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Effect of precipitation on the temporary and permanent crop in Kangra. Source By authors . . . . . . . . . . . . . . . . . . . . . . . . Land use land cover change in Kangra district over the 20 years time period (1995–2015). Source By authors based on Landsat, MODIS, and IRS-P3 . . . . . . . . . . . . . . . . . . . . . . . . . . Block-wise proportional sub-divided pie diagram on livelihood vulnerability for Kangra district. Source Calculation based on primary survey . . . . . . . . . . . . . . . . . . . . . . .

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List of Figures

Fig. 7.12

Fig. 8.1

Fig. 8.2

Fig. 8.3

Fig. 8.4 Fig. 8.5

Fig. 8.6

Fig. 8.7

Fig. 8.8

Fig. 8.9

Fig. 8.10

Asset pentagon for livelihood groups in baseline (present) and under climate change scenario (the 2020s). Source By authors based on primary survey . . . . . . . . . . . . . . . . . . . . . . . . . . Methodological flow chart on changing climatic variability, changes in livelihood security, local coping, and adaptation strategies. Source By authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . a Sources of livelihood. Source By authors. b Reasons for crop diversification among landholders. Source By authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . a Livelihood sources among sampled HHs. Source By authors. b Problems of livelihood identified by HHs. Source By authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . General awareness regarding climate change. Source Primary survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . a Jhumpa explaining the decrease in snowfall duration in Puling village. b Army retired personal reporting shift in horticultural variety in Panchrukhi and surrounding blocks. c The elderly have been advocating a decrease in snowfall amount and duration during the last 30 years . . . . . . a Reported horticultural shift towards litchi, lingti (local vegetable), loquat, and mango across villages in Kangra. b Increasing case of deemak (termites) attack in Bada Bhangal . . . a Extinction in plant species varieties and respondent’s observation regarding foreign weed intrusion and extinction of existing medicinal species in Aweri village. b Early flowering in plant species. c Reduction in apple fruit sizes due to intensification in length of growing days in Tarmehr. d Adjustment with school holidays from May– June to July–August (monsoon months). e Alteration of growing crop seasons from May–June to July–August (shift in monsoon months), almost 40 days advanced . . . . . . . . . Nomadic Gujjars temporary residences near Pong Dam survive by selling buffalo milk in neighboring villages during summer month from May to July . . . . . . . . . . . . . . . . . . . . a Climate change impact on forest-based livelihood. Source Primary survey. b After and before snowfall in Cherna Village, beside the timber stocks, locals are devoid of any option . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . a Kripal Chand Kuhl for irrigation in Palampur. b Kuhl gravity channels are being used in producing small scale hydro-electricity in Tarmehr . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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Fig. 8.11

Fig. 8.12

Fig. 8.13 Fig. 8.14 Fig. 8.15

Fig. 8.16

Fig. 8.17 Fig. 8.18

Fig. 8.19

Fig. 9.1

Fig. 9.2

List of Figures

a Potato, vegetable shed-farming, and sustainable solar energy promotion technology in Badagram. Source Primary survey. b Kangra’s golden tea garden. c Government and cooperative initiative to revive the Kangra tea plantation with the help of CSK-HPAU, Palampur. Source The Tribune (2001) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . a Crop diversification for millets, maize, mushrooms, capsicum, garlic, and onion in Baijnath block. b Trout fish farming at Badagram and aquaculture at Pong Dam . . . . . . . . . . Livestock ranching and wool farming at Tarmehr and Puling village. Source Primary survey . . . . . . . . . . . . . . . . . . Automatic hydro-electric atta-chakki in Chota Bhangal. Source Primary survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Educational status and level of unemployment among male and female in the 9 sampled blocks. Source Primary survey, 2014 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Regular women workforce in small and medium scale industries (SMEs) and road construction under NREGA in Baijnath and Palampur block . . . . . . . . . . . . . . . . . . . . . . . . . . . Synergy between top-down and bottom-up for mitigation at the local level. Source By authors . . . . . . . . . . . . . . . . . . . . . . . a Mandatory UGC training in colleges across Kangra to promote self-employment. Source Navbharat Times. b Promotion of ‘Green Bonus’ and regional cooperation initiative in the region. Source The Indian Express (2009). c Miniature painting promotion scheme through Gandhi Kutir Yojna. Source The Tribune (2001) . . . . . . . . . . . . . . . . . . . . a Marginal, small, and medium-size workers in per cent across 27 villages. Source Primary survey. b Solutions to secure livelihood during crisis period. Source Primary survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Highlights of UN sustainable development goal 13 concerning India’s effort; climate action and goal 11: sustainable cities and communities. Source Adopted from United Nations Organization . . . . . . . . . . . . . . . . . . . . . . . . . Institutional arrangement for climate change adaptation policy planning and implementation in India . . . . . . . . . . . . . . . .

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List of Tables

Table 1.1 Table 3.1 Table 3.2 Table 3.3 Table 3.4 Table 3.5 Table 3.6 Table 3.7 Table 3.8 Table 3.9 Table 3.10 Table 3.11 Table 3.12 Table 3.13 Table 3.14 Table 3.15 Table 4.1 Table 4.2

Table 4.3

United Nations Conference of Parties (COPs) chronological order . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Season-wise average annual temperature in Kangra . . . . . . . . . Forest types in Kangra district by area, 2018–19 (ha) . . . . . . . . Comparative status of forest area and tree-covered area in the districts of Himachal Pradesh . . . . . . . . . . . . . . . . . . . . . . The principal tributaries of the Beas River . . . . . . . . . . . . . . . . . Comparative status of sources of irrigation in the state and district, 2016–17 (ha) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . The demographic structures of district Kangra vis-à-vis Himachal Pradesh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Comparative per capita income status for the year 1993– 94 to 2018–19 (at present values in |) . . . . . . . . . . . . . . . . . . . . . Comparative status of workers distribution in Kangra and H.P. (%) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Land utilization pattern (in km2 ) . . . . . . . . . . . . . . . . . . . . . . . . . The land utilization pattern changes from 1990 to 2016 (in %) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A comparative status of block wise land-use pattern (area in ha) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Land holdings variations over the year 1980–2016 (%) . . . . . . . Crop wise area in district (2010–11) . . . . . . . . . . . . . . . . . . . . . . Comparative status of infrastructures across blocks in Kangra in per cent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Number of panchayat officials, 2011 (Block wise) . . . . . . . . . . Season wise average annual temperature, Kangra 2010–14 . . . Comparative analysis of annual, winter and monsoon precipitation trend of Dharamsala (highest rainfall) and Kangra (district average) . . . . . . . . . . . . . . . . . . . . . . . . . . . . Seasonal Temperature (T˚C) and Precipitation (R in %) change in Kangra District using WRF model for the RCP 4.5 and Emission Scenario (RCP 8.5) . . . . . . . . . . . . . . . . . . . . .

6 48 49 52 52 55 62 64 65 66 67 69 71 73 74 78 89

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Table 5.1 Table 5.2 Table 5.3 Table 5.4 Table 5.5 Table 5.6 Table 5.7 Table 5.8 Table 5.9

Table 5.10

Table 5.11 Table 5.12 Table 5.13 Table 5.14

Table 5.15

Table 5.16 Table 5.17 Table 5.18

Table 5.19

Table 5.20

Table 5.21

List of Tables

A chronological development in sustainable livelihoods . . . . . . Understanding livelihood capitals, its indicator and resultants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sampled village across nine selected blocks falling in different AEZs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Natural capital parameters and its assigned score . . . . . . . . . . . Physical capital parameters and its assigned score . . . . . . . . . . . Assigned scores for social capital parameters . . . . . . . . . . . . . . Assigned scores for financial capital parameters . . . . . . . . . . . . Assigned scores for human capital parameters . . . . . . . . . . . . . . (a)Multiple regression analysis of income and population variables, (b) ANOVA analysis of income and population variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Population profile, total income, per capita income and per capita/day/person income in 27 sampled households across Kangra . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Educational profile in sampled villages under classified categories (in %) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Occupational details of the households in the sampled villages (in %) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Income stratification of the households in sampled villages . . . (a)Multiple regression analysis of physical capital parameters, (b) ANOVA analysis of physical capital parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Village wise natural capital scores (Z) parameters based on landholdings, crop production, combination and diversification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Village wise physical capital scores (Z) parameters based on combined household assets Z score . . . . . . . . . . . . . . . . . . . . Village wise human capital index based on respective combined Z-score values . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . (a) Multiple regression analysis of human capital on combined Z-score values, (b) The ANOVA analysis based on total population, literacy, number of migrants access to health based on landholding size . . . . . . . . . . . . . . . . . Village wise human capital calculation for marginal, small and medium-size LHs based on Z-score, standard deviation (SD) and combined Z-score . . . . . . . . . . . . . . . . . . . . . Village wise social capital calculation for marginal, small and medium-size LHs based on Z-score, standard deviation (SD) and combined Z-Score to show overall SCI . . . Village wise financial capital calculation for marginal, small and medium-size LHs selected parameters Z-score, standard deviation (SD) and combined Z-score for total FCI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

122 126 129 136 138 140 141 141

144

148 150 151 153

155

156 158 162

164

166

168

173

List of Tables

Table 6.1 Table 6.2 Table 6.3 Table 7.1 Table 7.2

Table 7.3

Table 7.4 Table 7.5 Table 7.6 Table 7.7 Table 7.8 Table 7.9 Table 8.1 Table 8.2 Table 8.3 Table 8.4 Table 8.5 Table 8.6 Table 8.7 Table 8.8 Table 8.9 Table 8.10 Table 8.11

xxxi

Village wise combined capital calculation for LSI index and ranking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Village wise combined livelihood capital multiple correlation matrix for LSI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Village wise capital correlation coefficient (r values) with livelihood outcome (total income) . . . . . . . . . . . . . . . . . . . Total and sampled households and family size in the selected villages of the Kangra district . . . . . . . . . . . . . . . Indexed minor variables, major component for livelihood vulnerability index without climate change scenario in the district . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . LVI results summary for all 62 sub-components, 13 components, and 5 livelihood capitals vulnerability in 27 sampled villages of Kangra district . . . . . . . . . . . . . . . . . . . . . . . Livelihood vulnerability index ranking for sampled villages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . List of 12 core climate indices and the rate of change over 1970–2014 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Production of cereals, pulses, oilseeds, and vegetables in (‘000 MT) in Kangra . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Area, production, growth per decade (1991–2015) of cereals crops in Kangra . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Growth of primary sector during 1991–2015 in Kangra . . . . . . Land use land cover change matrix in Kangra district over the 15 years time period (1995–2010) (area in Km2 ) . . . . Occupational profile of the sampled households (HHs) . . . . . . . Area under horticulture production from 1980–81 to 2010–11 in the district . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Land uses, productivity, cropping pattern, cultivation, horticultural, and aquaculture in 9 sampled block . . . . . . . . . . . Response regarding the change in climatic condition (in per cent) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Changes in forests category based on various crown cover classes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Major, medium, and minor irrigation projects in Kangra district (2000–2015) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Area under tea production in selected blocks of Kangra district . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Trend in aquaculture production in Kangra from 2004 to 2011 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Sericulture development and number of benefitted households in Kangra district (2005–15) . . . . . . . . . . . . . . . . . . Infrastructures, irrigation, and flood protection schemes . . . . . . Schemes for providing agricultural assistance . . . . . . . . . . . . . .

180 183 184 202

203

210 214 217 220 221 221 224 235 236 242 244 248 251 254 255 257 265 265

xxxii

Table 8.12

Table 9.1 Table 9.2 Table 9.3

Table 9.4 Table 9.5 Table 9.6 Table B.1 Table B.2

List of Tables

Schemes for productivity enhancement, non-farm initiative in micro and small enterprises, and support to the weaker section . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Summary of climate change projections for India by 2030s . . . India’s greenhouse gas emissions in comparison to other significant emitters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Fundamental developments in climate change measure across scientific, political, and environmental purviews; 1950–2020s . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . National Action Plan on Climate Change missions . . . . . . . . . . National Action Plan on Climate Change sub-initiatives . . . . . . National sectoral strategies and policies showing climate change action their plans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Livelihood security capital calculations . . . . . . . . . . . . . . . . . . . Indexed sub components, major components for natural disasters, climate variability, and overall LVI for 27 sampled villages in Kangra district . . . . . . . . . . . . . . . . . . . . . . .

267 276 277

281 287 288 291 308

310

Chapter 1

Climate Change and Livelihood Security: An Integration of Trans-disciplinary Study

The danger posed by war to all of humanity and to our planet is at least matched by the climate crisis and global warming. I believe that the world has reached a critical stage in its efforts to exercise responsible environmental stewardship. —UN Secretary-General Ban Ki-moon

Abstract Climate plays an instrumental role in the lives and livelihoods of the people. It is a driver imperative for the survival and growth of the ecosystem. Its effect ranges from macro to micro level in the biosphere with variable manifestations. The vital air, foods, fruits, sartorial, shelters, energy, and livelihood together with every basic component of lives are shaped by the average temperature and rainfall conditions. Even small perturbations in the climatic elements can transform the entire global and local environmental system. This chapter encapsulates the science and philosophy of climate change and livelihood security to comprehend the related biophysical and anthropogenic processes. It presents the conceptual evolution of climate change, its relation to livelihood, the probable indicators to study livelihood security, a variegated argument on diverse approaches; physical, socio-economic, ecological, and equity interface, to analyze livelihood security. Keywords Anthropogenic climate change · Livelihood · Chronological climate concept · Ecology-economics and equity interface

1.1 Introduction The existence of mankind on the blue planet is facing a serious threat in the form of global climate change. No group, society, or sector in a country is untouched by this problem, though the income level modifies the levels of vulnerability. The poor and tribal populations who are directly and completely dependent on their immediate environment and natural resources are the most vulnerable groups. The vulnerability to climate in a fragile ecosystem is putting incessant pressure on the ecosystem services and disturbing ecological balance. In this persistent situation, the scientific community is in a state of debate over the issue of rate of changing climate over time © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 S. Singh and R. B. Singh, Simulating Climate Change and Livelihood Security, Advances in Geographical and Environmental Sciences, https://doi.org/10.1007/978-981-16-4648-5_1

1

2

1 Climate Change and Livelihood Security: An Integration …

however, all have agreed that it is changing. The planners and politicians together are trying to formulate mitigation strategies but have still to decide who should initiate first. And the common man is in a dilemma about his fate. Whatever be the nature of climate change in a region, the outcome would be the permanent displacement of normal human activity and livelihoods. Regardless of many endeavors to decrease the anthropogenic causes, human-induced changes are persistent in the natural system and are expected to remain this way for the upcoming decades. The economic growth and increasing population are expected to intensify the pressure on the concerned natural resources of an area (IPCC 2001a; IPCC 2001b; IPCC 2001c; FAO 2020). The natural resource systems have already been influenced by prolonged global change. The augmented pressure on resources will substantially disturb the natural system of its goods and services (MEA 2005). Consequently, only the mitigation steps to minimize climate-related issues are not sufficient to solve the problems, an urgent need is arising to improve the adaptive capacity of the people to reinforce it. Therefore, the most important requirement has focused the research on the sectoral and micro-regional vulnerability so that the natural adaptive capacity and the sensitivity of an ecosystem can be assessed. Whenever there is a talk regarding climate change and livelihood security, the developing countries are placed on the forefront because of high reliance on the primary sector. On the scale of vulnerability, India being a developing country attains a high score. Its steadily-growing population is highly dependent on its climate-sensitive agriculture and forestry sectors (Patra 2016). Expeditiously depleting natural resources and fragile environment including exhaustive, nonrenewable resources, improper infrastructure, malnourished underweight children, large unskilled marginal class labor, and population are few important factors that have put India into one of the most vulnerable categories. The fragile but rich in natural resources, hill regions are highly susceptible to the loss by even slight changes in the climate. The unsustainable exercises further intensify the problem. The traditional practices and indigenous knowledge suffice the most important solution to this problem through a sustainable approach together by building adaptive capacity in administering and coping with the related insecurities of climate in the hill region.

1.2 Conceptual Evolution in Climate Change Studies Climate change has been extensively studied and can be defined as the earth’s evolutionary nature of weather patterns over the long term. The earlier assumption among the Greeks and Roman schools of thought were narrowed on the changing climate has been the anthropogenic response since antiquity. Hippocrates (c. 460– 370 BC), was a venerable, environmentalist with a deterministic inclination stated how different climates (local or regional) affects cultures (Coen 2018). In the late 19th and early twentieth centuries, Friedrich Ratzel, a German geographer followed by his disciple Ellen Churchill Semple worked on ‘Influences of Geographic Environment.’ Whereas Ellsworth Huntington’s heyday claimed through his writings on

1.2 Conceptual Evolution in Climate Change Studies

3

the ‘Civilization and Climate’ in 1915 continued in dominant shape up until World War II. Griffith Taylor and other geographers of the early twentieth century shaped the concept of human ‘progress or decline’ based on his regional climate (Carleton, 1999; Coen, 2018; Sörlin and Lane, 2018).

1.2.1 Linear Chronology of Climate Concept Human activities are largely responsible for introducing changes in the climate. Anthropogenic activities such as destroying trees, cultivating fields, irrigating desert areas, etc. have been implicated for alterations of temperature and precipitation in a region. It was only realized after an experiment by a French physicist Joseph Fourier in the year 1824. He was the first one to quantify carbon dioxide (CO2 ) and other gases, their occurrence in the earth’s atmosphere and suggested that it may cause the ‘greenhouse effect.’ It was pointed out that the composition of the atmosphere has been changing since the Ice Age. But the greenhouse analogy was trapped for almost forty years and been accused of an oversimplification of reality. It was in 1861 when an Irish scientist and mountaineer John Tyndall has started investigating the function of atmospheric gases including methane and other volatile hydrocarbons were most likely to play a role in absorbing sunlight. Tyndall’s laboratory tests exhibited that these gases significantly absorb electromagnetic wavelengths of the insolation. The greenhouse gas CO2 can alone absorb insolation like a sponge. Later, Tyndall collaborated with the Swedish chemist, Svante Arrhenius in 1896 who had shown that decreasing 50 per cent of CO2 in the atmosphere can lower the temperature by 4 °C to 5 °C and if CO2 levels were doubled the global temperatures would increase by the same amount. This experiment was supported by Arvid Högbom and his colleagues, who also observed CO2 emission from factories besides volcanoes and other natural carbon sinks sources such as forests and oceans. It was realized that anthropogenic activities are an added cause of global warming. They together developed the science of uncertainty in climate studies. During the 1930s, a keen meteorologist, Guy Stewart Callendar who was a British engineer by profession used weather station documentation across Europe. He validated that the temperature had increased over the erstwhile century with an increased concentration of CO2 and established the fundamental principle of changing climate. The International Geophysical Year (IGY) 1957 was a turning point when an anthropological researcher at Chicago University was investigating the role of radioactive carbon14 to find the age of ancient Egyptian mummies. It influenced a chemist Hans Suess and Navy oceanographer Roger Revelle. They were the first who applied carbon14 into studying carbon in trees and oceans and calibrated that the oceans absorb much less CO2 than predicted previously. A geochemist Charles D. Keeling led the most famous project of his time at Scripps Institution of Oceanography, Mauna Loa Observatory, Hawaii in 1958 during the IGY. His project on measuring the concentration of CO2 in the atmosphere supplemented with empirical research studying air bubbles trapped deep in Antarctic and

4

1 Climate Change and Livelihood Security: An Integration …

Greenland ice caps. The discovered ice core data from the field was plotted in the graph through advanced computer modeling famously known as the ‘Keeling Curve’. The ascending trajectory of this curve was seen as tooth-shaped, showed a stable rise in CO2 levels, accompanied by jagged up and down levels that are created by repetitive wintering and greening of the Northern Hemisphere. This supported the findings of Tyndall, Arrhenius, and Callendar that a 50 per cent increase in CO2 could produce warming of 2ºC. During the 1970s the post-war boom faced a different kind of climate concern due to an increase in aerosol pollutants, causing global cooling. Therefore, in the year 1965, the Environmental Pollution Panel of the United States President’s Scientific Advisory Committee presided by Roger Revelle and held by Charles Keeling, recommended fossil fuel is increasing CO2 level and act as ‘the invisible pollutant’. Throughout the 1960s and 1970s, scientific research and policy interventions have moved the world towards the popular green movement. The year 1972 has seen the first United Nations Environment Program (UNEP) conference that acknowledged the pivotal role of climate in the world in terms of food production. Indian Prime Minister Mrs. Indira Gandhi was the only head of state to attend the Stockholm United Nations Conference on the Human Environment in 1972. She drew attention by establishing the link between poverty and environmental degradation. Some efforts were made to address environmental issues in 1972 - the Ministry of Environment was set up in India. The UN World Water Conference in Mar Del Plata, Argentina, 1976; the UN Desertification conference and the UN Economic and Social Council (ECOSOC) Resolution recommended the WMO initiation of the World Climate Program (WCP) drew attention to the global climate change condition. In February 1979 the first major international meetings on climate were held in Geneva under the umbrella of the World Climate Program (WCP). This has led to a clear identification of climate-related issues. The integrated impact studies and research on climate variability, climate change have directed the establishment of the World Climate Research Program (WCRP) and the International Council of Scientific Unions (ICSU). It has further put the foundation of the Intergovernmental Panel on Climate Change (IPCC) by WMO and UNEP in 1988, to explore evidence on climate-related change and its anthropogenic causes (Singh 2010; Singh and Singh 2014). A significant number of intergovernmental conferences were held aiming at increasing scientific evidence related to climate change have raised international concerns about the issue, challenges, and adaptation strategies in addressing both the scientific and policy issues for global action during the late 1980s early 1990s, and 2000s. The key events were; the Villach Conference in October 1985, the Toronto Conference in June 1988, the Ottawa Conference in February 1989, the Tata Conference in February 1989, the Hague Conference and Declaration in March 1989, the Noordwijk Ministerial Conference in November 1989, and the Cairo Compact in December 1989, the Bergen Conference in May 1990 and the Second World Climate Conference in November 1990, etc. In 1992, the Rio Earth Summit has taken place and the United Nations Framework Convention on Climate Change (UNFCCC) was established. It was officially a treaty but it did not comprise anything legally compulsory rather than delivering specific international treaties framework for negotiation having annual meetings since 1995 under Conferences of the Parties (COPs). COP3

1.2 Conceptual Evolution in Climate Change Studies

5

held at Kyoto, Japan in 1997, famously known as the Kyoto Protocol, is possible of greatest significance and was signed by the US President, Bill Clinton (Table 1.1). This protocol aimed to nail the initial framework with compulsory Green House Gases (GHGs) reduction targets in 41 countries plus the European Union to 5.2 per cent below 1990 levels during the target period of 2008 to 2012. While the Other COPs meeting like COP15 in 2009 at Copenhagen was also held with elevated hopes but largely considered a disappointment (Table 1.1). It was only during the 9th fiveyear plan (1997–2002), India started ensuring environmental sustainability in the development process through social mobilization, and participation of people at all levels came as key a priority.

1.2.2 Facilitative Footprints The IPCC probably can be best understood as a machine of scientific advice to government’s published assessments and special reports. There has been five assessment reports in total as the First Assessment Report (FAR) in 1990, the Second Assessment Report (SAR) in 1995, the Third Assessment Report (TAR) in 2001, the Fourth Assessment Report (AR4) in 2007, and the Fifth Assessment Report (AR5) in 2014, besides several recent special reports like; Special Report on climate change and land (SRCCL) in August 2019 and Special Report on the Ocean and Cryosphere in a Changing Climate (SROCC) in September 2019. Since the TAR, IPCC has been split into three Working Groups (WG). The WG I for the physical science basis, WG II for impacts, adaptation, and vulnerability, and WG III for mitigation (WMO 2010; IPCC 2001a; IPCC 2001; IPCC 2002; IPCC 2013). After TAR of IPCC in March 2001, the United States President Mr. George W. Bush announced that the USA would not implement the Kyoto Protocol. Six years later, in 2006, former Vice President and presidential candidate, Al Gore won the 2007 Nobel Peace Prize for his debut film ‘An Inconvenient Truth’ on global warming. This has inspired the National Action Plan on Climate Change (NAPCC) in India that was launched with 8 identified missions to address climate change mitigation, adaptation, and knowledge management in 2008. Later in COP 21 (2015) through Nationally Determined Contributions (NDCs) the United States President Barack Obama signed onto the Paris Climate Agreement with 189 countries including India that had unconditionally placed Paris Agreement GHGs commitment for 2030 except Iran and Turkey. Among those expressing skepticism over global warming has included the USA president Mr. Donald Trump. In 2017 Donald Trump came into power and declared to withdraw from the Paris treaty, although independent analyzes by NASA and the National Oceanic and Atmospheric Administration (NOAA) discovered that the surface temperature in 2017 was the warmest since modern recordkeeping began in 1880 that can create the direst and irreversible consequences on the earth. The recent climate strikes in August 2018 by a Swedish teenager and climate activist Greta Thunberg began through a ‘school strike for climate’ protested to raise awareness for global warming caught the world by storm where more than 17,000

6 Table 1.1 United Nations Conference of Parties (COPs) chronological order

1 Climate Change and Livelihood Security: An Integration … Item

Held in year

Held at

COP 1

1995

Berlin

COP 2

1996

Geneva, Switzerland

COP 3

1997

Kyoto, Japan

COP 4

1998

Buenos Aires, Argentina

COP 5

1999

Bonn, Germany

COP 6

2000

The Hague, Netherlands

COP 6

2001

Bonn, Germany

COP 7

2001

Marrakech, Morocco

COP 8

2002

New Delhi, India

COP 9

2003

Milan, Italy

COP 10

2004

Buenos Aires, Argentina

COP 11/CMP 1

2005

Montreal, Canada

COP 12/CMP 2

2006

Nairobi, Kenya

COP 13/CMP 3

2007

Bali, Indonesia

COP 14/CMP 4

2008

Pozna´n, Poland

COP 15/CMP 5

2009

Copenhagen, Denmark

COP 16/CMP 6

2010

Cancún, Mexico

COP 17/CMP 7

2011

Durban, South Africa

COP 18/CMP 8

2012

Doha, Qatar

COP 19/CMP 9

2013

Warsaw, Poland

COP 20/CMP 10

2014

Lima, Peru

COP 21/CMP 11

2015

Paris, France

COP 22/CMP 12/CMA 1

2016

Marrakech, Morocco

COP 23/CMP 13/CMA 1–2

2017

Bonn, Germany

COP 24/CMP 14/CMA 1–3

2018

Katowice, Poland

COP 25/CMP 15/CMA 2

2019

Madrid, Spain

COP 26/CMP 16/CMA 3

2020 (Postponed)

Glasgow, UK

Source UNFCCC 2020

1.2 Conceptual Evolution in Climate Change Studies

7

students in 24 countries participated in these climate strikes. In March 2019 she was nominated for the Nobel Peace Prize. She attended UN submits by taking a boat across the Atlantic instead of flying to reduce her carbon footprints with a message to achieve net-zero emissions by 2050. Whereas, the earlier ideological approach of the Government of India (GOI) has changed into pragmatic policy reform by adapting ‘green technology’, growing environmental awareness, and responsibility to mitigate climate change at the local to the global level. A significant awareness of the GOI has been reflected by changing the name of the Ministry of Environment and Forests to the Ministry of Environment, Forests and Climate Change (Saryal 2018).

1.3 Statement and Significance of the Problem Climate change signifies a change in the climatic parameters as; average precipitation, temperature, wind intensity, and velocity, etc. for over thirty years or more. Generally, global warming is used synonymously with the term climate change although both have a distinct meaning. On one side global warming is having a hybrid origin both from human-induced emissions of Green House Gases (GHGs) and variations in solar irradiance. On the other hand, climate changes insinuate average change in its variable’s properties over a prolonged period, normally a decade or so. The changing state of the climate is identified by its persistent variability. The external and internal forcing of climate shapes the local and regional climate. The dynamic external forces include; variations in solar radiance intensity, deviation in the orbit of the earth, and the GHGs concentration level both through natural and anthropogenic processes (Singh and Singh 2014; Teske 2019). It can be said that the role of the human is very important in changing the earth’s climate. During the past, change in climate was induced by periodical solar cycle changes, tectonic movement in the lithospheric plates of the earth, and other natural cycles. But in recent times, the changes in climate are more anthropogenic in nature. Likewise, the far higher pace in the changing rate of climate has been recorded as compared to the past, which can be attributed to human activities including fossil fuel burning, industrial emissions, rice cultivation, and others. The accelerated rate of these processes of change is responsible for variability in climate. The ability to foresee the impending circumstances of climate concerning the contemporary state is also accountable to generate anxiety about its variability. Nevertheless, the ability to foresee through the identification of the most vulnerable regions, sectors, economies, and communities has led to design and establish improved strategies against the threats. The increasing carbon dioxide (CO2 ) emissions from deforestation, land-use changes, and burning of fossil fuels, followed by aerosols and cement manufacturing (inducing suspended particulate matter in the atmosphere) are the principal anthropogenic factor. The ozone depletion, livestock ranching, and agriculture are the secondary factors of concern in the context of changing climate. The reconstructed past climate has become the basis to identify the factors that affect climate change. Furthermore, the evidence for the changing climate is through indirect sources like; vegetation dynamics, changing ice cores, glacial

8

1 Climate Change and Livelihood Security: An Integration …

geology, sea-level change, and dendrochronology, etc. The developing countries in the tropics are more susceptible than the temperate countries to these changes in climate due to large dependence on their local ecosystem. The gravest impact of changing climate is projected on the production of food. Moreover, highly populated India is monsoon dependent country and if the monsoon weakens it will lead to food and livelihood insecurity to the large parts of its population which would be beyond the coping mechanism. The average global Surface Temperature (ST) has increased by about 0.6 ± 0.2˚ C (IPCC 2001). It has been established by the World Meteorological Organization (WMO, 2010) that the decade of 1998 - 2007 was the warmest decade on record. The global mean ST is computed for the year 2007–08 and it was found that it has increased up to 0.41˚C / 0.74˚F and reached at 14.41˚C above the 14˚C of the decadal annual average of 1961–1990. It is also affirmed by them that a record low Arctic sea ice extent was first observed during the same period led to the gateway of the Canadian Northwest Passage chronicled in 2007. India, being a developing country and the majority of its people living below the poverty line, where the state of the economy, environment, and society comes under record vulnerable groups. The unity in diversity in its climatic condition makes it susceptible to different types of climatic hazards including flood, cyclone, drought, landslide, avalanche, etc. Besides these, the Indian monsoon variability and the majority of its population dependency on the agriculture sector also augment the vulnerability component in livelihood security. Even a slight increase in temperature might cause a huge fall in the production of crops and finally, make the society vulnerable in terms of food security. Hingane et al. (1985) have worked on 100 years of observations regarding the mean annual surface air temperature (MASATs) over India and have explained how it is enhanced by 0.4˚ C in the last century. Successively, it has been revealed through several studies that the warming trend is dominating India. It has been reported to increase at around 0.56˚ C per century. The intensified warming and the changing rainfall pattern over the Indian region are expected to unfavorably affect the population, socio-economic infrastructure, and the natural ecosystems (Kumar et al. 1994). This might also proceed to a high likelihood of loss of fertility of the soil and a decline in the productivity of agriculture in the hill region. The impacts of climate extremes until now have dropped most seriously on the poor and fragile hill region and population (IPCC 2002, 2013). By contemplating on a range of equilibrium simulated models for the changing climate scenarios project a temperature rise of 2.5˚ C to 4.9˚ C for India. It was estimated by Kumar et al. (1994) as well as Parikh and Parikh (2002) that without considering the CO2 fertilization effects that per hectare yield losses for rice and wheat will vary between 32 to 40 per cent, and 41 to 52 per cent respectively in a usual scenario for 2020. The Gross Domestic Product (GDP) would plunge by 1.6 to 3.2 per cent in just one year, with several indications on the farm level impacts of climate change by using an alternative methodology on adaptations in the Indian agricultural system, it would stay significant. It has also been estimated by them that with an additional increase of + 1.86˚C in temperature and more than + 6.96 per cent increase in precipitation changes the total net revenue from the farming sector

1.3 Statement and Significance of the Problem

9

would fall by 8 to 9 per cent in business as usual situation, although with a projected increase in temperature of around + 3.15˚C and precipitation change of approximately + 14 per cent, the farm level net revenue would drop around 26 per cent (Kumar 2009; Parikh and Parikh 2002; Singh and Jha 2014). The projected impact on the hill region shows extreme behavior and variability in the climatic pattern, with a few exceptions, it is becoming significantly hot and much wetter. Increasing temperature is foremost intimidation to the organism which exists in areas especially those who are at almost near heat tolerance limits. Simultaneously, the impact on hydrology, water balance, and vegetation is also projected to be critical to them. The optimal cultivation time generally recognized as the Length of Growing Periods (LGPs) is also being altered by the significant changes in the rainfall patterns and temperature regimes by influencing the native hydrological and plant physiological cycle for particular crops. Worldwide the vegetation-land with sound LGP level will decrease by 50–55 million hectares by 2020 if the variability of climate persists in the same manner (IPCC 2013). A suitable LGP is desired to ensure maturity to the crops. Few varieties of crops gain immediate maturity and are available readily for use in a briefer period, while others including cereal crops require long LGP to attain maturity. Therefore, it can be said that those Agro Climatic Zones (ACZs) which are having long LGPs are capable enough to grow wide crops variety throughout leads to greater food production vis-à-vis. Although changing climate is increasing the LGPs variability over the globe where some regions are experiencing shortening and some lengthening as predicted by the General Circulation Model (GCMs) (Vanuytrecht et al. 2016), has been discussed in succeeding chapters for the regional level and study area. The prediction regarding LGPs, GHGs, temperature, and precipitation variability can be made at a large scale through GCMs to assess livelihood for an agrarian economy of India. Being a large developing country where, virtually 702 million rural population are directly dependent on climate susceptible sectors like; agriculture, forestry, and fisheries for the sustenance and livelihoods. The key requirement is to understand the meaning of livelihood first and then it would be easy to relate it with climate change impacts. Various scientific evidence (Eakin and BojórquezTapia 2008; Hahn et al. 2009; Singh et al. 2014; WCED 2018; Duku et al. 2018) have given one of the extensively established definitions of livelihoods; a livelihood comprises the capabilities, assets (including both material and social resources), and activities required for a means of living. A livelihood is sustainable when it can cope with and recover from stresses and shocks to maintain or enhance its capabilities and assets both now and in the future, while not undermining the natural resource base. The central or pivotal point of this definition is determining the vulnerabilities of households in calculating the resilience of livelihood assets. This study has been done to develop the ideas of the dynamics vulnerabilities of livelihoods based on climate change, where five essential asset approach outlines of livelihood have been identified as: 1.

Natural capital: It is famously known as the natural resource reserves on which livelihood flows are dependent.

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2.

Social-political capital: This could be defined as a group of social relationships that represent the pursuit of the concerned livelihood. Human capital: It is basically dependent on human skills, knowledge, ability, and good health of labor. Human capital is an important tool to investigate the degree of relationship a household has with its surrounding environment and people. The individual household is being judged under evaluation of this approach through both their productivity and ability to work in society. Physical capital: It is defined by the basic infrastructure. The transport, buildings, communications, water management, energy, tools, machinery, etc. come under this capital that empowers people to pursue varied livelihoods. Financial capital: This resource or asset is available to the household in the form of social security, payments, insurance, savings, supplies of credit, regular remittances and pensions, etc. to secure livelihood.

3.

4.

5.

1.4 Measuring Livelihood Security: A Development Indicator The livelihood paradigms, welfare goals, resource, and technological conditions are prevalent at a given point in time explained by and large the emergence and relevance of any particular set of welfare indicators (Swaminathan 1991). In the post-war years, when economic growth was considered the panacea for all economic and social ills, human welfare was measured mainly in economic terms as indicated by the Gross Domestic Product (GDP). But when economic growth failed to advance social development, the focus shifted to social and human development together with wellbeing indicators. But now an ever-increasing population, increasing consumerism, and over-exploitation of natural resources has resulted in resource and population imbalance, which is leading to ecological imbalances. Hence, today, the Sustainable Development (SD) has extended its horizon to encompass ecological, economic, and equity concerns by necessitating entirely a new set of welfare indicators from transcending disciplinary boundaries. Here, the evaluation is specified based on a set of indicators, enlisted to examine the suitability to develop Micro Level Sustainable Livelihood Security Indices (MSLSI). The list is not exhaustive but illustrative and suggestive to develop MSLSI therefore, various indicators like economic, social, physical, ecological ecology, and equity interface have been taken together one by one to give a comprehensive justification for the selection of few particular indicators to the study of MSLSI in the western Himalayan case study.

1.4.1 Economic and Social Indicators GDP is often described as the most important measure of economic development. It measures the net value added in the primary, secondary, and tertiary sectors at factor

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cost plus the consumption of fixed capital and net indirect taxes. Since GDP does not refer to or take into account, the quality of human life and the status of environmental assets, it is increasingly being discarded as a measure of welfare and livelihood. The disenchantment with GDP related measures has led to the emergence of ‘poverty indices’, based on the income level corresponding to the cost of a ‘commodity basket’ considered essential for maintaining a reasonable standard of living, along similar lines, Larson and Wilford (1979) have proposed the Physical Quality of Life Index (PQLI) as a measure of the physical wellbeing of people. Although PQLI captures the social and equity dimensions ignored by the GDP indicator it fails to account for both the economic and ecological dimensions. Therefore, the Human Development Index (HDI) been developed by UNDP. It has been similar in spirit and methodology to PQLI. Since 1990, HDI has been registered every year as a part of the UNDP, Human Development Report (HDR). It comprises of three equally weighted sub-indices, that are aggregated by the arithmetic mean of Life Expectancy Index, Education Index (decomposed into an adult literacy index and a Gross Enrolment Ratio Index), and a Gross National Product (GNP) Index (Desai 1991). The two composite indices (PQLI and HDI) reach a common conclusion, that is, economic growth is necessary but does not provide a sufficient condition for human and social development. They also share a common drawback; that is ignoring the ever crucial environmental concerns. Therefore, just economic and social indicators could not be taken to develop MSLSI.

1.4.2 Physical and Ecological Indicators The physical concept of Net Primary Productivity (NPP) is often considered the ecological counterpart of the economic measure of GDP. Gross Primary Productivity (GPP) is the total amount of energy assimilated by the primary producers per unit of time; NPP equals GPP minus respiratory loss. Ecological Footprint (EF) provides a quantitative assessment of the biologically productive area. It is required to produce the necessary resources (food, energy, and materials) and to absorb the wastes produced by a given population (Wackernagel and Rees 1997). EF is based on the quantitative land water requirements for sustaining a living standard into infinity, thereby assuming certain efficiency and improvements (Bohringer and Patrick 2007). The EF report reveals that human beings are using natural resources beyond the carrying capacity; they are almost consuming 20 per cent more natural resources annually that can be regenerated. And this amount is growing every year (Singh et al., 2016; Singh and Singh 2014). EF measures only the size and not the location of the footprint, and hence is not the right measure for assessing the natural resource sustainability and livelihood security of a country or a state or block. The Environmental Sustainability Index (ESI) is a composite index targeting environmental, socio-economic, and institutional indicators as a means of assessing sustainability. The core components of ESI are: environmental systems, reducing stresses, reducing human vulnerability, social and institutional capacity, and global stewardship (World

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Economic Forum 2002). The ESI score has been able to preserve valuable environmental resources effectively over a period of several decades. The ESI integrates 20 indicators where each of which combines two to eight variables, for a total of 68 underlying datasets. ESI is highly data intensive. The Living Planet Index (LPI), a global biodiversity indicator, was developed by WWF (1998). It measures trends in a sample of more than 2,000 specimens drawn from more than 1,100 species of vertebrates in terrestrial, freshwater, and seawater ecosystems. The Environmental Vulnerability Index (EVI) consists of 30 indicators of hazards, eight indicators of resistance, and 10 indicators of damage measurement. The EVI is also high data intensive. Maximum Sustainable Yield (MSY) ensures physical optimality by maintaining a constant and optimally renewable stock (Daly 1990 and 1992). The Food and Agriculture Organization (FAO) has evaluated the carrying capacity of 117 countries in terms of their maximum food-producing capabilities (FAO 2020). Under the Concept of Carrying Capacity (CCC), the maximum population (of humans and other life forms) that can be supported by the resource base has been measured. In the Pressure State Response (PSR) model, developed by the Organization of Economic Cooperation and Development (OECD), pressure and the state are focused mainly on the physical and ecological aspects, while the response indicators were related to policy responses to various stress state conditions (OECD, 1991). In addition to their contextual nature, the most severe limitation common to most of the physical and/or ecological indicators is that they are essentially deep ecology-based and hence do not take into account economic and equity concerns (Fig. 1.1).

