Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/13214
Title: Assessing district-level climate vulnerability in Madhya Pradesh, Central India: an integrated environmental and socio-economic approach
Authors: Kumar, Arvind
Thangavel, Mohanasundari
Issue Date: 2024
Publisher: Springer
Citation: Kumar, A., & Mohanasundari, T. (2024). Assessing district-level climate vulnerability in Madhya Pradesh, Central India: An integrated environmental and socio-economic approach. Theoretical and Applied Climatology. Scopus. https://doi.org/10.1007/s00704-023-04814-5
Abstract: Climate change poses significant challenges to human societies and natural ecosystems, necessitating comprehensive vulnerability assessments to develop appropriate adaptation stratigies. This study focuses on Central India and employs a multidimensional approach to evaluate the composite vulnerability at the district level. By integrating environmental (8 indicators) and socio-economic (5 indicators) factors, this study offers a nuanced understanding of vulnerability patterns in the region. The methodology involves the selection of indicators based on past literature and preliminary investigation, followed by secondary data collection from environmental and socio-economic factors. The data is analysed using an indicator-based approach, normalisation, weighting, and developing vulnerability indexes. This analysis is structured in three phases: Environmental Vulnerability Index (EVI), Socio-economic Vulnerability Index (SVI), and Composite Vulnerability Index (CVI). The results of CVI revealed that districts with a lower CVI (0.321–0.378), such as Gwalior, Jabalpur, and Bhopal, exhibited decreased vulnerability because of a lower level of climatic extremes affected areas, reduced percentage of socially deprived population and a higher value of HDI. Districts with medium CVI (0.381–0.407), such as Damoh, Indore, and Shahdol, exhibited moderate resilience. On the other hand, districts with high (0.409–0.402) and very high CVI (0.448–0.540), such as Narsimhapur, Betul, Balaghat, Chhindwara, Alirajpur, and Barwani, encountered notable susceptibility because of factors such as dependence on agriculture, a substantial proportion of socially deprived population, occurrences of droughts and floods. Hierarchical cluster analysis validated vulnerability classifications, enhancing the credibility of assessments. The research underscores the importance of considering climate change vulnerability assessments for effective policy formulation and adaptive strategies. © 2024, The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.
URI: https://doi.org/10.1007/s00704-023-04814-5
https://dspace.iiti.ac.in/handle/123456789/13214
ISSN: 0177-798X
Type of Material: Journal Article
Appears in Collections:School of Humanities and Social Sciences

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