A field-based data-driven modeling approach for livelihood vulnerability examination of rice farmers' considering climate risk in parts of West Bengal, Eastern India

Abstract

Agriculture is crucial for the rural economy in India, making it essential to assess how environmental and climatic changes impact rice farmers’ livelihoods. This study employed the Evaluation based on Distance from Average Solution (EDAS) model for a multi-criteria decision analysis method, to compute a Livelihood Vulnerability Index (LVI) and an IPCC-based LVI, reflecting rice farmers’ adaptive capacity, exposure, and sensitivity. Data from 1814 rice farmers across eight districts in West Bengal were collected in 2023. In 2023, field surveys of 1814 rice farmers across eight West Bengal districts were conducted. The LVI values ranged from 0.17 to 0.93, with an ROC-AUC accuracy of a model classification accuracy (ROC-AUC) of 0.89. LVI-AC ranged from 0.02 to 0.97, LVI-E and LVI-S from 0.00 to 1.00, and LVI-IPCC values from − 0.48 to 0.54, with an ROC-AUC accuracy of 0.86. Component indices varied widely: adaptive capacity (LVI-AC) ranged from 0.02 to 0.97, and exposure/sensitivity (LVI-E/S) from 0.00 to 1.00. The composite LVI-IPCC ranged from − 0.48 to 0.54 (ROC-AUC = 0.86). District-level analysis showed that Birbhum and Murshidabad were the most vulnerable districts, whereas Purba and Paschim Bardhaman were relatively less vulnerable (e.g. nearly half of Murshidabad’s area was highly vulnerable vs. less than 10% in Purba Bardhaman). Adaptive capacity was lowest in Jhargram and Paschim Bardhaman, reflecting limited adaptation resources, whereas Purba Bardhaman was the most exposed to climate risk. In contrast, exposure vulnerability was minimal in Bankura. Sensitivity to climate hazards was highest in Bankura and Jhargram. The LVI-IPCC analysis identified Birbhum as highly vulnerable to climate change. Notably, the combined LVI-IPCC measure singled out Birbhum as particularly vulnerable to climate change impacts. By highlighting livelihood vulnerabilities, this study informs interventions that support poverty reduction and food security (SDGs 1–3) while promoting sustainable economic growth (SDG 8) and climate resilience (SDG 13). The approach provides a practical tool for policymakers to target adaptation strategies and enhance climate-adaptive farming practices among vulnerable communities.