1.4.3 Indicators Focused on the Ecology–Equity Interface IPOC (2001) has developed the Relative Measure of Sustainability (RMS), which explicitly considers the issue of inter-generational trade-offs, a kind of bargaining between the present and future generations, which is implicit in the Bruntland Report. Toman and Crosson (1991) have proposed the concept of the Safe Minimum Standard (SMS) for inter-generational resource management and conservation. SMS identifies the boundary where market-based approaches should end and where moral and ethical imperatives should begin for guiding resource management decisions. SMS is not an indicator but only an approach to an indicator. Its concern with equity is only partial, as its focus on inter-generational equity is only at the cost of intra-generational equity. The Wellbeing Index (WI) is a composite index for evaluating human and ecosystem wellbeing. WI is based on the belief that assessing the combination of these two elements offers insight into how close a country is to become sustainable? WI is an equally weighted average of the Human Wellbeing Index (HWI) and the Ecosystem Wellbeing Index (EWI). Both consist of five dimensions; the former comprises health and population, household and national wealth, knowledge and culture, community, and equity; the latter consists of land, water, air, species,

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13

Livelihood Capital Assets Livelihood outcome

Human

Natural

Transforming polices and institutions

Social

Financial

Physical

Climate change impacts and vulnerability

Livelihood vulnerability

Livelihood strategies

Ecology

Livelihood interface

CBA EIA NRA EDP

NPP EF EStI LPI EPI EVI CCC MSY PSR

SLSI CDI SNBI

RMS SMS WI

PQLI GDP

HDI

Equity Economy DOMESTIC

LANDSCAPE

GDP PQLI HDI NPP EF EStI LPI EPI EVI MSY CCC PSR RMS SMS WI CBA NRA EDP EIA CDI ISEW SNBI SLSI

Gross Domestic Product Physical Quality of Life Index Human Development Index Net Primary Productivity Ecological Footprint Environmental Sustainability Index Living Planet Index Environmental Performance Index Environmental Vulnerability Index Maximum Sustainable Yield Concept of carrying capacity Pressure-State-Response Relative Measure of Sustainability Safe Minimum Standard Well Being Index Cost Benefit Analysis Natural Resource Accounting Environmental Adjusted Domestic Product Environmental Impact Assessment City Development Index Index of Sustainable Economic Welfare Sustainable Net Benefit Index Sustainable Livelihood Security Index

Fig. 1.1 Existing and overlapping indicators of livelihood security through the lenses of climatic vulnerability. Source By authors

and resource use (Pachauri and Reisinger 2007; Singh and Singh 2011). This category of indices cannot address the economic development issues that limit its wider acceptability.

1.4.4 Indicators Focused on the Ecology–Economics Interface Cost-Benefit Analysis (CBA) has often been used as an indicator of the economic viability and ecological feasibility of individual projects. In addition to the practical problems in evaluating environmental effects within a market framework, there are also ethical issues involved in the choice of both the planning horizon and the

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discount rate in the CBA exercise. Natural Resource Accounting (NRA) is done under CBA which is a measure of the creation or depletion of environmental capital into GDP. As natural resources provide several use values and non-use values for human welfare and the sustainability of all species, NRA measures the sum of use values and non-use values, which constitute the total values (Kadekodi 2001). Genuine Savings Index (GSI) defines the reinvestment level from resource rents. These are reinvested to ensure that the social capital reserve should never decline. The societal capital stock consists of human capital together with his knowledge, skills, etc., and natural resource capital. All the values are monetized and aggregated to achieve simple addition to construct GSI. Here, a lot of subjectivity is involved in monetizing human capital. The Environmentally Adjusted Net Domestic Product (EDP) is outlined to develop the scope of the system to the integrated environment and economic accounting through the United Nations Environmental Program, The United Nations, European Commission, International Monetary Fund, Organization for Economic Cooperation and Development, and the World Bank (WCED 2018). Environmental impact assessment (EIA) identifies, predicts, evaluates, and mitigates the biophysical, social, and other relevant effects of development proposals. EIA has been a more focused version of CBA, with a relatively sharper focus on environmental impacts than on economic concerns. This category of indices cannot focus on the distributional issues that delimit their acceptability scope. However, CBA could be modified to accommodate equity parameters.

1.4.5 Indicators Focused on Ecology-Economics and Equity Interface Under the SD paradigm, the scope of human welfare has been broadened enough to encompass economic, ecological, and equity concerns through necessitating an entirely new set of welfare indicators that can transcend disciplinary boundaries. Several important other indicators under this category have been described as; The City Development Index (CDI), proposed by the United Nations Center for Human Settlements (HABITAT) consists of five sub-indices: (i) an infrastructure index, that is built on equally weighted four indicators where the percentage of households are connected to clean water, electricity, canalization, and a telephone network (but are without a mobile phone); (ii) a two-fold equally weighted waste index is composed of the percentage of untreated sewage in total wastewater and the percentage of disposal of solid waste in total solid wastes; (iii) a two-fold (diversely weighted) health index, which considers life expectancy and the infant mortality rate; (iv) a two-fold (equally weighted) education index, which is calculated by adding the per cent of the literacy rate and the combined enrolment rate; and (v) a city product index, which is based on the logarithmic value of a city’s GDP. CDI, as the name suggests, is an important indicator for measuring the SD level of a city, and is not appropriate for use in a rural setting. The Index of Sustainable Economic Welfare (ISEW) has been developed

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to integrate environmental and social externalities in national welfare accounting with some modifications to the original accounting method (Cobb and Cobb 1994). Accordingly, ISEW includes several social and environmental benefits and costs that invariably escape market valuation. Here also, all the values are monetized. The Sustainable Net Benefit Index (SNBI) is similar to ISEW. It mainly differs in the explanation of the rationale for an alternative index and the presentation of the items used in its calculation. The total of the cost account is subtracted from the benefit account to obtain the SNBI. The Sustainable Livelihood Security Index (SLSI), originally proposed by DFID and empirically illustrated later by Swaminathan (1991). He has attempted towards formulating a comprehensive indicator to reflect the ecology economic equity interface of SD. The conceptual and methodological bases, as well as the information efficiency and flexibility of SLSI, have been treated. Although the indices in this category (CDI, ISEW/GPI, SNBI, and SLSI) were composite, combining information on ecological, economic, and equity aspects within a unifying framework, they differ in terms of their methodological basis and information content. CDI, as the name suggests, did not apply to a rural setting. While ISEW, GPI, and SNBI have temporal indicators. SLSI is essentially a cross-sectional measure that has been very useful in evaluating the relative sustainability status of a given set of entities (households, villages, districts, ecosystems, regions, nations, etc.). Consequently, SLSI requires only a minimum amount of easily available ecological, economic, and equity information. Furthermore, the cross-sectional character, simplicity, and information efficiency of SLSI have made the indices creation very easy to work on, replicate, and suitable for generalization across various evaluation levels. The diagrammatic representation of the position of existing indicators of sustainable development is important to understand. A critical evaluation of the indicators developed to date revealed that the major snag in indicators of developmental activities was not the scarcity of approaches or methodologies but the inadequacy of crucial environmental and ecological information (Swaminathan 1991). SLSI has the potential to function in a context-independent of generic tool for evaluating SD concerns at various interrelated levels; households in a village context, villages in a district context, districts in a state context. There is a strong need to examine the livelihood issue. The thrust area in assessing climate change impact on livelihood is to examine its status in the region together with an evaluation of how and where livelihoods have been thriving or threatened, to what extend it is vulnerable to the climatic changes, and what are the chief constraints in the area concerning the historical archives. Today the world requires an efficient mitigation strategy to cope with the harsh impacts of climate change on livelihood together with adaptive measures. Before it, there is an urgent requirement to ascertain the hierarchy of vulnerable livelihoods so that vulnerable sectors and sections of the population can be prioritized later. The livelihood vulnerability is defined as the degree to which a person or a household is susceptible to, or unable to cope with adverse effects of climate changes. The exposure, sensitivity, and adaptive capacity are the three components of livelihood vulnerability, which can be understood through a composite function. These functional components are shaped by a

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variety of biophysical and socio-economic factors (IPCC 2002). The understanding of changing climate is an evolutionary science. While knowledge of the effects of climate change on livelihood is increasing, there is still a dearth of micro-level studies that can provide a better understanding. It is important to take preventative measures. The key requirement is to incorporate climate change projections into sustainable livelihood strategies, which has been missing at the micro level. Therefore, to combat the impacts of changing climate on livelihood, it is crucial to develop an efficient integrated strategy.

1.5 Organization of the Study For this purpose, the research work has been divided into nine chapters. The first chapter deals with the conceptual background of climate variability and its relationship to livelihood, where several indicators have been debated to work on. The second chapter basically focuses on the drivers of climate change research pathways to determine the aims and objectives of the work and related methodologies. The third chapter encapsulates the geographical profile of the study area and the existing livelihood situation. It provides detail about location, extent, physiography, climate, soils, demography, land-use pattern, cropping pattern, livelihood opportunities, and its sectoral distribution to understand rudimentary criteria for livelihood research. This explores the agro-ecology of the study area for climate change simulation modeling through the WRF model in the fourth chapter. Projected scenarios of climate for 2020, 2050, and 2080 have been illustrated through maps and diagrams on each AEZs. The climate change scenario modeling, where temperature and precipitation have been simulated on the grid for analyzing grid-level changes over decades to divulge the subtle changes in livelihood patterns later. The fifth chapter revolves around the drivers of livelihood security. Where the chronological order of sustainable livelihood concepts have been outlined to discover the best-suited methodology to study all five livelihood capitals separately through Pearson coefficient, ANOVA, multiple regression, Herfindahl Indices, etc. these tools have been used to analyze the capital security in the district. The outcome of the analysis has been schematically presented to investigate the gaps in livelihood capital security through the pentagon (spider diagram) study in chapter six. Chapter seven scrutinizes the combined analysis of the above 4th , 5th and 6th chapters in measuring livelihood vulnerability and security in the study area. This investigation has been performed both ways; with and without climate change impact analysis for providing unbiased results. Chapter eight focuses on sustainable livelihood adaptation and mitigation strategies to identify and prioritize the sectors for climate mitigation based on vulnerability. A vulnerability index has also been constructed to measure the sensitivity of agriculture, forestry, and other sectors across the Kangra district. Furthermore, the adaptation and mitigation strategies that have been outlined in the same chapter that has been given more emphasis on traditional and local knowledge. The ninth chapter on Indian climate change policy assessment and the interplay of the international and domestic

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policy, planning, and program discourse. It summarizes India’s initiatives on climate change diplomacy at the international platform by first scrutinizing several landmark decisions on climate policies and initiatives undertaken. It has gazed deeply into the constitutional and legislative provisions through environmental protection articles, laws, acts, and statues of India for multifaceted understanding. The last tenth chapter concludes the book with the note that the complexity of climate change and livelihood vulnerabilities are an interlinked system of sustainable development. It has attempted to fulfill the research gap by putting people first in mainstreaming sustainable development policy’s missions.

1.6 Concluding Remarks Geographical studies are not limited to human and lands only, it also includes the interactive environment. The historical appraisals through WMO, UNFCCC, and IPCC have provided definite evidence to support climate change. The evident variability in local, regional, or global climate tends to indicate harsher impacts on weather-dependent societies and rural mountain communities. The Himalayan regions have limited information technology, poor access to services, inequitable access to productive assets, low adaptive capacity, and limited livelihood options. The Government of India (GOI) has shown strong commitment to deal with these vital issues through the implementation of various national and local schemes to harvest non-conventional and alternative resources such as; solar, hydropower, thermal and wind energies, etc. and put forward an inordinate foundation to reduce toxic environmental impacts along with producing real benefits to local people. The MSLSI in the Himalayan environment may consume the bottlenecks of sustainable development. It may provide evidence that India’s vision of sustainable development is not merely following ‘Western’ trajectories. The term ‘transforming’ India is the new beginning from the conventional carbon trap to the foreseeable optimistic future.

References Bohringer C, Patrick EPJ (2007) Measuring the immeasurable: A survey of sustainability indices. Ecological Eco 63:1–8 Carleton AM (1999) Methodology in climatology. Ann Assoc Am Geogr 89:713–735 Coen D (2018) Climate in motion: Science, empire, and the problem of scale. University of Chicago Press, London Cobb CW, Cobb JB (1994) The green national product: A proposed index of sustainable economic welfare. University Press of America, Maryland Change IPOC (2001) Climate change 2007: Impacts, adaptation and vulnerability. Genebra, Suíça Daly HE (1990) Towards some operational principles of sustainable development. Ecological Eco 2:1–6 Daly HE (1992) Allocation, distribution, and scale: Towards an economics that is efficient, just, and sustainable. Ecological Eco 6:185–193

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Desai M (1991) Human development: concepts and measurement. European Eco Review 35:350– 357 Duku C, Zwart SJ, Hein L (2018) Impacts of climate change on cropping patterns in a tropical, sub-humid watershed. PLoS One 13:e0192642 Eakin H, Bojórquez-Tapia LA (2008) Insights into the composition of household vulnerability from multicriteria decision analysis. Glob Environ Chang 18:112–127 FAO (2020) Early warning early action report on food security and agriculture (January–March 2020). Food and Agriculture Organization of the United Nations, Rome Hahn MB, Foster SO, Riederer AM (2009) The livelihood vulnerability index: A pragmatic approach to assessing risks from climate variability and change–A case study in Mozambique. Glob Environ Chang 19:74–88 Hingane LS, Rupa Kumar K, Ramana Murty BV (1985) Long-term trends of surface air temperature in India. J Climatol 5:521–528 IPCC (2001) Climate Change: Synthesis Report. A Contribution of Working Groups I, II, and III to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge IPCC (2001a) Climate change: The scientific basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge IPCC (2001b) Climate change 2001: Impacts, adaptation and vulnerability, Contribution of Working Group II to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge IPCC (2001c) Climate change: Mitigation, Contribution of Working Group III to the third assessment report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge IPCC (2002) Climate change and biodiversity - IPCC Technical Paper V. Intergovernmental Panel on Climate Change, Geneva IPCC (2013) Climate change: The physical science basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge Kavi Kumar KS (2009) Climate sensitivity of Indian agriculture do spatial effects matter? Cambridge J Reg Econ Soc 4:221–235 Kadekodi GK (2001) Valuation of natural resources: What have we learnt from Indian experience? Indian J of Agri Eco 56:285–311 Kumar KR, Kumar KK, Pant GB (1994) Diurnal asymmetry of surface temperature trends over India. Geophys Res Lett 21:677–680 Larson DA, Wilford WT (1979) The physical quality of life index: A useful social indicator? World Dev 7:581–584 Millennium Ecosystem Assessment (MEA) (2005) Ecosystems and human well-being: Synthesis. Island Press, Washington OECD (1991) The state of the environment. Paris: Organization for Economic Cooperation and Development (OECD) Parikh JK, Parikh K (2002) Climate change: India’s perceptions, positions, policies and possibilities. Organization for Economic Co-operation and Development (OECD) Patra J (2016) Review of current and planned adaptation action in India. CARIAA working paper No 10. International Development Research Centre, Ottawa Pachauri RK, Reisinger A (2007) Climate change 2007: Synthesis report. Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Geneva, Switzerland Saryal R (2018) Climate change policy of India. South Asia Res 38:1–19 Singh RB, Singh S (2011) Rapid urbanization and induced flood risk in Noida. India, Asian Geographer 28:147–169

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Singh RB, Jha S (2014) Agriculture and forestry based livelihood capital assessment. In: Singh RB, Hietala R (eds) Livelihood security in Northwestern Himalaya: Case studies from changing socio-economic environments in Himachal Pradesh. Springer Tokyo, India, pp 95–106 Singh RB, Singh S (2014) Human-induced biome and livelihood security. In: Singh RB, Hietala R (eds) Livelihood security in Northwestern Himalaya: Case studies from changing socio-economic environments in Himachal Pradesh. Springer Tokyo, India, pp 53–66 Singh RB, Singh S, Sen Roy S (2016) Assessing climate change signals in Western Himalayan district using PRECIS data model. In: Singh RB, Schickhoff U, Mal S (eds) climate change, glacier response, and vegetation dynamics in the Himalaya. Springer International Publishing, pp 103–115 Singh S (2010) GIS application in urban heat island: A crusading anthropogenic driver to climate change. Urban India 30:74–92 Sörlin S, Lane M (2018) Historicizing climate change—engaging new approaches to climate and history. Clim Change 151:1–13 Swaminathan MS (1991) Sustainable agricultural systems and food security. Outlook Agric 20:243– 249 Toman MA, Crosson P (1991) Economics and sustainability: Balancing trade-offs and imperatives. Energy and Natural Resources Division, Resource for the Future, Washington, DC, pp 91–105 Teske S (ed) (2019) Achieving the Paris climate agreement goals: Global and regional 100% renewable energy scenarios with non-energy GHG pathways for +1.5 °C and +2 °C. Springer International, p. 491 UNFCCC (2020) Conference of the Parties (COP). https://unfccc.int/process-and-meetings/confer ences/road-to-glasgow. Accessed 21 December, 2020 Vanuytrecht E, Raes D, Willems P (2016) Regional and global climate projections increase midcentury yield variability and crop productivity in Belgium. Reg Environ Change 16:659–672 Wackernagel M, Rees W (1997) Our ecological footprint: Reducing human impact on the earth. New Society Publishers, Gabriola Island WMO (2010) WMO statement on the status of the global climate in 2009. WMO, Geneva WCED (2018) Report of the World Commission on Environment and Development: Our common future. World Commission on Environment and Development World Economic Forum (2002) World Economic Forum’s Global Leaders for Tomorrow Environment Task Force, Yale Center for Environmental Law and Policy (YCELP), and Center for International Earth Science Information Network (CIESIN) of Columbia University. The Environmental Sustainability Index (ESI). New Haven, Conn: YCELP WWF (1998) Living planet report, Gland, Switzerland: World Wide Fund for Nature (WWF)

Chapter 2

Drivers of Climate Change Research Pathways

Abstract This chapter provides a framework to identify multifarious drivers to understand climate change, its relationship and linkages between the states of changing global climate, adaptation, and mitigation strategies in climate impacted livelihoods. It also conceptualizes the research problem through a detailed literature review on climate change, the need for climate change modeling, GHGs emissions, sustainable livelihood, adaptation and mitigation strategies in climate impacted livelihoods, etc. All related concepts to study have been significantly defined. Further, it deals with a brief description of the study area, research questions, objectives, and a concise account of the methodology of each objective. Keywords Global and regional circulation model · Downscaling · Vulnerability · Exposure · Sensitivity

2.1 Introduction The total terrestrial area covered by mountains is 16.5 million km2 accounts for almost 27% of the land surface of the earth and is occupied by 7% of the global human population. This enormous reservoir of resources provides equilibrium in the world by its upland and lowland relationship that grants directly or indirectly resources and ecosystem services to more than 50% of the world’s population (Schild and Sharma 2011; Singh et al. 2016c; Körner et al. 2017). This young fold mountain region is characterized as the ‘roof of the world’ famously known as the ‘water tower of Asia’ (Qu et al. 2019) and ‘third pole’ (Schild and Sharma 2011) across the globe, having human habitation at 3300 m Above Mean Sea Level (AMSL). The precipitous slope, erratic slope aspects, uneven terrain, and changing altitude induces variability in the climate both vertically and horizontally. It is the utmost complex, having an exceptionally active-vital geodynamic condition, fragile, exposed, and susceptible topography where even insignificant alteration may trigger distressing proportion into its system. The evident rise in the global surface temperature of about 0.75 °C ± 0.3 °C is exhibiting the long-term warming signals where the anthropogenic contribution of 0.1–0.3 °C per decade is modifying the intensity and frequency trends of climate © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 S. Singh and R. B. Singh, Simulating Climate Change and Livelihood Security, Advances in Geographical and Environmental Sciences, https://doi.org/10.1007/978-981-16-4648-5_2

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extremes especially in mountainous regions (Singh et al. 2016b; IPCC 2018). These regions are prone to several hazards and disasters; landslide, earthquake, forest fires, land subsidence, avalanche, cloudburst, flash-flood, hailstorm, Glacial Lake Outburst Flow (GLOF), etc. are the major threat to life and assets.

2.2 Drivers of Climate Change and Livelihood Framework The research work on the changing climate and livelihood security is based on scientific inquiries on systematic thinking, factual observations, and past evidence. A critical and thorough insight into the research study becomes imperative for conceptual clarity and methodological improvement in the current research work. Upholding the above perspective, the drivers of climatic changes and its impact on livelihood have been reviewed through the literature and arranged concisely in discussing the challenges posed by the changing climate under the following sub-heads: the state of changing worldwide climate, increasing GHGs emissions, livelihood portfolios, changing climate and its impact on livelihood security, and simulation modeling of livelihood security.

2.2.1 The State of Changing Global Climate The changing climate is gradually recognized as a critical challenge to future development, human well-being, and ecological health (Coen 2018; IPCC 2001; Kriegler et al. 2012). Many scientists have reported the possible causes and consequences of climate change across the world. According to the ‘Theory of Double Exposure’ (O’Brien and Leichenko 2003; Leichenko and O’Brien 2008), globalization and climate change are proceeding simultaneously and the regions, sectors, ecosystems, and social groups are often challenged by the impacts of the climate processes. The unsustainable consumption patterns of the rich industrialized nations are responsible for the threat of climate change. The Daily Temperature Range (DTR) (measures rages between daytime high temperature and night-time low temperature) has decreased for the most part of the world during the period 1950–1993 (Karl et al. 1993; Easterling et al. 2000). There are indications that the western Himalayas region is showing a different response to global warming (Rao et al. 2012; Schickhoff et al. 2016; Krishnan et al. 2019; Li et al. 2019), with an increase in DTR and a decrease in mean temperature in some seasons, are possibly induced by local natural forcing (PMO 2008; Pandve 2009). The annual decreasing rainfall trends of almost −29.7 to −2.1 cm/100 years in Himalayan districts have been observed by (Jain and Kumar 2012) at Joshimath, Mussoorie, Mukteshwar, Srinagar, and Shimla while Pithoragarh, Dehradun, Pauri, Nainital, and Almora are experiencing an increase in precipitation trend (3.65–27.77 cm/100 years) (Bhutiyani et al. 2010; Vaidya et al. 2019). Singh and Mal (2014) have analyzed the monsoonal variability

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and trends in rainfall seasons across six surface observatories; Munsyari, Joshimath, Dehradun, Mukteshwar, Roorkee, and Tehri in the western Himalaya and pronounced that the winter monsoon rainfall and inter-season variability was low across high altitudes while high variability is seen in plains. Gadgil and Guha (1996) have analyzed the summer and winter rainfall during 1964–2006 have shown an increasing trend whereas monsoon rainfall is declining in the same region. The variability has led to a reduction in effective snowfall duration across Dhauladhar and Pir Panjal range in Himachal and Kashmir Himalaya. Singh and Singh (2014) have also computed and explored the differential temperature magnitude during extreme winter and summer inter-season by using Landsat TM data and have said that it shows variations with the land use/cover. Parry et al. (2008) have analyzed that without any definite mitigation measure if one compares the pre-industrial temperature levels, the global temperature may increase up to 2–7 °C and sea-level rise, up to 0.1–0.9 m by 2100. Ropelewski and Halpert (1987), Millar et al. (2017), Schott et al. (2009) and IPCC (2001) have claimed that the warm occurrences of the El Niño Southern Oscillations (ENSO) and droughts over India and other tropical countries have multiplied. The Climatic variability is increasing year after year.

2.2.2 The Green House Gas Emissions and Changing Climate The IPCC (2013) has accumulated the evidence regarding the magnitude of change in temperature and carbon dioxide (CO2 ) for different parts of the world and has stated that the CO2 level is persistently increasing. It has been observed in simulation analysis by IPCC (2001, 2018) that the CO2 level may upsurge from 396–415 ppm in 2010 to 604–756 ppm by the 2070s. The other GHGs with CO2 might cause an enormous greenhouse effect and thus may increase the earth’s average temperature. The discovered ice core data from the field was plotted in the ‘Keeling curve’ through advanced computer modeling also showed an ascending tooth-shaped trajectory, showed a stable rise in CO2 levels across Northern Hemisphere. This analysis is supported by Tyndall, Arrhenius, and Callendar’s investigations that 50% increase in CO2 could produce warming of 4 °C (Singh and Jasrai 2012; Mora et al. 2013; Bräuning et al. 2016; White et al. 2018; Sörlin and Lane 2018). The reckless deforestation plays a major role in increasing CO2 concentration besides industrialization, cement manufacturing, vehicularization, land-use, and land-cover changes (Ma et al. 2014). With the increasing level of temperature and CO2 affect crop productivity directly and indirectly. The direct impact could be on the physiological processes of the plant-like; photosynthesis, respiration, evapotranspiration, and phenology. While the indirect impact could be through weather-induced diseases, thermal and water stress occurrences, etc. (Bräuning et al. 2016; Dusenge et al. 2019; Jat et al. 2014). The global atmospheric concentration of CO2 was 379 ppm in 2005 globally which

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has increased at an average rate of 1.88 ppm/year during 1995–2005 (Rödenbeck et al. 2018; UNFCC 2018). The current trends in GHGs emissions and potential agricultural losses have induced an alarm on livelihood sustainability. It is crucial to measure the futuristic quantitative impact of GHGs on the productivity of crops in the hilly region of Himachal Pradesh (Gadgil and Guha 1996; FAO 2006; Teske 2019). It has been reported through various studies compiled that the productivity of food grain crops could drop by 30% in the following thirty years (Eakin and BojórquezTapia 2008; FAO 2020). The atmospheric CO2 has a direct and significant positive relationship with the growth of the crop and yield but it is reciprocal in terms of temperature. Rogers et al. (2017) have united their research outcome with Kimball and Idso (1983), where they explained that the productivity of crops is improved with amplified CO2 and declines with increasing Surface Air Temperature (SATs). The increasing emission of GHGs into the atmosphere promotes compounding problems. Although India’s contribution to global GHGs emissions is only 0.09% in terms of climate change impact, it is among the most vulnerable country. McJeon et al. (2014), Stocker et al. (2013) and WCED (2018) have analyzed that 25% of the global population that lives in the developed countries releases more than 70% of the total global CO2 emissions and consumes 74–79% of varied reserves of the world. Therefore, there is an urgent need to have an in-depth study on areal differentiation regarding CO2 status, trend, its impact on major crops and livelihoods.

2.2.3 Sustainable Livelihood in Changing Climate The emphatically advanced effect of climate change has provided undeniable evidence for global risk. The changing climate and its impacts on global warming are a chief instrumental factor that is significantly not just limited to the local or regional environment. In its Fourth Assessment Report (AR4), IPCC has provided irrefutable observations regarding an increase in SATs and Surface Skin Temperatures (SSTs). The increasing SATs and SSTs are triggering extensive de-glaciations inducing a slow and steady rise in average sea level globally (IPCC 2001; Gornall et al. 2010; Bisht et al. 2016; Rödenbeck et al. 2018) Over the last 130 years since the 1880s global climate records of large scale warming have already been evident from calibrations that showed a crucial interplay of physical and anthropogenic dynamics. The latest estimates demonstrate that during the twentieth century the average earth’s SSTs have increased by 0.73 °C (Anderson et al. 2013; Kumar et al. 2006; Park et al. 2017). The exceptional rise is having ruthless impacts on the ecosystem, sea level (0.1–0.9 m in a century), and hydrological cycle which is impacting the crop and related yields (Singh 1998; Gornall et al. 2010; Duku et al. 2018). One of the greatest threats under the current climate change is environmental conservation and livelihood security. Thus, in order to secure key development concerns; livelihoods, it is essential to address the climate change issue. The Brundtland Commission in 1987 has presented Sustainable Livelihood (SL) especially in rural areas as the resource proprietorship and the right to basic needs and livelihood security (WCED 1987; Hák

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et al. 2018). Ellis (2000), Mehta et al. (2019), Ellis and Allison (2004) and Fraser (2007) have focused on the tropical forest and agricultural ecosystems because it represents a shared legacy with livelihood portfolios pooled by the majority of the population especially in natural resources dependent on developing countries. Kavi Kumar (2009) has explained the mounting apprehensions regarding livelihood security that is putting stress on the asset vulnerability and the capacities of different groups in managing or minimizing risk to cope with various types of shock and stresses. Researches have suggested that there is an urgent need to support rural producers who have been affected by disasters and have argued to have a serious perspective on political dimensions of vulnerability (Nelson and Geoghegan 2002; Hahn et al. 2009; Singh and Singh 2014). Department for International Fund Development elaborated sustainable livelihood approach and explained it as a way to improve understanding of the livelihoods of the poor. DFID’s inherent focus is on insecurity related to food and it argues for a strong conjectural shift to draw attention to the main drivers to improve livelihood outcomes (DFID 2005). Hobley and Shields (2000) had analyzed livelihood diversification and found that it is an appropriate strategy to generate wealth and smooth consumption in several rural areas. Rahut and Micevska Scharf (2012) have assumed that economic diversification will reduce climatic vulnerability. Rural farmers are opting for economic diversification intending to improve livelihoods, together with improved levels of consumption and economic opportunities. Fraser et al. (2006), Basannagari and Kala (2013), Singh and Hietala (2014) studied the impact of changing climate in recent years on apple cultivation in the Himachal Pradesh. Based on climate information reports and farmer’s perceptions they found how apple cultivation is shifting to a higher altitude. It made a clear understanding of how climate change is affecting apple cultivation and its dependent population’s livelihood. It is clearly apparent from studies that precipitation in apple-growing regions in Himachal Pradesh shows decreasing trends while the temperature is increasing (Singh et al. 2007, 2016a; Basannagari and Kala 2013). FAO (2020) have emphasized on decreasing per hectare yields and explained how the provisioning ecosystem services have been jeopardized by the rapid conversion of forest lands into cropland and residential area. This focuses on the urgency to seek balanced ways for achieving co-existence between the sources of food supply and livelihoods. The report also highlights that land productivity is declining due to the intensification in intrusion towards marginal lands. Therefore, the extensive use of these available marginal lands will probably aggravate the soil erosion and degradation risks (Lal 2004; FAO 2017). The large proportions of the marginal agricultural lands have already been degraded by organic matter loss, excessive disturbances, acidification, salinization, etc. (Swaminathan 1991; Abildtrup et al. 2006; Gornall et al. 2010; OECD 2020). It was Carney who has been cited by the International Institute for Sustainable Development (IISD) defined livelihood. She explained livelihood in terms of capabilities, assets, and activities, which are required for a means of living. According to IISD ‘livelihood assets are the means of production, accessible to a given community that can be used to generate sustainable material resources for the survival of the community’ (Ashley and Carney 1999; Carney 2003). It was also argued that natural resources are unquestionably the most important and

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vital for the community’s sustenance. Scoones (1998), Gwimbi (2009), Ashley and Carney (1999) and Eakin and Bojórquez-Tapia (2008) have linked the livelihoods of rural-community to the resilience-building for disaster risk reduction. They have realized that developing countries are largely dependent on natural resources and are thus severely affected by even small environmental changes. It was found that during the 10th FYP period in India, the growth in agriculture and allied activities have drastically declined from 4.45% in the 1980s to 3.21% of 1990s and finally, it became 2.31% (in the year 2000s), which is lower than ever after the green revolution in India. Likewise, there is a large alteration from staples to cash cropping. This alteration is due to climatic variability and less profitability in staple cropping could be a major reason for food insecurity (Slariya 2014). The area under food grain crops during 1960–61 was 46.1 million hectares that have gone down drastically to 29.52 million hectares in 1998–99. In the meanwhile, during 1990–91 the area under food grains and coarse grain crops have also started declining at 2% and 18% respectively even after the introduction of the new economic policy to improve agriculture (FAO 1999, 2017; Government of India 2018). Nevertheless, with increasing demand for fruits, fish, milk, vegetables, and other produce to the large population of India, the agricultural sector is facing new challenges of diminishing land resources, declining productivity, loss of biodiversity, natural resource degradation, widening economic inequality, etc. (Gornall et al. 2010; Wheeler and Von Braun 2013; Government of India 2017). These all are having serious insinuations on the livelihood vulnerability. Hiremath (2007) have studied Indian agriculture during liberalization and concluded that the marginal and small farmers in the hill regions are trying to pursue modern agricultural tools and technologies in their fields to lessen the changing climatic impact on crop productivity and yield. Ruedi and Baumgartner (2004) had explained that education, skill, and training are crucial for the development of social infrastructure and human capital. Ratna Reddy et al. (2004) have studied livelihood security through watershed development at Uttrakhand. They have investigated that household income and employment are statistically correlated and significant improvements have been observed due to watershed development on physical capital security in all the sampled villages. The physical, financial, and social capitals were not found significant in mountainous regions but improvements have been observed in the human capital indicators (Singh and Jha 2014; Srinivasan 2018). Deschenes and Greenstone (2007) have studied and concluded that forests and agriculture are predisposed to climate change. Climate change has been acknowledged, that affects agrarian livelihood, agricultural production directly. Turner et al. (2003) have explained that due to climate change, carbon emission is believed to be gradually benefited. On the other hand, a state like Himachal Pradesh has contributed almost nothing to GHGs emissions from anthropogenic responses yet climate change has impacted its ecosystem largely (Lal 2004).

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2.2.4 Modeling Changing Climate and Livelihood Security Alcamo et al. (2005) have explained spatial level categorical changes in the global and regional livelihood security through modeling and have focused on several prominent research efforts. They have developed several plausible projections for the future climate with the help of the Millennium Ecosystem Assessment (MEA) research team. Each projection has been outlined based on regional population, technology, and economic growth estimates as well as projections for food and energy demands that are going to increase by the year 2080. Adams et al. (1995) have used a set of agriculture, climate, and water supply data to prepare International Food Policy (IFP). While Netherland’s Integrated Modeling of Global Environment (IMAGE) team (Stehfest et al. 2014) in collaboration with the MEA team (2005) have interpreted these likely regional changes agriculture and forestry sector on the global grid level for the decade 2050s and 2080s. Nelson and Daily (2010), Nelson and Geoghegan (2002) and Kamusoko et al. (2009) have included cellular automata in agent-based modeling in the livelihood framework provided by DFID. von Döhren and Haase (2015) have produced a report and database to assess the impact based on the four grid cell level livelihood maps, biodiversity, ecosystem service production, and wellbeing. Challinor et al. (2018) have done it to explain how the state’s low adaptive capacity, over-dependence on natural resources and agricultural sector give birth to several stressors. In recent years, there has been considerable interest in developing high resolution gridded data sets. It was advocated by New et al. (1999), Mitra et al. (2003), Yatagai et al. (2005) and Rajeevan and Bhate (2009) to develop a high resolution daily rainfall data set (1° latitude × 1° longitude) from India Meteorological Department (IMD) observatory. IPCC (Parry et al. 2007) have simulated that onethird of biodiversity is under the threat of extinction and further, substantial impacts of changing climate on livelihood securities are projected based on wide studies on the dynamic vegetation modeling. The livelihood based on natural resources is facing lots of uncertainties due to forest biodiversity loss and declining restoration capacity especially in the mountains of tropical areas. Nelson and Daily (2010) together with Davis et al. (2005) have said that predicting climate change impact and modeling it at a micro or regional level is difficult. The prediction modeling for subsistent farming is either absent or having great difficulty in getting a benchmark location-specific data to compute at the regional level. The household’s capability to assimilate offfarm and on-farm endeavors may reduce the farmer’s livelihood vulnerability from a range of stressors (Altieri 1999; Sajjad and Nasreen 2016). have made climate change projections, it was extracted from six Regional Climate Models (RCMs) under the medium emission A1 B scenario showed a clear increase in temperature, while trends in precipitation are masked by the highly variable nature of the precipitation (Foley et al. 1996; Collins et al. 2001; Bonan et al. 2003). The analysis of climate change scenarios, represented by more dry years, higher evaporative demand, and less irrigated water supply in the western part of India have resulted in a reduction of the irrigated area by 25% just in one projected decade between 2010–2020 (Kumar et al. 2006; Li et al. 2019).

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2.2.5 Adaptation and Mitigation Strategies in Climate Impacted Livelihoods Ellis (2008) and Hinz et al. (2020) have investigated that the farmer’s capability in getting perennial livelihood to support their own household is getting weaker and this has not improved for over a decade. While FAO (2006) have emphasized on adaptation planning under desired circumstances and professes countless challenges wherever livelihood management is concerned. It has also been pointed out that there is an urgent requirement of an institutional framework to enable operations across multiple spatial scales as; local, regional and national levels with numerous time frames as; short, medium, and long term (Mora et al. 2013; Duku et al. 2018). UNFCC (2019) had adopted strategies to deal with climate change and its impact on rural livelihood. It has agreed on a viewpoint that the mitigation and adaptation strategies are harmonizing and non-exclusive when it is being dealt with an integrated manner (NATCOM 2012). Mitigation is concerned with anthropogenic intervention. It is premeditated to enhance sinks or to reduce the emission of GHGs at the source only. Broadly, it can be said that the adaptation in the context of changing climate is all about adjustments in systems through both natural and human responses. The adaptation regarding the actual and expected stimuli of climate may provide beneficial opportunities and create bases for mitigation later. The adaptation and mitigation together perform as a major component in sustainable livelihood development because of their cumulative influence on the settlements, health, infrastructure, food security, forests, agriculture, marine, and another ecosystem simultaneously. According to Göpel et al. (2018) and Hinz et al. (2020), adaptation is the first response presented by the population in any area while dealing with the impacts of changing climate, moreover, the mitigation procedures may join later because it is a part of long-term strategy to show any effect. It explains further on how sustainable livelihood approaches can be used at both policy and project levels to initiate new poverty reduction activities or modify existing activities to improve livelihood outcomes. There is no use of all the scientific and technical literature being generated out of continuous high-quality research if they do not reach the common people (Singh and Sen Roy 2002). It has been debated by Bohle et al. (1994) that proper knowledge and insight of present climatic vulnerability is required for developing coping strategies to mitigate the harsh impact of the changing climate. Similarly, Kates (2000), has said that presently several efforts are being put from the government and non-governmental organizations to address mitigation and preventive action to delimit GHGs due to the changing climate rather than only focusing on adaptation strategies. As socio-economic consequences manifest themselves, human behavior and institutions adapt (Singh and Sen Roy 2002). Regarding climate change latest review research and scientific investigations have explained that how Indian research on climate change and analysis concerning other developing countries have attained a prestigious status but the adaptation studies at the micro-level are still awaiting from the researchers across streams (Ghosh et al. 2018; Mehta et al. 2019; Hinz et al. 2020). A similar viewpoint has been comprehended through Kandlikar and Sagar (1999) and Adam et al. (2018) research work

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that immense attention is being paid in India regarding climate change mitigation rather than on developing adaptation strategies. The book intends to address the following research questions.

2.3 Research Questions 1. 2. 3. 4. 5. 6.

Is there any scientific evidence to support climate change in the western Himalayan region? If so, what are the expected changes in the climate? Do actual climate change and that predicted by simulation modeling from historical baseline show similar results? What is the expected impact of climate change on livelihood security? Is there any role of MLSLI impact assessment in sustainable livelihood development? What are the vital issues to be addressed by the policy-makers towards minimizing the expected livelihood vulnerabilities? What are the research gaps that need to be addressed?

In the subsequent chapters, the authors will explore each of these questions to observed, simulate and analyze the changing climate and its impact on livelihood security in the western Himalayan region.

2.4 Aims and Objectives An attempt has been made to analyze livelihood security in the Kangra district of Himachal Pradesh, where the economy is predominantly agrarian and the majority of the population is rural. The objectives of the study are; 1. 2. 3. 4. 5.

To explore evidence and exhibit climate-related changes in Kangra district, To quantify and assess the livelihood securities, To quantify possible linkages and potential impacts of changing climate on livelihood securities by developing projected scenarios, To analyze the impact of socio-economic transformation and economic development on livelihoods, To develop adaptation and mitigation synergy for sustainable regional livelihood framework.

2.5 Study Area The present research on climate change simulation and livelihood security in western Himalaya focuses on the most populous district of Himachal Pradesh; Kangra. It is

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positioned between 31° 21 to 32° 59 N and 75° 47 to 77° 45 E, Dharamsala is the administrative headquarters of this district. Kangra covers a total of 5739 km2 geographical area and with this, it constitutes 10.31% of the geographical area of Himachal Pradesh (H.P.). The Beas is one of the largest rivers of this district that contributes to the fertility of the land here. Agriculture and forests are the major sources of livelihood where two-fifths of the total area in the district is under forests, which is much higher as compared to the state average of 24.20%. The contribution of district Kangra to the H.P’s agriculture is immense. It accounts for almost one-fourth of the food grain area in the state. Individual crop-wise contribution from the district is quite high, where rice adds 45%, maize, wheat and pulses respectively account for 20, 26 and 14%. Concerning the non-food grain crops, the district contributes 39, 20 and 12% to the state area under oilseeds, fruits, and vegetable crops, respectively. The food grain crops account for over 90.17% of the total cropped area in Kangra. The economy of the district is primarily agrarian with 66.06% of the working population directly dependent on agriculture (Government of India 2018). Therefore, the particular study area has been selected to develop and identify changing livelihood conditions and its relation to climate change over time.

2.6 Data Base and Research Methodology Even though, neither surveys nor quantitative data alone produce sufficient enough resources to answer all the questions raised for measuring the sustainable livelihoods in Kangra district but through a hybrid inductive and deductive information system, it is possible to cover the key aspects of the sustainable livelihood framework. Such an integrated combined approach will principally provide much convincing analysis than any other method alone. It could be because in the real world the responses of the population differ and quantification might not be easy for the qualitative information. The hybrid usability of quantitative and qualitative methods together offers a finer base for analysis. During the study on climate change and livelihood; key informant interviews, focus groups, socio-economic surveys, in-depth household case studies, and other relevant secondary data were used. The study has conjoined qualitative, quantitative, socio-economic, biophysical, participatory and conventional (or extractive) data that relies on quantitative collective social information, qualitative economic information, and together it has been used.

