Navigating coastal futures: Harnessing GIS and multi-criteria decision analysis for sustainable resilience in Kerala's vulnerable Shores.

Abstract

Extreme weather occurrences, particularly in densely populated coastal places like India, cause loss and devastation, hindering disaster preparedness and long-term viability of vulnerable populations. Research shows that hybrid models, such as Bayesian Networks and Coastal Vulnerability frameworks, outperform traditional methods for measuring coastal vulnerability to Sea Level Rise (SLR). However, their extensive geographical coverage has considerable limitations, including data scarcity and challenges in effectively capturing differences in tiny locations. This study uses Geographic Information systems (GIS) and Multi Criteria Decision Analysis (MCDA) to assess coastal vulnerability in two villages in Alappuzha district, Kerala. The parameters used include lithology, elevation, significant wave height, land cover, road network density, and population density. The Coastal Vulnerability Index indicates that site A (27.39/53.7%) is three times more vulnerable than site B (9.13/ 18%). The results show that lithology limits agricultural lifestyles at both locations. Geology, coastal slope elevation, and wave energy all influence risk exposure. Land use and cover changes have had different causes at each site, resulting in varying socioeconomic consequences. The study emphasizes the need for evidence-based methods that include local ecological knowledge and involve communities to improve coastal resilience in line with the Sustainable Development Goals (SDG). This work contributes to our knowledge of how localized adaptations minimize disaster risk and strengthen resilience in vulnerable coastal communities confronting climate change and socioeconomic pressures.