A data-driven framework for enhancing coastal flood resilience in resource-crunched developing nations

This paper adopts a data-driven, evidence-based approach to assess climate-induced flood risk and validating the efficacy of mangroves(as context-specific adaptation measure) in reducing residential building damage. A comprehensive Flood Resilient Scenario Model (FReSMo) employs a data-driven, evidence-based approach for assessing climate-induced flood risk and validating the efficacy of mangroves as a context-specific adaptation measure in reducing residential building damage. Based on an improvised Source–Pathway–Receptor–Consequence–Evidence concept, FReSMo follows a three-step analysis. First, hazard mapping estimates coastal flood extents for various return periods under different Shared Socioeconomic Pathways.

Second, the model maps the exposure of residential buildings to these flood extents by projecting built-up areas for 2050 using the FUTURES model, based on physiographic, socio-demographic, and economic parameters. Finally, a data-driven probabilistic damage model is applied to estimate built-up area damage for a 100-year coastal flood event (SSP2-6). The pre- and post-adaptation damage estimates demonstrate the efficacy of nature-based solutions (NBS), specifically mangroves, in reducing coastal flood risk. A 100 m mangrove patch on the Sagar coastline reduced building damage costs by 70% for a 48-hour flood and 75% for a 24-hour flood. Considering plantation costs for 6.2 km², the total benefit, despite persistent losses, resulted in a 222% return on investment. FReSMo transcends conventional risk assessment frameworks by offering a comprehensive approach for evaluating the cost-effectiveness of adaptation investments in developing countries, making it an invaluable tool in the context of climate change.