2.6.1 Data Bases The preceding objectives have been empirically supported by the analysis of primary and secondary data.

2.6 Data Base and Research Methodology

2.6.1.1

31

Primary Database

The primary data collections from a purposive stratified random sample of 270 households (HHs) have been selected from village panchayats from the Kangra district with the help of a structured questionnaire. An equal number of households have been selected from each village based on stratified random sampling. In the present study, livelihood security has been assessed at two levels viz. block and household levels. The secondary data has been used to assess livelihood security at the block level, while primary data has been used for assessing it at the village and household level through the questionnaire method. Several questions include open-ended, fixed alternative, and projective questions as well. The fixed alternative questions provided multiple-choices to answer. Questions have been designed; close-ended, dichotomous, and multi-chotomous responses. Dichotomous questions were having two possible opposing responses, for example, yes and no, while multi-chotomous questions were having a range of responses. The questions have been asked verbally and the responses were recorded accordingly. As the questionnaire is close-ended, it has become easy for the respondents to answer. The sampling has been done with great care for people from various age-groups, gender, and educational levels to fairly express their perception. There are altogether 8 AEZs falls in the 15 development blocks in the district. Therefore, from each AEZ, the block has been selected like; AEZ 1.1 (Indora, Fatehpur, Paragpur, Dehra), AEZ 1.2 (Dehra, Kangra, Nagrota), AEZ 2.2, 3.2 and 4.1 and 4.2 (Dharamsala), and AEZ 4.2 and 4.3 (Baijnath). It has been kept in mind that there should be at least one representative block from each AEZ, although there are 3 blocks that have been selected from AEZ 1.1 and 1.2 because these blocks represent the surrounding area near Pong dam, where the maximum change in land use has been observed from secondary data sources. From each 9 blocks, numbers of Gram Panchayats (GPs) have been identified to select at least three villages having the largest population. Two hundred and seventy households were interviewed (covering 9 blocks, 3 villages from each block and 10 households from each village means 9 * 3 * 10 = 270 HHs). Three blocks from the high hills wet sub-temperate (Dharamsala and Multhan) including 3 villages from each with 10 households, 3 blocks with 9 villages from the valley region and Pong dam, 2 blocks with 6 villages from the Changar region, and one block with 3 villages from Shivalik foothill region. The sampled villages have been selected in such a way so that microclimatic variations, population distribution, farming systems, livelihood conditions, alternative livelihood options, and cropping productivity in sampled blocks can be captured.

2.6.1.2

Secondary Database

The historical climate data of a minimum of 44 years from 1970 to 2014, for preparing the baseline has been taken from the secondary data sources especially from IMD and WMO. Both are having standard measures of maximum and minimum rainfall, temperature, and rainy days. The meteorological data have been acquired from the

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Indian Institute of Tropical Meteorology (IITM), monthly weather records were taken from the Indian Daily Weather Reports (IDWRs) with the help of Palampur University and the Indian Meteorological Department (IMD). The related information on forest cover, water resources, water bodies, and mineral resources have been extracted from the Survey of India (SOI) and Geological Survey of India (GSI) respectively. The SOI degree topographical sheet number; 43P, 44 M, 52D, 52H, and 53A together cover the entire district. The data provided by the IMD grid where the north-east corner of this grid is 31° N, 75° E and the southeast corner is 32° N to 77° 45 E, giving the grid 56 rows and 68 columns correspond to the terrestrial location. The climate observation records have been taken to prepare a baseline for projected climate over simulated time-periods (January 2020–December 2050 and January 2050–December 2080). The climate change scenario modeling has been done after downscaling the model from GCM to RCM. However, later it has been noticed that the meteorological stations during the updated current period comprise significantly fewer stations, therefore, for the current ten years/decade Atmospheric Infrared Sounder (AIRS) satellite and Tropical Rainfall Measuring Mission (TRMM), from National Aeronautics and Space Administration (NASA) have been considered to analyze the gap. The methodological flow chart exhibits the investigation sketch undertaken in the present study at a broad level, while each chapter is having a separate methodology that has been dealt with in the related chapter itself (Fig. 2.1). The data on cereal and non-food grain crops are taken from the District Agriculture Statistics Handbook. Data pertaining to poverty, income, per capita, and income source has been taken from the website of the Himachal Pradesh Government. For creating the Livelihood Vulnerability Index (LVI) the data on the landholding size, irrigated area, density of population, literacy level, population growth rate, etc. have been collected from the Census of India office, District Statistical Office, Joint Director Statistics Office, respective block headquarters office, tahsil and Patwari Circles. The secondary database has been divided into spatial and non-spatial data sets.

Spatial Elements The topographic sheets on the scale of 1:50,000 have been obtained from Survey of India.

Non-spatial Elements The human resource data (Census Data) including various parameters like demography (population, sex ratio, and density), the literacy rate has been procured from the Census of India. The Economic parameters including working population, marginal workers, agriculture workers, etc. have been obtained from the Department of Economics and Statistics, H.P. The land cover/land use class parameters such as the area under forest, pastures, un-culturable, culturable waste, and cropping intensity have been procured from Department of Land Record and Directorate of Planning,

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DATA COLLECTION

DATA REPRESENTATION

Household Survey

Questionnaire Kangra District (271)

Figures Climate Change

Observations

Secondary Data Sources Livelihood Security

Primary Data Sources

Maps Photographs

Directorate of Statistics and Evaluation, H.P.

9 Sampled Blocks and 27 villages, 270 HHs

IMD stations data for 1970 to 2004

District Statistical Office Respective Block Headquarters

Households

Tables

DATA ANALYSIS

TRMM 2000 to 2014

Census Publications District Agricultural Office

AIRS 2000 to 2014

Tahsil and Patwari Circles

Downscaling at 0.25°x0.25° Livelihood Assets Status • Natural • Physical • Social • Health and Human • Financial

Regression/ Correlation

Multi-criteria and Pentagon analysis

Micro Level Sustainable Livelihood Framework

Isotherm and isohyet Maps

Surface creation using ArcGIS

Ranking/ Indexing

Time-Lines Matrix Analysis

SPSS COMPUTATION & ANALYSIS LIVELIHOOD VULNERABILITY Migration Shift in Seasonal Calendars Shift in Species/Crops Economic Diversification Livelihood Capital alterations

Spatio-temporal change maps from 1970 - 2014

Fig. 2.1 Methodological flow chart. Source By authors

H.P. In the present research, the data have been filtered sorted and refined so that it can be incorporated with the GIS platform to generate the proper thematic visualization for much clear result and feasible work plan in analyzing livelihood security in socio-economic environment of Kangra district.

2.6.2 Methodology and Data Analysis The correlation between irrigation intensity, agricultural productivity, cropping pattern, major cropping systems, farm machinery use and gaps in farm mechanization, existing block-level schemes for agriculture and rural development, block-level schemes for allied agricultural sectors, unemployment status, potential and current enterprises for employed/unemployed, distribution of workers and categories of farmers, block-wise demographic and institutional features have also been done with the help of SPSS version 20. Finally, the collected and processed data has been analyzed and tabulated for the preparation of Livelihood Security Indices (LSI)

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and maps to explain the status, vulnerability, and security of livelihood at village and block level. The spatio-temporal data analysis has been performed by using the following techniques:

2.6.2.1

Moving Average

It has been used to obtain the temperature and rainfall trend and variation over the years and decades.

2.6.2.2

Mann–Kendall Non-parametric Test

The Mann–Kendall test has been calculated for the 45 years (1970–2015) baseline temperature and rainfall data for the non-parametric test from: R=

i−1 n  

(xi − x j)T =

i=2 j=2

i−1 n  

(xi − x j)

i=2 j=2

where, n = data set length while xi and xj = standard chronological data values.  Zr = R −

√1 V



 Zt = T −

√1 V



The independent and randomly distributed variables from T max T min and T mean provide data set length n ≥ 3 similarly for Rtotal and Rdays where n ≥ 2. The nonparametric temperature statistic T and R are distributed normally with variance and neutral or zero mean. With the times-series length, the standardized test statistic is calibrated from Zt score for temperature and Zr for rainfall value to test the null hypothesis as: if variance V > 0, or V = 0 or V is < 0 The increasing temperature T max and T min trend indicate a + Z value and a decreasing T max and T min temperature trend indicates −Z value. The significant T max and T min levels of 0.05, 0.01 and 0.001 have been converted in to percent later.

2.6.2.3

Downscaling and Climate Change Scenario Modeling

For downscaling, the regional adaptive responses for climate change have been computed as; Csc = f (CL, Ᵽs)

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35

where, Csc is the micro-scale climate, which is downscaled through the functional relationship of C L is the large scale climate and Ᵽs is the micro-level physiographic details.

2.6.2.4

Livelihood Vulnerability Index Without Climate Change

For calculating the livelihood vulnerability and changing livelihood, 270 households from the sampled area of the district with semi-structured questionnaires were interviewed (individually and in groups). The village location has been taken as point coordinates and was saved on a hand-held GPS receiver to map the interview track. The exploratory inductive research, methodological triangulation have been done for obtaining data from different sources to increase the validity, reliability of the findings and simplify data analysis (Bierbaum et al. 2010; Swaminathan 2010; World Bank Group 2018). It was done to crosscheck individual interview answers, where the questions were focused on past and current livelihood indicators such as; household composition, general household livelihood security, net sown area availability, land use/change, crop production/combination, livestock, soil productivity, soil fertility, migration, education, the status of employment and earnings, transfers, social assistance and other income, household assets, urban agriculture, fish production, savings, loans, housing, environment, water and sanitation, daily food, consumption, illnesses, health, nutrition knowledge and practice, utilization of health care facilities, community participation, socio-economic conditions and constraints to improved livelihood. Above all the data were coded and seeded in SPSS 20.0 for calculation and analysis, the LVI concept has been operationalized mathematically as:  V=F

Ps − Pmin Pmax − Pmin

 +

n n 1 1 Di x − I Ri x n x=1 n x=1

Or can be summarized in the following way Vulnerability (V) = f (E + S − AC) In this equation, V is the vulnerability of the block/village, 1 is the exposure to vulnerability (reflected in the amount problem occurrences like flood/drought, etc.), S is the sensitivity to perturbation (like the sensitivity of produce to climate distresses), and Ac is the adaptive capacity to cope with exposure, that can be determined using socio-economic proxy indicators. Thus on this basis, the LVI has been calculated in the range of −1 to +1 where, −1 is the least vulnerable, 0 vulnerable, and +1 is the most vulnerable without the climate change factor.

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2.6.2.5

2 Drivers of Climate Change Research Pathways

Vulnerability Exposure Index Exposure(E) =

Ps − Pmin Pmax − Pmin

where 1 is the exposure in each season in the respective village, Ps is the latest year production or facility recorded, that is based on three years moving point average of increase or decrease in facility/production. Pmax and Pmin are the maximum and minimum values during the observation period.

2.6.2.6

Vulnerability Sensitivity Index

The Sensitivity has been calculated from S=

n 1 Dix n x=1

where average sensitivity is calculated by S, for the ith variable n is the number of drivers and Dix drivers the of the sensitivity of each variable.

2.6.2.7

Assessing Adaptive Capacity Adaptive Capacity(AC) =

n 1 I Ri x n x=1

where Ac is the average adaptive capacity of ith variable, n is the number of variables and IRix represents the influence of resilience.

2.6.2.8

The Climate Change Vulnerability Indices

The Tropical Rainfall Measuring Mission (TRMM), Indian Meteorological Department (IMD), and Atmospheric Infrared Sounder (AIRS) - NASA data Center is the main sources from where the data have been acquired and downscaled at latitude and longitude of 0.5° × 0.5° between 1970 and 2014 (44 years). AIRS gridded temperature data for the study has been obtained for the distribution, latent heat, and the variability of monsoon in terms of Outgoing Longwave Radiation (OLR) or Albedo, Length of Growing Period (LGP). The climate change indices have been prepared by using Climate Change Vulnerability Index (CCVI) equation through the following steps and then it has been overlaid on LVI results to calculate CCLVI or the climate impacted vulnerabilities on livelihood in the sampled villages of the Kangra district. To calculate the composite index of CCLVI, the LVI has been linked to CCVI. The

2.6 Data Base and Research Methodology

37

range of CCLVI lies between −1 and +1, where −1 denotes least vulnerable, 0 signifies vulnerable and 1 designates highly vulnerable, the calculation has been done through the following steps as; VPrt =

TProb − TPrmin TPrmax − TPrmin

where VPrt is the productivity of a particular crop has increased with temperature variable that has been computed based on 45 years data, TProb is observed productivity in that temperature range, TPrmin and TPrmax are minimum and maximum productivity at that temperature range. In other words, it is (observed − minimum) / (maximum-minimum). Finally, the CCVIs of all 27 villages have been clubbed together with their respective LVIs to show climate impacted livelihoods for all the respective Natural Capital Indices (NCIs), Physical Capital Indices (PCIs), Human Capital Indices (HCIs), Social Capital Indices (SCIs), and Financial Capital Indices (FCIs) across the district.

2.6.2.9

Measuring Livelihood Security Indices

When measuring livelihood security the key informant interviews, farmer’s observation, focus group discussions, geo-referenced household surveys, land cover analysis, scoring tools, published documents, and statistics have been considered. Livelihood sustainability and resource accessibility have been worked out from a large number of indicators including; percent population above the poverty line, percent of the working population to the total population, storage capacity for crops and perishable items, length of the surface road, etc. By using the technique of standard score in an additive model (combined Z-score) to a categorized level of livelihood security among 27 villages in 9 blocks, 5 capital indices were prepared. The outcomes in the form of results from the discussed tools, methods, and techniques have been represented by applying numerous diagrams, graphs, cartographic techniques, and thematic maps. Furthermore, the results and discussion have been made to outline the need for MLSLI (explained in the methodological framework).

2.7 Limitations of the Study The study focuses on climate change and livelihood security, where the change in climate has been evaluated and analyzed based on primary data collection and downscaling of the RCM. The high-quality RCM downscaling takes an exceptionally long time to compute every grid information. RCM to micro level is an extra burden of a petabyte of data computation. Besides this, the sensitivity of parameters, grid overlapping, uncertainty, local forcing plays a limiting factor. Changes

38

2 Drivers of Climate Change Research Pathways

in statistical parameters like; scale and surface topography (constant parameters) with dynamic weather parameters (mean, variance and coefficient), when applied to observed baseline time series, deliver moving uncertainties and errors associated with the dynamical downscaling technique. The IMD data was not persistently available for the entire time frame. There are few limitations arisen during the field survey also. The high hill region of the Multhan sub-tehsil and Dhauladhar range accessibility was a big question for the researcher, it generally takes 4–5 days of rigorous trek to reach Bada Bhangal. So the entire area could not be covered during the survey. Moreover, the study is based on sampled blocks and predicting climate-related changes at the block or village level is a little precarious.

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Gwimbi P (2009) Linking rural community livelihoods to resilience building in flood risk reduction in Zimbabwe. JÀMBÁ J Disaster Risk Stud 2:71–79 Hahn MB, Foster SO, Riederer AM (2009) The livelihood vulnerability index: a pragmatic approach to assessing risks from climate variability and change—a case study in Mozambique. Glob Environ Change 19:74–88 Hák T, Janouškova S, Moldan B, Dahl AL (2018) Closing the sustainability gap: 30 years after ‘our common future’, society lacks meaningful stories and relevant indicators to make the right decisions and build public support. Ecol Indic 87:193–195 Hinz R, Sulser TB, Huefner R et al (2020) Agricultural development and land use change in India: a scenario analysis of trade-offs between UN Sustainable Development Goals (SDGs). Earth’s Futur 8:e2019EF001287 Hiremath BN (2007) The changing faces of rural livelihoods in India. In: National Civil Society Conference: what it takes to eradicate poverty, held at institute of Rural Management, Anand, India, pp 4–6 Hobley M, Shields D (2000) The reality of trying to transform structures and processes: forestry in rural livelihoods. Overseas Development Institute IPCC (2001) Climate change: impacts, adaptation, and vulnerability. Cambridge University Press, USA IPCC (2018) Summary for Policymakers (SPM). Geneva, Switzerland Jain SK, Kumar V (2012) Trend analysis of rainfall and temperature data for India. Curr Sci 102:37–49 Jat R, Pathak P, Wani S et al (2014) Climate change mitigation and adaptation potential of conservation agriculture: Effects on rainwater use efficiency, runoff, soil moisture, soil organic carbon and energy use. Mitig Adapt Strateg Glob Change 12:11–12 Kamusoko C, Aniya M, Adi B, Manjoro M (2009) Rural sustainability under threat in Zimbabwe– simulation of future land use/cover changes in the Bindura district based on the Markov-cellular automata model. Appl Geogr 29:435–447 Kandlikar M, Sagar A (1999) Climate change research and analysis in India: an integrated assessment of a South-North divide. Glob Environ Change 9:119–138 Karl TR, Jones PD, Knight RW et al (1993) A new perspective on recent global warming: asymmetric trends of daily maximum and minimum temperature. Bull Am Meteorol Soc 74:1007–1024 Kates RW (2000) Cautionary tales: adaptation and the global poor. Clim Change 45:5–17 Kavi Kumar KS (2009) Climate sensitivity of Indian agriculture do spatial effects matter? Cambridge J Reg Econ Soc 4:221–235 Kimball BA, Idso SB (1983) Increasing atmospheric CO2 : effects on crop yield, water use and climate. Agric Water Manage 7:55–72 Körner C, Jetz W, Paulsen J et al (2017) A global inventory of mountains for bio-geographical applications. Alp Bot 127:1–15 Kriegler E, O’Neill BC, Hallegatte S et al (2012) The need for and use of socio-economic scenarios for climate change analysis: a new approach based on shared socio-economic pathways. Glob Environ Change 22:807–822 Krishnan R, Shrestha AB, Ren G et al (2019) Unravelling climate change in the Hindu Kush Himalaya: rapid warming in the mountains and increasing extremes. In: The Hindu Kush Himalaya Assessment. Springer, Berlin, pp 57–97 Kumar KR, Sahai AK, Kumar KK et al (2006) High-resolution climate change scenarios for India for the 21st century. Curr Sci 90:334–345 Lal R (2004) Carbon sequestration in soils of central Asia. L Degrad Dev 15:563–572 Leichenko R, O’Brien K (2008) Environmental change and globalization: double exposures. Oxford University Press Li Y, Li Z, Zhang Z et al (2019) High-resolution regional climate modeling and projection over western Canada using a weather research forecasting model with a pseudo-global warming approach. Hydrol Earth Syst Sci 23:4635–4659

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Ma M, Haapanen T, Singh RB, Hietala R (2014) Integrating ecological restoration into CDM forestry projects. Environ Sci Policy 38:143–153 McJeon H, Edmonds J, Bauer N et al (2014) Limited impact on decadal-scale climate change from increased use of natural gas. Nature 514:482–485 MEA (2005) Millennium Ecosystem Assessment, 2005. Ecosystems and human well-being: synthesis. World Resources Institute, Washington, DC Mehta L, Srivastava S, Adam HN et al (2019) Climate change and uncertainty from ‘above’ and ‘below’: perspectives from India. Reg Environ Change 19:1533–1547 Millar RJ, Fuglestvedt JS, Friedlingstein P et al (2017) Emission budgets and pathways consistent with limiting warming to 1.5 C. Nat Geosci 10:741–747 Mitra AK, Das GM, Singh SV et al (2003) Daily rainfall for the Indian monsoon region from merged satellite and rain gauge values: large-scale analysis from real-time data. J Hydrometeorol 4:769–781 Mora C, Frazier AG, Longman RJ et al (2013) The projected timing of climate departure from recent variability. Nature 502:183–187 NATCOM (2012) India: second National Communication to the United Nations Framework Convention on Climate Change. New Delhi Nelson EJ, Daily GC (2010) Modelling ecosystem services in terrestrial systems. F1000 Biol. Rep. 2 Nelson GC, Geoghegan J (2002) Deforestation and land use change: sparse data environments. Agric Econ 27:201–216 New M, Hulme M, Jones P et al (1999) Representing twentieth-century space–time climate variability. Part I: development of a 1961–90 mean monthly terrestrial climatology. J Clim 12:829–856 O’Brien KL, Leichenko RM (2003) Winners and losers in the context of global change. Ann Assoc Am Geogr 93:89–103 OECD (2020) Towards Sustainable Land Use. OECD Pandve HT (2009) India’s national action plan on climate change. Indian J Occup Environ Med 13:17 Park I-H, Min S-K, Yeh S-W et al (2017) Attribution of the 2015 record high sea surface temperatures over the central equatorial Pacific and tropical Indian Ocean. Environ Res Lett 12:44024 Parry ML, Canziani OF, Palutikof JP et al (2007) IPCC, 2007: climate change 2007: impacts, adaptation and vulnerability. In: Contribution of working group II to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge, UK Parry M, Palutikof J, Hanson C, Lowe J (2008) Squaring up to reality. Nat Clim Change 1:68–71 PMO (2008) Prime Minister Council on Climate-National action plan on climate change. New Delhi Qu B, Zhang Y, Kang S, Sillanpää M (2019) Water quality in the Tibetan Plateau: major ions and trace elements in rivers of the ‘Water Tower of Asia.’ Sci Total Environ 649:571–581 Rahut DB, Micevska Scharf M (2012) Livelihood diversification strategies in the Himalayas. Aust J Agric Resour Econ 56:558–582 Rajeevan M, Bhate J (2009) A high resolution daily gridded rainfall dataset (1971–2005) for mesoscale meteorological studies. Curr Sci 558–562 Rao SA, Dhakate AR, Saha SK et al (2012) Why is Indian Ocean warming consistently? Clim Change 110:709–719 Ratna Reddy V, Gopinath Reddy M, Galab S et al (2004) Participatory watershed development in India: can it sustain rural livelihoods? Dev Change 35:297–326 Rödenbeck C, Zaehle S, Keeling R, Heimann M (2018) History of El Nino impacts on the global carbon cycle 1957–2017: a quantification from atmospheric CO2 data. Philos Trans R Soc B Biol Sci 373:20170303 Rogers A, Medlyn BE, Dukes JS et al (2017) A roadmap for improving the representation of photosynthesis in Earth system models. New Phytol 213:22–42 Ropelewski CF, Halpert MS (1987) Global and regional scale precipitation patterns associated with the El Niño/Southern Oscillation. Mon Weather Rev 115:1606–1626

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Ruedi H, Baumgartner R (2004) In search of sustainable livelihoods: managing resources and change. Sage Publications Pvt. Ltd., California Sajjad H, Nasreen I (2016) Assessing farm-level agricultural sustainability using site-specific indicators and sustainable livelihood security index: evidence from Vaishali district, India. Community Dev 47:602–619 Schickhoff U, Bobrowski M, Böhner J et al (2016) Climate change and treeline dynamics in the Himalaya. In: Climate change, glacier response, and vegetation dynamics in the himalaya. Springer International Publishing, pp 271–306 Schild A, Sharma E (2011) Sustainable mountain development revisited. Mt Res Dev 31:237–241 Schott FA, Xie SP, McCreary JP (2009) Indian ocean circulation and climate variability. Rev Geophys 47 Scoones I (1998) Sustainable rural livelihoods: a framework for analysis. Institute for Development Studies, Brighton Singh RB (1998) Land use/cover changes, extreme events and ecohydrological responses in the Himalayan region. Hydrol Process 12:2043–2055 Singh RB, Hietala KR (2014) Livelihood security in Northwestern Himalaya: case studies from changing socio-economic environments in Himachal Pradesh, India. Springer, Tokyo Singh A, Jasrai Y (2012) Response of crops to elevated atomspheric carbon dioxide. Proc Indian Natl Sci Acad 78:45–49 Singh RB, Jha S (2014) Agriculture and forestry based livelihood capital assessment. Livelihood security in Northwestern Himalaya. Springer, Tokyo, pp 95–106 Singh RB, Mal S (2014) Trends and variability of monsoon and other rainfall seasons in Western Himalaya, India. Atmos Sci Lett 15:218–226 Singh RB, Sen Roy S (2002) Climate variability and hydrological extremes in a Himalayan catchment. In: ERB and Northern European FRIEND Project 5 Conf., Slovakia Singh RB, Singh S (2014) Human-Induced biome and livelihood security. Livelihood security in Northwestern Himalaya. Springer International Publishing, Netherlands, pp 53–66 Singh RR, Bhagat R, Kalia V, Lal H (2007) Impact of climate change on shift of apple belt in Himachal Pradesh. In: Impact of climate change on agriculture. ISPRS Archives XXXVIII-8/W3 Workshop Proceedings, pp 131–137 Singh N, Sharma DP, Chand H (2016a) Impact of climate change on apple production in India: a review. Curr World Environ 11:251 Singh RB, Singh S, Sen Roy S (2016b) Assessing climate change signals in Western Himalayan District using PRECIS data model. In: Climate change, glacier response, and vegetation dynamics in the Himalaya. Springer International Publishing, pp 103–115 Singh S, Kumar R, Bhardwaj A et al (2016c) Changing climate and glacio-hydrology in Indian Himalayan Region: a review. Wiley Interdiscip Rev Clim Change 7:393–410 Slariya MK (2014) Shifting from traditional food cropping to cash cropping. In: Livelihood security in Northwestern Himalaya. Springer, Tokyo 83-92 Sörlin S, Lane M (2018) Historicizing climate change—engaging new approaches to climate and history. Clim Change 151:1–13 Srinivasan N (2018) State of India’s livelihoods report, New Delhi Stehfest E, van Vuuren D, Bouwman L, Kram T (2014) Integrated assessment of global environmental change with IMAGE 3.0: model description and policy applications. Netherlands Environmental Assessment Agency (PBL) Stocker TF, Qin D, Plattner G-K et al (2013) Climate change: the physical science basis. Cambridge University Press, Cambridge, UK and New York, NY, USA Swaminathan MS (1991) Sustainable agricultural systems and food security. Outlook Agric 20:243– 249 Swaminathan MS (2010) Agriculture and food systems. In: Science and sustainable food security: selected papers of MS Swaminathan. World Scientific, pp 331–343 Teske S (2019) Achieving the Paris climate agreement goals: global and regional 100% renewable energy scenarios with non-energy GHG pathways for +1.5 °C and +2 °C. Springer Nature, p. 491

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Turner BL, Kasperson RE, Matsone PA et al (2003) A framework for vulnerability analysis in sustainability science. Proc Natl Acad Sci U S A 100:8074–8079 UNFCC (2018) UN climate change annual report. Bonn, Germany UNFCC (2019) Climate action summit. New York, USA Vaidya P, Randhawa S, Sharma P et al (2019) Climatic variability during different phenophases and its impact on temperate fruit crops. J Agrometeorol 21:366–371 WCED (1987) Report of the world commission on environment and development: our common future. Gro Harlem Brundtland. Oslo WCED (2018) Implementation of Agenda 21, the programme for the further implementation of Agenda 21 and the outcomes of the World Summit on Sustainable Development and of the United Nations Conference on Sustainable Development-(A/73/81-E/2018/59) Wheeler T, Von Braun J (2013) Climate change impacts on global food security. Science 341:508– 513 White S, Pfister C, Mauelshagen F (2018) The Palgrave handbook of climate history. Springer, Berlin World Bank Group (2018) World development report 2019: the changing nature of work. World Bank Yatagai A, Xie P, Kitoh A (2005) Utilization of a new gauge-based daily precipitation dataset over monsoon Asia for validation of the daily precipitation climatology simulated by the MRI/JMA 20-km-mesh AGCM. SOLA 1:193–196

Web References The Tropical Rainfall Measuring Mission (2020) https://gpm.nasa.gov/missions/trmm. Accessed 15 May 2020 The Atmospheric Infrared Sounder (2020) https://airs.jpl.nasa.gov/. Accessed 15 May 2020 Indian Remote Sensing (2020) https://bhuvan.nrsc.gov.in/data. Accessed 15 May 2020 Indian Institute of Tropical Meteorology (2020) http://cccr.tropmet.res.in/home. Accessed 15 May 2020

Chapter 3

Study Area: A Geographical Profile and Livelihood Pattern

Abstract The geographical profile of the study area is required to provide accurate, orderly, rational explanation and analysis of the location, physiography, resources including; elevation, slope, soil zones, water resources, kuhl irrigation, climatic conditions, the status of forests and vegetation cover, sanctum sanctorum variables, etc. It seeks to describe and interpret a brief description of land use, socioeconomic characteristics, demographic statistics, occupational structure, operational landholding size, infrastructure characteristics, accessibility to the health care system, social empowerment, work participation, etc. Keywords Physiography · Demography · Land use · Infrastructure · Social-economic empowerment

3.1 Introduction The district Kangra is characterized by varying altitudes and complex topography. The north-west to south-east traverse of the Shivaliks and Dhauladhar altitude varies between 427 m AMSL to around 5500 m AMSL. The districts of Chamba, Lahaul, and Spiti, make its boundary in the north, Hamirpur and Una cover it from the south, Mandi and Gurdaspur district bound it in the east and west respectively (Fig. 3.1). The existing district Kangra emanated from the reformation of districts of Punjab and Himachal by the Government of Himachal Pradesh on 1st September 1972. It was the largest district of composite Punjab in terms of the area earlier. The reorganization of composite Punjab on the 1st November 1966, the area constituting Kangra district was transferred to Himachal Pradesh along with the districts of Shimla, Kullu, Lahaul and Spiti and tehsils of Una and Nalagarh together with three villages of Gurdaspur district (Imperial Gazetteer of India 1864; Kant 1995; Mittoo 2001; Jreat 2006). In the year 1962, Kullu Tehsil got separated into another district. The same happened to the Lahul and Spiti that was part of Kangra, carved out later in the 1960s as a separate district. The area coins its name from Kangra town in ancient Nagarkot region that was having Kangra fort and was formerly a portion of the early Trigarta region during Mahabharat time, which comprises of the area lying between the river © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 S. Singh and R. B. Singh, Simulating Climate Change and Livelihood Security, Advances in Geographical and Environmental Sciences, https://doi.org/10.1007/978-981-16-4648-5_3

45

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3 Study Area: A Geographical Profile and Livelihood Pattern

Fig. 3.1 Locational setting and administrative division of Kangra district, 2011. Source By authors based on Government of India

Shatadroo (Sutlej) and Ravi. A tract of land to the east of Sutlej that probably is the area of Sirhind in Punjab also formed a part of Trigrata that had two provinces. One in the plains with headquarters at Jullundur and the other in the hills with headquarters at Dharmasala (the present Kangra). Being hilly western Himalayan district having 94.29% of the district’s rural population direct dependence on climatesensitive livelihood opportunities. The variability in climate is giving birth to the new challenges into these limited adaptive capacities and less accessible hill regions.

3.2 Location and Extent Kangra is positioned in the Western Himalaya with an extent of 31° 2 to 32° 5 N and 75° to 77° 45 E (Fig. 3.1), constitutes a geographical area of around 5,739 km2 , which is 10.31% of the total geographical area of Himachal Pradesh, with 15 blocks, 19 tehsils, 519 patwari circles, 748 g panchayats, 3908 revenue villages, and 7 Nagar Nigams (Municipal Councils). The lowest altitude being in the plain areas bordering Gurdaspur district of Punjab in the west, Una and Hamirpur districts to the south while the highest being amidst the Dhauladhar mountain range which forms the border with Chamba and Kullu districts (Fig. 3.6f) (Government of India 2011).

3.2 Location and Extent

47

It is covered under the Survey of India topographical sheet number 43P, 44M, 52D, 52H, 53A.

3.3 Physiography and Climate The district is considerably having diverse physiography therefore, it has been distributed into five sub physiographic divisions; the Pir Panjal (high hills), Dhauladhar (wet sub-temperate), the Shiwalik (foothills region), the Kangra Valley, and the Beas Basin (Ranital region). The Bada and Chotta Bhangal areas lie in the high hill region of Pirpanjal, which originates from the district boundaries of Mandi, Kullu, and Chamba. The valley region is cumulatively formed by Palam, Kangra, and Nurpur valley. The Palam valley includes areas of Agogar, Ghatta, Ghanetta, Kandwari, Chobu-Chobin, Baijnath, Pahra, Dheera, etc. The valley area of the district includes areas of; Malan, Yol, etc. The foothills of the joining Punjab province are characterized by the Nurpur valley in the southwestern part of the Kangra. The areas dropping between foothills and Nurpur valley make the Changar region of the district. The Shivalik foothill region is characterized by Paragpur block. This block starts from the Dhaliyara and passes through the Sansarpur terrace falls. The entire region is having an undulant mountainous terrain with the varying altitude that ranges from 427 m to 5500 m AMSL (Wadia 1966). The slope escalation is gradual till about 1500 m AMSL thereafter it becomes steep suddenly. The region is having a maximum longitudinal length in the east to the west track of about 150 km starts from the Baijnath to Indora block. Whereas in the north Rait block to south direction till Pragpur block it extends to a distance of about 100 km. apart from the 15% of the total area that falls in Nurpur Tehsil, the entire district is mountainous. Several abysmal valleys comprising vast territory lies between the mountainous ranges of varying elevations. On the altitudinal basis, the district has been divided into three distinct zones (Government of Himachal Pradesh 2012). These are: • The Low hills and valley areas run up to an elevation of about 901 m AMSL. This particular part accounts for about 49.1% of the total area in the district. • The Mid hills region extends from 902 m to 1501 m AMSL and is nearly 16% of the total area of the district. • The High hills region rising from about 1502 m to 5501 m AMSL account for the remaining 34.9% of the total region. The district climate conforms along the low hills, valleys to mid and high hills. The sub-tropical climate is found in the low hills and valley region, the sub-humid to temperate in the mid and high hill region respectively. The region receives around on an average 205 cm rainfall annually. There is a disparity in the distribution of rainfall as it falls about 100 cm in the southern parts and goes on to 250 cm in north-eastern areas (Government of India 1883; Ganguly et al. 2015). Maximum rainfall of about 80% is received from June to September months (monsoon months). In contrast,

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3 Study Area: A Geographical Profile and Livelihood Pattern

Fig. 3.2 Average annual temperature and rainfall in Kangra. Source By authors based on IMD data

Table 3.1 Season-wise average annual temperature in Kangra

Seasons

Months

Temperature (approximate) (°C)

Monsoon season

From July to September

2–24

Winter

December to February

0–20

Summer

April to June

25–38

Source IMD (2010)

the average annual rainfall in the state is 1850.6 mm, comparatively very high than the national average (Fig. 3.2). The Dharamshala, Multhan, and Baijnath areas in the northern part receive snowfall. The average maximum temperature ranges in the district are about 35 °C in southern parts to around 25 °C in northern parts during summers (India Meteorological Department 2010). The season-wise average annual temperature in the district exhibits high temperature ranges between 25 and 38 °C while in winter and rainy season the temperature goes as low as 0 °C in north-eastern parts of the district (Table 3.1 and Fig. 3.3).

3.4 Forests The total forested area in this district is around 284.18 hundred km2 (Table 3.2). One of the most picturesque valleys of the lower Himalaya, sheltered by the sublime Dhauladhar range, looks green and luxuriant. It provides a tremendous contrast like places. The region is having four distinct types of forests dispersed in its Dharamshala, Dehra, Nurpur, and Palampur division. Besides these four divisions, the Una forest block controls an additional set of two forest divisions (Forest Survey of India 2015;

3.4 Forests

49

Fig. 3.3 Annual mean maximum and minimum temperature profile of the Kangra district. Source By authors based on TRMM and IMD on Inverse distance weighting (IDW) method

Table 3.2 Forest types in Kangra district by area, 2018–19 (ha) Category

Region

Total

Dharamshala

Dehra

Nurpur

Palampur

Reserved forest

137.81

3210.3

4252.73

–

7600.84

Demarcated protected forest

33,340.05

2837.14

6053.74

13,294.40

55,525.33

Un-demarcated protected forest

2725.71

7814.03

25,324.75

103,208.89

139,073.38

Unclassified

–

16,523.36

17,112.89

17,188

50,824.25

Others*

630.01

4712.04

215

1186

6743.04

Total

36,833.58

35,096.87

52,959.11

134,877.29

259,766.85

Source Forest Survey of India

Sharma et al. 2019). intotal seven wide ranging types of forests have been identified in the district can be classified as.

50

3 Study Area: A Geographical Profile and Livelihood Pattern

3.4.1 Alpine Forests Dry Type They are open types of forests, mainly concentrated in the Chota Bhangal and Bada Bhangal areas in the district. The flora in these wooded areas is largely xerophytes; Cotoneaster Juniper, Artemisia, Lonicera, etc.

3.4.2 Moist Alpine Scrub Forests This forest category is flourishing between the snow-line and the tree growth line in Dhauladhar range of the district. Commonly characterized by grassland in its southern slope and scrubland on the northern slope. The main plant species found in these forests regions are; Salix, Lonicera, and Viburnum. Numerous therapeutic aromatic plants, herbs like; Commiphora Wightii (guggal), wolf’s bane, L. Aconitum Napellus, karru, Ranunculaceae, etc.

3.4.3 Sub-alpine Forests The forests of these types are characterized by a grassland having dispersed substandard and often hemmed in by Kharsu oak tree, maple tree, etc. These types of forests are found as a sandwich between the moist Alpine and dry Alpine forests that originates above the altitude of 3500 m. AMSL. Betula-utilis and Kharsu stand as the two principal types found in these sub-Alpine forests category. At definite elevation, the Himalayan temperate parklands are found, which are used for grazing by nomadic sheep and goat herds usually carried along by Gaddi’s (trans-human).

3.4.4 Himalayan Moist Temperate Forests The district is having a large area under the elevation range of more than 1500 m but less than 3000 m. AMSL is characterized by this forest type. The Cedrus deodara is the most valuable species found here whereas, spruce and the silver firs are also found in areas of mixed coniferous forests. Such forests occur in Kangra and Palampur tehsils.

3.4 Forests

51

3.4.5 Wet-Temperate Forests The forests of these categories are found primarily in Dharamshala, Palampur, and Kangra region of the district. The two major species in wet-temperate forests category are the Chir and Kail found along the wet hill slopes of the mountain. Few patches of exquisite Ban oak and silver fir have also been recorded in the region. The bamboo groves shelters around the lower reaches of the west slope, where the long sturdy Deodar trees are usually found neighboring.

3.4.6 The Tropical Hill Forests It can be classified into two as; (a) sub-tropical pinewood forests like; Pinus roxburghii. These types are found at elevations between 1000 and 2200 m. AMSL in the lower Shiwalik region in Dehra and Nurpur areas. (b) The sub-tropical broad leaves hill forests include Khair, tun, siris, kachnar, beul, bamboo, and other broad leaves found below 1000 m. AMSL, be located in the Pragpur, Dehra, and Indora forest zones. The actual and recorded forest area shows a differential pattern. Rendering to lawful forest classification the aggregate recorded area under forests is 259.76 hundred km2 that comes to 49.8% of the total geographical area. However, the existing forest area is 144.3 hundred km2 that can be counted as 1/4th the total geographical area (Forest Survey of India 2015). Comparatively, the district is having good forest cover, which only comes after Chamba, Shimla, Kullu, and Mandi districts of Himachal Pradesh (Table 3.3). The soil erosion, scarcity of water, and poor infrastructures are some of the highlighted major problems with which the district suffers.

3.5 Water Resources 3.5.1 The River There are two major rivers that dominates the district. The biggest one is Beas together with its tributaries, drains central and other parts excluding the extreme north-eastern part which is drained by the river Ravi. The drainage system of both rivers is characterized by structural slopes and river terraces. The Beas altogether constitute the central drainage system, it arrives in the district near village Harsi from the east and follows the regional slope by moving towards the west. It is having several south-flowing tributaries and khads. The khads in the district are completely snow fed and perennial in nature and originate from high ranges in Dhauladhar. The Neugal, Binnu, Naker, Awa, Gaj, Baner and Dehar khads are south flowing and perennial

52

3 Study Area: A Geographical Profile and Livelihood Pattern

Table 3.3 Comparative status of forest area and tree-covered area in the districts of Himachal Pradesh Districts

Total geographical area

Total forested region

Total tree-covered region (km2 ) Very dense forest

Moderate dense forest

Open forest

Total forest cover

Per cent of total area

Bilaspur

1167

428

24

171

167

362

31.02

Chamba

6522

5030

853

773

810

2436

37.35

Hamirpur

1118

219

39

92

114

245

21.91

Kangra

5739

2842

310

1221

531

2062

35.93

Kinnaur

6401

5093

82

263

257

602

9.40

Kullu

5503

Lahaul and Spiti

13,841

Mandi Shimla

4952

586

789

583

1958

35.58

10,133

15

32

146

193

1.39

3950

1860

373

735

565

1673

42.35

5131

3418

739

1037

608

2384

46.46

Sirmaur

2825

1843

130

568

685

1383

48.96

Solan

1936

728

55

404

390

849

43.85

Una

1540

487

18

298

205

521

33.83

Total

55,673

37,033

3224

6383

5061

14,668

26.35

Source Forest Survey of India Report (2015)

while the north-flowing streams are transient in nature called ‘choes’ causes flash floods during the monsoons. Table 3.4 outlines various khads/streams together with their catchment area, that includes the upstream, downstream, and constituents of the Pong reservoir including; Banganga, Neogal, Awa Gaj, Dehar, Bohl, and Nand Khads Table 3.4 The principal tributaries of the Beas River

S. No. Name of Rivers/Khads

Total catchment Characteristics (area in km2 )

1

Nand khad

39

Joins directly

2

Buhl khad

104

Pong Ram Dam

3

Dehar khad

477

Pong Ram Dam

4

Gaj khad

616

Pong Ram Dam

5

Bunner khad 782 (Banganga Khad)

Pong Ram Dam

6

Pola khad

47

Pong Ram Dam

7

Naker khad

184

Joins Beas river

8

Neogal khad

–

Joins Beas river

9

Binno

–

Joins Beas river

Source Annual administrative district panchayat report, 2017

3.5 Water Resources

53

Nadaun. Being perennial and snow fed, these khads are characterized by U-shaped glacial valleys, truncated spurs, V-shaped deep valleys, moraines, etc. The upstream valleys are narrow and canyon shaped while the downstream are wide with a gentle slope/gradient. The course of these rivers is structurally controlled. The gradient of the slope together with the flow of the river is being exploited since ancient times. The gravity channels have been made by locals called Kuhls for diverting water flow in lower reaches. These small channels are being used for small hydro-power generation, irrigation, and public usages. Even in recent times several other small and medium hydro-power projects are being considered based on ancient khuls system (Baker 2007). The width of these stream channels varies from less than a kilometer to more than 2 km. The channel areas are generally devoid of vegetation. These rivers contribute to the fertility of the land. There are two important lakes in the district, namely; Dal Lake and Kareri.

3.5.2 The Beas Basin This 752.68 km2 basin area has dried up after the construction of the Pong Dam in Dehra Gopipur region in the district, where the large area has been reclaimed by inhabitants. This area is prone to floods whenever excess water is released from the Pong Dam (Figs. 3.4 and 3.6e).

