Multivariate indicator-based flood hazard mapping using primary drivers of coastal flood for India

Coastal regions are densely populated and economically vital but highly exposed to multiple hazard drivers, including cyclones, storm surges, high tides, and intense rainfall. The IPCC AR6 (2021) emphasizes the need to assess coastal hazards as multi-driver compound hazard events. India, with its extensive coastline of ∼11,098 km, is particularly prone to these drivers, necessitating a comprehensive multi-driver coastal flood hazard assessment. This study adopts an indicator-based approach employing Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) with three objective weight estimation methods: equal weighting, statistical entropy-based weighting, and Principal Component Analysis (PCA)-based weighting, to comprehensively assess coastal flood hazard across India's coastal districts. The key indicators of coastal flood hazard include the total number of cyclones, probable maximum storm surge, probable maximum wind speed, maximum tidal range, and extreme precipitation exceedance probability. Methodological comparisons reveal that entropy-based weighting emphasizes cyclone frequency due to high data dispersion, while PCA-based weighting provides a balanced assessment by capturing overall variance across indicators. The entropy-weighted TOPSIS reflects a more optimistic hazard scenario, whereas the PCA-weighted TOPSIS offers a more conservative perspective. Our findings indicate that North-eastern and North-western coastal districts are highly hazard-prone. Coastal districts in Odisha and West Bengal consistently exhibit high hazard levels across all decades studied, while Kerala and Tamil Nadu generally show low hazard levels. Extreme rainfall and high tides predominantly drive high hazard levels in Gujarat and Maharashtra, whereas frequent cyclones are the primary hazard drivers along the Bay of Bengal coast. These findings provide a scientific basis for region-specific flood mitigation strategies, guiding policymakers in optimizing resource allocation for enhancing coastal resilience.