Village-level assessment of climate-induced migration risk in the Indian Sundarbans using a composite vulnerability index

Climate-induced migration in deltaic environments such as the Indian Sundarbans requires vulnerability assessments that are both spatially explicit and analytically objective. This study advances existing approaches by integrating the distance correlation-based CRITIC (D-CRITIC) technique with village-level environmental and socio-economic indicators to develop an unbiased Migration Risk Index (MRI) for 86 villages in the Pathar Pratima Block. Unlike traditional equal-weighted or expert-based methods (e.g., AHP, TOPSIS), D-CRITIC quantifies interdependence among indicators to derive data-driven weights, minimizing redundancy and improving diagnostic precision. Results indicate that 10.34% and 24.14% of the total area fall into very high and high vulnerability categories, respectively, while incorporating adaptive capacity reduces overall vulnerability by about 10%. The MRI reveals that 59.8% of villages exhibit moderate-to-very high migration risk, with significant hotspots along the southern coast. By quantifying interdependence among indicators, D-CRITIC offers a data-driven alternative to subjective weighting methods, potentially minimizing redundancy and improving consistency in vulnerability assessment. A ground-truth validation using household survey data from ten villages demonstrated a moderate-to-strong agreement between the model predictions and observed migration patterns, with a Receiver Operating Characteristic–Area Under the Curve (ROC–AUC) score of approximately 0.85. This result indicates that the model possesses good discriminatory and descriptive capability in capturing migration dynamics, thereby providing preliminary empirical evidence supporting the applicability and reliability of the proposed framework.. Beyond reaffirming coastal exposure, this study uncovers emerging mid-delta transition zones where exposure and adaptive capacity interact to shape migration pressures. The methodological innovation of D-CRITIC thus provides a replicable, data-driven framework for mapping migration risk and informing resilience planning in deltaic and other climate-sensitive regions.