3.5.3 The Maharana Pratap Sagar or Pong Dam Reservoir The Maharana Pratap Sagar also is known as the Pong Reservoir, which was created in 1975, by building the highest earth or earthen dam in India on the river Beas. It forms a major wetland zone, declared by the Ramsar Convention. This wetland is famous for its wildlife sanctuary. Out of the total area, the reservoir covers an area of 24,529 ha and the wetland spreads over almost 15,662 ha (Fig. 3.6e). Moreover, this area provides the most important reservoirs and fishing zone in the Himalayan foothills of Himachal Pradesh. During the rainy season, the excess water of the Beas River is released downstream to Pandoh Dam to augment the flows that are impounded in the Pong Reservoir.

3.5.4 Major Rivulets Neogal, Uhl, Chakki, Binva, Banganga, Gaj, Hehar, Bhul, Tall and Luni are major rivulets, are generally perennial and known as khad in the district (Table 3.4).

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3 Study Area: A Geographical Profile and Livelihood Pattern

Fig. 3.4 Major drainage profile of the Kangra district, 2011

3.5.5 Khad and Reservoir The district is characterized by both natural and artificial reservoirs. The Kareri and the Dal reservoirs are natural in landscape and located in the upper reaches of Gaj khad at an altitude of 2083 m and 3000 m. AMSL, respectively. The Kareri is a perennial lake, located in the Mecleodganj area of Dharamshala. Due to its strategic location, this lake has witnessed harsh impacts of urbanization. It has been converted to a silted small pool and only revives during the monsoon season. Another bunch of glacier lakes is also found between 4650 and 4850 m. AMSL in the Bada Bhangal region of the Beas river catchment (Srikantia and Bhargava 1998). On the other hand, an artificial reservoir on the Beas has been constructed in 1974 known as the Pong Reservoir. Through a diversion channel, the normal flow of the river Beas has been diverted to Pandoh and later to the river Sutlej (Govind Sagar-Bhakra Dam). The diversion has been made as such that it can generate hydro-electricity for the benefit of the entire region.

3.5 Water Resources

55

3.5.6 The Kuhl Irrigation The district is well drained by several rivers, streams, rivulets, and springs but besides these gravity channels are the epoch’s old technique that redirects water from various small rills to the agricultural fields. Regardless of constitutional rights in Indian states on water, the Kuhls continues to be the utmost appropriate system in the local conditions. Nevertheless, the present arrangement proposes a copious possibility for upgradation in the Kuhls system by sealing losses through leakages. This district stands in the top two when considering the list of the highest proportion of area under irrigation in the state of Himachal Pradesh. The net irrigated area is 25,116 ha, which is 22.8% of the gross irrigated area of the district (Table 3.5). Kuhls serves 88.78% area in the district stands as a chief source of irrigation. Even at the state level it dominates and covers 80% of the area under its irrigation network, whereas, remaining 6% is irrigated by private wells, 3% area is irrigated by private lift irrigation, and 2% by private tube wells. The (Department of Agriculture 2019a). Table 3.5 Comparative status of sources of irrigation in the state and district, 2016–17 (ha)

S. No.

Irrigation sources

Kangra (%)

Himachal Pradesh (%)

1

Canals (government)

–

4495 (3.93)

2

Tube wells (government)

–

10,979 (9.59)

3

Tube wells (private)

700 (2.08)

7541 (6.59)

4

Tank

–

282 (0.24)

5

Gravity channels (Kuhls)

29,767 (88.66)

81,735 (71.45)

5.1

Government

–

3758 (4.59)

5.2

Private

44 (0.13)

77,977 (95.41)

6

Lift irrigation (government)

–

1341 (1.17)

7

Lift irrigation (private)

1005 (3.00)

2586 (2.16)

8

Wells (government)

–

778 (0.68)

9

Wells (private)

2056 (6.13)

4797 (4.19)

Total irrigated land

33,572 (100.00)

114,381 (100.00)

Source Department of Agriculture (2019a, 2019b)

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3 Study Area: A Geographical Profile and Livelihood Pattern

3.5.7 The Underground Water The first Hydrograph Grid Station was founded in the district by the Geological Survey of India (GSI) in the year 1969 for spatio-temporal monitoring of groundwater levels. Subsequently, several hydrological and geological studies are being conducted in the district by the Central Ground Water Board (CGWB) and GSI. These studies are mostly concentrated around the Pong Dam area and adjacent Nurpur and Indora blocks. The dynamicity of groundwater resources inventory has been assessed only for these two given blocks and the rest are in the process. Annually the level of water is actually being monitored in each quarter by CGWB where the total utilizable groundwater reserves are 60.96 Metric Cubic Meter (MCM) and the net amount available is 13.54 MCM. This leaves a surplus of 47.42 MCM intended for additional usage. With the current phase of groundwater monitoring and development, the district was having 22.2% area under the ‘white’ category in the year 1992. But gradually increased around 2% by 1997 (24%) and witnessing steady rise since then. The utilizable irrigation potential has been assessed around 12,830 ha procured from natural recharges (CGWB 2013). The groundwater is constantly revitalized by the uninterrupted supply through the Kuhls. But still, the complete potential of groundwater resources is still unexplored whereas Palampur and Kangra valley fills, which are readily available are yet to be assessed.

3.5.8 The Water Harvesting Water harvesting may prove very beneficial in the district as it receives the average annual rainfall of about 2500–3000 mm (India Meteorological Department 2010). Where most of the rainy days lie in the monsoon months of June, July, and August (JJA). Throughout the winter season when the amount of precipitation is not adequate for agricultural purposes, the traditional measures of water harvesting have been extremely valuable (Singh and Singh 2014; Singh et al. 2016). The agrarian economy of the district is dependent on several small scale water harvesting units since ancient times, even today those are still very feasible and consistent with the economics of forthcoming development. The indigenous knowledge and technology for natural resource conservation and management including water resources have been growing to support local livelihood during the tough winter months but requires to speed up more through Public–Private Partnership Model (PPP).

3.6 The Soils Soils of the district are largely divided into three broad categories; Alfisols, Entisols, and Inceptisols, where these have been reclassified again into three sub-groups and

3.6 The Soils

57

further into twenty-four soil family groups. The soils order from outer Himalayas to Shivalik varies greatly in their typology. The lesser/outer Himalaya is characterized by sandstone, slate, quartzite, phyllites, and gneiss, while the unsorted alluvial deposits of calcareous conglomerates, sandstone, shale are found in the Shivalik region. The climate and regional topography play a pivotal part in shaping the physical appearance of the soil. The foothills of the Dhauladhar range of the district demonstrate clearly established A and B horizons with deep and fine textured soils. Whereas, the soils of Shivalik are characterized by thinto moderately thin profiles. These soils are having coarse to medium consistency (Wadia 1966; Raychaudhary and Govinda Rajan 1971; Yadav and Thakur 1972; Singh and Rowbotham 1995; Sidhu 1997; Srikantia and Bhargava 1998). In general, the soils are neutral in response with the exception of which are found in Baijnath, Panchrukhi, Bhawarna, Nagrota, Kangra, and Rait blocks. Available phosphorus is medium to low and deficiency is particularly noticed on maize, wheat, and soybean crops in blocks of Baijnath, Panchrukhi, Bhawarna, Nagrota, Kangra, and Rait, where soil pH is in the acidic range. Organic carbon is low to medium in Dehra, Nurpur, Indora, and Lambagoan blocks, while medium to high in the rest of the blocks. Available potassium is medium to high. The soils in the district have a very diverse profile that varies from low hill to medium and high hill region (Department of Agriculture 2019a) (Fig. 3.6f).

3.6.1 The Soils of Lower Hill The lower hill zone soils outspread up to an elevation of 910 m. AMSL. These soil types have been brought and deposited by the running water in the foothill, covers the area of Nagrota Surian, Nurpur, Indora, Paragpur, Dehra, and part of Rait block, characterized by a thin horizon and coarse grains (implanted with gravel, stones, and pebbles). In this part of hill zones, only valley bottoms are having scarce amount of alluvial soils and the rest are concocted by choes (north-flowing tributaries) those have put massive expanse of coarse-grained sand in this region. The alluvial soils comprise of great amount of clay, rich in organic matter, lime and iron but deficient in phosphorus, and nitrogen contents. It is a neutral soil reaction zone (pH = 7) having carbon and nitrogen of ratio 10:1 are fairly appropriate for the cultivation of rice, wheat, and vegetable farming (Yadav and Thakur 1972).

3.6.2 The Soils of Middle Hill The middle hill zone starts around 910 m. AMSL and runs up to 1517 m. AMSL spread in chir pine trees and mixed deciduous forests region of Kangra and Rait. The mid-hill soils are greyish-brown in color, loamy to clay-loam in texture so it is well drained. Being rich in iron, potassium, carbon and nitrogen but deficient in lime and phosphorus having neutral to slightly acidic (pH ≥ 7) are very suitable for

58

3 Study Area: A Geographical Profile and Livelihood Pattern

maize, wheat, and tobacco cultivation. The carbon-nitrogen ratio fall between 10:1 and 12:1.

3.6.3 The Soils of High Hill This zone covers the areas just above the mid-hill zone, falls between 1517 and 2122 m. AMSL. The soils of this zone are nitrogen rich but lack in potash and phosphorus because it has been formed in the mixed forests on steep slopes made of silt-loam to clay-loam having good drainage. Organic matter is medium to high is the reason for its dark brown color (Fig. 3.5).

3.6.4 The Mountainous Soil The mountain soils are found between 2122 and 3034 m. AMSL elevations ranges. Its rich organic matter caused dark brown color and its texture varies from loam to silt-loam found in the central sub-division of Palampur, Kangra and Nagrota are well drained. The soil reaction is moderately acidic (pH ≤ 7) is rich in iron and carbon, but deficient in mineral constituents, salts and other.

3.6.5 The Soils of Dry Hill The dry hill zones are found between 3100 and 5500 m. AMSL covering the Bada and Chhota Bhangal region. These two are divided by Thamsar pass at the elevation range of 4500 m. AMSL falls in the Baijnath block. This soil zone is usually very poor and infertile besides having medium to high organic content, it is only good for bushes, shrubs, and vegetables.

3.7 Rocky-Mineral Resources The large body of undifferentiated crystalized substance of mineral is known as rocks. The Shiwalik group is most famous for having different formations of shale, sandstones, and clay rock type, the major ones are; Subathu, Salooni, Manjir, Jutogh, Shali, and Sundarnagar formations. The rocks of Subathu formation are extremely complex structures of outer Himalaya, formed throughout late Palaeocene to mid Eocene, spread between Manji and Manuni, adjacent to Karti, Bhanjerl, and Rakh. This group of fine-grained ferric oxide rich green shales and fossil-rich limestones comprises rocks of the oldest Himalayan foreland basin. The silica rich (SiO2 ≤

3.7 Rocky-Mineral Resources

59

65%) granitic and gneissic rocks of Dhauladhar located in the Main Boundary Thrust (MBT) formed during the Miocene period that spread to a breadth of five kilometers are of this group only. The rocks of this group spread into several kilometers on the extensive precipitous hill ranges at northward facing fault scarps of Nurpur, Kangra, Jawalamukhi, Kotla, Dehra Gopipur, and Damtal region of the district (Srikantia and Bhargava 1998). The Salooni formation which is a terminal Proterozoic establishment on the basic lava flow is exposed at Dhamsar pass. The Permian Salooni comprising black shale, calcareous slates, phyllites, schists, and limestones. The Manjir formation is basically famous as Manjir Conglomerate that forms the core of huge anticline which can be seen between Bada Bhangal and Kankarna, subjugated by quartzite, phyllite, and limestone. The older rocks here in the district belong to the Jutogh, Shali, and Sundernagar formations comprising basically slate, schist, dolomite, quartzite, marl, and basic lava flows. The Jutogh is the oldest group of rocks in given three formations that can be seen along the stretch from east of Bir to Dharmkot. The Sundernagar formation of basic lava flow is well exposed between the north of Tundi khad, Luni, Sansal khad, and Chakki nala. The Mandi-Darla volcanic rock patches are found in small squares near Sansal khad, Bir khad, and Luni. The Shali formation is only visible along the frontal part of Larji-Kullu-Rampur window in the form of a thickly bedded group of fine-grained blue-grey dolomite. The Dharamkot region is having cement grade limestone and salt grits from the Shali formation (Wadia 1966). This district is having far rich economically substantial rock types but only slates and limestone are used for marketable exploitation. The followings are.

3.7.1 Slates The slate mining zone is mostly limited within reserved forests perimeters. That is why the Ministry of Environment and Forests is required to give authorization for mining under the Forest Conservation Act, 1980. Being widely used as a roofing substance consists of phyllites and slates, its mining is limited to Chandpur formation of Bhagsunath, Khaniara, Thatri, Narwana, and Kareti region, dated back to the 1880s (Srikantia and Bhargava 1998). Initially, these diggings were functional only by the local contractors from the local panchayats having mineral rights but lately, the GOI has reserved mineral rights with scientifically organized mining techniques.

3.7.2 Limestone The cement rating limestone is located two kilometers north of McLeodganj at Dharamkot. The thickly bedded Shali formation having pink, dark grey, dolomitic limestone and shales, where the earlier two (the pink and dark grey) having the

60

3 Study Area: A Geographical Profile and Livelihood Pattern

largest reserves around 19 million tons, are like cement (Economic and Statistics Department 2020).

3.7.3 Coal, Natural Gas, and Oil The foreland fold and the thrust belt of this region have been under vigorous investigation for hydrocarbons since the commencement of the Oil and Natural Gas Corporation of India (ONGC) in 1956. The thin limestone bearing from Subanthu formation is famous for several surface oil gas seepage consisting methane (87%), a small amount of CO2 , N2 and O2 together with other non-commercial gas. Subsequently, numerous investigative wells have been bored even at a depth of 6500 m to establish the fact that the original deeply concealed Subathu formation is having coals/carbonaceous shale that may be a probable source rock for this gas (Wadia 1966). Even though the commercial detection of hydrocarbons has been subtle till date, but the poly-tectonic tertiary basin of the Jawalamukhi is considered most promising while another region Nurpur and Balh are having similar methane value (all are in Dharamsala structural region).

3.7.4 Sand, Stone, and Bajri The Kangra district was extracting 428,712 tons of sand, stone, and bajri from its khads/rivers annually by the year 2005 which has increased additional five folds during the last thirty years. By 2015 more than 200 crushers and stone grinders were available in the district and employing 2500 people directly into extraction.

3.7.5 Iron Ore These ore deposits are learned from the oldest Himalayan foreland basin at the Uhl valley in the district. Its formation band is having average outcrop width of 20 m visible for about 2500 m from Multhan to Kothi Kohar in the form of fine-grained ferric oxides, green shales, and fossil-rich limestones. The district is famous for iron ore (limonite type), olivine, and magnesite extraction, limonite is poorer quality ore having yellow color comprising 40–60% iron but advantageous in mining because of easy and low-priced mining (Economic and Statistics Department 2020).

3.8 Sanctum Sanctorum

61

3.8 Sanctum Sanctorum The historical city Kangra is mentioned in several texts at Vedic times. It is having more than 3500 years old culture that has witnessed quite a lot of invasions. Presently, it’s headquarter is Dharamsala, that is also the headquarters of the Tibetan government in exile. It is commanded by the His Holiness Dalai Lama. The important area is Jwalamukhi, which is also recognized as Jwalaji. Jwalaji is a very eminent ancient temple contained its name on the goddess of divine conflagrations. The incessant fire runs on its natural gas. Other significant temples include Brajeshwari Devi temple, Chamunda Devi temple, Chintpurni temple, Bhagsunag temple in McLeodGanj, Mahakal, and Baijnath’s Shiva temple in Baijnath block. The world-famous Masrur rock temple devoted to Lord Shiva is having a style of North Indian Nagara architecture and is motivated by the framework (Fig. 3.6d). There are also some key Buddhist temples in Dharamshala like the Sidhbari and the Bir Tibetan Colony in Bir with several historical villages viz., Pragpur and Garli (Fig. 3.6a).

3.9 Socio-economic and Demographic Profile 3.9.1 Demography The Census of India 2011 reports depicts the overall population of the Kangra is 1,510,075 of which 750,591 are male and 759,484 are female, the highest in the state (22% of the population) with 262 people/km2 . The district is having a high sex ratio, standing with 1013 females per thousand males in 2011. The Scheduled Tribes (STs) population remained low ≤1% while the Scheduled Caste (SCs) accounted for 20.91% of the total population of this district (Government of India 2011). There are twenty-one community developmental blocks in 2019 (after the recent reorganization of the district). Earlier these were nine, increased to fifteen in the year 2001. The Dharamsala block was later added after the year 2000. In the Census year 2001, the total population was 1,339,030 increased from 1,174,072 (1991) witnessing an increasing trend but with slow growth. The decadal growth rate of the population has reduced evidently because of the increase in literacy rate and awareness levels regarding family planning. The literacy rate remained at 86.49% in 2011, with male and female literacy 91.5 and 80.02 respectively. The male literacy rate is higher in comparison to females (Table 3.6).

3.9.2 The Economy The district is characterized by the agrarian economy, where an immense population is reliant on farming activities. The cultivation of tea, vegetable, horticulture

4,237,569

5,170,877

6,077,248

6,856,509

2001

2011

1,510,075

2011

1991

1,339,030

2001

1981

1,174,072

1991

Persons

965,848

Year

1981

Per cent to state

100

100

100

100

22.00

22.03

22.71

22.78

15.59

17.39

20.79

22.46

19.40

14.01

18.50

20.56

Decadal growth (%)

Source Government of India, District Census Handbook-Kangra (2011)

H.P.

Kangra

Population

123

109

93

76

263

233

205

168

Density

(person/km2 )

Table 3.6 The demographic structures of district Kangra vis-à-vis Himachal Pradesh Sex ratio (F/1000M)

974

970

984

988

1013

1027

959

1058

90.48

86.02

75.36

52.36

92.5

88.19

80.12

56.7

Male (M)

Literacy (%) Female (F)

75.33

68.08

52.13

31.39

80.62

73.57

61.39

39.79

Total

89.96

77.13

63.86

41.94

86.49

80.68

70.57

48.01

62 3 Study Area: A Geographical Profile and Livelihood Pattern

3.9 Socio-economic and Demographic Profile

63

Fig. 3.5 The spatial distribution of physiography, soils, and 3D slope of the Kangra district. Source By authors

plays a crucial role in the economy. Whereas Kangra tea is famous worldwide for its rich aroma, taste and color have occupied in the areas of Palampur and Baijnath. With the upcoming modernization few small scale industries have also come up including; water packaging, building supplies, and potato chips. Tourism has always shared a significant portion of the economy, Dhauladhar trek, Biling, and Bir region have already been developed centers for ecotourism and aero-sports. Several forts in Kangra fort (Fig. 3.6c) and Nurpur fort (Fig. 3.6b) attracts lots of tourists. The district economy is primarily agrarian engaging directly 66.4% of the working population. Agriculture and allied sector contribute around 18.63% in the Gross State Domestic Product (GSDP) annually (2018–19). Interestingly, the domestic product of the district raised at a 13% annual rate during 1993–94 to 2001–02 equivalent to the State Domestic Product of Himachal. The districts per capita income (PCI) (at current prices in |) have improved from |6927 in 1993–94 to |18,127 in 2001–02 to |86,637 in the year 2018–2019, recording a rise of 11.28%/annually. Depending upon the data it can be said that in terms of PCI Kangra has improved a lot among all Himachal Pradesh districts. It was standing at 9th rank (1993–94) and leaped to 5th during 2018–19 (Table 3.7). It can be understood through a simple statistic that during 1993–94 the maximum PCI was found in Lahaul and Spiti district. It was standing with triple fold income in comparison to Kangra, but by the economic year 2018–19 it has successfully minimized the gap to only

64

3 Study Area: A Geographical Profile and Livelihood Pattern

Fig. 3.6 a The sixteenth century heritage village Garli in Rakkar, b The Pathania rajput’s-Nurpur fort, c The Kangra fort, d Henotheistic Masrur rock temple near Nagrota Bagwan ara> Table 3.7 Comparative per capita income status for the year 1993–94 to 2018–19 (at present values in |)

Economic year

Kangra

Himachal Pradesh

1993–94

6927

7870

1998–99

13,846

16,144

2003–04

22,241

28,333

2008–09

38,787

49,903

2013–14

69,883

114,095

2018–19

86,637

147,277

Compound annual growth rate

12.60

11.51

Source Economic and Statistics Department

3.9 Socio-economic and Demographic Profile

65

1.25 times (Economic and Statistics Department Government of Himachal Pradesh 2017). Even though its share of the primary sector has degenerated from 39.4 to 32.8%. Contrastingly to other districts of Himachal, its secondary economic sector reached to 27.46% (2019–20) from 20.7% (1993–94). Whereas the tertiary sector grew from 28.01% in 1993–1994 to 65.08% (2018–19). Unexpectedly, the input of service sector continued stationary at about 40% over the previous decade that was conflicting with the national tendencies of striking progress in recent times. However, it is noteworthy that the compound annual growth rate of the district is higher (12.60) as compared to the H.P. state average (11.51) in 2019 (Table 3.7).

3.9.3 The Occupational Structure The district, as well as the state, shows the predominance of an agrarian economy. Almost, 66.4% of the total workforce is in primary sector. This sector of the economy is having both public and private sections where workforces primarily rely on for their basic livelihood services. The laborer in agriculture, animal husbandry, and allied services accounts for almost 7% of the total workforce. It further divulges that there has been a marginal decline in the agriculture dependent work force since 1981, and an increase in other sectors. The district has the largest number of (3.4 hundred thousand) cultivators, as compared to 19.6 hundred thousand cultivators are in the state (Table 3.8). The agro-climatic situations are very advantageous for the cultivation of horticulture, sericulture, apiculture (bee-farming), fungiculture (mushroom cultivation), pisciculture (fisheries), poultry, and dairy farming, etc. These diversifications in primary and allied sectors of the economy is having a great potential in strengthening the economy through regeneration, curbed youth migration, and superfluous employment prospects. Therefore, it can be said that the primary sector of the economy Table 3.8 Comparative status of workers distribution in Kangra and H.P. (%) Year Kangra

HP

Total workers

Cultivators (%)

Agricultural laborer (%)

Total (%)

Other

1981

248,393

60.04

5.87

65.91

34.09

1991

300,274

56.27

6.58

62.85

37.15

2001

589,442

56.98

6.66

63.64

36.36

2011

564,543

56.73

6.61

63.34

36.66

1981

1,436,284

69.44

2.93

72.37

27.63

1991

1,729,089

65.19

3.52

68.71

31.29

2001

2,991,448

65.55

3.10

68.65

31.35

2011

3,189,543

65.81

3.00

68.81

31.19

Source Compiled from the Economic and Statistics Department, Government of Himachal Pradesh

66 Table 3.9 Land utilization pattern (in km2 )

3 Study Area: A Geographical Profile and Livelihood Pattern Area under usage

Total area in km2

Area under cultivation

515.5

Area under horticulture

13.92

Area under tea cultivation

4.81575

Under orchard area

12.41

Area put under non-cultivation

882.5

Area under Forest

939.72

Source Department of Agriculture, Government of Himachal Pradesh (2019a)

here in the district needs special attention from the government because it not only absorbs underemployed/unemployed workers but also generating alternative livelihood for future sustainability. The total land available for horticulture is almost 14 km2 while for tea, it is 4 km2 in the district (Table 3.9). These cultivators require both an extensive and intensive use of land for production to sustain their lives and livelihoods.

3.10 Temporal Pattern of Land Use The land utilization pattern in the districts has continued almost unchanged over the years. The maximum geographical area (55%) falls in the category of forest and pastured land. Thus, the further scope for extension of cultivation is restricted. Almost 20% of the total geographical area is under cultivation, and 13% area is under non-agricultural uses in the district (2018–19). The fallow land and land put to non-agricultural uses are continuously increasing and even this region is witnessing alteration in the land put to agricultural uses due to a substantial increase in nonagricultural land prices (Table 3.10). There has been extensive construction along the roads in the peripheral region having luxury real estate, hotels, and other new buildings together with the upcoming construction of infrastructural amenities on prime cultivational fields is not a new scene in the district. The current scenario of development urgently requires a prudent land-use policy to save this vital agricultural land conversion into non-agricultural uses.

3.10.1 Land Utilization Across rural areas in India land is a vital asset that regulates the entire socioeconomic position of the family. Its dispersal and development are dependent upon numerous indicative driving forces, incorporating directly and indirectly into agricultural advancement. The sustainable agriculture development is directly linked to

40.08

39.43

40.28

40.16

40.18

40.20

1990–91

1995–96

2000–01

2005–06

2010–11

2015–16

2.22

2.19

3.12

2.52

0

6.37

Barren land

13.64

13.64

13.42

13.36

14.33

13.59

Non-agricultural land uses

4.72

4.78

4.74

4.72

7.02

8.81

Culture able wasteland

15.15

15.16

15.14

15.77

17.06

8.13

Pasture

Source The Economic and Statistics Department, Government of Himachal Pradesh

Forest land

Kangra

Table 3.10 The land utilization pattern changes from 1990 to 2016 (in %)

1.30

1.36

1.34

1.26

0.37

0.8

Misc. Trees/groves

1.95

1.91

1.83

1.63

1.62

1.38

Current fallow

0.07

0.06

0.07

0.05

0.75

0.07

Other fallow

21.22

21.01

20.18

20.42

19.41

20.78

Net sown area

3.10 Temporal Pattern of Land Use 67

68

3 Study Area: A Geographical Profile and Livelihood Pattern

the landholding allocation that plays a crucial role in the reducing gap between the rich and the poor. Therefore, an in-depth investigation regarding land utilization has been done in the rural areas of Kangra. This can be seen through varying land utilization patterns in different blocks in the district (Table 3.11). This district is having huge land diversity, its Baijnath block is having the largest geographical area which is almost nine times larger than the smallest block (Panchrukhi), Dehra stands in the second position trailed by the Rait block. Nevertheless, the proportion of the geographical area of the blocks did not align with the proportion of area under cultivation. Since Panchrukhi records the largest area available for cultivation (40.73%) followed by Indora (37.13%) and Nurpur (36.45%). On the other side, it was quite low in Baijnath (4.83%), Rait (7.81%), and Dehra (16.73%). The total area under irrigation facilities is quite high across Kangra with few exceptions. In the Bhawarna region, 80.58% of the cultivated area was under irrigation during 2015–16. The areas like Sulah, Panchrukhi, Rait, and Nagrota Bagwan had more than 50% irrigated area against the respective cultivated area. The areas where less than 10% of the expanse is under irrigation were; Nurpur (7.04%), Lambagaon (6.52%), Nagrota Surian (4.21%), and Dehra (1.6%). Whereas, the forest area is concerned Rait had the highest proportion of geographical area under forests (66.22%) trailed by the Baijnath (63.51%) and Bhawarna block (54.28%). The blocks of Fatehpur (15.56%), Dehra (16.20%), and Lambagaon (18.07%) were found to have the minimum forest cover. The proportions of cultivable wastelands were moderately high in the Fatehpur block (30%), Lambagaon (25%), Sulah (23.39%), and Pragpur (23.17%). The Dehra block is having almost 50% area not available for cultivation, which is very high, followed by Pragpur and Lambagaon (30%) and the Baijnath block (28%) (Government of India 2017; Department of Agriculture 2019b).

3.10.2 Operational Landholding Size The distribution of holdings in the Kangra district depicts the predominance of marginal and small landholding sizes. Kangra is currently having around 224,759 operative landholdings, out of it approximately 209,505 ha area was under cultivation. More than 74% of the holdings in the district are marginal (

67.36

15.63

55.94

54.23

Net irrigated area (%)

70 3 Study Area: A Geographical Profile and Livelihood Pattern

5.33

4.41

3.66

3.27

3.22

1990–94

1995–09

2010–11

2015–16

22.35

26.17

27.98

30.42

33.43

42.13

7.04

7.28

7.86

8.41

9.02

10.32

22.21

22.16

22.07

23.35

22.23

21.23

76.77

75.15

73.63

74.22

71.21

67.10

No

29.31

29.32

28.06

26.34

26.14

19.42

Area

Marginal (4 Ha)

1980–84

Year

Table 3.12 Land holdings variations over the year 1980–2016 (%)

14.42

14.3

14.85

15.42

16.32

17.11

No

22.35

22.33

21.89

21.12

21.33

19.01

Area

Small (1–2 ha)

232,551

229,690

224,759

215,008

191,185

166,722

No

Total

266,274

206,581

209,505

208,142

212,082

219,119

Area

3.10 Temporal Pattern of Land Use 71

72

3 Study Area: A Geographical Profile and Livelihood Pattern

voice of concern for policy intervention. The normal size of landholding in the district is merely 0.92 ha as compared to 1.14 at the state as a whole (Department of Agriculture 2019a). With the reduced size of holdings, the involvement in agriculture is less profitable and do not provide reasonable income and employment to sustain families of the farming community. This has generated a grave absentee ownership problem with a precipitous increase in migration from rural to urban or to semi-urban areas for off-farm jobs and wage job exploration. It requires a distinct horizontal and vertical employment diversification in synchronization with multi-level planning so that the rural youth migration can be bunged.

3.10.3 Agriculture—As a Principal Means of Livelihood The one-fourth of the food grain production of the state is produced from the Kangra. Where rice, wheat, maize, and pulses contribution individually are relatively high with 45, 26, 20, and 14% respectively. The district occupies quite an amount of area under oilseeds (39%), fruits and vegetable crops (20%), the non-food grain crop (12%) of the state. The greater portion of oilseeds are from Palam valley. The area under fruits and orchards (orange, kinnow, mango, and litchi, etc.) are accounted in the sub-tropical area with relatively plaintopography in the district. The production of the main cereal crops stands parallel with the areas including wheat, rice, barley, food grains, vegetables, and oilseeds with under these crops/crop groups, the production of maize, pulses, and fruits are miserably low in the district. The food grain crops account for over 90.17% of the total cropped and the respective shares of the major cereals of wheat, rice and maize are 42, 17, and 27%, respectively (Table 3.13). Recently, diversification of crops together with off-season vegetable culture has been adopted by the district farmers besides the traditional vegetable cultivation in Nagrota Bagwan, Kangra, Shahpur region. Several additional regions including Lambagaon and Chhota Bhangal have also included their names in leading the offseason vegetable cultivation. Tea is a traditional crop, grown over 2321 ha expanse is still a hopeful opportunity under non-food grain crops category (Government of India 2018).

3.11 The Infrastructure Characteristics The study region accounting for 10.3% of the total geographical area is the fifth largest in terms of the state population. Being an agrarian economy almost two-thirds of the population is directly involved in agriculture.

3.11 The Infrastructure Characteristics Table 3.13 Crop wise area in district (2010–11)

S. No.

73 Crop types

Production area in ha Kangra

Himachal Pradesh

1

Rice

37,144 (44.60)

83,273

2

Maize

58,685 (20.02)

292,801

3

Wheat

91,775 (25.53)

359,439

4

Barley

2,575 (10.91)

23,596

5

Pulse

4,100 (13.61)

6

Total Food grains

1,94,728 (24.05)

7

Oilseeds

6,623 (38.76)

17,089

8

Vegetables (all)a

7,392a

(11.85)

62,356

9

Fruits

45,523 (20.41)

223,035

30,128 809,753

Source Department of Economics and Statistics Note Fig in additions specify proportions of state totals a Comprises potato and ginger

3.11.1 Infrastructure This sector is having resilient regressive and advancing connections to generate development. It involves all kinds of infrastructure including physical, social, economic infrastructure. The banking, financing, real estate, roads, railways, telecommunication facilities, electricity, construction activities, etc. This sector is having the capacity to generate ranges of livelihood prospects that involve both skilled and unskilled workforce. It has put the previously unconnected economic system into mainstream, converging livelihood options by diverging networks. Concerning the topography of this hilly district of Himachal Pradesh, there are lots of hurdles in putting up any infrastructure but its visionary Dr. Y. S. Parmar the first Chief Minister of Himachal Pradesh has eruditely given a mantra, ‘paharon mein sirf sadak de do, vikas apne aap ho jayega’ (just gives roads in the hills the development will be followed automatically). This slogan has surprisingly shaped this region and its performance has been lauded by all after that. The vision has been followed by the consecutive governments, therefore, its evaluation was mandatory thus approximately eight indicators have been pondered which are having direct relation to the infrastructure. It includes road density (both paved and mud roads per ’00 km2 of the area), road connectivity, transportation availability within 5 km in the villages, access to banking (commercial bank and post office) within 5 km of distance, cooperative societies in each village (including self-help groups, mahila mandal), the proportion of villages having local/government power facility, number of Fair Price Shops (FPS) per 10,000 of the population of the region (Table 3.14).

74

3 Study Area: A Geographical Profile and Livelihood Pattern

Table 3.14 Comparative status of infrastructures across blocks in Kangra in per cent Block

Road density

Trans Faci.

Power

Comm. Bank

Coop. Soc.

PO

Irri.

FPS

Pragpur

149.2

59.9

90.5

39.4

50.3

60.2

3.9

5.4

Bhawarna

76.9

59.9

98.1

59.8

69.8

62.1

20.0

9.7

Dehra

62.1

50.1

94.2

50.0

48.8

80.3

0.2

9.1

Nagrota Bagwan

143.5

57.9

90.7

39.9

63

64.6

17.3

6.9

Sulah

199.8

72.3

95.4

51.8

66.4

72.2

18.1

9.2

Indora

138.8

51

91.4

26.2

57.6

68.6

8.4

7.4

Kangra

105

54.9

95.4

51

75.3

61.5

11.5

5.1

Lambagaon

324.4

60

96.3

56

56.4

71.4

1.7

10.6

Baijnath

18.4

61.6

90.1

56.8

55.9

59.7

2.1

9.0

Rait

100.7

47.4

94.1

42.8

57.6

60.6

8.9

9.0

Fatehpur

205.1

41

94.1

52.1

69.4

75.2

2.9

4.2

Nagrota Surian

93

47.6

89.2

43.4

50.5

26.4

1

5.3

Nurpur

209.3

59.4

93.1

43

59.1

71.9

2.6

8

Panchurki

128.3

67.7

96.4

65.9

73.6

67.1

27.4

7

Total

121.6

56.3

94.1

48.4

62.5

68.2

6.2

6.3

Source District Human Development Report Kangra, Department of Planning, Government of Himachal Pradesh, 2011 Note (road density in per ’00 km2 of area), Trans. Faci.—Transport The facility, Comm. Bank— Commercial Bank, Coop. Soci.—Cooperative Societies, PO—Post Office, Irri.—Irrigation, FPS— fair price shops

3.11.2 Road Density The road density is a ratio of the total length of road including paved roads and mud roads taken together per 100 km2 of the area. The district is having a fair density of roads 121.61 km/km2 . But the disparity exists between different high altitude blocks. The maximum road density is found in Lambagaon block (324.45 km). It is almost 19 times more than the bottommost block Baijnath in terms of road density (18.6 km). The plain accessible region having a higher density of roads, i.e., Nurpur (209.33 km), Fatehpur (204.67), and Sulah (200 km) while the lower reaches at Pong dam and rugged region of Baijnath block is characterized by low road density. Nagrota Surian (92.95 km), Bhawarna (76.9 km), and Dehra (62.15 km) fall in the lower road density category (Department of Planning 2011).

3.11 The Infrastructure Characteristics

75

3.11.3 Transportation Facility The role of transportation can hardly be ignored in the modern era. Since von Thunen’ land-use classification its significance in agriculture and other sectoral development can not be ignored. This service saves lots of time, effort and brings accessibility even for market produce. The study region is having a fair density of roads so the level of transport is also in quite a good shape, where the blocks like Sulah is having 71.42% of villages under a good transport network within a distance of 5 km. trailed by Panchrukhi (68%) and Bhawarna (61.39%). On the supplementary side the far reaches and high hill regions; Nagrota Surian (47.64%), Rait (46.38%), and Fatehpur (41.04%) are struggling with low transportation facilities in the current situation (Department of Planning 2011) (Table 3.14).

3.11.4 Electricity Facility This self-reliant district is having almost 93% electrified villages on average in each block. The villages in Panchrukhi, Sulah, Lambagaon, and Bhawarna, have been highly electrified (>95%). Even the blocks which are considered having less electrified villages like Nagrota Surian (89.15%), Baijnath (89.09%), and Pragpur (87.5%) is having much better electricity infrastructure than most of the plains capital district’s villages (Department of Planning 2011). Kulhs in Kangra provides local sustenance through small scale hydro-electricity systems across all high, mid, and low altitude villages.

3.11.5 Banking Infrastructure Facility This infrastructure plays a very critical role in rural capital creation because it accumulates the isolated savings of the rural population through different deposit schemes. It allocates loans/funds to different sectors for starting a productive and self-reliant economic action. The availability and accessibility to banking facilities in high hill region villages are a big question. Several governmental policies for rural farmers, land less workers as kisan credit card, jan-dhan yojna, etc. have been started to provide financial support to the people in productive ventures. Ease of use to banking also supports in improving rural savings. The government, commercial and cooperative society’s banks act alike. For livelihood capital examination banking infrastructural have been calculated and results have been depicted in the later parts of results. The primary examination revealed that the accessibility to commercial banks (that are available at a distance of less than 5 km from all the villages in each block) was maximum in Bhawarna (59.86%), Panchrukhi (65.86%), and Lambagaon (56%).

76

3 Study Area: A Geographical Profile and Livelihood Pattern

While the least proportion of villages were found in Pragpur (39%), Nagrota Bagwan (40%), and Indora (26%) block (Department of Planning 2011; HDR 2019).

3.11.6 Cooperative Societies The district is having fair access and availability to the cooperative credit societies. Only in the Kangra block is having agricultural credit societies in around 73% ofvillages located within a radial distance of 5 km. The Panchrukhi (73.65%) and Bhawarna (69.8%) block closely follow it while the Nagrota Surian (51%), Pragpur (50%), and Dehra (49%) stand at a lower margin.

3.11.7 Postal Facilities The post offices have been pivotal in initial banking, investment, and development of rural India ever since and before Independence. This critical role witnessed a dynamic spatio-temporal shift through the telecommunication revolution. The instant mobile banking, transfer, paytm and google pay have been introduced recently where the where accessibility/reachability used to be the biggest hurdle in the hill region to fulfill the motto of ‘har haath ko kaam do, aur har kaam ko pura daam do’ (give work to each hand and pay the money to all the working hands). It has been found in the primary investigation that those blocks which are having the least presentation in commercial, private, and modern baking facilities are having better postal facilities. The blocks like Dehra, Fatehpur, and Sulah, having respectively 80.3, 75.2, and 72.2% of the villages equipped with postal services within a distance of 5 km. While the little developed blocks including Rait (61%), Pragpur (60%), and Nagrota Surian (26%) have been poorly performing.

3.12 Health Care Institutions (PHCs) One way of looking at the health infrastructure across the blocks is to examine the accessibility to the health care institutions in terms of distance. At the district level, 37.56% of the total villages were found to have PHCs within a distance of 5 km and 30.53% of the villages had PHCs within a distance of 5–10 km. Further, around a fourth of the total villages had PHCs beyond a distance of 10 km. Across nine of the total fourteen blocks, the percentage of the villages having PHCs in the range of less than ( x  j i

(4.11)

where, n is the extent of the time successions, x = values at times i and j (even that time when j ≥ i or ≤ i). After this, through the standardized test statistic, the significance of the trend has been calculated for relating it to the standard significant

96

4 Kangra: Climate and Climate Change Scenario Modeling

normal variate. z = s/[var(S)]0.5

(4.12)

Here the z score test evaluates the strength of the variables of the climatic trend which are based on ranks. The variance of S is as follows: Variance(S) =

n(n − 1)(2n + 5) 18

(4.13)

For the study area in testing the null hypothesis, the significance level (a) was taken 5% (a = 0.05) where +ve values of z shows an increasing trend vis-à-vis.

4.4.5.6

Sen’s Slope Estimator

The Sen’s slope estimator provides the linear rate of change in climatic variables (on time successions) after the Mann–Kendall test. The set of linear slopes has been considered (Sen 1968) as follows: dk =

x j − xi for(n ≥ j ≥ i ≥ 1) j −i

(4.14)

where, d k is the slope at k = 1, 2, …, n x = signifies the climate variable at i and j times n = the extent of temporal succession. Afterward, the trend magnitude has been calculated from the slope estimator (bSen ) that was considered from the median for all the linear slopes acquired from Eq. 4.14. Similar to z-score, bSen + ve value shows an increasing trend vis-à-vis in the time successions.

4.5 Results and Discussion 4.5.1 The Observed Spatio-temporal Change in Temperature The temporal change in temperature and rainfall have been plotted based on the monthly decadal average for the region for four nearly decades namely; 1970–1990 and 1990–2014. The summer (June) and winter (January) temperature in 1990–2014 have witnessed variable change (Government of Himachal Pradesh 2012; Singh and Singh 2014; Forest Survey of India 2015). The maximum and minimum temperature increase ranges between 0 and 0.8 °C. While a noticed decline of almost 10 cm of

4.5 Results and Discussion

97

rainfall during three months summer monsoon (June, July, and August) average from 49.3 cm (1970–1990) to 39.3 cm (1990–2014) has been perceived whereas the winter rainfall months as; November, December and January have seen the decline of 4.5 cm from 7.6 cm during 1970–1990 to 3.1 cm during 1990–2014. Comparably, IPCC Fifth Assessment Report (AR5) has observed global amplification in the average surface temperature is around 1.74 ± 0.18 °C (2.33 ± 0.32 °F) during the twentieth century steered by the increasing emission of GHGs ever since the last century (IPCC 2018). During the last 44 years, the temperature has shown great variability with an average rise of about 0.5 °C for the June month. The average temperature during 1970–1990s rose from 22.9 to 23.7 °C during 1990–2014 though the temperature graph shows a decline in temperature in the later part (Fig. 4.4). The mean annual temperature of Kangra district shows a significant warming trend of 0.8 °C per decadal year through the period 1970–2014. It represents a considerable increase in the rate of warming in the last four decades. Therefore, the aggregated data from seven meteorological stations; Nurpur, Dharamsala, Pong Dam, Palampur, Kangra, Malan, and Dehra have been computed on the spatial scale in this Cwa type of climate. The average annual temperature ranges between 10 and 26 °C in January month while in the summer month of June the temperature ranges between 14 and 36 °C. The district’s climate changes from sub-tropical in low hills

Fig. 4.4 Comparative status of average monthly decadal rainfall (cm), maximum and minimum temperature (°C) of Kangra district for 1970–1990 and 1990–2014. Source By authors computation based on gauge data

98

4 Kangra: Climate and Climate Change Scenario Modeling

and valleys to sub-humid to temperate in the mid and the high hills respectively. Southward and eastward latitudinal shifts in isotherms have been observed and it is markedly visible in the central and southern sections of the district over 1970 and 2014. Meanwhile, a marginal shift has also been witnessed by the northern and extreme eastern section of the region (Fig. 4.5a, b). The January isotherm of 12, 14, and 20 °C has noticed a strong shift similarly in the case of June isotherms. The major shift in June isotherms can be noticed in 20, 22, 30, and 31 °C isotherms, which are passing through central and western tracts where the general direction of the shift is southwestward. The winter isotherms show maximum deviation where 10 and 12 °C isotherms are shifting much northward and 20 °C isotherm in intruding in central and eastern blocks of the district. Over the last 30 years, Palampur and Baijnath have witnessed 16 and 18 °C isotherm shift towards more northward during June and Dehra Gopipur, Kangra, Pong Dam have been witnessing the average northward and central shift in 30, 32 and 36 °C isotherm which pass through western and southern parts in the district (Fig. 4.5a, b). The mean annual temperature displays a substantial trend of warming of 0.06 °C/10 year all through the period till 1970 and 0.22 °C/10 year during the recent decade of 2000–2014. During the last three to four decades it shows a significant increase in the rate of warming; therefore, it portrays a major turnaround in the asymmetry of the diurnal trends of temperature. From spatio-temporal analysis, it is quite evident that the temperature change ranges between 0 and 0.5 °C during summer months with a western and central section in Nurpur, Fatehpur, Dehra and Kangra are experiencing the highest change between 0.6 and 0.8 °C in the month of June over the years. The least change in temperature of about 0–0.2 °C has been seen in the eastern part of the Bada Bhangal, Tarmehr, and Baijnath region. For the winter season, the maximum change noticed is of 1.0–1.2 °C and a minimum of 0.2–0.4 °C respectively in the western and eastern regions. The trends of temperature rise in October–January months are just reverse of what one can observe from June to July months. The T max and T min trends are determined for the entire Kangra region with the help of the Mann–Kendall non-parametric test to evaluate the probability of temperature test that how it is statistically different from zero. In this test the parameters are always in sequential order and depending upon the number of occurrences or chances greater than the mean is counted. While Sen’s method has been used to find out the increase as well as a decrease in the slope of trends in the temperature time series during the same time period of 1970–2014 (Sen 1968). The Mann–Kendall non-parametric test for the independent and randomly distributed temperature and rainfall variables for T max , T min , T mean , Rtotal and Rdays provides data set length n ≥ 5, whereas the temperature and rainfall statistic are distributed normally with the variance and neutral or zero mean. The increasing temperature T max and T min trend indicate a + Zt value and a decreasing temperature trend indicates −Zt value. The significant T max and T min levels of 0.05, 0.01, and 0.001 have been converted into percent to plot the monthly deviation in the data graph (Fig. 4.6). On a regional level, the variation in mean maximum and minimum temperatures from 1970 to 2014 has observed a net escalation in temperature ranges from 0.86 °C ± 0.04 °C.

4.5 Results and Discussion

99

Fig. 4.5 a Spatio-temporal change in January isotherm and b Change in the June isotherm for the years 1970 and 2014. Source By authors

100

4 Kangra: Climate and Climate Change Scenario Modeling

Fig. 4.6 Mean seasonal temperature pattern in Kangra district over the period of 1970–2014 and T max and T min graph of mean monthly change in climatological records (percent) during 44 years. Source By authors based on Mann-Kendal and Sen slope geospatial analysis

The five color categories of seasonal temperature change ranging from less than 0.0 °C to more than 0.75 °C of Kangra district with a general rise in mean seasonal temperature in all its blocks from 1970 to 2014 explains that the temperature variability has increased over time. The North-Eastern Multhan, Baijnath, and small adjoining parts of Bhawarna are the only area to experience a decrease in seasonal temperature. A very significant increase in the north region (between 0.45 and 0.75 °C), including; Talnu, Satobari, Naddi, Bhagsunag, Dal lake, and Barafar has been observed. The temperature trend is not uniform over the north-eastern region and annual temperature has risen by 1.5 °C in the last century with winter warming (Bhutiyani et al. 2009; Bhutiyani 2016). An increasing trend of temperature in post monsoon and winter while decreasing trend in monsoon has been observed for Nurpur, Pancrukhi, Baijnath, and Dehra Gopipur, whereas Multhan has experienced warming during the last 100 years (Based on data analysis). An increase in temperature 0.0–0.25 °C has been observed across Lambagaon, Rait and the very northern portions of Kothi Koher of Baijnath block, while an increase between 0.25 and 0.5 °C has been found along Palampur, Sulah, Paragpur, and the southernmost part of Kundalia and Jawalamukhi. Lastly, a small noticeable increase of less than 0.25 °C has been observed in much of southern Multhan, north and western parts of Rait and Nagrota Surian, the south-western part of Jaisinghpur tehsil including Thural

4.5 Results and Discussion

101

sub tehsil. From 1970 to 2014, approximately 51% of the total area and almost 52% of the total population of the district has experienced 0.25–0.5 °C increase (Fig. 4.6). Approximately, 14.5% of the population acknowledged a more significant increase of 0.75 °C and more, signifying almost 30.1% of the total district’s geographical area. The longitudinal temporal trend has also been analyzed separately from TRMM data and the graph provides valid reasoning on latitudinal climate change over time besides temporal and spatial isothermal shifts. This trend has been computed at the grid level of 180 × 360, which has been downscaled to 3 × 4 (latitude x longitude) grid level. There are three latitudes (30° 5 N 31° 5 and 32° 5 N) together with four longitudes (74° 5 E, 75° 5 , 76° 5 and 77° 5 E) on which the temperature variations have been computed for around a decade from 2003 to 2014 for three months (June, July, and August). This has been plotted through the MATLAB program (Fig. 4.7). The climate modeling and simulation in MATLAB program for past, present, and futuristic situations of changing weather, atmosphere, and terrestrial

Average T=20 ˚C Av. Precipitation =250cm RH= 66.4

Fig. 4.7 The cleaning outlier data for geophysical flows data and parallel algorithm analysis in MATLAB for temperature and precipitation on longitudes in the study region. Source By authors

102

4 Kangra: Climate and Climate Change Scenario Modeling

ecology explains its interpretation through differential equations to model climate dynamics with geophysical flows and parallel algorithms analysis (Fig. 4.8a–c).

Fig. 4.8 Longitudinal distribution of mean annual seasonal temperature trend, a June, b July and c August months. Source Downscaled and computed from raw TRMM data from NASA by authors

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103

4.5.2 The Simulated Temperature Trend The simulated trend is often computed in the time domain where the common procedure of fitting a linear trend assumes that the parameter is not constant over time. The basic assumption of simulated temperature trend modeling is the warming of the planet rather than a simple result of time, therefore; it has a function with numerical significance. The temperature computations for Nurpur, Kangra, and Bada Bhangal have been used to regress and project the scenarios. To circumvent minor anthropogenic and other problems in the global temperature, the signals are computed using an ensemble of the RCMs. The modeled RCM results constitute a comprehensive representation of the current identification of the methods of climate variability and change. The AR-WRF based simulation on combined TRMM, AIRS, and IMD grid data has been used. The regional mean temperature records of the grid output on the Kangra district is showing a slow and steady increase in temperature for 2020, 2050, and 2080. The inter-annual temperature component is also computed to observe the accurate point from where the departure in temperature has been taken place. It has been plotted by the difference between black and green traces in the figure for the residual. The trend (red), decadal (green), and inter-annual (blue) lines are marked in order to display the time scale as applied to an averaged area of each block (Fig. 4.9). The temperature scenario processing consists of three steps. Firstly, the screening of the individual grid box values for the chronological data, secondly, the de-trending; to extract slow changes, and lastly, filtering to isolate the high and low-frequency constituents. The temperature data is processed in 3 × 3 grid, the averaging over grid boxes are then performed before the time scales for Kangra district. The result of simulation modeling for the 2020s signifies swelling GHG concentrations and throughout warming. The overall annual mean surface air temperature is projected to rise by 0.86–1.2 °C in the 2020s. The winter months are getting warmer by around 0.25 °C near the end of 2020s except for the Bada Bhangal region. This particular region displays contrasting results. The mean temperature variability during the winter months is more as compared to summer, monsoon, and post-monsoon months. As per result, the annual mean temperature of the district is anticipated to increase from 1.2 ± 0.5 °C to 2.3 ± 0.69 °C during the 2020s and 2050s respectively.

4.5.3 The Observed Spatio-temporal Precipitation Trend The land and the ocean surface evaporate water after being heated by the solar radiation that then gets transfer through the winds in the atmosphere, finally condenses to form clouds to fall back to the surface of the earth as precipitation. The amount of it varies, over decades and from year to year, changes in its amount, frequency, intensity, and type (snow or rain) affect the environment, society, and livelihoods. Where the steady and moderate rainfall is soaked by the soil and benefit the plants, the same amounts in a short period may cause local flooding, landslide, runoff, and

104

4 Kangra: Climate and Climate Change Scenario Modeling A

Jan 1970

Jan 2000

Jan 2019

Variation Trend

Jan 2050

Jan 2080

Jan 2000 Jan 2019 Jan 2050

Jan 2080

C

Jan 1970

Jan 2000

Jan 2019 Jan 2050

Jan 2000

Jan 2019

Jan 2050

Variation Trend

B

Jan 1970

Jan 1970

A’

Jan 2080

Jan 1970

Jan 2000

B’

Jan 2019 Jan 2050

Variation Trend

Jan 1970

Jan 2080

Jan 2000 Jan 2019 Jan 2050

Jan 2080

C’

Jan 2080

Fig. 4.9 The Simulated trend lines for differential decadal (a–c) and Annual (a –c ) variation during 1970, 2000, 2019, 2050 and 2080 for a Nurpur, b Bada Bhangal and c Kangra blocks. Source By authors, computation based on raw data processing, downscaling and simulation of IMD and AIRS. Note Bada Bhangal is having downward negative differential decadal and annual trend in thermal climate exhibit inconsistent signals of cooling in the high altitude north-eastern blocks, in the district as compared to other parts in the region

leaving the soil in the poor condition. The temperature variability provides a very vital control on precipitation its amount and type due to the water vapor holding capacity of the air at a particular temperature (Schwab et al. 2016; Gaji´c-Cˇapka et al. 2018). As climate varies or changes, several direct influences alter precipitation amount, intensity, frequency, and type (Gerlitz et al. 2016; Li et al. 2019). The local information on spatio-temporal variations for water management in agriculture, power generation, and drought monitoring is important in understanding the hydrological balance. Almost 80.5% of total rainfall received in the district is during the southwest monsoon season (June–September). The average annual rainfall in the district is around 250 cm overall but it exhibits variability in its southern and northern areas where it receives about 100 cm in

4.5 Results and Discussion

105

southern parts and 250 cm in the areas of its northeast. In contrast, the average annual rainfall of the state is around 125.5 cm, this monsoonal rainfall is crucial for the agrarian economy of Kangra (India Meteorological Department 2010; Basannagari and Kala 2013). The real-time rainfall monitoring and observation on its daily distribution record are essential to evaluate its progress and status. That plays a pivotal role in initiating necessary action in relegating drought, flood situation and other impacts on economies and livelihoods. The highest climatological rainfall is seen over the north and north-eastern blocks in the district. The regions; Dharamsala, central and northern Palampur, Nagrota Bagwan, Yol, northwestern Baijnath, and north-eastern high hill region of Kangra receive more than 25 mm/day. Several parts of western and south-western interior blocks including; Indora, Fatehpur, Jaswan, and Rakkar collect more than 12 mm/day or around. Most of the southern and western blocks together with the extreme eastern blocks of this region experience the lowest seasonal mean rainfall ( 90th percentile

Days

4.8 (3.7…13.6)

TY90p

Warm days

Percentage of days when TYmin > 90th percentile

Days

−0.8 (−2.0…0.9)

Source By authors—derived from AIRS and TRMM

218

a

7 Climate Dynamics and Livelihood Vulnerability Assessment 600

Rainfall (mm)

500 400 300 y = 5.5094x + 76.18 R² = 0.0232

200 100 0

1970-1980 2000-2010

Total rainfall (mm)

b

2000 1800 1600 1400 1200 1000 800 600 400 200 0

1980-1990 2010-2014

1990-2000 Linear (1970-1980)

y = -8.6246x + 1531.3 R² = 0.0222

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Year

Fig. 7.6 a Maximum and minimum temperature pattern of 44 years (1970–2014). Source By authors. b Current annual rainfall trend in Kangra from 2000 to 2014. Source By authors

decrease with predicted increases in climate variability that varies from crop to crop because different crops respond differently to warming. The food-grain, particularly the wheat crop dominates its entire cropped area and production, that claims up to 64% share. There has been a consistent shift in agriculture composition, with a gradual decline in cereal crops and an increase in Non-Cereal Agriculture (NCA) that comprises livestock, fisheries, and forestry. Out of the total net cultivable area, 36% is single cropped, 59% is double-cropped and almost 13% is triple cropped.

7.5.2.3

Impact of Temperature and CO2 : Growth and Productivity of Crops

Agriculture is primarily rain-fed across villages of the district where most of the farmers use farmyard manure. There are very few villages where farmers produce surplus because of the subsistence cropping. Except for Sohara, Nangal Chowk,

7.5 Results and Discussion

219

Fig. 7.7 a Struggling between inaccessibility and firewood demand. b Inaccessibility is a biggest question here: four days trek to reach Bada Bhangal. c Remoteness and traditional livelihood options. d Creating alternative livelihood possibilities

Kangra, Zamana Bad, Re Khas, and Indora where the surplus of crops are sold in markets, the rest of the villages like; Puling, Tarmehr, Aweri, and Ulharli are totally dependent upon the cash crops or horticulture. They sell the cash crops in various adjoining areas to meet their basic requirement. Wheat (Triticum Vulgare) is the main cereal crop grown across villages, while other food-grains and pulses are sown in adjoining areas of Punjab. The climatic conditions in the district with a wide range of altitudinal and temperature difference in the region provides a range of potentialities for growing vegetable and horticultural crop as; onion, chilly, brinjal, bhindi, plums, apricot, little-apple, dry fruits and other citrus fruits (Fig. 7.7d). The important wet

220

7 Climate Dynamics and Livelihood Vulnerability Assessment

season crops (green gram and rajmah) and two dry season crops (wheat and maize) have been showing early flowering and maturity due to temperatures increase. The marked reduction in the Leaf Area Index (LAI) that in turn expresses a gradual reduction in the total biomass and yield of the crop increase in Length of Growing Period to more than 9 days in the study area (Table 7.5). With increasing warm nights and decreasing DTR, the wheat crop has shown a larger extent of reduction in the yield due to high thermal sensitivity as compared to other crops like potato, rajmah, etc. During the last two decades agriculture sector has been witnessed HYV seed growth and related issues, with a persistent decline in average farm size, and per capita cultivated area that has decreased from 3 Kanal in the 1980s to only 0.6 Kanal/person in 2011 (GOI 2008–15). Due to the exhaustive utilization of land, degradation and decline in soil fertility have become a normal phenomenon that is persistently lowering the land productivity due to lack of a proper replenishment system. Despite all these adversities, with the ever-increasing population from 13.5 million (2001) to 15.2 million (2011) the transformation in agricultural practice is remarkable with the effect of the HYV miracle and farmer’s adaptability to climate change. The continuous decrease in the production of pulses and oilseeds throughout 1990–2013 and increment in vegetable and other horticultural crops from 49 thousand MT in 1990–91 to 143 thousand MT in 2010–15 is showing that legumes are less profitable crop (Department of Economics and Statistics 2013) (Table 7.6). The area under food-grains including wheat is highest in the district as well as in its villages but the growth rate is continuously declining for wheat the decadal growth rate in 1991–01 was 6.32 has come down to 5.35 by 2015. The maximum growth rate has been achieved by vegetables and horticultural crops due to balanced seasonal profitability (Tables 7.7 and 7.8). It has been observed that with an increase in CO2 level (380 µmol/mol) from 1995 to high CO2 level in 2015 (440 µmol/mol) level the biomass of crops will initially increase then decline sharply with decreasing yield (Fig. 7.8a). The same happens when the crops are exposed to temperatures increase that has been observed in the district (+0.6–1.2 °C) (Fig. 7.8a, b). After exposure to high temperature and CO2 for more than a month, these crops showed a maximum detrimental effect on their reproductive growth. The crop production fluctuates over Table 7.6 Production of cereals, pulses, oilseeds, and vegetables in (‘000 MT) in Kangra Year

Cereals

Pulses

Oilseeds

Vegetables

1985–1990

5429.10

230.00

579.30

49.00

1990–1995

6740.46

110.47

142.82

56.00

1995–2000

13,407.00

122.83

228.10

58.00

2000–2005

15,238.40

125.00

70.00

62.00

2005–2010

14,478.00

71.00

62.00

229.00

2010–2015

13,840.00

75.00

25.00

164.00

Source Department of Economics and Statistics

7.5 Results and Discussion

221

Table 7.7 Area, production, growth per decade (1991–2015) of cereals crops in Kangra Crops

Area under (ha)

Production (MT)

Growth (per cent/decade) 1991–2001

Growth (per cent/decade) 2001–2011

Maize

58,576

92,921

5.18

4.42

Paddy

38,145

49,667

9.65

8.65

Pulses

4213

2956

3.19

2.38

Wheat

92,975

175,421

6.42

5.46

Barley Food-grains Vegetables

2570

3410

3.19

2.20

192,721

313,844

6.76

5.97

7127

111,735

4.15

31.33

Source Department of Economics and Statistics

Table 7.8 Growth of primary sector during 1991–2015 in Kangra

Items

Growth rate (per cent/annum)

Agriculture

6.91

Horticulture

14.32

Livestock

15.28

Fisheries

16.47

Overall primary sector excluding fisheries

9.34

Source Department of Economics and Statistics

time showing a similar trend as rainfall, whenever the rainfall is less the production decreases and vice versa. The production of cereal crops and horticultural crops has shown a decreasing trend for 30 years. Therefore, the statistics exhibit that all types of farming are getting impacted and it is just not limited to cereal or horticultural or other food-grain for marginal farmers but it does show the same trend across with low yield and production (Fig. 7.9).

7.5.2.4

Climate Change and Forest Resources

The district is categorized into four forest divisions; Dharamshala, Dehra, Nurpur, and Palampur division. The Forest area by legal status in the district is 28,418,000 ha that is 49.2% of the total geographical area of the district. But according to legal classification, the actual forest area is 143.3 thousand ha. The Land use and cover map have been generated for the years 1995 and 2015 to show the actual change in the forest and other land use categories and their impact over the time in the district (Fig. 7.10 and Table 7.9). The forests of the district can be classified into seven broad types as follows: (i) dry alpine forests found in Chhota Bhangal and Bada Bhangal areas of Multhan sub-tehsil, (ii) moist alpine scrub forests; are found

222

7 Climate Dynamics and Livelihood Vulnerability Assessment

a Yield of wheat (kg/sq.m)

1400 1200 1000 800

CO 2 (380 ppm)

600

CO 2 (440 ppm)

400 200 0 Biomass (G/m2)

Grain Yield (G/m2)

Biomass/Seed yield (G/m 2 )

b 1400 1200 1000 800 600 400 200 0

Biomass (G/m2 ) Grain Yield (G/m2)

T1(+0˚)C

T2 (+0.6˚C) T3 (1.2˚C) Temperature increment

Fig. 7.8 a Effect of elevated CO2 on the growth yield of wheat crop. Source Simulated by authors. b Effect of elevated temperature on the growth yield of wheat crop. Source Simulated by authors

Fig. 7.9 Effect of precipitation on the temporary and permanent crop in Kangra. Source By authors

below the snow-line but above the tree growth line on all the southern aspect in the region famously considered for medicinal herbs and plants like guggal and karru, (iii) sub-alpine forests are found below the altitude of 3500 m. These are being used for grazing grounds by migratory herds of sheep and goats, (iv) Himalayan moist temperate forests cover the largest part of the district, having

7.5 Results and Discussion

223

Fig. 7.10 Land use land cover change in Kangra district over the 20 years time period (1995–2015). Source By authors based on Landsat, MODIS, and IRS-P3

an elevation of more than 1500 m, where Spruce and silver fir Cedrus deodara is the most valuable species of these forests, (v) wet temperate forests are found mainly in Dharamshala, Kangra and Palampur areas where Chil and Kail are two important species of these wet hill slopes, (vi) sub-tropical pine forests and (vii) sub-tropical broad-leaved hill forests (Forest Survey of India 2015). The land use and cover matrix divulge that the maximum geographical area (54.5%) reported were under forest and pastures under satellite observation and ground-truthing, which gives limited scope for further extension of cultivation. About 20% of the geographical area is under cultivation in the district (2000–15), where pasture land has been increasing from 1995 to 2015. It has increased twice due to climatic variability in the region. There has been an increase in the fallow land area and area put to non-agricultural uses due to the conversion of agricultural land area to non-agricultural uses for infrastructural facilities like road transport, etc. The construction of roads in the adjacent villages like Cherna, Swar, and Bijling hinterlands for hydel power projects are transforming the entire land uses with the new buildings and infrastructural facilities on prime agricultural lands.

40.28

40.16

1995–2000

2000–05

2005–10

3.12

2.52

0.00

6.37

Barren land

13.42

13.36

14.33

13.59

Non-agri. uses

Source By authors based on Landsat, MODIS, and IRS-P3

40.08

39.43

1990–95

Forest land

Year

15.77 15.14

4.74

17.06

8.13

Pasture

4.72

7.02

8.81

Culturable waste

1.34

1.26

0.37

0.80

Misc trees/groves

1.83

1.63

1.62

1.38

Current fallow (5 years)

Table 7.9 Land use land cover change matrix in Kangra district over the 15 years time period (1995–2010) (area in Km2 )

0.07

0.05

0.75

0.07

Other fallow

20.18

20.42

19.41

20.78

Net sown area

224 7 Climate Dynamics and Livelihood Vulnerability Assessment

7.5 Results and Discussion

7.5.2.5

225

Climate Change Impact on Livelihood Capitals

The Participatory Research Appraisal (PRA) surveys have become the basis to derive the livelihood pentagons for the climate impacted scenario. This CCLVI study has been done in two situations. The first is based on access to resources under climate change in the 2020s and for the baseline (1970–2014) and the other is overall LVI. The present situation shows the livelihood pentagon in the study area on the present (baseline) and climate change scenario. The proportional sub-divided circle for each sampled 9 block has been constructed based on population data for their respective blocks. The average capital scores for each capital of sampled three villages in the block have been taken to plot the arc length of each livelihood vulnerable sector consequently the central angle and area is proportional to the quantity the pie signifies. The proportions of the population are more vulnerable in the plain region blocks of Kangra district as; Nagrota Bagwan (9087), Dehra (81,954), Kangra (97,522), and Indora (96,684) is having more than 25 and 15% of vulnerable population in terms of natural resources and social relationships while the higher hill reaches are little secure in term of social and natural capitals due to the close-knit bonding but financially and physically they are more vulnerable due to lack of infrastructure and investments (Fig. 7.11).

Fig. 7.11 Block-wise proportional sub-divided pie diagram on livelihood vulnerability for Kangra district. Source Calculation based on primary survey

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7 Climate Dynamics and Livelihood Vulnerability Assessment

The baseline the farmers are having overall 75% access to the natural resources, but due to climate change the access on land, crop, forests water, etc. will reduce further by 49%, 28.8%, and 16% respectively which gives overall access of only 49.5% of natural resources. The increased disaster like floods and droughts in the region have brought down the physical asset access from 74.5 to 61.9%. Similarly, access to human capital for farmers has reduced down from 78 to 64.8% (Fig. 7.12). The livelihood status of each village was summarized in terms of five capital assets; Fig. 7.12 Asset pentagon for livelihood groups in baseline (present) and under climate change scenario (the 2020s). Source By authors based on primary survey

Farmers

Financial

Physical Baseline

Natural 0.8 0.6 0.4 0.2 0

Human

Social Climate Change Condition

Fisherman

Financial

Physical Baseline

Natural 0.8 0.6 0.4 0.2 0

Human

Social Climate Change Condition

Laborers

Financial

Physical Baseline

Natural 0.8 0.6 0.4 0.2 0

Human

Social Climate Change Condition

7.5 Results and Discussion

227

natural, human, social, physical, and financial. Marked differences were observed within and between villages, in particular between the two agro-climatic zones. This chapter presents the composite indices of the individual livelihood assets and the overall composite index. The total livelihood vulnerability has been calculated, grouped, and ranked into five categories as highly vulnerable (from rank less than 5, characterized by 4 villages), high level of vulnerability (from rank 5 to 9, characterized by 5 villages), medium level vulnerability (from rank 10 to 14, characterized by 5 villages), low level of vulnerability (rank 15 to 19 from, characterized by 5 villages) and very low level of livelihood vulnerability (rank 20 and above characterized by 8 villages) respectively have been illustrated on following capital calculations as the livelihood asset index is a composite of the previous five separate asset indices and varies from 0.13 to 0.86. This highlights relatively very high asset indices in the Sansar Pur (4.25%), Gangath (4.40%), Hara (4.59%), and Ghan Ban (4.25%) villages with all belonging to the top level in Livelihood Vulnerability Index (LVI) 17.5%. Ulharli (4.16%), Raja Khas (4.14%), Samkar (4.20%), Re Khas (4.24%), and Pong Dam (4.25%), occupies high LVI with total 20.99%, while Nangal Chowk (4.10%), Indora (4.05%), Zamana Bad (4.09%), Ghiyori (4.03%), Abdulla Pur (3.98%) squats with the total (20.25%) at medium level in LVI. While Sidhpur (3.67%), Uparli Barol (3.36%), Mundla (3.67%), Garh (3.68%), Puling (3.23%) stabilizes at a low level in LVI with a total 17.61%. The mountainous villages are famously known as deprived and cul-de-sac are having very low LVI meaning thereby these villages are far more secure in the case of livelihood as compared to those plain and agricultural predominant villages with quiet high physical infrastructures. These are; Gabli Dar (3.09%), Chogan (2.94%), Baijnath (2.97%), Averi (2.74%), Jhalot (3.08%), Bada Bhangal (3.09%), Sohara (3.19%), Tarmehr (2.56%), stay intact with total 23.67% in LVI.

7.6 Concluding Remarks The climate dynamics have been better analyzed and displayed when livelihood capital assessment is done in both ways with and without climate change parameters, which has been taken into account in this research. The livelihood capitals on the AEZ region are showing distinct characteristics: it can be concluded that among all the primary capitals, the natural capital is most vital. It is because of the increasing fragmentation of natural resources. Even the social capital has also shown a significant disparity in its outcome across all the 27 villages. Those villages which were not having adequate opportunities to progress land assets (i.e., natural capital), promoting the social capital was extremely important there. This situation has been clearly observed across villages and among lower levels and vulnerable groups of the farming classes and communities. The investigation shows impartial results for livelihood security, where the blame is not put on climate change without logical investigation. The findings of the study are based on local people’s response to climate change, where the authors have tried to establish a micro-level sustainable livelihood security framework for varied livelihood communities. The extracted grids for

228

7 Climate Dynamics and Livelihood Vulnerability Assessment

climate change scenarios have shown a clear increase in temperature, while precipitation trends are showing large variability. The CO2 and temperature simulation modeling results indicate that rain-fed crops have been impacted at large and yield might decline further in business as usual scenario. The impact was also observed for the loss of productive agricultural land that has forced many youths and active labor force to go to Mandi, Kullu, and other districts in search of employment. This has created a labor crisis in their communities and has been subjected to influence women’s labor force to rescue and rehabilitate their families and livelihood assets. Thus, the climatic and non-climatic stressors will continue to increase the degradation and pressurized natural resource base that will further exacerbate the society’s vulnerability. Another interesting characteristic found across the entire region was that the villages located away from forest areas are in a somewhat better position than their counterparts. Due to the availability of irrigation and other factors, these villages had done remarkably well in several sections. However, the role played by several livelihood capitals among the villages together exposed that none of the capital alone can be vital for growth and sustainability. Even though the financial capital is measured more on monetary terms it plays an important role in defining the livelihood outcome. The one important conclusion that can be drawn from the analysis is that the farming community is not limited to the single opportunity in form of agriculture which is provided by the natural capital, they perform a multitude of livelihood activities to generate their livelihood. Thus, livelihood diversification and expansion is an important contributor in producing sustainable livelihood for the people where the vulnerability can only be minimized by the integration of public, private and governmental initiatives.

References Baker J (2007) The Kuhls of Kangra: community-managed irrigation in the western Himalaya. University of Washington Press, Washington Basannagari B, Kala CP (2013) Climate change and apple farming in Indian Himalayas: a study of local perceptions and responses. PLoS One 8:e77976 Biswas S, Acharya SK (2020) The interrelationship amongst livelihood, income and calorie intake of farm women in West Bengal: the analysis and understanding based on socio-ecological perspectives. Stud Indian Place Names 40:3475–3485 Census of India (2011) Provisional population totals. New Delhi, Office of the registrar general and census commissioner Department of Economics and Statistics (2013) District statistical abstract-Kangra Gov Himachal Pradesh Fischer RA, Santiveri F, Vidal IR (2002) Crop rotation, tillage and crop residue management for wheat and maize in the sub-humid tropical highlands: I. Wheat and legume performance. Field Crop Res 79:107–122 Forest Survey of India (FSI) (2015) State of forest report. Ministry of Environment and Forests, Dehradun Frank S, Havlík P, Soussana J-F et al (2017) Reducing greenhouse gas emissions in agriculture without compromising food security? Environ Res Lett 12:105004

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Gaji´c-Cˇapka M, Güttler I, Cindri´c K, Brankovi´c C (2018) Observed and simulated climate and climate change in the lower Neretva river basin. J Water Clim Change 9:124–136 Gould SJ (1965) Is uniformitarianism necessary? Am J Sci 263:223–228 Government of Himachal Pradesh (2008–15) Annual administrative report. Shimla, Himachal Pradesh Hickey S, Seekings J (2020) Who should get what, how and why? DFID and the transnational politics of social cash transfers. Effective States and Inclusive Development Research Centre, The University of Manchester, Manchester Jamshed A, Birkmann J, Feldmeyer D, Rana IA (2020) A conceptual framework to understand the dynamics of rural–urban linkages for rural flood vulnerability. Sustainability, 12: 2894. Jayanthi SLSV, Keesara VR (2020) Observed and simulated climate variability and trends in a semi-arid region. Spat Inf Res 28:129–138 Karki R, Gerlitz L, Schickhoff U et al (2017) Quantifying the added value of convection-permitting climate simulations in complex terrain: a systematic evaluation of WRF over the Himalayas. Earth Syst Dyn 8:507–528 Lal R (2013) Food security in a changing climate. Ecohydrol Hydrobiol 13:8–21 Li Y, Li Z, Zhang Z et al (2019) High-resolution regional climate modeling and projection over western Canada using a weather research forecasting model with a pseudo-global warming approach. Hydrol Earth Syst Sci 23:4635–4659 Marqu´ınez J, Lastra J, Garcia P (2003) Estimation models for precipitation in mountainous regions: the use of GIS and multivariate analysis. J Hydrol, 270:1–11 Mishra PK (2017) Socio-economic impacts of climate change in Odisha: issues, challenges and policy options. J Clim Change 3:93–107 Norris J, Carvalho LMV, Jones C et al (2017) The spatiotemporal variability of precipitation over the Himalaya: evaluation of one-year WRF model simulation. Clim Dyn 49:2179–2204 Schickhoff U, Bobrowski M, Böhner J, Bürzle B, Chaudhary RP, Gerlitz L, Lange J, Müller M, Scholten T, Schwab N (2016) Climate change and treeline dynamics in the Himalaya. Climate change, glacier response, and vegetation dynamics in the Himalaya, 271–306 Shah RDT, Sharma S, Haase P et al (2015) The climate sensitive zone along an altitudinal gradient in central Himalayan rivers: a useful concept to monitor climate change impacts in mountain regions. Clim Change 132:265–278 Singh RB, Jha S (2014) Agriculture and forestry based livelihood capital assessment. In: Livelihood security in Northwestern Himalaya. Springer, Tokyo, pp 95–106 Singh RB, Singh S (2014) Human-induced biome and livelihood security. In: Livelihood security in Northwestern Himalaya. Springer International Publishing, Netherlands, pp 53–66 Singh RB, Singh S, Roy SS (2016) Assessing climate change signals in Western Himalayan district using PRECIS data model. In: Climate change, glacier response, and vegetation dynamics in the Himalaya. Springer, Cham, pp. 103-115 Swaminathan MS, Howard H (2010) Agriculture and food systems. In: Science and sustainable food security: selected papers. World Scientific, 3: 275 Tubiello FN, Rosenzweig C (2008) Agricultural impact metrics to assess the benefits of climate policies. J Integr Assess 8:165–184 UNICEF (2000) DFID. UNICEF Prep. Response 1999 Kosovo refugee emergency. A joint UNICEF/DFID evaluation UNISDR Building Disaster Resilient Communities (BDRC) (2007) Good practices and lessons learned. United Nations Dev Program, Geneva

Web References Indian Remote Sensing (2020) https://bhuvan.nrsc.gov.in/data. Accessed 15 May 2020

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The Atmospheric Infrared Sounder (2020) https://airs.jpl.nasa.gov/. Accessed 15 May 2020 The Landsat (2020) https://landsat.gsfc.nasa.gov/. MODIS. http://modis.gsfc.nasa.gov/. Accessed 15 May 2020 The Tropical Rainfall Measuring Mission (2020) https://gpm.nasa.gov/missions/trmm. Accessed 15 May 2020

Chapter 8

Systems Approach in Sustainable Livelihood Adaptation and Mitigation Strategies

Abstract This chapter deals with the recent findings on how sustainable practices at the local level support to accomplish both the mitigation and adaptation goals while continuing relevant to the livelihoods of the marginal and smallholders in the Kangra district. It focuses on the science of adaptive policy, people’s perception of changing climate, spatial livelihood variation, and coping mechanism together with the governmental plans and policies related to the changing climate and measuring livelihood security. It is an effort to encapsulate all the strategies and actions taken by the local, state, and national level government. The primary survey, observations, and perceptions of respondents have been taken into consideration before putting forward any suggestions and recommendations to progress on poverty eradication and sustainable livelihood. Regardless of the apparent condition, the puny efforts of locals and policymakers together reducing the voids towards achieving sustainable livelihood through the strategic plan for the nomadic livelihood, tea, horticulture, mushroom cultivation, and social help programs are being seen as a win-win approach. It has been analyzed that despite coherent strategies, mitigation actions and several strong steps taken by policymakers the desired results have not been much evident in the district. It concludes that development towards reformed and sustainable livelihoods has been analyzed through the accumulation of assets in spider diagram/pentagon on which the mitigation measures have been evaluated and mapped. Keywords Systems approach · Science of adaptive policy · People’s perception · Coping mechanism · Strategies in farm sector · Integrated and forward investigation and analysis A holistic system approach in sustainability, measured by livelihood uniqueness when this embraces the geo-social abilities, resources, and cumulative conclave action of an individual/community required for a maintainable ecosystem and means of living, without any fear for the days ahead.

© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 S. Singh and R. B. Singh, Simulating Climate Change and Livelihood Security, Advances in Geographical and Environmental Sciences, https://doi.org/10.1007/978-981-16-4648-5_8

231

232

8 Systems Approach in Sustainable Livelihood Adaptation …

8.1 Introduction The system approach has been adopted for the study on changing climate and livelihood security because it inter-relates and integrates all the elements of livelihood security into a unified set of directions. This systems perspective is vital to follow the synergies between different elements of agriculture and livelihood. It further analyzes and addresses the trade-offs and ensures cost and benefit investigations. This offers a universal perspective of the organization and emphasizes on its adaptive nature. It also analyzes the system at different levels and provides a framework for effective interaction between the climate, farmers, agriculture, tools, technology, opportunity, etc. in considering the impact of environment and the interaction of the external environment with households and their livelihoods. To accomplish the numerous objectives of the output, productivity, food-security, enriched farmer resilience, and reduced GHGs emissions from agriculture and allied sectors the agriculture dominant region must embrace various systems perspectives. The climate change impact on the agrarian village’s livelihood is likely to be more alarming in the view of its altitude and high dependency on monsoon. Around 73% of the total annual rainfall happens to fall from June to September in the study region and that reveals a high coefficient of variation in the western and southwestern villages. It has been proven through calibration that how this skewed distribution has resulted in a decrease in the number of rainy days, the summer days have increased by more than 7, together with warm nights, i.e., more than 5 in a year and these anomalies in temperature and precipitations are likely to increase further in future 2020 and 2050 scenarios. The increase in the night temperatures are accelerating crop respiration, Length of Growing Period (LGP), and reducing yields eventually. These anomalies have already been posing great risks of crop failure, poor yields, increasing crop water demand, shift in the tree line and access to services, etc. which are constraining or enhancing the current coping capabilities to climate change. The small land holdings and rain-fed farming are the principal elements of all the villages across Kangra that have almost every type of Agro-Ecological Zone (AEZ) condition ranging from subtropical to dry temperate. The district comprises mosaics of opportunities being valley and hill region to earn livelihoods. As it has already been proven that these livelihood strategies are not only vulnerable to temperature, precipitation, and CO2 trends, the weather seasonality, or peripheral disturbances but also to the changes in endogenous capital ownership. The analysis has already been done on the livelihood capital security to find out the adaptation, mitigation, and coping mechanism across the climatic regions that have been grouped into farm and non-farm sectors with special emphasis on gender, education, income, age, and area in this chapter. These capitals provide varied livelihood platforms such as; farming, livestock rearing, or fishing to the households and they adopt diverse livelihood strategies concerning demographic trends, technological changes, policies, programs, together with external stresses/shocks on their livelihoods as; floods, drought, landslide, and other turmoil, etc. Primarily two main strategies that households have adopted in the study region are; adaptation and coping strategies.

8.1 Introduction

233

During the crisis time, the auction of the assets is usual phenomena, either they make changes in the farming system or migrate to surrounding areas. Therefore, to analyze village specific micro-level sustainable livelihood security five core livelihood principles have been carved out, it includes; community-centric, holistic, dynamic, strengths building, and macro to micro linkages. These core principles necessarily have to be flexible in their application but this does not mean that it should be compromised at any ground. The micro-level sustainable livelihood framework has been made based on DFID guidelines but constructing a framework would not be robust without having proper synergy and integration of public, private, and governmental response in any area. The primary focus of this chapter is to confer in detail about the existing realities in the area with special reference to coping mechanisms, adaptation, and mitigation synergy. The climate variability impacts the very basic agrarian economic structure of the district and predisposing society to the risks and related vulnerability. This impact might be more on particularly poor rural people who are totally reliant on climate sensitive natural resources. Indeed, the dangers of global warming and environmental change have already being felt in agriculture, forestry, water resources including other areas that contribute to the livelihoods of rural people. The green revolution may have revitalized the agrarian system but recurrent droughts, floods, and reduced productivity have negatively impacted this sector where livelihood option has been minimized. Thus, to address the challenges associated with thermal warming, increasing rainfall variability, and changing overall climate, the society would need a robust knowledge network in generating the adaptation-mitigation strategies through system analysis. There is also a need to assess the available information on climate change impacted environmental products and ecosystem services by building environmental sensitivity and promoting the capacity of rural communities to respond to these challenges.

8.2 Data Base and Methodology The coping mechanism is based on the household’s perception recorded on short term stresses and how he/she applies a brief strategy to cope with them. The adaptation and mitigation strategies have been measured primarily with the help of the Government of Himachal Pradesh planning, program, monitoring and statistics department, other statistical reports, outlines and records like; Directorate of Agriculture and Statistics, has been considered to substantiate the results. A combined, structured questionnaire based on the household survey and open-ended interviews have been done for 270 households, with an almost equal representation of both the genders where each has been asked questions regarding their observation of climate change, coping mechanism, and adaptation approaches (Annexure I). The issues like; climate change, number of warming days or increasing thermal intensity, declining duration of the snowfall, shifting crops/vegetables/flowers, the intrusion of foreign weeds, changing crop variety/yield/production, etc. have been asked to study and understand the levels of awareness among local communities regarding climate change and

234

8 Systems Approach in Sustainable Livelihood Adaptation …

accordingly, the coping mechanism has been examined for sustainable adaptation and mitigation strategies where local communities and government share common grounds (Fig. 8.1). The ordinal scale was put in the form of codes for strongly agree (4), agree (3), disagree (2), and don’t know (1), for their respective answers, and the combined scores have been calculated in the latter part of this chapter.

Climate indicators

Slow onset

Drought/floods/ Landslide

Temperature

Sudden onset

Floods/landslides Rainfall

Changes

Cumulative

Extreme

Local perception

Meteorological data

Demographic/ economic data

Crop production Floods/landslides

Temperature and rainfall variability

Price/ availability and access to food/ fodder/ capitals

Livestock production

Drought/Dry spell Asset/ capital sell Changes in livelihood/insecurity

Coping/Resilience/ Adaptation strategies

Fig. 8.1 Methodological flow chart on changing climatic variability, changes in livelihood security, local coping, and adaptation strategies. Source By authors

8.3 System Approach: Households and Livelihoods

235

8.3 System Approach: Households and Livelihoods The sampled households are involved in different socio-economic activities that shape the status of well-being. Each household has a unique perception regarding livelihood security, for some, it might be limited to the well-being meaning thereby just having enough to eat, a shelter for the family, and a basic level of security, but for others, they strive to achieve a level of sustainability. There are primarily three broad reasons to act on livelihood security issues in an exigent manner; first is the growth of the economy and individual, second is the equity among the communities and third is the environment for which everybody should be concerned. Thus if a set of activities ensures food and income throughout the year without harming their surrounding environment then the livelihood of the household is considered sustainable. The households and communities surviving with limited infrastructure, harsh climate, limited technological and financial access in these sampled villages across nine sampled blocks are most exposed to varied risks however, these risks are also insinuating many opportunities for coping mechanisms from agricultural, and meteorological jeopardies. Out of the total cropped area, paddy crops area occupies 9.4% in 1990–1991. The under, it was only during 1995–2001, diseases, insects and pests have decreased extraordinarily due to adequate rainfall and farmers have dedicated more than 17.2% area for paddy cultivation and are having high yield (The Tribune 2001). The story repeats with Barley a well, which is another major crop of temperate and sub-temperate parts of the villages in the district that was earlier used in religious ceremonies to provide fodder to animals and for manufacturing local beer but the area under this crop has witnessed excessive crop diversification for horticulture, floriculture, cash, and other vegetables crops. The occupational details explain that out of the sampled households almost 83% of them are directly dependent on the agriculture sector that only contributes almost 18.61% in the Gross State Domestic Product (GSDP) during 2010–11 (Economic and Statistics Department Government of Himachal Pradesh 2017). The vulnerability to climate change is undoubtedly significant due to considerable population dependence on the primary sector (Table 8.1). This is a widespread phenomenon across other districts in the state as well, therefore, over time people have evolved coping mechanisms (short term) and adaptation strategies (long term) to mitigate the unrelenting impact Table 8.1 Occupational profile of the sampled households (HHs) Occupation

Number of households

Per cent of the total

Agriculture and service

135

50.0

Only agriculture

90

33.3

Ironsmith/carpenter/tailor/mason

29

10.8

Others

16

5.9

270

100

Total HHs Source By authors

236

8 Systems Approach in Sustainable Livelihood Adaptation …

of climatic change. These occupational categories are a sign of the economic activities where an individual is engaged almost throughout the year. Further, these economic activities have been again re-classified into a principal livelihood and consequent livelihood activities where the main livelihood activity is characterized by involvement of an individual for more than 180 days in a year and consequent livelihood signifies occupation commenced for a shorter duration. Almost 44% of HHs in sampled villages are directly involved in their own farm activities, 14% are dependent on livestock consumption and trade for their livelihood. The other livelihood sources among sampled HHs are forestry and salary employment, whereas 58% HHs have experienced crop loss on regular basis and quoted it as the chief problems of livelihood (Fig. 8.3a, b). The majority of households (almost 68%) have said they are dependent on their farm activities for livelihood sources, 20% of them on livestock, 7% on forests while households across marginal, small and large land holdings have said that they are going for crop diversification because the traditional system is insufficient to provide them economic sufficiency moreover the new diversified crop and horticultural produce are capable enough to generate income in a short time period (Figs. 8.2 and 8.3). Moreover, the area and production under horticultural produce have been on an elevated track. During 1980–81, only 1193 ha land was denoted for horticulture that produced almost 5914 metric tons but in 2010–2011 the total area devoted to fruits rose up to 6787 ha and production has witnessed 20% increment during the same period (Table 8.2). Table 8.2 Area under horticulture production from 1980–81 to 2010–11 in the district

Horticulture production in Kangra

Total area (ha)

Production (MT)

1980–81

1193

5914.00

1990–91

2163

8632.30

2000–01

4339

16,238.00

2010–11

6789

22,769.00

Source Compiled from Horticulture Department

Fig. 8.2 a Sources of livelihood. Source By authors. b Reasons for crop diversification among landholders. Source By authors

8.3 System Approach: Households and Livelihoods

a

237

b

Fig. 8.3 a Livelihood sources among sampled HHs. Source By authors. b Problems of livelihood identified by HHs. Source By authors

8.3.1 Science of Adaptive Policy The climate policy for adaptation and mitigation strategies cannot remain static therefore, the policymakers and practitioners should however be very careful while implementing the policy. The adaptive policy has become the prerequisite of a society in order to reduce the ambiguity accompanying with changing climate. The sustainable adaptive policies design to anticipate and plan for small to the large heterogeneous areas. These designed adaptive policy functions on decentralized planning, multi-stakeholders negotiations, and adaptive integration.

8.3.1.1

Using Integrated and Forward Investigation and Analysis

It can be done through the identification of the key factors that affect policy performance. It is much required to investigate that how these factors are being shaped in the current and future time scale to create area-specific policies that would be more vigorous to a range of expected situations. It may further initiate several essential spatio-temoral policy adjustments.

8.3.1.2

The Monitoring Indicators in Generating Integrated Policy

The intrinsic irregularity can be anticipated through scenario analysis for the economic, social, and ecological conditions. The local level information, analysis, and monitoring would further felicitate in generating integrated policy for bringing out sustainable development from within micro village system (Figs. 8.2 and 8.3).

238

8.3.1.3

8 Systems Approach in Sustainable Livelihood Adaptation …

Commissioning Constant Formal Policy Review and Knowledge Network

It has to be done in continuation even when the policy has been implemented and thriving the routine reviews; pilot studies may help in addressing emergent issues for important policy modifications.

8.3.1.4

Multi-stage and Variegated Stakeholder Planning

It can help to diagnose the problem from different perspectives before making decisions and provide a complete understanding of the causal relationship at all levels.

8.3.1.5

Empowering Planning and Communication

Policies should not challenge the prevailing social capital. Some of the processes that strengthen participants’ ability to respond to unexpected events include; interacting with people, sharing good practices, and removing barriers where self organization can be encouraged.

8.3.1.6

Decentralizing Decision Making at the Lowest and Most Effective Jurisdictional Level

Decentralization which has become the integral part after 5th FYP it has become the accountability of the designatory authority in creating logical decision making at the lowest and most effective jurisdictional functional unit to perform effectively.

8.3.1.7

Policy Responses Variant Campaign

The biosphere is a complex interplaying system where it interacts with hydrosphere and atmosphere. The social, cultural, and ecological structures at the micro-level points out further intertwined complex and diverse policy varies from one another. Thus, diversity in unity has to be considered by keeping the logical framework based on science of adaptive policy has to be executed in accomplishing anticipated outcomes. The above described seven tools and techniques are useful in providing realistic guidance to the policymakers who are working in a highly complex, dynamic, and uncertain framework like; climate-induced risks and the impending requirement for dynamic spatio-temporal adaptation and mitigation strategy. The Government of India has launched the Agro-Climatic Regional Planning (ACRP) scheme in June 1998 with an purpose to investigate the state-wise agro-ecology and impact

8.3 System Approach: Households and Livelihoods

239

of changing climate on the same (Planning Commission 2008). The importance of conveying the risks posed by climate change and the need of economic growth and poverty eradication in the Kangra region has been investigated already. The need to find mechanisms which allow integrated development goals by bringing the benefits of cooperation in addressing climate change. In this context, regional risks to the impacts of climate change, and adaptation-mitigation strategy requirements have been discussed to promote the integration of policy, plan, and development agenda.

8.4 Livelihoods and Coping Mechanism The coping mechanism is used to minimize the stress and are short term responses to a specific shock such as; landslide, earthquake, flooding, and drought, which is also affected by the status of livelihood capitals. The fragile ecosystem of villages in Kangra has been witnessing complex livelihood changes through climate-induced impacts, being experienced by its communities that are totally dependent on natural resources. Any changes in their natural habitat due to differential warming in the eastern and western parts of the district with 6 days increase in summer days and 0.86 °C increase in maximum temperature during winter between October to March is already affecting the livelihoods of local communities across Kangra. The reduction in the overall availability of drinking water, shifting forest cover, vegetation and biodiversity is having an impact on the local communities. Therefore, there is an urgent requirement to study community participation at the time of need, their perceptions regarding climate change, and the perceived local key indicators for coping strategies towards sustainable development and planning. Accordingly, the coping mechanism has been studied in the following ways; primarily local level awareness regarding the changing climate, their indigenous mechanism to escape from the harmful impacts together with the adjustments they make to reduce the influences to produce long term sustainable synergy. The coping mechanism has been investigated with special emphasis on gender, education, income, age, and region in two ways; first is based on their general understanding of climate and its impact on livelihood and second is their short term measure.

8.4.1 People’s Perception of Changing Climate The people’s lives and livelihood are directly linked to the climate and candidly visible in this region even if a very small variability occurs. This chapter offers an effort in exploring the potential bearing of climate variability on livelihoods and its future sustainability by researching on people’s perception as; how and to what extent they can escape or adjust to the climatic variability and also try to compute the accuracy of these observations in relation with temperature, rainfall and agricultural production records. Climate change is a long term phenomenon therefore,

240

8 Systems Approach in Sustainable Livelihood Adaptation …

Fig. 8.4 General awareness regarding climate change. Source Primary survey

the perception of people may play a pivotal role in its examination. The insignificant variations in climatic factors over a period of time may provide signals to declining yield or incursion of some foreign weeds or traditional fodder degeneration due to these. Questions were asked regarding the general awareness about climate change, increasing warming days, decreasing winter intensity and day counts together with their perception on the intensity of sunlight during winter months. It can be said that across the village households were having an above-average level of awareness (more than 80%) for each question regarding general discernment about climate change (Fig. 8.4).

8.4.1.1

General Perception Regarding Climate Variability

‘When I was a kid approximately 15 years ago, I used to feel bad to see snow around me for continuously four months, we could not even go out and play but now I feel my kids don’t feel that bad because snowfall is just for 2 months (December–January) and that too 3–4 ft. only’ explained by Jhumpa 25-years old resident in Puling village (Fig. 8.5a). It is not limited to this particular village, entire Chota and Bada Bhangal have the same story to tell. The residents of Palampur and Panchrukhi belongs to the mid-hill region (900–1500 m AMSL) and have narrated the same about litchi, stone fruit, and mango trees that for about 20–25 years they have never seen these varieties of trees in their village but now it has become common in every household’s orchard due to increase in temperature in the Muthan, Nagrota Bagwan, Kangra, Palampur, and Dharamsala areas. Loquats and litchi are being grown in Kangra Valley however these fruits are famous in a sub-tropical warm region. Its commercial cultivation was initially limited to Uttar Pradesh, Punjab, and Maharashtra but for the past decade, it is being grown here as climate is warming (Fig. 8.5a, b). The old people who have witnessed long term climatic variability in Tarmehr have explained how the number of snowfall days and amount of it has decreased over the years from 2.7 to 3.4 m snow to 0.60 to 1.31 m over the past 30 years (Fig. 8.5c). The sparklines in the worksheet (Table 8.3) cell show the trends in production with

8.4 Livelihoods and Coping Mechanism

241

Fig. 8.5 a Jhumpa explaining the decrease in snowfall duration in Puling village. b Army retired personal reporting shift in horticultural variety in Panchrukhi and surrounding blocks. c The elderly have been advocating a decrease in snowfall amount and duration during the last 30 years

highlighted minimum and maximum values. The soil erosion is increasing across blocks with a decrease in land productivity but showing a promising result in the case of horticulture trends across blocks. Similarly, there were orange trees in the Dehra, Paragpur, Nurpur, and Indora villages, but now they are nowhere to be seen (Fig. 8.6b and Table 8.3), although villagers have tried to re-plant them again and again but these horticultural trees could not tolerate the increasing temperature in these areas, therefore, this has now been replaced by low altitude Malta fruit variety. The rapid growth of deemak (termites) during the last 3–5 years in Dharamsala, Baijnath and Multhan villages are creating unsafe living because it has degenerated Pinewood trees and thereby villagers are not able to construct safe houses (Fig. 8.6a, b). These local observations are very much similar when compared with the secondary and simulated data analysis over the study area that has clearly shown increasing rainfall and temperature variability for the same.

8.4.1.2

People’s Perception, Climate Variability, and Livelihood

The significant modification in temperature and its distribution has been observed by people across villages in the study area. There has been a definite decrease in

242

8 Systems Approach in Sustainable Livelihood Adaptation …

Table 8.3 Land uses, productivity, cropping pattern, cultivation, horticultural, and aquaculture in 9 sampled block Land Use Details

Baijnath

Punchrukhi

Nagrota Bagwan

Kangra

Dehra

Pragpur

Nurpur

Indora

Fatehpur

Dharmshala

T_Geo_Area (ha.) Forests (total/per cent)

94,683 81960 (86.59)

9,846 649 (6.69)

44,375 14814 (33.38) 14,814 0 3950 (8.9)

5,233 1654 388 (1.1)

24,422 0 825 (2.34

Land put to nonagricultural uses Culturable waste

2713 (2.86)

86 (0.88)

0

2345 (6.65)

1057 (10.59)

826 (13.76)

3,067 (9.1) 672 (1.99)

3791 (10.07)

594 (0.62)

40,814 6480 (15.88) 6,000 0 5450 (13.3) 2350 (5.76) 850 (2.08)

35,243 24422 (69.29)

551 98 215 (2.19)

58,251 11177 (19.19) 11,177

37,650 6887 (18.29)

81,960 0 2380 (2.52)

33,690 15204 (45.13) 15204 0 1506 (4.4)

36,534 3240 (8.87)

Productive Degraded Barren land

26,029 12686 (48.73) 12686 0 2927 (11.5)

6692 (17.77)

613 (1.74)

2647 (7.86) 2,647 342 8445 (25.06) 0 4 0 66.68

Permanent pastures and other grazing lands Productive Current fallow Cultivated land

40 (0.050

130 (1.32)

40 0 6996 (7.39)

78 258 7213 (73.25)

Danger of forest fire (% of Panchayat) Degraded forest Soil erosion Land sliding

25

0

2659 (10.22) 2,659 30 6901 (26.51) 20

0 25 0

50 0 0

0 0 20

Land levelling Fencing (length in m) Reclamation Check dam (length in m)

231 9,92,912 248 28

912 12,950

3,928 3,741 -

Cereals Maize

2,118.03

109.89

1,146

4,325.20

Paddy

4,408.44

5,811.96

4,054.50

2,561.90

Wheat

4,992.90

5,664.70

3,568

6,332.70

Vegetables Spices Lift irrigation Command area (ha) Tube wells Command area (ha) Kuhl Command area (ha) Tank irrigation Command area (ha) Canal irrigation Command area (ha)

5 200

-

220.52 39.59 4 145 48 6.5 -

2,124 63.45 3 115.65 10 513.08 70 7.5 -

50 80 24 276 80 140 -

Existing_Area (Ha) Production (Tons.) Households (No.)

12 156 30

-

-

-

Existing_Area (Ha) Production (Tons.) Households (No.)

-

85.8 1,201 121

-

-

18221 (31.2) 6494 (11.15) 1458 (2.5) 5380 (9.24) 5,380 0 11552 (119.93)

71.45 0 14.29

3,240 0 1248 (3.4) 3656 (10.24)

3645 (10)

832 (2.32) 2081 (5.70)

2100 (4.73) 726 (1.63)

1415 (4.11)

726 0 18315 (41.27) 0

1860 (4.56) 1,800 60 16249 (39.81) 0

5052 (13.42)

2,081 0 25061 (68.59) 87.5

2,930 2,122 12375 (32.87)

1,415 0 5343 (15.16)

66.67

0

50 0 37.5

33.32 0 16.66

25 25 50

0 66.67 50

50 75 25

Sparkline

Improvement Needed to Increase Productivity of Land (Ha) 3,87,392 11,702

1,813 2,36,298 -

766 1,41,202 -

7,496 1,38,117 -

2,903 14,88,871 497 -

6,347 5,28,247 1,302 1,042

742 1,311 1641

8,349

4,654

11,117.12

5,859

834.12

2,474.25

2,409.16

11,038.72

1,380.24

2,792.72

8,424.75

2,409.16

11,038.72

1,380.24

2,792.72

182.25 112.5 5

1,811.16 47.32 10 955.22 28 943.32 2 63.05 1 1.2 -

8,005.13 41.16 11 30 926 3 500 1 9000

454.68

28

1 926.46 9 19.5 2 4400

-

Cropping Pattern (Ha) 10,023.0 4 29,187.8 4 13,102.7 2 1,479.68 14 1 28 2 63.05 -

2 35 20 280 50 350 -

-

Existing Block Level Schemes for Horticulture Development Apple -

-

-

-

-

-

65.25 1,165 570

52 780 520

-

-

-

635.5 8,752 2,588

647.3 12,953.60 6,760

20,194.80 9,125

574 12,628.80 4,070

241 4,579 728

530.8 12,341 3,961

1,648 45,140 13,295

1,895 61,588 3,900

1,009 29,412.35 4,570

340.04 7,650 910

45 774.25 563

52 795 577

98.5 1,710 1,142

66 1,122 744

127 2,467 410

17.25 846 775 5 8

104 486.84 459 150 250

170 5,107 500 600 700

0 0

80 200

1

20

35

0

36

Stone fruit -

Citrus fruit Existing_Area (Ha) Production (Tons.) Households (No.)

220.4 2,856 853

237 2,844 1,295

335.1 5,733.40 812

446 6,980 1,185

436.32 6,924.90 1,833

Existing_Area (Ha) Production (Tons.) Households (No.)

604 18,887 2,102

364.75 8,972.18 2,665

1,810 287.72 6,912

2,225 707.5 16,980

64.75 1,014.91 1,758

71.8 122.7 1075

210.65 2,949.10 839

25 100

20.9 480.5 250 4 11

10 200

44.8 1,428.50 2,960 10 5

10

9

8

1

Mango 580.8 11,790 3,167

Litchi Existing_Area (Ha) Production (Tons.) Households (No.)

Guava Existing_Area (Ha) Production (Tons.) Households (No.) Fish production (Qty.) Potential Production (Tons.) Households engaged (No.)

Source By authors

the duration of winter days reported by almost 90% of the people. The winter onset has also altered and shifted from October last week to mid-November. The hottest month’s duration has also increased due to advanced onset and has perceived significant warming in the month of March and April which used to be pleasant months earlier in Dehra, Indora, Kangra, and Fatehpur blocks. The assessment has directed towards hybrid responses in the level of environmental awareness among

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243

Fig. 8.6 a Reported horticultural shift towards litchi, lingti (local vegetable), loquat, and mango across villages in Kangra. b Increasing case of deemak (termites) attack in Bada Bhangal

people, about 14% of the population in the three villages (Sohara, Zamana Bad, and Aweri) were confused about the issues related to environmental conservation but almost everybody (97%) has some level of environmental awareness and informed about warming and increasing temperature (Table 8.4). A sizeable number of people feel that these changes are causing a decline in the forest and other natural resources. Dr. Ranbir Singh Rana and his various research team from Palampur Agricultural University have outlined several species that are on the verge of extinction as; kuth (Saussurea costus L.), saffron (Crocus sativus L.), kala zira (Bunium persicum Bioss.), buckwheat (Fagopyrum esculentum species those are on the verge of extinction as; Moench.), hops (Humulus lupulus L.), and amaranth (Amranthus candatus L.). It has also been told by him that few species are shifting the habitation and migrating towards higher altitudes such as Atella phalenta, Papilio polytus and Anapheus auorta, etc. due to low-temperature availability. The changing variability in climate has also affected the species longevity and length of growing days, initially the Gladiolus flower used to be fresh for almost 12–15 days but now it is crisp and vigorous just for 4–5 days meaning thereby its durability has declined sharply as explained by a gardener in Palampur. Similar observations regarding temperature change have been made by villagers in Tarmehr, Billing, and Chogan that the quantity of buds per plant in jatamasi, stone

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Table 8.4 Response regarding the change in climatic condition (in per cent) S.No.

1

2 3

4

5 6

Issues

Perception

Understanding about the term climate change Awareness about warming Climate change During winter between November to March, the month of March has become more warm as compared to previous years Sweat/ Intense warm wind has increased during summers Shivering (Intensity of cold) during winters has decreased Warming/Cold Days Winter duration (changed from 5 to 3 months) More intense sunlight during winter days Decrease in snowfall duration Snowfall Duration Decrease in snowfall amount Climate change has increased the risk of crop failure Decrease in production of Rice Flowering, fruiting and harvesting time of crops have changed Decrease in crop production (winter crops) Production/Yield Wheat Barley Maize Climate change has facilitated the availability of fresh vegetables/ fruits etc. in the area. Have you observed any species shift in your area Shifting Species Crops varieties/ types have been changed Replacement of species has been observed Foreign weeds intrusion have increased Weeds New unknown weeds have come up

Per cent Response 83 97 85 90 90 81 100 93 74 98 55 70 84 60 100 90 32 79 56 96 80 10

Source By authors

fruit, Kinnow, and peas has decreased since past 4–5 years (Horticulture Department 2019). The medicinal plant species like; Ramban (Agave amricana Linn), Kashmal (Beriberis aristata DC), and Lady’s purse (Capsella bursa-pastoris) have decreased drastically in Aweri, Tarmehr, Uparli Barol, Sidhpur, and Puling villages whereas Juniper, birch, and kasoonar that are shrub used for firewood in Bada and Chota Bhangal including Gabli Dar are all on the verge of extinction (Fig. 8.7a). Households in Paragpur, Dharamsala, and Panchrukhi have indicated climate impact on mango flowering that use to happen in mid-February but due to temperature increase in these areas, it is flowering around 10th–15th January same with a reduction in the size of apple fruits in Bada Bhangal due to temperature variability (Fig. 8.7b, c). People’s perception on the variability of rainfall is somewhat very similar to the ground data that has indicated the late onset of monsoon. A respondent in Aweri village has said that earlier the schools used to be closed during June due to rainfall and the sowing season but now they get a break from 1st week of July for the same. This is just not limited to lower and mid-hill regions villages in Kangra but also in high hill villages in Tarmehr, Puling and Bada Bhangal where the schools were closed during July 2014 survey and respondents offered the same answer (Fig. 8.7d). Late onset of rainfall is hampering paddy and other crops including maize because it is hampering the crop maturity. Even the kuhls (gravity channels) were dry as it has been observed during the monsoon season (Baker 2007; Singh and Jha 2014). The northern flowing kuhls tributaries famously known as ‘choes’ are causing flash floods during the monsoon season because of irregular usability and have deteriorated their conditions, few khads with an age-old method of directing water from various streams, and springs through channels to the cultivated fields as; Pragpur, Nalsuha, Chanour, and Dada Siba Khad are decreasing in the district. Through discovering the level of awareness regarding climatic variability and its impact on their local habitat it has been proved that people are much responsive and alert across villages. It is also reasonably noteworthy that the changing trend of temperature and rainfall

8.4 Livelihoods and Coping Mechanism

245

Fig. 8.7 a Extinction in plant species varieties and respondent’s observation regarding foreign weed intrusion and extinction of existing medicinal species in Aweri village. b Early flowering in plant species. c Reduction in apple fruit sizes due to intensification in length of growing days in Tarmehr. d Adjustment with school holidays from May–June to July–August (monsoon months). e Alteration of growing crop seasons from May–June to July–August (shift in monsoon months), almost 40 days advanced

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are fully coinciding with the meteorological and climatological data. The climate is described as being much erratic and warmer, although the spatial variation in temperature, as well as rainfall, is positively correlated therefore, the local weather cycle is exhibiting a significant shift in the data (Chap. 4). It could be said on the above basis and previous data analysis that the cold weather has shifted to January and February which was earlier confined between November to March, and the monsoon months of July–August are witnessing dry warm nights despite typical humid and rainy months (Fig. 8.7e). Hence, based on overall investigations, it can be said that this study provides the basis for further coping mechanisms (Singh and Singh 2014).

8.4.2 Spatial Livelihood Variation and Coping Mechanism The varied livelihood of the district can be understood in two ways; firstly the general agrarian livelihood of the district, secondly the livelihoods of Gaddis and Gujjars, and thirdly the non-farm sector livelihood that involves processing units.

8.4.2.1

The Nomadic Livelihood

The Gaddis in the district is generally found on high hills in the Bada Bhangal area. They are transhumant, semi-nomadic, and tribal people whi rear sheep and goats. The term ‘Gaddi’ has been originated from the Gaddi (throne) of Lord Shiva in Mount Kailash, has been reported by Government as Scheduled Tribe (ST). They are high altitude shepherds and in order to avail green pastures, they migrate to the plain and valley region during the winter season (October–March) but generally reside in high hills in Bada Bhangal during summers. Due to increasing climatic variability, these people in their native area have started crop diversification rather than growing wheat initially (Fig. 8.8). The horticultural produce stabilizes their economy nowadays and making them less vulnerable to climatic change. Due to the

Fig. 8.8 Nomadic Gujjars temporary residences near Pong Dam survive by selling buffalo milk in neighboring villages during summer month from May to July

8.4 Livelihoods and Coping Mechanism

247

consequent migration to the lower valley area after fulfilling basic needs they are undergoing lots of transformation. Higher education and economic empowerment policies with the help of the local and state government, the traditional dynamic lifestyle has been vanishing. Similarly, with the other nomadic tribe; Gujjars (both Hindu and Muslim) are also trying to avail education facilities in the district but both have different chronicles like; the Hindu Gujjars in the district are now permanently settled but their Muslim counterparts are still fixed with the tribal nomadic pastoralist culture found in the plains of Pong Dam, Dehra, and Nurpur areas. They are basically landless, uneducated, and very poor whose livelihood is primarily dependent on animal husbandry and forests. Their coping strategies are just limited to migration where education plays a pivotal role in their unstable residency and backwardness and even the government is unable to support them much.

8.4.2.2

Forest, Wildlife, and Environment

Ecologically and economically the dense forest cover has been enriching the district due to its advantageous latitudinal location. It was just after independence that the regional planners have identified these forests as a source of timber, NTFPs and other merchandises that have steered to enormous deforestation and dissipating green reserve areas are available either for livelihood or for agricultural opportunities to meet the demands (Sajjad and Nasreen 2016; Hoy and Katel 2019). The district-wise forest statistics show that Kangra is having 2842 km2 , the area under forest and has witnessed a decline of 105 km2 area during 1997–1999, which is the poorest in the state where the rest of the other districts are having an increase in the forested areas (Forest Survey of India 2015). The Government and people have blamed it on the growth and spread of city, satellite towns, road networks, organizational development, accommodation, and tourism. Even the locals around the villages have perceived that these decreasing forest resources are impacting their livelihood. Fifty-four per cent of respondents from high and mid-hill villages have claimed that it is causing a reduction in fuelwood. The 21% have claimed that they are having problems due to wood stocks becoming insufficient for construction and the other 9% are suffering from declining income sources. It would be a contrast to say that 16% of the households have said that their livelihoods are not having any impact from declining forested area or forest cover but in reality, these households are generally from lower reaches and valley areas in Kangra and are already having diversified economic opportunity (Fig. 8.9a, b). It is not easy for the survival of these 54% households whose lives and livelihoods are totally dependent on forest due to the unavailability of other resources in those three months frost season when nothing works. The forest classification based on the crown cover has depicted a marked decline from 2104.3 to 2006.4 km2 in dense forest cover category during 1995–1999 but simultaneously Government involved Samridhi Mahila Cooperative Society (SMCS), Kangra Forest Cooperative Society (KFCS) and Participatory Forest Managements (PFMs) for afforestation program in especially three blocks that were

248

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Fig. 8.9 a Climate change impact on forest-based livelihood. Source Primary survey. b After and before snowfall in Cherna Village, beside the timber stocks, locals are devoid of any option

having the largest area under forests like; Rait (66.22%), Baijnath (63.51%) and Bhawarna (54.28%). From 2001 onwards the improvement has been visible in the forest cover. The decline in the total forest area from 1991 to 2003 is due to the unclassed forest area and protected forest area. Nonetheless, during 2003 the area under forests had seen an increase from 1999 baseline across the district (Table 8.5). Table 8.5 Changes in forests category based on various crown cover classes Crown cover category (area km2 )

1991

1996

2001

2006

Dense forest (≥40% CD)

1960.42

2104.30

2006.40

2294.38

Open forest (CD 10–40%)

631.18

645.92

871.64

864.82

1666.50

1384.24

998.36

854.48

163.76

158.84

116.26

96.62

4421.86

4293.30

3992.67

4110.29

Scrub (CD below 10%) Unproductive barren (alpine pasture, snow area, etc.) land Total

Source Compiled from forests statistics from Forest Survey of India

8.4 Livelihoods and Coping Mechanism

249

Joint Forest Management (JFM) and Clean Development Mechanism (CDM) Joint Forest Management (JFM) effort in Kangra has started during 1990 by developing village level Forest Development Committees (VFDCs) with an aim to involve local communities and voluntary agencies in degraded forest regeneration. Due to constitutional 73rd and 74th amendments Panchayati Raj Institutions (PRIs) have come up to empower local villagers and support forest-based livelihood management (HPFD 2019). With further involvement of locals and cooperatives in forestry management, it has generated admirable results in the Baijnath and Dharamsala region. The VDCs have been directed by Himachal Pradesh Government during 2005 to support CDM by discouraging illegal forest felling and encourage housewives to use kerosene as an alternative fuel. They also have supported women for carpet weaving, foot-mats making, and other related activities across villages in Kangra through Participatory Forest Management (PFM) by launching Sanjhi Van Yojana (SVY). The scheme like SVY played a crucial role in a clean development mechanism to bring sustainable livelihood options by minimizing carbon emission by promoting non-leguminous afforestation and Natural Regeneration and Afforestation policy (NRAs). CDM was a big step in empowering women by recruiting women forest guards (WFGs) because they are primary gatherers of forest produce and directly dependent on it. However, it needs further replication to other areas in the district.

Conservation and Protection of Wildlife and Biodiversity The conservation of wildlife and biodiversity in 12.5% area in the district has been taken up by PRIs, VFDCs, and CDM. The rich sites like; Pong Dam, Bada Bhangal, and Dharamsala region have been in the urgency list for biodiversity conservation. The precise areas of action for the district comes under the national primacy that includes the advancement of agroforestry in order to reinforce livelihoods among forest-dependent communities via the Protected Wildlife Mammals Plan (PWMP). The PWMP is for birds, reptiles, and threatened biota that includes; spotted deer, Kashmir stag, musk deer, Himalayan black bear, ibex, snow leopard, flying fox, lynx, barking deer, etc. The bird’s list includes primarily tragopan, monal, snow cock, Cheer pheasant, white spoonbill, koklas, red jungle fowl, chukor, hornbill, whistling teal, mountain quail, Siberian white crane, etc. While the reptiles list under PWMP includes; yellow monitor lizard, Common Indian monitor lizard, Indian python, etc.

8.4.2.3

Irrigation and Coping Mechanism

The water rights and management of the age-old kuhl system for irrigation in the district are famous for crucial reserved water rights through the introduction of the Minor Canal Act, 1976. It is the same for all the irrigation network systems, natural or regular streams, and all other water bearing sources. It has been put under custom

250

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Fig. 8.10 a Kripal Chand Kuhl for irrigation in Palampur. b Kuhl gravity channels are being used in producing small scale hydro-electricity in Tarmehr

irrigation channel that is known as Riwaz-I-Abpashi in local language. Various kuhls (Fig. 8.10a, b) in Palampur including the Diwan Chand Kuhl, Kusmal Kuhl, Kripal Chand Kuhl, Dai-di-Kuhl, etc. are in the claims of individuals and communities where people have joined hand together and created Water Users Associations (WUAs) to cope from untimely monsoon rainfall the Participatory Irrigation Management (PIMs) has also been doing well in the district. These small scale gravity channels (kuhls) are being used for generating hydro-electricity in several high hill villages to cope with power failure. Through the Cultivable Command Area (CCA) major (10,000 ha and more) and medium irrigation projects (more than 2000 but less than 10,000 ha) have been launched to support nearly 93 villages across the district through Shah-Nahar Project on the river Beas initially. However, the Government of Himachal Pradesh has extended it towards several Medium Irrigation Projects under CCA through irrigation projects like; Giri Irrigation project (5263 ha), Phase-I, Bhabour Sahib Project (923 ha), Phase-II, Bhabour Sahib Project (2640 ha), Balh Valley Project (2410 ha), Sidhata Project (8990 ha), etc. Several minor irrigation projects are also being operated on public as well as on private farms through tube-wells, kuhls, and lift irrigation. The Government is providing subsidies directly to the farmers in the Kangra district to develop their own shallow wells, kuhls, or tube-wells under the Micro-Management of Agriculture Projects (MMAP) and Well Irrigation Scheme (WIS). Thus through Command Area Projects (CAPs), the Beas river catchment area is being used extensively to reduce soil loss through fixing the soil binding plants, grasses, and trees even through constructed bunds, stonewalls, etc. Through these projects, more than 200 new major and medium irrigation projects have been promulgated during 1997–2010, while the number of kuhls has remained stationary with a large increase in minor projects (supports less than 2000 ha). The district has witnessed nearly 2000 minor irrigation projects over the same time due to CCAs and CAPs (Table 8.6). There are 14 watersheds programs working in the district to support 5200 ha arable land and 5400 non-arable lands under the District Watershed Development Agency (DWDA). DWDA is working comprehensively through Nahan, Dehra, Paragpur, Indora, Lambagaon watershed projects intending to prosper village life by promoting rainwater harvesting, treating degraded lands with low cost, and locally accessed

8.4 Livelihoods and Coping Mechanism

251

Table 8.6 Major, medium, and minor irrigation projects in Kangra district (2000–2015) Irrigation projects

2000 (existing)

Major and medium irrigation

2187

2003

2006

2009

2012–15

Cumulative

60

30

30

40

2347

Minor irrigation

16,519

400

400

424

360

18,103

Kuhls and others

18,559

–

–

–

–

18,559

Total

37,265

460

430

454

400

39,009

No of watersheds in Kangra

Arable land (ha)

Non-arable land (ha)

Total (ha)

14

5178

5401

10,579

Source Eleventh five-year plan, Himachal Pradesh Note (–) shows N.A

technologies, and promoting conservation measures through afforestation, social forestry, etc. The Ex-Chief Minister of Himachal Pradesh Prem Kumar Dhumal has placed a foundation of |205 million for the irrigation scheme. Through this Medium Irrigation Scheme (MIS) around 4 cusecs of water will be tapped for irrigation which is proposed to support nearly 60 villages by constructing a dam in Lahru village at Chakki Khad in the Nurpur block. This MIS is supposed to irrigate more than 4 thousand ha of farmland in the area and is likely to be completed by 2015.

8.4.2.4

Strategies in Farm Sector

Crop Diversification Till the 1990s this district was characterized by double cropping in lower and mid hills and mono-cropping in high hills where cropping season only happens to fall in between April to October because it stays under snowfall for almost six months. The lower and mid-hill regions like Kangra, Fatehpur, Dehra, and Nurpur were used to grow rice and wheat only while the high hills like Bada Bhangal and Chota Bhangal area was dominated by potato followed by maize, rajma (broad bean), and wheat. The subsistence cropping pattern was limited from hand to mouth. On high hills where people used to migrate to lower areas to explore laboring and related jobs on road and rail network creation sites, timber, lumbering, etc. where the hardearned livelihood was insufficient to accomplish their basic requirements and even could not save enough to reach back to their respective places, thus they started lease-in land on nominal rent for vegetable and other horticultural produce like; cabbage, radish, rajma (broad beans), potato, cauliflower, etc. The Seed Potato

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Development (SPD) and Ginger Development (GD) projects have been launched under Vegetables Development Project (VDPs) by the Himachal Government to promote crop diversification, subsidiary income, and employment generation activity. This modification is in the direction of market-based requirements for high-value crops. Due to these participatory projects, even the marginal farmers have started going for commercialization in the farming system by selling their produce in nearby areas namely; Joginder Nagar, Mandi, Jalandhar, Haryana, and even Delhi where almost half of the produce is marketed now (Fig. 8.11a). The crop diversifications have created a noticeable impact on the livelihoods and well-being because it is only after this landlessness has become less in villages. The farmers in Puling and Tarmehr villages feel that the overall impact of crop diversification on vegetables and horticulture has tremendously changed their lives and now none of the families in any of these villages migrate to Joginder Nagar, or Baijnath during the winter season. They are now having sufficient income to stay peacefully in their villages. It is not income that is bothering them now but it is the scarcity of basic infrastructure like; schools, hospitals, and roads. Though every household has installed dish antennas and is having BSNL cellular services due to perennial electricity and water supply but education and medical infrastructures are still a major concern for them.

Tea Horticulture and Mushroom Cultivation: Coping Mechanism Tea is a promising option brought by Dr. Jameson in the district around the year 1849. He recommended it in the lower slopes of (between 900 and 1400 AMSL) Dhauladhar range due to its ideal suitable location for the tea industry because that area is having high annual rainfall (1500–2500 cm) and soil pH is below 6.0. Shahpur and Palampur produced good quality tea that was outstanding quality and had won several gold and silver distinctions in USA, London, and Amsterdam markets during 1880s (Imperial Gazetteer of India 1864). The total tea area in Kangra was more than 3700 ha during 1901 but the great earthquake in 1905 has ruined this flourishing industry, where Palampur and Kangra block have witnessed the largest land use alteration afterward in tea plantation (Imperial Gazetteer of India 1864; Himachal Pradesh Agricultural University 2011). After the colonial period, it encountered various other complications due to inept technical knowledge, poor processing facilities, fragmented land holdings, etc. the Government of Himachal Pradesh has established four cooperative tea factories recently in Bir, Baijnath, Palampur, and Sidhbari with the help of Palampur Agricultural University to regain the status of ‘Kangra Tea’ (Fig. 8.11b, c). During 2010–2015, this tea has earned |9.52 million by additionally employing 6179 workforces in Palampur, Baijnath, Dharamsala, and Kangra tehsils. The district with the help of local participation now reports the largest area that is 91.7% under tea but there is vastly mistreated and abandoned tea areas or the potential non-customary area (32%) could be brought under tea plantation in the district that can play a pivotal role for this optional livelihood (Table 8.7).

8.4 Livelihoods and Coping Mechanism

253

Fig. 8.11 a Potato, vegetable shed-farming, and sustainable solar energy promotion technology in Badagram. Source Primary survey. b Kangra’s golden tea garden. c Government and cooperative initiative to revive the Kangra tea plantation with the help of CSK-HPAU, Palampur. Source The Tribune (2001)

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Table 8.7 Area under tea production in selected blocks of Kangra district Tehsils

Total area (ha) in 1901

Overall area (ha) 2011

Derelict area (ha)

Abandoned area (ha)

Palampur

2298

1256

258

154

651

Baijnath

676

564

91

313

2500

Dharamsala

435

232

26

42

112

Kangra Total

Suitable area (ha) for tea cultivation under non-traditional category

298

66

3

44

143

3707

2118

378

553

3406

Source Imperial Gazetteer (1905) and Department of Tea Husbandry and Technology (2011)

Animal Husbandry, Poultry and Aquaculture Animal husbandry, poultry, aquaculture, and dairy promotions play a pronounced role in the rural economy by generating employment and enhancing livelihood prospects. The livestock; cows, buffalos, sheep, and goats have been used for meat and milk. Poultry has recorded a striking 10–20% per annum annual growth rate. The farmers have been trying their best to bring this activity at an affordable price with low production cost, adept technical cooperation, and management ability. Fishes are a very cheap source of protein and recently it has been promoted in reservoir, rivers, and ponds across the district where the ideal average temperature and water are found. Pong Dam, Dehra, and Chota Bhangal have well-organized fish farms through cooperatives. Pong Dam is the principal reservoir and retains the tremendous potential for aquaculture through local management measures, where carp, Trout, silver carp, Mahseer, Rohu, Mrigal, Gidbata, Catla, goldfish, grass carp, etc. species are farmed. Initially during the early twenty-first century aquaculture industry has witnessed a declining trend in the production due to fish fungal diseases, inappropriate technology, and management which led to a sharp decline from 4201 metric tons in 2004–05 to 288 metric tons in 2008–09. However, the district administration with the help of local cooperatives in Fatehpur, Lambagaon, Dehra, and Chota Bhangal areas has recently been able to develop Integrated Agriculture and Aquaculture (IAA) (Department of Agriculture 2019) that has steered an increase in its production during 2010–11 to 304 metric tons (Table 8.8). These are the major regions where the maximum number of households are employed in these aqua-farms. This practice safeguards an increase in food, income, nutrition availability, developed use of resources, and encourages community cooperation. The humid conducive environment of the district facilitates to produce button mushrooms at a much lower rate as compared to other parts of India due to the profound availability of wheat straw even though the marketing infrastructure is poor for this industry. About 7% of people are now involved. The district government has been trying to bring this industry at large scale due to humongous potentiality

8.4 Livelihoods and Coping Mechanism Table 8.8 Trend in aquaculture production in Kangra from 2004 to 2011

255

Year

Production in metric tons

2004–05

420.6

2005–06

306.4

2006–07

311.6

2008–09

288.3

2009–10

300.0

2010–11

303.5

Source Compiled from the Department of Agriculture

Fig. 8.12 a Crop diversification for millets, maize, mushrooms, capsicum, garlic, and onion in Baijnath block. b Trout fish farming at Badagram and aquaculture at Pong Dam

therefore, with the help of Agricultural University they have involved households and seasonal growers at micro-scale to establish technical units for its cultivation in Nagrota Bagwan, Palampur, and Baijnath blocks (Fig. 8.12a, b). The agro-climatic condition is ideal for horticultural produce like; stone and citrus fruits including mango, litchi, guava, plum, and apricot. Whereas, Chota and

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Bara Bhangal together with other adjoining areas produce apples but the total area devoted to horticultural plantation and production has been experiencing a sharp positive growth rate. Horticultural produce is at a large gain in terms of income where aquaculture is growing with 15.57%/annum, livestock at 14.26%/annum, the horticultural produce is growing at 13% per annum (Department of Agriculture 2019). The district’s total horticultural yield is around 7.1 × 105 quintals (Annual Administrative Report 2016) which comes from mainly these four blocks Nurpur, Indora, Dharamsala, and Chota Bhangal where the highest area and production devoted to mango trailed by citrus and stone fruits. The Horticulture Technology Mission (HTMs) has played an important role in transforming the most sidelined subsistence mono-cropped in the villages like; Tarmehr, Aweri, Chogan, Uparli Barol, and Sidhpur.

Sericulture and Beekeeping Sericulture and Beekeeping have been practiced as a subsidiary occupations, to provide additional occupation and complementing income for the poor farm families. This viable alternative is being promoted at the local level for harvesting and processing silk from cocoons. Initially, only one silk seed station was established at Palampur to practice this farming in the spring and autumn months but now it has been introduced to Dehra, Pachrukhi, Lambagaon, Nagrota Bawan, Nurpur, and Rait block also. As a consequence, the district produces total cocoon production around 20–25% of the entire Himachal Pradesh (Directorate of Industries-Sericulture Wing 2016). The total cocoon production has gone up from 46 to 564 metric tons in 2011–12. While there is almost 10% progress in the number of benefited families in the district over the same time with the help of MGNREGA cooperative support and governmental schemes through Central Silk Board schemes (Table 8.9). The cooperatives and MGNREGAS are working together in the district to support especially small and marginal farmers, SCs/STs, and BPLs across villages because these sections of the society signify a sizable proportion in this activity to create mulberry wealth by offering their own farm. Beekeeping was first introduced in 1962–62. During the 1970s, the production was just 4 metric tons that have increased up to 250 metric tons during 2014– 15 with the help of private entrepreneurs and Governmental integration (Annual Administrative Report 2016). These entrepreneurs have launched bee breeding and multiplication centers under centrally sponsored Government plans. Kandrori region is a good example that is being accomplished by the Agro-Industry Corporation Limited (AICL) and has become a lucrative domestic enterprise. Various Apis mellifera stations have also been established by Chaudhary Sarwan Kumar Himachal Pradesh Agricultural University (CSKHPU), Palampur for rearing beekeeping practice at Nagrota Bagwan and providing 4–5% employment across the district. These entrepreneurs have launched bee breeding and multiplication centers under centrally sponsored government plans.

45.828

2205

Silkworm seed consumption (in ounce)

Production of green cocoon (M. tons)

Number of benefited HHs

2006–07

2220

33.69

1200.9

Source Directorate of Industries (Sericulture Wing) (2016)

2005–06

1617

Category/year

2310

35.55

1154.4

2007–08

2417

41.49

1255.8

2008–09

2483

42.63

1288.5

2009–10

2516

31.5

1305.6

2010–11

Table 8.9 Sericulture development and number of benefitted households in Kangra district (2005–15) 2011–12

2535

45.69

1332.6

2012–13

2589

45.81

1425.9

2013–14

2590

44.82

1521.3

2014–15

2713

564.09

1545

8.4 Livelihoods and Coping Mechanism 257

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8 Systems Approach in Sustainable Livelihood Adaptation …

Fig. 8.13 Livestock ranching and wool farming at Tarmehr and Puling village. Source Primary survey

Agricultural Promotion and Marketing Infrastructure As it has already been discussed that the conducive climatic conditions provide ample opportunities for production and removal of agricultural farm produce, beekeeping, livestock products, horticultural and vegetable crops therefore, the marketed surplus of cereals, pulses, oilseeds, fruits, milk, wool, honey, and silk have drastically enhanced livelihood in the district. The Margin Money Scheme (MMS), Rural Employment Generation Programs (REGPs), and Prime Minister Employment Generation Programs (PMEGPs) are also directly playing a role in livelihood promotion (Planning Commission 2015). Milk and wool are sold by local traders to the outside district even. The Himachal Pradesh Wool Federation has recorded one of the maximum exports from this district where wool is being sold to Jaipur, Jaisalmer, and even Kashmir (Fig. 8.13) by locals as well as traders. The milk production in the district is also a prestigious level in Kangra, Dehra Gopipur, Nagraota Bagwan, and Fatehpur blocks, they stand in the prime lane in milk production in the district but the marketing infrastructure facilities are lacking because of markets regulation. Different market facilities like; market center, storage, godown, market-related information infrastructure, marketing cooperative society, banking, and insurance facility are little more needed in the blocks like; Chota Bhangal, Bada Bhangal, Rait, and Baijnath in the district. The agro-processing units; atta-chakki, rice, maize, and oilseed processing units are now being given importance due to local initiatives. Still, people rely on traditional hydropower generated attachakki in various blocks for their needs (Fig. 8.14). For agricultural marketing, the new Agro Product Marketing Cooperation Act (APMC) under H.P. Agricultural and Horticultural Produce Marketing (Development and Regulation) Act at district, have been made functional which the administration is planning to launch at the block level by the end of 2015. The chief aim of these acts is to promote information to the local farmers about everyday market rates and that is being distributed through All India Radio/Doordarshan/AGMARKNET.

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Fig. 8.14 Automatic hydro-electric atta-chakki in Chota Bhangal. Source Primary survey

Fig. 8.15 Educational status and level of unemployment among male and female in the 9 sampled blocks. Source Primary survey, 2014

Drudgery of Youth and Women Unemployment among youth is predominant in the district; the overall level of unemployment with matriculate, graduate, and even technically trained youth is quite high. With the local help and support through the farm and non-farm activities, the potential enterprises are speedily coming up in the district. The youths are now being involved in cereal, tea, mushroom, dairy, horticulture, and vegetables medicinal and aromatic plant farming together with beekeeping, nursery building, and sericulture. Out of the total, almost 9146 people are unemployed and 54% of them are male while women occupy a little less that is 46% in the entire district. Baijnath, Paragpur, and Indora are the blocks having the highest number of youth unemployment both for males and females (Fig. 8.15). Women in the hilly region play an important role in family sustainability, agricultural development as well as sustainable livelihood through community participation and Weather Based Crop Insurance Scheme (WBCI). It has been observed that almost 87% of work related to road construction, farming, and others

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Fig. 8.16 Regular women workforce in small and medium scale industries (SMEs) and road construction under NREGA in Baijnath and Palampur block

are being done by women only. Most of the agriculture and farming activity is manually done besides threshing activity, where women’s involvement is much high (Fig. 8.16). Farm Women Empowerment Programs (FWEPs) have been launched in the district to support farm women and empower them through agriculture and other Extension Programs for Extension Reforms (EPERs) policy at the district level. It is one of the major plan proposals towards revitalizing decentralized agricultural extension with major emphasis on the modernizations in the technology broadcasting, through National Technology Projects (NTPs). It is being successful at the state and district levels to provide gender concerns by mobilizing and training farm women. Therefore, it is now clear that these coping mechanisms in the farming and non-farming sector are highly dependent on potentialities and their harnessing techniques. The short term coping response may not be feasible for the long term sustainability of livelihood without any external support or governmental response. However, the block and village level concerns are still awaited for responses from the government, thus, it would be better to investigate the other potential sectors through these decentralized policies to interlink it with new governmental policy, Non-Government Organizations (NGOs) and other local Self Help Groups (SHGs) in these blocks and respective villages. Various processing units like garlic and tomato processing units, wool and wooden toys, or novelties are being promoted. People are raising general issues related to roads and medical facilities, etc. because the connectivity is a prime concern but it is pending in Chota and Bada Bhangal for the past 27 years since 1987. If the promise can be implemented these deprived villages can stand up in self-sustaining villages without any further external support. People are not demanding metaled roads, the simple RCC roads can bring phenomenal change in their livelihood. Similarly, the medical facility in these areas is very poor and no medical facility is available in any of the probable or potential industrial regions in the district. Through the Social Welfare Programs (SWPs) intensive attempts have been planned to recover and expand the efficiency and quality of public amenities delivery by 2015.

8.5 Integration of Policies with the Development Strategies

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8.5 Integration of Policies with the Development Strategies The institutional strengthening and its integration at various levels; state, district, block, panchayat, and the village can play a pivotal role in overall livelihood security. This work is delimited at the village and block level to measure livelihood security in a changing climate because there are ample numbers of plans, policies, as well as responses at the state and district level in an umbrella cut framework whose implementation is still lacking at the bottom level. All policies in the Kangra district are mainly focused on food, shelter, livelihood, and capacity building. The decentralized bottom-up approach has been promoted since the 1990s to increase adaption and mitigation strategies to combat the large impact of climatic variability but still in the neophyte stage (Fig. 8.17).

8.5.1 Poverty Eradication and Social Help Programs There are mainly two programs viz., National Social Assistance programs (NSAP) and Rural Poverty Alleviation (RPA) that have been brought by the district Government through bottom-up and decentralized approaches to alleviate the harsh climate change impacts. The RPA program works under the broad framework of the daily wage employment and SHGs program for employment generation among

Fig. 8.17 Synergy between top-down and bottom-up for mitigation at the local level. Source By authors

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youth and women, development of rural artisans and women by providing them food, shelter, employment, and pension, and other constitutional benefits. Therefore, Jawahar Rozgar Yojana (JRY), Integrated Rural Development Program (IRDP), Training for Rural Youth for Self-employment (TRYSEM), Employment Assurance Scheme (EAS), Development of Women and Children in Rural Areas (DWCRA), and Pradhan Mantri Awas Yojana that was known as Indira Awaas Yojana (IAY) have been brought under the umbrella of RPA. All the employment schemes of the government have been put under Sampoorna Grameen Rozgar Yojana since 2001. The improved tool kits supply in Baijnath, Muthan, and Dharamsala artisans have already been implemented whereas the provision of sanitation, water supply, and housing demands of shelter have also not been ignored, therefore, the Rural Water Supply Scheme (RWSS) and Rural Sanitation Programs (RSP) have been seriously taken up by the district Government officials under the RPA programs. The National Social Assistance Program (NSAP) has also been brought recently during the 11th five-year plan for providing maternity and family benefit, and pension schemes to the old age retired people (Planning Commission 2008). These are being converged under RPA to fulfill the Directive Principle of the Indian Constitution. The main components program has been outlined as:

8.5.1.1

Integrated Rural Development Program (IRDP)

A society recognized as the Himachal Pradesh State Rural Livelihood Mission (HPSRLM) has been set up for the execution of NRLM. It is a poverty alleviation program, which was launched in the year 1980 with the objectives of providing income-generating activities, capital, assets building, and rural self-employment opportunities. Though, this scheme was merged with Swarnajayanti Gram Swarozgar Yojana (SGSY) in 1999 to support rural youth for self-employment and capital subsidies from banks.

8.5.1.2

Development of Women and Children in Rural Areas (DWCRA)

It was launched as a sub-scheme of IRDP during the year 1982–83, with the cumulative aim of raising the income among rural women, skill training, infrastructure support for self-employment, providing health, education, safe drinking water, sanitation, nutrition, facilities by organized participation of local women groups.

8.5.1.3

The Training of Rural Youth for Self-employment (TRYSEM)

TRYSEM has started in 1979, for the preparation of pastoral youth to generate occupation by giving them basic education, technical and tactical expertise in agriculture, farming, non-farming, and other allied sectors.

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Fig. 8.18 a Mandatory UGC training in colleges across Kangra to promote self-employment. Source Navbharat Times. b Promotion of ‘Green Bonus’ and regional cooperation initiative in the region. Source The Indian Express (2009). c Miniature painting promotion scheme through Gandhi Kutir Yojna. Source The Tribune (2001)

8.5.1.4

The Jawahar Rozgar Yojana (JRY) and Employment Assurance Scheme (EAS)

JRY has started by amalgaming the two wage-based employment programs including the National Rural Employment Program (NREP) and Rural Landless Employment Guarantee Program (RLEGP), with an objective of employment generation for including both men and women. The EAS was started with an aim to provide 100 days of employment during the lean agricultural season for restoring ecological balance and optimum utilization of natural resource regeneration activities (Fig. 8.18a, b).

8.5.1.5

Rajiv Gandhi Digital Vidyarthi Yojna

The student of 10th and 12th have been provided 500 notebooks in Indora and Kangra block to promote technical education among rural and urban youths in this region rest other blocks are untouched from the program activity.

264

8.5.1.6

8 Systems Approach in Sustainable Livelihood Adaptation …

Indira Awaas Yojana (IAY) and Gandhi Kutir Yojana (GKY)

The free of cost dwelling units to SCs, STs, and bonded laborers are being provided by Indira Awaas Yojana (IAY). Currently, the non-scheduled castes and non-scheduled tribes have been given benefits under this as well. The Gandhi Kutir Yojana has also been implemented and is being beneficial in Dehra, Baijnath, Dharamsala for the families living under the BPL category. The Kangra miniature paintings are being promoted at the world level with the assistance of |16,000 being given to each beneficiary but have been still put on the shelf in any of the blocks in the district (Fig. 8.18c).

8.5.2 Capacity Building: Gram Panchayats and Local Community Participation The administrative aptitude of Gram Panchayats (GPs) in accounting, economic management, planning, execution, and broadcasting have been supported with this approach. The capacity building with Participatory Rural Integration (PRIs) is initiated with GPs elected officials, representatives, SHGs, NGOs, and local people. This focuses on (i) the technical skills enhancements, (ii) information improvement, (iii) training all stakeholders and (iv) institutionalization of GPs for the human resource development and enhancement of capacity building. Its sub-components are designed to increase general awareness regarding the environment, public participation, and overall transparency. It has the aim of targeting the general public, NGOs and GPs. It has already started promoting Kangra’s paintings made by natural colors and also promoting traditional folk theatre and dance.

8.5.2.1

The Observance and Appraisal

An operational monitoring and evaluation approach has been started for continuous monitoring and enhancing the decision making power of the community. The creation of cultivator groups, women empowerment, SHGs, improvement in the quality of life, change in ownership of land, and improving social lives are an integral part of it.

8.5.2.2

Infrastructure Development, Productivity Enhancement and Non-farm Initiative

Among other schemes, it has been taken for road creation and the provision of irrigation facilities has been taken up (Table 8.10). The major productivity enhancement objective is to require interventions in farm technology equipment,

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Table 8.10 Infrastructures, irrigation, and flood protection schemes Activity

Scheme name

Nodal department

Road

PMGSY

Public Works Department (PWD)

CMGSY

Planning

NREGA

Rural development

Water supply

AWRSP

Irrigation and Public Health Department (IPH)

Employment generation

NREGA

Rural development

Irrigation

Flood protection, medium irrigation, lift irrigation schemes

IPH

Marketing and infrastructure

Vikas mein jan sahyog

Planning

SGSY

Rural development

Local district planning

Planning

Source Compiled by authors

cropping pattern diversification, soil conservation, quality improvement, and improved seeds and fertilizer. Various nodal agencies are assisting with these activities (Table 8.11). One of the major reasons for the degradation of the natural resources in various blocks in Kangra is over-dependence on these, thus by developing non-farm sector activities in this area sustainable ecological management is already being promoted. Approximately 15 new buses were introduced in Kangra and Dharamsala to offer Government to Citizen (G2 C), Business to Citizen (B2 C) and Citizen to Citizen (C2 C) facilities for fair, speedy and economical transport but it is still in very novice stage in the district. Table 8.11 Schemes for providing agricultural assistance Action

Scheme

Concerned department

Dissemination of HYV seeds for agriculture

Agriculture inputs

Agriculture

Fertilizer

Agriculture inputs

Agriculture

Insecticide and pesticide

Agriculture inputs

Agriculture/horticulture

Poly houses

Horticulture Technology Mission (HTM)

Horticulture

Source Compiled by authors

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8.5.3 Integration for Livelihood Support The district is characterized by small landholding sizes across its villages and blocks, where terrace farming is widely being practiced (Fig. 8.19a). The small size of land holdings (less than 2 kanals) in the area is very common that is why poverty prevails at a wide scale. Moreover, difficult terrain is also hampering road connectivity and health infrastructure, especially in the Baijnath, Tarmehr, Puling, Cherna, Bada, and Chota Bhangal. The drinking water and regular electric supply are available to the majority of households in each block except Dehra, Nurpur, and Fatehpur but high dependents on forests and other natural resources are making the situation unsustainable. The horticultural produce provides them the best average return of nearly |82,000 per ha, but still the marginal and small farmers depend upon subsistence agriculture and villagers are improving their income by selling their livestock and other capital/asset. In order to secure livelihood, many villages either migrate, sell their crops, or work

120 100 80 60 40

Total

Ghiyori

Pong Dam

Samkar

Ghan Ban

Hara

Re Khas

Polling

Tarmehr

Bada Bhangal

Sohara

Abdulla Pur

Zamana Bad

Indora

Raja Khas

Gangath

Garh

Sansar Pur

Ulharli

Nangal Chowk

Jhalot

Mundla

Aweri

Chogan

Baijnath

Uparli Barol

0

Sidhpur

20 Gabli Dar

Landholders type in per cent

a

................Villages....... Marginal

Per cent HHs attempetd to solution

b

100 90 80 70 60 50 40 30 20 10 0

Small

Medium

97 82

77 57 43

43

38

35

32 22

12

Crop loss Sold Assets

8

2

4

4

4

Crop illness Loss of Job Shortage of Income ..........Crisis category.......... Worked as Labourer Sold Crops Migrated

Fig. 8.19 a Marginal, small, and medium-size workers in per cent across 27 villages. Source Primary survey. b Solutions to secure livelihood during crisis period. Source Primary survey

8.5 Integration of Policies with the Development Strategies

267

as daily/casual laborers. Approximately 97% households have said that they work as a laborer during crisis period while around 50% said that they have sold their crops to secure livelihood (Fig. 8.19b).

8.5.3.1

Support to the Weaker Sections and Improving Quality of Life

The overall aim of the plans and programs is to support the weaker section of the society and improving the quality of life under various institutional arrangements with the help of public participation at the local level. The SHGs and User Groups (UGs) of the local community’s beneficiaries have been constituted for sharing the responsibility for the operation and conservation of complete local assets. Its basic role and responsibility pivot around the further assertion of quality works and implementation of the program with the help of SHGs, Gram Sabha, Gram Panchayat, and others by properly maintaining the records for the decision making (Table 8.12). The Gram Panchayat performs a pivotal role in the implementation and execution of activities. The main function of the GPs is to facilitate convergence. The User Groups and SHGs have been created in Baijnath, Paragpur, Dehra, and Nagrota Table 8.12 Schemes for productivity enhancement, non-farm initiative in micro and small enterprises, and support to the weaker section Action

Scheme

Concerned department

Housing and construction

IAY/AAY and housing scheme for SC/STs welfare

Rural development and Welfare department

Self-employment

SGSY

Rural development

Education and apprentice

Basic computer literacy, free text books, scholarship scheme for different categories of students, mid-day meal scheme

Education department

Schemes for improving quality of life

Modular employable scheme, training under different trades through ITI

Methodological learning

Support to weaker section

Rural Industrial Program (RIP) Rural artisan

Rural development SC/ST organization and backward programs organization

Prime Minister Employment Generation Program (PMEGP)/Program (RAP) Self-Employment Scheme Swablambhan Yojana (HSY), Laghu Vikray Kendre Yojana, Interest-Free Loan Scheme Loan to OBCs on lower interest (6%) Source By authors

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Bagwan to support and mitigate local problems. The GPs are enhancing capacity building with the help of the Community Operation Manual (COM) that provides guidelines for the resource generation, training, and capacity building component enhancements at the GP level.

8.5.4 Strategic Climate Change Knowledge Network Mission The National Mission on the Strategic Knowledge for climate change recognizes the need for research in specific areas of climate science to improve understanding of climate processes. The key areas for action under the Kangra Regional National Campaign are; (a) to establish networks for viewing and develop local together with temporary climate information, (b) high-resolution climate modeling development, (c) establish critical infrastructure for high data storage, sharing, operation and calculation by scientists and researcher community.

8.6 Enhancement of Adaptive Capacity Through MGNREGA More recently, the district is doing comparatively well in the implementation of the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA). While the MGNREGA aims to provide a basic 100 days wage-based employment guarantee in rural areas, however very little has been done in the past but is improving currently. Natural resource-based activities also contribute directly to climate change and improve resilience by reducing the vulnerability of the rural poor under the MGNREGA. through; (i) the water harvesting and water conservation, (ii) landslide and flood proofing, including tree plantation afforestation and reforestation activity, (iii) improving irrigation through kuhls/canals irrigation, (iv) improvement of the policy framework for horticulture, irrigation facility, land development, and plantation, (v) rehabilitation of traditional water bodies, including tank desiltation, (vi) land development, (vii) flood management and protection function, including wetlands. It would be useful to learn from the more effective examples of those activities and apply learning in all regions so that MGNREGA activities could provide benefits to many through reducing poverty and vulnerability, improving resilience, reducing climate change, and adaptability. In other words, the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) addresses climate change and poverty at the same time. The connection is straightforward and characterized by improved stability and reduced risk. The land-based activities are being done under MGNREGA, and thus indirectly it is contributing to both adaptation and mitigation strategies for climate change. The climate change mitigation through forest restoration by sequestering a large amount of carbon in the soils across Kangra has

8.6 Enhancement of Adaptive Capacity Through MGNREGA

269

already been analyzed under CDM supported by MGNREGA. Similarly, rainwater harvesting, water conservation, land development, natural forest regeneration, and afforestation can be enhanced by improved resilience of rural people and their systems. Increased biomass, groundwater recharge, and enhanced soil fertility can address both geographical and biological together with livelihoods strategies. Several efforts can be streamlined in order to unifying and strengthening it under the MGNREGA. It is necessary to prioritize above-discussed activities in the villages across Kangra through MGNREGA so that it can meet with a combined set of proofing criteria of the climate. This can also be confirmed by the measurable indicators of social and economic sustainability (i) reduction or reintroduction of GHGs, (ii) conservation, (iii) increased productivity and access to livelihoods and resources for local people, (iv) poverty reduction and vulnerability, and improved resilience or capacity flexibility, (v) spatial capacity and skills development, (vi) cooperation with international and international steel objectives and (vii) integration or integration into sustainable development strategies.

8.7 Concluding Remarks It is critical to define who is getting what, where, and how and this is applicable at all levels. The high altitude remote villages; Tarmehr, Puling, and Bada Bhangal are the areas where the land holdings are little large as compare to those in other blocks and villages in the district but the average size of land holdings are not enough to create much sustainability because most of the land areas are either infertile, barren or not useful to support any economic activity. In these regions, the livestock numbers are great but productivity is insufficient for sustainable livelihood. There are other well-flourished villages where land is fertile and having all the support but the size of holding is so small that they can not even support a single household. The marginalized groups like; the poorest traditional occupations who are dependent upon grazing the livestock, fodder collection, fuelwood, and Non-Timber Forest Products (NTFPs) collection are predominant in the district and that forms major livelihood source across villages. The Gram Panchayat with the help of SHGs, professionals, etc. are initiating participatory processes in the district at a large scale for livelihood analysis, resource mapping, and livelihood assessment on the basis of raw material availability. The women in Panchayati Raj Institutions are getting several benefits like; 33% reservation for various categories; banking, loan, and subsidy system. Through this system, banks have started giving loans to women-headed households at the rate of only 4% per annum recently in 2014 under an agricultural extension program to help and support especially women or those who are devoid of any landholding by providing them a guarantee of self-employment generation activity in the non-farming sector. Therefore, it is important to know how the presentday village communities are maintaining resilience and adapting to the unexpected climatic changes, and implementing the new adaptations strategies to enhanced

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and face the challenges through policy integration and decentralization. The Indian climate change policy is required to understand thoroughly in a chronicle manner to understand this micro-level situation better. Therefore, it has been discussed in detail in the next chapter (Chap. 9). The system approach that has been followed in adaptation-mitigation strategies can be either structural (like; water harvesting, modified farming system, institutional and technological infrastructures, etc.) or nonstructural (like; increasing awareness, strengthened institutions and adaptive norms, etc.) but have to work in a cohesive and integrated way like hardware and software unitary mechanism for more inclusive sustainable growth and livelihood, which has been adopted in this chapter.

References Annual Administrative Report (2016) Horticulture Department, Government of Himachal Pradesh, Shimla (various issues in Hindi) Baker J (2007) The Kuhls of Kangra: community-managed irrigation in the western Himalaya. University of Washington Press, Washington Department of Agriculture (2019) District agriculture plans of H.P. (DAPs). Palampur, Himachal Pradesh Directorate of Industries-Sericulture Wing (2016) Government of Himachal Pradesh. Shimla Economic and Statistics Department Government of Himachal Pradesh (2017) District domestic product of Himachal Pradesh 2011–12 to 2015–16. Shimla Forest Survey of India (FSI) (2015) State of forest report. Ministry of Environment and Forests, Dehradun Himachal Pradesh Agricultural University (2011) Department of tea husbandry and technology reports. Palampur, Himachal Pradesh Hoy A, Katel O (2019) Status of climate change and implications to ecology and community livelihoods in the Bhutan Himalaya. In: Environmental change in the Himalayan region: twelve case studies. Springer, Cham. 23–45 Imperial Gazetteer of India (1864) His Majesty’s secretary of state for India in Council. Clarendon Press, Oxford, pp 1908–1931 Planning Commission (2008) Eleventh five year plan (2008–2012). Volume I inclusive growth, New Delhi Planning Commission (2015) Eleventh five year plan 2007–12. Volume-III. Agriculture, rural development, industry, services and physical infrastructure. Government of India, New Delhi Sajjad H, Nasreen I (2016) Assessing farm-level agricultural sustainability using site-specific indicators and sustainable livelihood security index: evidence from Vaishali district, India. Community Dev 47:602–619 Singh RB, Jha S (2014) Agriculture and forestry based livelihood capital assessment. In: Livelihood security in Northwestern Himalaya. Springer, Tokyo, pp 95–106 Singh RB, Singh S (2014) Human-induced biome and livelihood security. In: Livelihood security in Northwestern Himalaya. Springer International Publishing, Netherlands, pp 53–66

References

Web Sources The Indian Express and Navbharat Times (2009) http://www.indiapress.org The Tribune (2001) https://www.tribuneindia.com/2001/20010827/himachal.htm

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Chapter 9

Indian Climate Policy, Programs, and Initiatives

Abstract Climate change has become a schmooze at an international and diplomatic level around the world since the 1970s and particularly from the time of 1992 Rio Earth Summit, which gave a whole new dimension to this issue by highlighting its importance to sustainable development. However, it is imperative to look at how it is translated into ginormous Indian national policies and program enforcement and then how these initiatives interacted at domestic levels? India’s predominantly agrarian economy and unique geographical setting play a very vital role to make the country one of the climate-sensitive regions in Asia. Realizing the fact that the climate change phenomenon can threaten the country’s developing economy and livelihood structures, therefore it has initiated various climate change policies, plans, and adaptation measures. Highlighting its national initiatives on climate change diplomacy at the international platform, this chapter first scrutinizes various relevant literature documents related to the climate issue, encapsulates landmark decisions on climate policies and initiatives undertaken by the Government of India. Afterward, it has set the scene for India’s role in climate change policy, plans, missions, and programs at both domestic and international levels. It has focused in detail on constitutional and judicial provisions of India in support of climate change and environment protection articles, laws, acts, and statutes of India for multifaceted understanding from people’s perspective. Keywords Climate programs and initiatives · Missions · Adaptation and mitigation · Five-year plans · Constitutional provisions · Judiciary and climate · International treaties and conventions

9.1 Introduction Climate change is one of the most undeniable global challenges in the recent history of mankind. It has already shown our standing at the cross-junction of a most defining moment. The global climatological events have exposed a vulnerability to climate change ranging from shifting weather that threatens agriculture and livelihoods to further endangering food security, sea-level rise leading to catastrophic flooding, © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 S. Singh and R. B. Singh, Simulating Climate Change and Livelihood Security, Advances in Geographical and Environmental Sciences, https://doi.org/10.1007/978-981-16-4648-5_9

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9 Indian Climate Policy, Programs, and Initiatives

melting of glaciers, coastal zone erosion, natural disasters, vector-borne diseases, and many more. The impact of climate change is not local but global in its scope and unprecedented in scale. No single country can take wholesome responsibility to make it right, but it should be collaborative in its effort to secure a sustainable path of development for all. According to the official definition of the United Nations Framework Convention on Climate Change (UNFCCC), climate change is linked to direct and indirect anthropogenic activities that can alter the composition of the earth’s atmosphere over a comparable period. Similarly, the Intergovernmental Panel on Climate Change (IPCC) in its reports clearly stated that climate change is a change in the state by altering its means and variability of its properties for an extended period (IPCC 2001; Change 2007; Holm and Winiwarter 2017; Ray 2020). The majority of the world’s countries recognize climate change as a grave risk to human development and called for collective action both from developed and developing countries. India together with China, the two most populous countries of the world also named as a major polluter of greenhouse gas (GHGs) by developed countries; the USA and most European countries. Though India is one of the world’s lowest per capita greenhouse emitters, yet it is declared as the 4th largest source of GHG producer of the world when looked into total tons produced (Center 2008; Thaker and Leiserowitz 2014). This bestowed a puzzling task of dichotomy at the international climate agreement arena for fair appropriations of responsibility in taking action against it. India, as being one of the highly vulnerable nations to climate change impacts, plays a critical role in world climate negotiations in determining the course of the global climate change agreements and gaze for better sustainable practices at the local levels. To take the matter seriously, the Government of India (GOI) has recently revised its national and domestic policy measures for adaptation and mitigation of climate change; it also changed the name of its Ministry of Environment and Forests (MOEF) to Ministry of Environment, Forests and Climate Change (MOEFCC) that is signifying the country’s responsibility for the global climate change awareness. India, covering the world’s seventh geographical area and home to more than 1.21 billion people (Government of India 2011). Geographically situated in diverse climatic conditions stretching from the Himalayan Mountain in the north to the Indian Ocean in the south, gives wide varieties of climatic experiences and bio-geographies. However, this uniqueness also exposes it to a range of extreme climatic events; floods, droughts, and cyclones, etc. that has put lives, economy, and livelihoods at risk. The country still predominantly revolves around the agrarian economy and sectors related to it. This has compelled India to look into its climate change policies and programs at the multi-governance level by bringing national and sub-national endeavors together for shaping Indian climate change policy. This second largest populous county of the world has every possible reason to be concerned about the changing climate and its impacts because its large population is still dependent on climate-sensitive sectors; forestry and agriculture for their livelihoods. Thus, even an insignificant adverse impact on water availability or weather condition has been threatening its food security, death of natural ecosystem, extinction of endangered species, health epidemic, economic losses, sustainable livelihoods, etc.

9.1 Introduction

275

Nonetheless, considering the facts about India’s economic and developmental needs, one can argue about additional prioritization on fast economic growth and modernization before much hue and cry on the environment. But, at present when climate changes are at its irreversible juncture not a single country can afford to become a spectator and definitely not in the case of India. Economic and social equity and development can be attained through a balanced approach to sustainable development. India is moving towards a balanced and interwoven approach at multilevel for climate change mitigation and adaptation along with economic development policy that may prove to be a rescuer for the climate-related issues and needs of people. The Indian Network for Climate Change Assessment (INCCA) was established in 2010 as a climate change body of India by the Ministry of Environment and Forests (MoEF) that broadcasted its first study in the same year. The study highlighted the impact of climate change on India and divided it into four ecosensitive zones to bring sustainability by 2030 namely; the Himalayan region, the North-Eastern region, the Western Ghats, and the coastal region along with its five climate change variables into five sectors agriculture, forests, biodiversity, water resources and coastal zones (INCCA 2010). The modeling of climate data for these five sectors presented not so rosy picture of development in all the four regions. Therefore, it was targeted to be focused on understanding India’s geo-environmental near future risks to better prepare the country with adaptation and mitigation policy measures (Table 9.1). The main variables that have been included were: • • • • •

Temperature variability Precipitation variability Sea-level rise Droughts and floods (extreme events) Environmental health risk.

Needless to say that, India’s vulnerability to climate variability was not induced by only bio-physical conditions but also shaped by hybrid non-climatic drivers such as social development, economic growth, institutional and technological factors. The poor and marginalized, mostly those who are engaged in agriculture and allied sectors are hard hit by both climatic and non-climatic variability. Thus, in recent few years, India has shifted its stances on environmental planning, policy, and programs at the international and domestic levels to become a contender and front line worrier in climate change moving away from its earlier stance as an observer. However, India’s journey to fight for sustainability has started early with the first global conference on the environment, in Stockholm in 1972 that kick-started a series of negotiations and discussions on the matter of international environmental issues. Wherein the Indian Prime Minister Mrs. Indira Gandhi’s speech prompted the role of the developed world is causing global environmental problems and putting the burden on poor and developing countries (Vihma 2011; Thaker and Leiserowitz 2014). This journey continued for twenty years, later at the Rio Earth Summit in 1992 where all countries got together to agree on the United Nations Framework Conventions on Climate Change (UNFCCC) to set the emissions targets and form a universal treaty with over 190 signatories. In each of these cases, India’s participation

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Table 9.1 Summary of climate change projections for India by 2030s Variable name

Climate change projection

Temperature variability

• Net increase in annual temperature by 2030s between 1.7 and 2.2 °C in all four regions • Warmer seasons by 2 °C by 2030s • Extreme min. and max. temperatures by 2030s

Precipitation variability

• Increase in precipitation by 2030s and this increase will more in the Himalayan and North-Eastern regions • 10–15% increase in monsoon precipitation in various regions • The number of rainy is projected to decrease however, the intensity of rain will increase

Sea-level rise

• Rise in sea level along with the Indian coastal areas with the rate of 0.3 mm/year and it will be more with global sea-level rise • Coastal inundation with 1 m sea-level rise in low-lying areas will be the mandatory norm

Droughts (extreme events) • A sharp drop in the groundwater level across the country by 2030s • Also, rivers across the country will experience water stress most of the time Floods (extreme events)

• Flooding will be a common scenario for all the regions with a higher magnitude of >10–30% • Increase in cyclone activities and intensity by 10–20% and more in the east coast region by 2030s

Environmental health risk • More frequent incidences of environment linked health issues due to extreme weather Source Information derived from INCCA (2010)

in the conference was explicit to the cause, though at that time it did not create much impact (Atteridge et al. 2012; Dubash and Khosla 2016). Yet, a significant report from the Center for Science and Environment (CSE), on ‘Global Warming in an Unequal World’, alleged developed countries for carbon colonialism and putting the blameworthiness on developing and the underdeveloped poor world (Agarwal and Narain 2012; Dubash 2019; Ray 2020). Slowly but steadily, India’s foreign policy on climate change started viewing transition, particularly with its growing power as an emerging economy and with international aspirations to hold a permanent seat in the UN Security Council. India outlived its ‘do nothing’ stance to its usefulness by shifting its strategies to gain more ‘bargaining power’ at an international platform (Kapur et al. 2009; Raghunandan 2012; Cameron et al. 2016). Understanding the importance of environmental policies in economic development and international bargaining power, India has gradually internalized its climate considerations into its domestic policies and became a testing ground for integrated climate policy considerations into its developmental process. This present phase of India’s climate change policy modification thus seems to have come up with realism by a peripatetic long journey. This chapter is an attempt to look behind the reasons for this highly significant policy shift to highlight the need and rationale for mainstreaming India’s domestic climate policies, adaptation, and mitigation plans in national planning and

9.1 Introduction

277

development. After brief contextual background, it further highlights India’s fiveyear development plan and especially focussed on the 11th and 12th five-year plan and Three-Year Action Agenda (2017–2020) by Niti Aayog to serve its agenda of sustainability and total development in long run with environmental considerations. This chapter encapsulates the constitutional and judicial provisions for a better understanding of India’s domestic response to its public requirement.

9.2 India’s International Climate Diplomacy—A Policy Shift from Rio to Paris Being one of the major emerging economies of the world along with China and Brazil, India is constantly under pressure from time to time since the 1990s by the industrialized world to adopt the international commitments on the reduction of its growing GHG emissions (IEA 2020). However, India and China had traditionally resisted this pressure with an argument that they bear only fractions of historical emissions and right now their emphasis is on development to uplift their economies, lives, and livelihoods (Le Quéré et al. 2020). This argument was somewhat true also as India is among one of the world’s lowest per capita GHG emitter (4.47%) with about 17% of the total world’s population, though it was yet the 5th largest GHG emitter by international statistics in the year 2000. China stood with nearly 12% of total global GHG emission, was the largest developing country emitter, ahead of India (Table 9.2). India has been facing a great dilemma and challenges to balance the development and environmental concerns. On one hand, it fears that promising the international Table 9.2 India’s greenhouse gas emissions in comparison to other significant emitters Country

1990

2000

Million tons of carbon dioxide equivalent

Per cent of the world total

Million tons of carbon dioxide equivalent

USA

5630.00

14.62

6525.20

15.81

China

3973.50

10.32

4890.40

11.85

Indonesia

2498.80

6.49

3065.60

7.43

Brazil

2641.80

6.86

2223.20

5.39

Russian Federation

2916.00

7.57

1969.40

4.77

India

1305.00

3.39

1843.80

4.47

Japan

1216.70

3.16

1321.00

3.20

Germany

1198.50

3.11

1009.40

2.45

Source INCCA (2010)

Per cent of the world total

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treaty would hamper its commitment to development and may reduce the poverty resolutions. On the other hand, the country has been facing adverse climatic extremities. It has been inevitable to see India’s role at the international platform in climate negotiations through exploring its empowered diplomacy by shifting its stand from traditional accord to just protect the vulnerable and poor rather than providing them choices and opportunities.

9.2.1 India’s Traditional Route to the Kyoto Protocol India’s long-standing position in international climate negotiations was built on the amalgamation of principles that comprises equity and pragmatic concerns. According to official Indian documents, developed countries produced mainly accumulated greenhouse gases (GHG) in the atmosphere (almost 75%), and thus they should be the prime in-charge of changing climate (Saran 2009; Prasad and Kochher 2009; Zheng et al. 2019). Therefore, these countries must have had performed their duty to act first according to the stipulations of the Kyoto Protocol, thereafter they should not expect commitments from other developing or less developed countries. India strongly mentioned that, according to global equity rights, each person can emit the same amount of carbon into the atmosphere and in this case, India was far below (per capita carbon emission from 2010 to 2018 was about 1.7 metric tons) than the other developed world and even to China, which was 6.2 metric tons for the same period (Le Quéré et al. 2020). In the year 1997 Kyoto Protocol was adopted by the Conference of Parties 3 (COP 3) after rigorous and intense negotiations between the world economies. Most of the developed nations and European economies (defined as Annex B countries) agreed to reduce their GHG emissions on an average of 6–8% below the level of 1990 by the year 2012 (Bodansky and Rajamani 2018; Upadhyaya et al. 2018). This meant that mainly rich nations pledged to reduce carbon emissions. India at that time did not take part in this action being a poor and developing country but played quite a substantial role in the negotiation talk. Indian negotiators pronounced some undeniable facts to justify the country’s stance of indifference towards climate change in international negotiations in terms of per capita emission, common but differentiated responsibility, equity, and environmental justice. The summary of the Indian view on emission negation read as follows (Rajan 1997): Even assuming high economic growth by developing countries and stabilization of energy consumption by the developed countries over the next 20 years, the developed countries would continue to be responsible for a major portion of the greenhouse gas emissions. The developing countries would [be] require[d] to increase their energy consumption for their development and for the alleviation of poverty. The responsibility for the reduction of greenhouse gas emissions to prevent climate change would, therefore, rest with developed countries. The developing countries will be prepared to cooperate in energy efficiency measures but no targets can be fixed for the reduction of greenhouse emissions by them.

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Nevertheless, with some initial thrust, this negotiation failed, as the USA never approved the Kyoto Protocol, and also other countries did not accomplish their pledge. Though, slowly India distanced itself from its traditional hardliner position before the Copenhagen summit in 2009.

9.2.2 Birth of BASIC and India’s Stand in Copenhagen Accord As the USA was not willing to fulfill the pledged reduction commitments and moved to stalled the deal further, Australia proposed a slightly modified version of the followup treaty in Copenhagen Summit in December 2009 by removing the difference between Annex B countries and the rest to call for an individual commitment by every emitter and promising in exchange of this a generous mitigation and adaptation assistance. India’s then Prime Minister, Dr. Manmohan Singh announced a general deliberation at the 63rd UN General Assembly about India’s position to support multilateral negotiations under the UNFCCC a day before the summit. He announced that India was ready to willingly reduce the emission intensity by 20–25% by 2020 as compared to 2005 (Jain 2012, 2015; Destradi 2018). His statement was read as; ‘the outcome must be fair and equitable and recognize the principle that each citizen of the world has equal entitlement to the global atmospheric space’ (Bhattacharyya and Pulla 2019; Nachiappan 2019). According to the Minister of the Environment of that time Mr. Jairam Ramesh, India’s stand of no emission reductions was not only disfavoured by the developed countries, small island states, and vulnerable countries but can also hinder its aspirations for permanent membership on the Security Council (Sethi 2009). This unilateral commitment from India was also a result of growing affiliations between India and the USA during the time of COP15 at Copenhagen and further with BASIC (Brazil, China, Indonesia, and South Africa) and the USA. After this, it was not very difficult for the United States to dispose of a final deal with the delegations of only these countries. The shift in India’s climate diplomacy attitude at the international level was not easily accepted at the domestic ground and even by Indian media. Many of the senior political leaders from oppositions criticized Minister of the Environment Mr. Jairam Ramesh for the undoing of India’s long fight against unfavorable climate change negotiations (Vihma 2011). Nevertheless, this whole issue at the national level gave much-needed momentum for several domestic steps to address climate change in the late 2000s, notably the formulation of the National Action Plan on Climate Change (NAPCC) came in 2008. It benefited at the country level but in the end, it failed to bring consensus upon a new climate agreement to substitute the Kyoto Protocol and top-down approach at Copenhagen (Hurrell and Sengupta 2012; Hochstetler and Milkoreit 2014).

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9.2.3 India’s Approach from Cancún to Paris COP 21 It seems that India’s active shift from its traditional approach was not enough to shock old loyalists of climate change, during the Copenhagen summit they further got harsh blows in 2010 COP 16 at Cancún. Here at the conference Minister of the Environment, Mr. Jairam Ramesh further broke the deal with India’s well-established old strategy by making an appeal that all the countries should take steps forward on legally binding commitments for reducing GHGs emissions. This paradigm shift created a massive uproar of criticism from opposition even in India. Simultaneously parties blamed the government for compromising on the development and sovereignty of the country (Ramesh and Talbott 2005; Lindzen 2006) However, at Cancún, India gained international accolades on its role in negotiations, issues of transparency, and personal thanking note from the COP president. This laid a new brick in India’s flexible climate policy and leadership. Nevertheless, the following year in 2011 at Durban (COP17), the Indian delegation led by the new Environment Minister Ms. Jayanthi Natarajan again reversed the stand and fallen back on the traditional approach of India’s international climate change diplomacy. Though, this stand marked reform in the international community approach towards the bottom-up methodology of climate governance. In 2013 at Warsaw COP 19, this idea fostered again leading to Nationally Determined Contributions (NDCs), which was adopted by global climate communities in 2014 at COP 20 in Lima. India submitted its NDC in October 2015 by committing to install clean energy capacities equivalent to 40% of its total electrical capacity in the country by 2030. This strong step came with a change in the political system in India after the general election of 2014. Under the new leadership of Indian Prime Minister Mr. Narendra Modi, India returned to pragmatism and attempted to revive back the agenda to deal with climate change (Menon 2014). It gave clear indications that India has established itself in a better economic and political position than before and countries like the United States, Japan, Russia, and even China showed its willingness to maintain not only economic but geostrategic interests with the country. Before COP 21 at Paris, the Government of India (GOI) unequivocally stated that each state should prepare a document on how they will combat adverse climate change impact. During this time the Minister for Environment, Forests and Climate Change submitted a joint report to the UNFCCC that has been discussed later in the COP 21 in Paris. The Paris Agreement culminated with a projected notion that, India has been a vital part of the solution to the global climate change problem (PMO 2019). Along with India other 188 nations had also submitted their individual climate action plans ahead of COP21 on how much they intend to cut their emissions by the year 2030. The chronological order of the timeline has been carved out regarding the international responses to climate change and India’s participation at international conferences might give a quick idea of climate change diplomacy (Table 9.3).

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Table 9.3 Fundamental developments in climate change measure across scientific, political, and environmental purviews; 1950–2020s Decade Before 1850s • In 1824, a French physicist Joseph Fourier experimented and quantified CO2 with other gases, their occurrence in the earth’s atmosphere and suggested that it may cause the ‘greenhouse effect’ • In 1861 an Irish scientist and mountaineer John Tyndall has started investigating the function of atmospheric gases, the tests exhibited that these gases were significant at absorbing electromagnetic wavelength of insolation • Svante Arrhenius in 1896 calculated that decreasing 50% of CO2 in the atmosphere can lower the temperature by 4–5 °C 1850s–1950s • During 1930s, a keen British engineer and meteorologist, Guy Stewart Callendar used weather station documentation across Europe, validated that the temperatures had increased over the erstwhile century with increased concentration of CO2 this has led to the fundamental principle of changing climate 1950s

• The year 1957 was a turning point declared as International Geophysical Year (IGY) for advanced carbon cycle research • Investigating the role of radioactive carbon14 , the chemist Hans Suess and Navy oceanographer Roger Revelle first applied carbon14 into studying carbon in trees and oceans and calibrated that the oceans absorb much less CO2 than predicted previously • Revelle found the ‘large-scale geophysical experiment’ where anthropogenic factors have been seen • In the year 1958 the Keeling curve revealed a rise in atmospheric CO2 • Plass calculated linkages between fossil fuel and global warming found it out as the main factor

1960s

• In 1965, the Environmental Pollution Panel of the United States President’s Scientific Advisory Committee recommended fossil fuel as ‘the invisible pollutant’ in increasing CO2 levels • Throughout the 1960s and 1970s become a popular green movement • The cooling trend (1940–1980) in global mean temperatures put the attention to the role of non-CO2 greenhouse gases, particles, and clouds • Scientists, policymakers, and NGOs started collaborating • After 1963 Conservation Foundation workshop, environmental organizations have come up to expand policy consideration to climate change

1970s

• In 1972 the first United Nations Environment Program (UNEP) first World Climate Conference was held which acknowledged the pivotal role of climate in world food production • The first World Climate Conference (WCC) took place in 1979 • Club of Rome’s Limits to Growth, Population Bomb by Erhlich, and the Tragedy of the Commons by Hardin publicly brought attention to the human role in environmental degradation and the greenhouse effect • The World Climate Research Program (WCRP) and the International Council of Scientific Unions (ICSU) were established • Scientific leading magnates succeed in educating and raising funds for climate change research (continued)

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Table 9.3 (continued) Decade 1980s

• The first time in 1985 ozone hole was discovered, so concern about abrupt climate change emerged from paleoclimatology • WCRP and ICSU further put the foundation of the Intergovernmental Panel on Climate Change (IPCC) by WMO and UNEP in 1988 • United Nations General Assembly (UNGA) that was working since 1946, the first time passed a resolution on international negotiations related to climate change • Several Conferences during the late 1980s; Villach (October 1985), Toronto (June 1988), Ottawa and Tata Conference (February 1989), the Hague Conference and Declaration in March 1989, the Noordwijk Ministerial Conference (November 1989), Cairo Compact (December 1989), etc. started the policy advice to meet the severity of global warming and policy issues • IPCC 1988 report found scientific beginning for policy concern. In its 2nd scientific assessment in 1998 confirms the human mark on the climate of the earth

1990s

• The first meeting of the Intergovernmental Negotiating Committee (INC) was held in 1991. In the year 1992, the INC adopted the UNFCCC text at the Earth Summit in Rio and during 1994 the UNFCCC enters into force led to the first Conference of the Parties (COP 1) at Berlin in 1995 • IPCC reports unbolted the scientific and political debate about the ‘hockey stick curve’ millennium trend • The 2nd World Climate conference called for a framework convention entered into force and led 1997 Kyoto Protocol

2000s

• IPCC has released the Third Assessment Report (TAR) in 2001 • Kyoto Protocol formally adopted at COP3 where it is first Meeting of the Parties (MOP 1) was held in 2005 at Montreal • The Fourth Assessment Report of IPCC (AR4) came in the year 2007 • In the year 2009, the Copenhagen Accord was drafted at COP15 in Copenhagen. Countries submitted emissions reductions pledges all non-binding

2010s

• Cancun Agreements at COP16 (2010) held with the objectives including; (i) mitigation (ii) transparency of actions (iii) technology (iv) adaptation (v) forests (vi) capacity building and (vii) finance • The Durban Platform for Enhanced Action was drafted and accepted at COP17 (2011) • In the year 2012 the Doha Climate Gateway at UNCCC in Qatar (COP18/CMP8) • The Green Climate Fund and Long-Term Finance at Warsaw Framework for REDD Plus started in 2014 • The COP21 was held in Nov.–Dec. 2015 in Paris • The IPCC Fifth Assessment Report (AR5) 2014, besides several recent special reports like; Special Report on climate change and land (SRCCL) in August 2019 and Special Report on the Ocean and Cryosphere in a Changing Climate (SROCC) in September 2019 were brought to focus on the severity of climate-related vulnerabilities • The year 2018 was marked by the rules for Paris Agreement decided ahead of COP24 in Katowice, Poland, a new IPCC report • The UN Climate Action Summit for world leaders in New York (2019) was seized to revise nationally determined contributions plans and COP 25 at Madrid, Spain (continued)

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Table 9.3 (continued) Decade 2020s

• The COP 26 that was scheduled to be held at Glasgow, UK postponed amid the COVID-19 Pandemic • The UNGA resolution number A/RES/74/269 and 242, agenda no. 24 and 20b adopted through silence procedure on biodiversity, agriculture, and sustainable development

9.2.4 The 2030 Agenda for Sustainable Development-17; Sustainable Development Goals (SDGs) The United Nation provided an agenda for sustainable development by 2030, which has adopted by all the UN member states in 2015. It outlined 17 Goals for Sustainable Development (SDGs) to be achieved by the year 2030. These SDGs are an urgent call for action by all the binding counties whether developed or developing. It covers a wide variety of issues including poverty alleviation, health, water, sanitation, energy, urbanization, education, global warming, gender equality, and other deprivations. This has been established with the belief that all issues must go hand-in-hand with strategies to reduce inequality and induce economic growth to deal with climate change and preserve the natural environment, oceans and forests (Fig. 9.1). India has already begun performing on its commitment to play its role in Sustainable Development Goal (SDGs). Its work towards climate change mitigation and adaptation plans at the domestic level as well as international level through active participation in conferences, treaties, and amendments. It is well aware of its status of the 4th highest emitter of CO2 and 6.9% of global emissions have started taking strict measures through various acts, e.g. The Green Tribunal Act, etc. without halting its developmental processes. In October 2015, India committed to reduce its emissions intensity by 20–25% from its 2005 levels by 2020 and moving towards further reducing it to 33–35% by 2030s (Upadhyaya et al. 2018). As a major step forward by the Indian Government, it also initiated NAPCC in 2008 and the National

Fig. 9.1 Highlights of UN sustainable development goal 13 concerning India’s effort; climate action and goal 11: sustainable cities and communities. Source Adopted from United Nations Organization

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Mission for Green India to address the climate change issue directly. These national plans, policies, and programs have been complemented by a congregation of specific programs on solar energy, enhanced energy efficiency, sustainable habitats, water, sustaining the Himalayan ecosystem, and encourage strategic knowledge for climate change. India has also outlined its sustainable communities and city’s goal of SDGs by broadly working on reducing adverse per capita environmental impact from urban areas by 2030 by paying special attention to air quality, municipal, and other waste management policies. It has been supporting quite a few positive economic, social, and environmental links between urban, peri-urban, and rural areas by strengthening national and regional development planning, mitigation, and adaptation to climate change and the other disasters with a motto of sabka saath sabka vikas (with all for overall development). Thus, the climate change diplomacy in India came a long way from the framework of externalizing the climate issues for the sake of poverty alleviation and economic growth to a more pragmatic approach of taking collective responsibility for climate action. This transformation is a result of India’s international aspirations to play a bigger role, increasing scientific consensus that believed in the need of reducing its GHGs emission even being a developing economy. It has on the go to play a bigger role in climate sustainability and awareness among local government, people, media, and grassroots organizations by adopting more proactive climate change policies and programs with the five-year plans and other short term plans.

9.3 India’s Actions on Climate Change at Domestic Ground Through Policies, Programs, and Plans India’s emission is growing day by day, being 4th largest emitter its CO2 emission is currently 4.8% (2019) that is almost doubled since 2005 despite turbulent economic growth. If measured with per capital usage, it is still low at merely 1.8 tons of CO2 , which is lower than the world’s average emission of 4.2 tons. Though, if it is seen from the historical perspective its average growth rate of emission over the past decade is quite high (Saryal 2018; Andersson 2019). Being a developing economy and having a large population this country is still struggling to meet the challenges of climate change. It has moved to multi-level planning for climate considerations. This section discusses the GOI’s action on climate change at planning, policy, and constitutional provisions through National Action Plan, national missions covering adaptation and mitigation, state action plans, five-year plans, and the most recent Niti Aayog’s three-year action agenda for greater investment on better scientific infrastructure. India’s journey to international climate change diplomacy has also been discussed simultaneously. The framework may deliver a commendable understanding of India’s national policy principles and design aspects in the present

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285

scenario that has been strongly influenced by international environmental agreements and policy interventions.

9.3.1 National Environment Policy (2006) National Environmental Policy, 2006 worked as a regulator reform guidebook for the integration of environmental considerations in all public development activities. It streamlined and decentralized the environmental clearances to promote standardized environmental accounting practices on better monitoring of environmental compliance in key areas; coastal areas, water resources, forests, agriculture, and health sectors. This policy targeted initially in increasing forest and tree cover up to 1/3rd of the country’s land area by 2012. Together with the enhancement of wildlife conservation areas, efficient use of groundwater, protection of the mountain ecosystems, and promotion in energy efficiency around states. It was the first initiative in introducing environmental management systems in large enterprises through eco-certification and provision for financial support to promote changes to clean technologies (Geevan 2004; GOI 2006). Through NEP several mechanisms have been adopted to evaluate of state’s performance in Clean Development Mechanism (CDM), where Himachal was the only state declared as carbon neutral. Stakeholders from different sections of society participated in the framing of the National Environmental Policy and it was decided to put it for revision every three years. The National Committee of climate experts and representatives from several key ministries have been recruited to assess the impact of climate change. This committee also advises the Prime Minister’s Council on Climate Change for planning, policy, mitigation, and adaptation issues related to national climate change (GOI 2006; PMO 2019).

9.3.2 Prime Minister’s Council on Climate Change (2007) Prime Minister, Dr. Manmohan Singh in October 2007 has established a high-level advisory council on climate change issues. It advised the government on National Action Plans for adaptation, mitigation, and assessment matters of climate change (Fig. 9.2). Together with the government and private body members collectively act under the guidance of the present Prime Minister Mr. Narendra Modi to reconstituted it and carved it out in the form of the National Action Plan launched in November 2014 (PMO 2019). It was done to create awareness on the threats posed by climate change in various forms among government representatives, the public, industry and communities as a whole and suggested steps at the national, and state levels to counter these changes.

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Fig. 9.2 Institutional arrangement for climate change adaptation policy planning and implementation in India

9.3.3 The National Action Plan on Climate Change (NAPCC), 2008 India made significant progress by the year 2007 at national and sub-national levels in establishing policy and institutional frameworks for the advancement of climate change. In June 2008, Prime Minister Dr. Manmohan Singh unveiled India’s first National Action Plan on Climate Change (NAPCC) by outlining existing and future climate change policies and programs for mitigation and adaptation. NAPCC consisted of eight national missions with long-term strategies on adaptation and mitigation goals. These goals were focused on energy efficiency and natural resource conservation. The adaptation policy framework to deal with climate change issues at various stages were prepared in 2008 under the guidance of the Prime Minister’s Council on Climate Change. The underline principle of NAPCC was centered on the ‘co-benefits’ at a multi-sectoral level. Therefore, keeping this in mind, NAPCC made provisions to implement various sector-specific and region-centric climate change action plans through eight National Missions (Table 9.4). Along with these eight national missions, four new missions to NAPCC were recently added by the government. These were; wind energy, human health, coastal resources, and waste-toenergy (Table 9.5) (Pandve 2009; Upadhyaya et al. 2018). The evaluation committee on NAPCC in 2012 indicated inadequate cooperation between ministries and dispute

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Table 9.4 National Action Plan on Climate Change missions Missions

Policy measures

Jawaharlal Nehru National Solar Mission (JNNSM)

Improving resource efficiency and energy security, through the utilization of abundantly available solar energy in India Empowerment of rural poor through decentralized energy supply technologies

National Mission on Enhanced Energy Efficiency (NMEEE)

To minimize the concern of depleting non-renewable energy resources this mission brings back energy security Making the installation cost-effective through market mechanisms Improved technological innovation through technological upgrades and the application of global efficiency standards

National Mission on Sustainable Habitat (NMSH)

Optimize energy demand through better urban planning and public transport Improve the resilience of infrastructure to climate change and disaster management

National Water Mission

Water conservation and waste minimization through integrated water resource management

Green India Mission (GIM)

Protection of livelihoods and of ecological balance and biodiversity, through forest protection and management Carbon sink potential Effective utilization of land as a key resource

National Mission on Sustainable Agriculture (NMSA)

Concerns of the vulnerable agricultural system, food security, livelihoods, and economic stability in rural India

National Mission for Sustaining the Himalayan Protecting the agricultural sector and other Ecosystem (NMSHE) water needs, by addressing predicted threats to the flow of perennial rivers National Mission on Strategic Knowledge on Climate Change

Enhancing national scientific and technological capabilities, by establishing networks of research institutions at the national level, and promoting collaborations at the global level

on the issue of co-benefit therefore, a state action plan on climate change has been introduced later. The NAPCC also describes other ongoing initiatives which are as in Table 9.5.

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Table 9.5 National Action Plan on Climate Change sub-initiatives Ongoing initiatives

Measures

Power generation

This might assist and support R&D on Integrated Gasification Combined Cycle (IGCC) and Supercritical Technologies for power generation

Renewable energy

Under the Electricity Act 2003, the central and the state electricity regulatory commissions must purchase a certain percentage of grid-based power from renewable sources

Proposals for the health sector

Providing enhanced public health care services and assessment of increased burden of diseases due to climate change

Energy efficiency

Large energy-consuming industries are required to undertake energy audits and an energy-labeling

9.3.4 State Action Plan on Climate Change (SCAP) Under the guidance of the Central Government and NAPCC, all the Indian state governments and union territories are advised to prepare State Action Plans on Climate Change (SAPCC) that aimed in creating institutional capabilities and implementation power to address climate change and sector-specific plans for it. So far only 21 States out of 28 have prepared the document for State Action Plan on Climate Change (SAPCC) including Delhi, Tamil Nadu, Madhya Pradesh, Uttar Pradesh, Arunachal Pradesh, and Karnataka among others (Bodansky and Rajamani 2018; Upadhyaya et al. 2018).

9.3.5 Five-Year Plans and Climate Change Five-year plans can be seen as a guidebook for holistic development planning and financial budgeting through long-term planning. These five-year plans have been set to encompass the visions of development and outlined a broad framework for sectoral policies and planning to achieve a set of socio-economic and environmental goals. Particularly, India’s 11th and 12th FYPs incorporated visions for sustainable and inclusive growth that favored environmental protection through climate change actions (Planning Commission 2015).

9.3.5.1

11th Five-Year Plan

Eleventh Five-Year Plan of India (2007–2012) has emphasized an urgent need for a balanced trade-off between economic growth and environmental sustainability. This FYP also acknowledged the danger of economic growth, overexploitation of natural resources, and burgeoning population pressure on climate sustainability. Therefore,

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during this FYP environmental development incorporated several policies targeting to reach 33% of forest and tree cover requiring additional coverage of 10–11 million hectares of forestland to achieve WHO targets for improving air quality in the major cities by 2012. In the case of climate change impact, it was mentioned that since the adverse impacts of climate change are unavoidable and wide-spread, priority should have been given to mitigation and adaptation plans. The areas of agricultural technologies and practices, forestry management, watershed management, coastal zone planning, and regulation and health were focused.

9.3.5.2

12th Five-Year Plan

The Twelfth Five-Year Plan (2012–2017) of the Planning Commission marked as the last five-year plan because the FYP concept has been scraped by bringing short term three-year strategic agenda. The Planning Commission has been renamed to Niti Aayog in 2015, which identified four critical, challenging areas where India needs to focus on were; climate change, managing energy requirements, water resource management, protection of the environment, and issues of rapid urbanization. The main focus areas of 12th FYP were: • • • • • • •

Environment management Market efficiency and inclusion of climate protection Rural transformation and sustained growth of agriculture Decentralization, empowerment, and knowledge for sustainable development Technology and innovation Improved access to quality education Managing urbanization.

The 12th FYP worked on the theme of inclusive growth by implementing the activities outlined under various missions of the National Action Plan on Climate Change and a low carbon mitigation strategy.

9.3.5.3

Three-Year Action Agenda by Niti Aayog

The Three-Year Action Plan (2017–2020) was prepared by Niti Aayog, suggested a substantial amount of expenditures by 2019–20 on education, energy, health, agriculture, rural development, and other categories for better environmental sustainability (Agarwal and Agarwal 2018). In Part VII, it addresses the issues of high levels of air pollution in the cities, black carbon pollution, use of biomass fuels in cooking, massive volumes of solid waste in urban areas, and deforestation (NITI Aayog 2015, 2017). It also provides the guidelines for different sectors to work in the line of inclusive growth and environmental sustainability by strengthening and streamlining regulatory structures of governance at multi-levels includes; • Relief measures in the event of natural disasters need to be improve

290

9 Indian Climate Policy, Programs, and Initiatives

• Enhance livelihood and income provision for farmers • Boosting productivity in agriculture in a sustainable manner • Water Management by desalinization, recycling, and water conservation.

9.3.6 National-Level Sectoral Policies The FYPs and NAPCC provided a guideline framework for the adaptation and mitigation policies in different sectors. These frameworks help recognize the potential risk of climate change and identify the adaption and mitigation measures of various kinds (NITI Aayog 2017; Dubash 2019). Table 9.6 outlines briefly by providing an assessment of the key sectoral policies and strategies in climate change and its adaptation plans. India’s recent activities at the national and international levels along with the domestic awareness campaigns on climate change and environmental protection has lead the Indian population on ever-expanding climate consciousness in the country. The urban, as well as a rural population, are well aware of the familiarity of climate change issues.

9.4 Constitutional Framework and Legal Actions on Environment Protection and Climate Change in India Indian constitution provides a basic foundation for all environmental laws, acts, and statutes. The constitution of India through its ‘Directive Principle of State Policy’ directs a duty to all the states for the protection and improvement of their environment, safeguard the forest and wildlife of the country. It declares the fundamental duty to every citizen to protect and improve the natural environment including; forests, lakes, rivers, and wildlife. The fundamental right to life in Article 21 of the constitution elaborated by judicial interpretation to incorporate the right to access a clean, healthy, and pollution-free environment.

9.4.1 Environmental Safeguard from Indian Constitution Outlook The Government of India and the Indian Constitution have put a great emphasis on environmental protection. It also included the right to access a clean and liveable environment as a fundamental right. It is also supportive of stringent environmental legislations and regulations to protect the environment. Much constitutional legislation in the past 30 years has been passed to tackle the problems of environmental degradation (Rajamani 2013; Badrinarayana 2016; Peel and Osofsky

9.4 Constitutional Framework and Legal Actions on Environment …

291

Table 9.6 National sectoral strategies and policies showing climate change action their plans Policies

Absent Climate change as a Possible actions for Identified targets for potential risk identified risk specific adaptation reduction measures

National Environment Policy (2006)

–

Yes

Yes

–

Integrated Energy Policy (2006)

–

Yes

–

–

National Policy for Farmers (2007)

–

Yes

Yes

–

National Biodiversity Action Plan (2008)

–

Yes

Yes

–

National Urban Sanitation Policy (2008)

–

Yes

Yes

–

National Policy for – Disaster Management (2009)

Yes

–

–

National Water Policy (2012)

–

Yes

Yes

–

National Agroforestry Policy (2014)

–

Yes

Yes

–

National Policy for – Disaster Management (2009)

Yes

–

–

National Health Policy (Draft) (2015)

Yes

–

New and Renewable Yes Energy Sector for the Period 2011–2017

–

–

–

Agricultural Policy Vision 2020

Yes

Yes

–

–

2018). The articles related to climate and environment protection of the Indian constitution have been outlined as follows; 1.

2.

Article 21 of the Constitution is a fundamental right that provides the right to life and personal liberty to every citizen of the country including the right to a clean, healthy, and pollution-free environment. Article 32 of the Constitution empowers all citizens of India to move the courts for violation of their fundamental rights.

292

3.

4.

5. 6.

7. 8.

9.

10.

11.

9 Indian Climate Policy, Programs, and Initiatives

Article 38 directs the State to strive for the welfare of the people by minimizing the inequalities in income, securing and protecting livelihoods, providing opportunities and justice. Article 39 of the Indian constitution gives guidelines and directions to the states for policymaking. It specifies the states where they have to work to grow as a welfare state in the interest of citizens of India. Article 41 gives the right to work, to education, and public assistance in certain cases in cases of unemployment and loss of livelihood. Article 43 of the Indian constitution is a Directive Principle of State Policy and is a non-enforceable part of the Indian Constitution. It says that the state shall endeavor to secure and provide all workers, agricultural, industrial, or otherwise, work, a living wage, conditions of work ensuring a decent standard of life. Article 47 of the constitution lays responsibilities on the states to raise the level of nutrition and the standard of living and improve public health. Article 48-A of the Indian constitution gives the Indian state’s responsibility to protect the environment it reads as follows: “The State shall Endeavor to protect and improve the environment and to safeguard the forests and wildlife of the country”. Article 51-A (g) mention that environmental protection is a fundamental duty of every citizen of this country to protect and improve the natural environment including forests, lakes, rivers, wildlife and to have compassion for living creatures. Article-243G gives powers, authority, and responsibilities to Panchayats related to drinking water, irrigation, village environment, family welfare, women, and child development. Most of the environment-related laws enacted by the India Parliament have been based on Articles 252 and 253 of the Constitution. Some of these legislations are regulatory while some are punitive to prevent damage to the environment.

9.5 Ministries Related to Improving Climate and Reducing Emission Load Since the ambient environment and reduced vulnerabilities due to climate change plays an important role in the lives and livelihoods of the people. Sustainable environmental development has overlapped with various other dimensions. Several ministries in India are working together to reduce emission load and carbon footprinting for overall development. Numerous ministries that directly and indirectly work on climate change and its components have been listed and it was found that out of total of 59 ministries, the following 32 are related to climate as; 1. 2.

Cabinet Secretariat Ministry of Agriculture

9.5 Ministries Related to Improving Climate and Reducing Emission …

3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32.

293

Ministry of Chemicals and Fertilizers Ministry of Civil Aviation Ministry of Coal Ministry of Corporate Affairs Ministry of Culture Ministry of Development of North-Eastern Region Ministry of Drinking Water and Sanitation Ministry of Earth Sciences Ministry of Environment and Forests Ministry of Heavy Industry and Public Enterprises Ministry of Home Affairs Ministry of Housing and Urban Poverty Alleviation Ministry of Law and Justice Ministry of New and Renewable Energy Ministry of Personnel, Public Grievances, and Pensions Ministry of Road Transport and Highways Ministry of Rural Development Ministry of Science and Technology Ministry of Shipping Ministry of Social Justice and Empowerment Ministry of Statistics and Program Implementation Ministry of Steel Ministry of Textiles Ministry of Tourism Ministry of Tribal Affairs Ministry of Urban Development Ministry of Water Resources Ministry of Women and Child Development Ministry of Youth Affairs and Sports Planning Commission Prime Minister’s Office.

9.5.1 Environmental Laws, Acts, and Rules by Indian Judiciary System The Indian constitution responsively takes action on the protection of the environment and establishes a dialogue between citizens and states about climate change. The law of the land commands the duty to both citizens and the state to protect and conserve the environment (Mohan and Wehnert 2019). The legislative regulation for the forested area can be traced back to the colonial period and now it includes a wide variety of specific legislation in the areas of water, air, forest, wildlife, health, and environment, etc. The government of Indian and the judiciary also enacted various national laws for the prevention, control, and management of industrial and urban pollution to combat global warming (Nandimath 2009; NITI Aayog 2017; Fernandes et al. 2019). The

294

9 Indian Climate Policy, Programs, and Initiatives

highlights of various legislative acts, rules, and laws have been briefly listed below in chronological order: • The Indian Penal Code (IPC) 1860, during the British period, used to deal with the offenses affecting public health, safety, and conveyance, covered with the aspects of water and environmental pollution. • The Indian Forest Act, 1927 dealt with four categories of the forest, namely, reserved forests, village forests, protected forests, and non-government (private) forests. According to it, a state has the right to declare forestlands or wastelands as reserved forests. • The Indian Wildlife Protection Act, 1972, amended 1999. • The Water (Prevention and Control of Pollution) Act, 1974, provide the prevention and control of water pollution and maintain and restore the purity of water in the country. • The Forest (Conservation) Act, 1980, was adopted to protect and conserve the forests. • The Air (Prevention and Control of Pollution) Act, 1981 to provide prevention, control, and abatement of air pollution for the establishment of the aforesaid purposes. • The Environment Protection Act (EPA), 1986 to provides a framework for the coordination of the activities for numerous central and state authorities established under previous laws, such as the Water Act and Air Act. • The Factories Act, 1948 (amended in 1987) to ensure the welfare of workers in their working environment to ascertain the safety and health of the workers. This Act contributes to environmental protection. • The Public Liability Insurance Act, 1991, to provide mandatory public liability insurance for installations handling hazardous substances to provide minimum relief to the victims. • The Coastal Regulation Zone Notifications, 1991 to impose restrictions on the setting up and expansion of industries, operations or processes, etc. in the Coastal Regulation Zones. • The Ozone-Depleting Substances (Regulation and Control) Rules, 17 July 2000, to regulate ozone-depleting substances. • Biomedical Waste (Management and Handling) Rules, 1998, for proper segregation, disposal, and transportation of infectious and hazardous wastes. • Municipal Solid Wastes (Management and Handling) Rules, 2000, to enable municipalities to dispose of municipal solid waste scientifically. • The Energy Conservation Act 2001 provides a legal, institutional arrangement, and a regulatory framework at the central and state levels in successfully implementing energy efficiency drive in the country. • The Wildlife (Protection Act) Amendment Act, 2002, to provide for the protection of wild animals, birds, and plants. Therewith to ensuring the ecological and environmental security of the country.

9.5 Ministries Related to Improving Climate and Reducing Emission …

295

• Biological Diversity Act, 2002, facilitates conservation of biological diversity, sustainable use of its components, fair and just sharing of the benefits arising out of the use of biological resources, knowledge, and for matters connected therewith. • The Electricity Act, 2003 enacted the provision for the development of gridinteractive renewable power that among other things, provides regulatory interventions for the promotion of renewable energy. • Hazardous Wastes (Management, Handling, and Transboundary) Rules, 2008, provides a guideline for manufacturing, storage and import of hazardous chemicals, and management of hazardous wastes. • Energy Conservation (Amendment) Act, 2010, No. 28, to amend the Energy Conservation Act of 2001. • The National Green Tribunal Act (NGT), 2010, to provide environmental protection, maintenance, and conservation of the Indian forests and other natural resources. It includes enforcement of any legal right related to the environment and gives relief and compensation for damages to persons or property. • The Companies Act 2013, is obligatory for companies to spend 2% of their profit on Corporate Social Responsibility (CSR). Environment sustainability is listed as one of the eligible CSR activities. • Biomedical Waste (Management and Handling) Rules, 2015 (Draft). • Solid Waste Management Rules, 2015 (Draft). • Construction and Demolition Waste Management Rules, 2016. • Compensatory Afforestation Fund Act, 2016 promulgated by the Parliament of India, to establish funds under the public accounts of India and the public accounts of each State to receive money from the user agencies towards compensatory afforestation. • Compensatory Afforestation Fund Rules, 2018, provides funds towards afforestation, wildlife management and conservation plans specifically collected, and deposited in State Fund and public accounts. • Environment (Protection) Amendment Rules, 2018, notifies that no building or infrastructural project requiring Environmental Clearance shall be implemented without the approval of the Environmental Management Plan inclusive of even dust mitigation measures. • The Societies Registration Act, 1860 and The Red Cross Society (Allocation of Property) Act, 1936, under the Government of India has provisions for voluntary groups to work for social, educational, environmental, and health benefits of the people of the country. • The core human rights threatened by climate change impacts are also protected under several human rights treaties of that India is also a party. • This includes the International Covenant on Civil and Political Rights and the International Covenant on Economic, Social, and Cultural Rights (International Covenant on Civil and Political Rights, 1966). India is obligated under these treaties to respect, protect and fulfill the rights of people contained in these treaties. Thus, climate and general environment-related concerns have begun to filter through to the courts and tribunals at various levels by the Judiciary and the Parliament

296

9 Indian Climate Policy, Programs, and Initiatives

of India. Indian judiciary acts as a dynamic actor in the separation of powers, making/implementing laws, acts, and policies, which plays a pivotal role in the functioning of the governance system. The Supreme Court, the High Courts, and various tribunals of India on the matter of environment protection and climate change have acknowledged the need for action and concerns on the context of environmental development trade-offs and decision-making. Constitutional litigation in India serves the purpose to catalyze action on environmental protection initiated by the Indian government. It sees every perspective statues concerning Public Interest Litigations (PILs) to fill the gap if void created by incompetent administration. Therefore, constitutional litigation serves its purpose by forcing the government to think in terms of the rights of the people if violated.

9.6 Concluding Remarks Considering India’s geopolitical establishment, the country is one of the most vulnerable to climate change impacts. On top of this, poor and vulnerable people are the most affected by climate variability. However, looking back in the past, showed that India drastically improved its response to climate change policies nationally and internationally. Though the country and its people are still required to take collective action for climate change adaptation and mitigation to reduce the risk of this global pandemic. Earlier, climate change vulnerabilities were not seen as a priority concern in the country. With a greater understanding of India’s risk and vulnerability to climate change, it is important to accelerate its efforts to utmost honesty to save the lives and livelihoods of the countrymen. A noticeable shift in India’s climate diplomacy by not just following western trajectories from has started around the year 2007 onwards. The green tribunals, revolutions, and acts have accounted emergence of India’s first comprehensive national policies on climate change called the National Action Plan on Climate Change (NAPCC) in 2008 and the Prime Minister’s Council on Climate Change in 2007. Similarly, at the international level, India in 2009 was approved in the Copenhagen Accord for binding GHG reduction commitment in the appropriate forum. Now, India has broadened its forms of engagement and ambition at international setup by submitting its international pledges from Copenhagen to Glasgow and showing the country is not going to turn back from progression, growing realization of its climate vulnerabilities, and engagement with the idea that climate change mitigation action and development. A modified co-benefit approach seems to be well suited to the Indian requirements. India has begun moving towards a balanced approach in achieving both economic development and climate protection for such a large vulnerable population and geographical area. The recent shift in climate change policy of India even at the domestic ground has been strongly applauded at the global, national and local arena. The country’s consistent economic growth has brought it closer to the other powerful nations and its image towards global leadership in climate change now matters. Also, the Indian judiciary, states, and people are cooperating with Indian aspiration by bringing more awareness about

9.6 Concluding Remarks

297

climate change and environmental actions through national policies, programs, acts, laws, and statutes. Thus, for India, a large window of opportunity has been opened to make the country and its countrymen more responsible partners in the global theatre of climate change negotiations and actions.

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IPCC (2001) Climate change: impacts, adaptation, and vulnerability. Cambridge University Press, USA Jain RK (2012) The European Union as a global power: Indian perceptions. Perspect Rev Int Aff, 2: 31–44 Jain RK (2015) Indian perceptions of the European Union. Stos Mi˛edzynarodowe 51:71–82 Kapur D, Khosla R, Mehta PB (2009) Climate change: India’s options. Econ Polit Wkly, 44:34–42 Le Quéré C, Jackson RB, Jones MW, Smith AJ, Abernethy S, Andrew RM, De-Gol AJ, Willis DR, Shan Y, Canadell JG. and Friedlingstein P, (2020) Temporary reduction in daily global CO2 emissions during the COVID-19 forced confinement. Nat Clim Chang, 10: 647–653. Lindzen R (2006) Climate of fear. The Wall Street Journal, p 12 Menon M (2014) PM’s climate change council recast. The Hindu, p 5, New Delhi edn. URL (consulted 20 June 2020), from www.thehindu.com/sci-tec/energy-and-environment/gov-recons titutes-pms-councul-on-climate-change/article6567187.ece Mohan A, Wehnert T (2019) Is India pulling its weight? India’s nationally determined contribution and future energy plans in global climate policy. Clim Policy 19:275–282 Nachiappan K (2019) Agenda-setting from behind: India and the framework convention on climate change. India Review, 18:552–567 Nandimath OV (2009) Handbook of environmental decision making in India: an EIA model. Oxford University Press, New Delhi NITI Aayog (2015) Raising agricultural productivity and making farming remunerative for farmers, An Occasional Paper, NITI Aayog, Government of India p 46 NITI Aayog (2017) On the implementation of sustainable development goals. Voluntary national report India Pandve HT (2009) India’s national action plan on climate change. Indian J Occup Environ Med 13:17 Peel J, Osofsky HM (2018) A rights turn in climate change litigation? Transnatl Environ Law 7:37–67 Planning Commission (2015) Eleventh five year plan 2007–12. Volume-III, Agriculture, rural development, industry, services and physical infrastructure. Government of India, New Delhi Prasad HAC, Kochher JS (2009) Climate change and India—some major issues and policy implications. Department of Economic Affairs, Ministry of Finance, Government of India, 43 p Raghunandan D (2012) India’s official position: a critical view based on science. In: Handbook of climate change and India. Routledge, pp 194–203 Rajamani, L (2013) Rights based climate litigation in the Indian courts: potential, prospects & potential problems. Centre for policy research, climate initiative, working paper 1 Rajan MG (1997) Global environmental politics: India and the North-South politics of global environmental issues. Oxford University Press, USA Ramesh J, Talbott S (2005) Making sense of Chindia: reflections on China and India. India Research Press Ray A (2020) Research and education in India on climate change. Sci Cult 86:28–37 Saran S (2009) Global governance and climate change. Glob Gov 15:457–460 Saryal R (2018) Climate change policy of India. South Asia Res 38:1–19 Sethi N (2009) Jairam for major shift at climate talks. The Times of India, p 19 Thaker J, Leiserowitz A (2014) Shifting discourses of climate change in India. Clim Change 123:107–119 Upadhyaya P, Fridahl M, Linnér B-O, Román M (2018) Comparing climate policy processes in India, Brazil, and South Africa: domestic engagements with international climate policy frameworks. J Environ Dev 27:186–209 Vihma A (2011) India and the global climate governance: between principles and pragmatism. J Environ Dev 20:69–94 Zheng X, Streimikiene D, Balezentis T et al (2019) A review of greenhouse gas emission profiles, dynamics, and climate change mitigation efforts across the key climate change players. J Clean Prod 234:1113–1133

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Appendix A

Questionnaire

Interview Question: Local Households 1.

Name ……………………………………………………………………………….. Sex…………………..

2.

Residential Location (Block name):

3.

Educational Level:

4.

No. of members in the Family:

Age …………….. Caste……………………………………

A) DEMOGRAPHIC INFORMATION: S.No

Name

Relation With Head of Household

Gender

Age

Marital Status U/M

Educational Qualification

Occupation

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021 S. Singh and R. B. Singh, Simulating Climate Change and Livelihood Security, Advances in Geographical and Environmental Sciences, https://doi.org/10.1007/978-981-16-4648-5

Migration Status

301

302

Appendix A: Questionnaire B) ECONOMIC ACTIVITY: 5.

How do you make your life? Code: 01. Agriculture……………… Code: 02. Business……… Code: 03. Cattle Rearing…Code: 04. Other (specify)………

6.

Years of experience as a farmer: a) 5-10_______b) 11-15________c) 16-20________ d) 21-25_______ e) 26 and Above……

7.

Since how long are you staying in this area?

8.

How much money do you earn per year (approximately)?

Code: 01 less than 10 years, Code: 02 Ten years to 20 years, Code: 03. Don’t remember Code: 01. Below -60,000 Code: 02. 60,000 –1,20,000 Code: 03. 1,20,000 and Above

Code:

04. Can`t say 9.

Do you own cultivable land? Code: 01. No. 02.Yes.

10.

If yes, area: Code: 01, 0 to 10 Kanal, Code: 02 for 10-20 Kanal, Code: 03 for. 20-30 Kanal, or Code: 04

11.

Do you have land area under cultivation? Code: 01. Un-irrigated, 02. Partially Irrigated 03. Irrigated

12.

If partially irrigated, what is the proportion of irrigated land? Code: 01. Less than 25 per cent, 02. 25-50

13.

Have you leased in land? Code: 01. for Leased in, 02 for No , 03 for Leased out and 04 for No leased out

14.

Sources of irrigation: 01. Ground water

for more

per cent, 03. 50-75 per cent,04 More than 75

02.Tube well 03.Well 04. Canal 05 Ponds

06. Others 07. All 15.

What form of farming do you practice? Code: 01. Traditional 02. Conventional, 03.Organic and 04.

16.

Do you know advantage of crop diversification? 01 Yes Aware 02. Not Aware

Mixed

17.

Do you practice crop diversification? 01.Yes Practice , 02.No Practice

18.

Distance to the nearest market (Km)_______

19.

Distance to the nearest main road (Km)__________

20.

What type of transport do you use to sell your produce? Code: 01. Public Transport, 02. Animal Cart 03.

21.

What are your agricultural assets? Code: 01.Tractor 02.Thresher

22.

Which type of farming are you practicing? Code: 01. Subsistence, 02. Commercial, 03. Mixed

23.

What are major crops and their productivity (Quintal per acre)?......................................

24.

How many crops are taken in the year? Code: 01. One Code: 02.Two and Code: 03. Three

25.

What type of crop was under cultivation by the respondent at the time of investigation? Code: 01.Cereals

Donkey Cart 04. Other, specify… 03. Planter, 04. Tillers 05. Other

Agriculture

/ Millets 2. Pulses 3. Oilseeds 4. Cash crops 5. Fruits and Vegetables 6. Flower Crops 7. Medicinal and Aromatic 26.

In case of crop failure do you get help and support Code: 01. No one, Code: 02. Only Family Member, Code: 03. Relatives, Code: 04. SHGs, Code: 05. Government

Appendix A: Questionnaire

303

C) TYPES OF INCOME 27.

What is your family’s main source for household sustenance (income and cash) Code: 01. Farm (Food Crops Consumed, Crop Sold, Livestock Consumed and Sold, Labor and Others, Specify) …………… 02. Non-Farm (i.e. Petty Trading: Sale of Fire Wood, Bole Soil, Sand, Vegetable, Grain and Others, Labor Outside the Local Area, Remittance, Fishing, Private or Gov. Job, Teaching/Health Officer)

28.

Does the income from non-farm activities enable you to buy food items and cover your household food deficiency?_______ If not why? ……………………………………………………………………….

29.

Income during ’good’ year (in Rs.) Code: 01. Below 60,000 Code: 02. 60,000-1,20,000

Code: 04.

> 1,20,000 Income during ‘Moderate’ year: Code: 01. >30,000 02. 30,000-6,0000 03. More Income in ’Bad’ year: a)