Assessment of flood mitigation strategy based on integrated approach of remote sensing and coastal vulnerability geospatial modeling at the coastal plain of Suriname

Abstract

Suriname is the smallest South American nation with a low-lying coastal plain that is vulnerable to inundation from the Atlantic Ocean and inland rivers, as well as pluvial flooding primarily due to rainfall. Paramaribo, the capital of Suriname, has the highest population density, and its demographics extend into the surrounding districts of Wanica and Commewijne. Suriname has experienced flood disasters almost annually, which has exacerbated in recent years, posing a significant socioeconomic challenge. The country must balance the need for flood disaster adaptation and climate resilience with the potential impact on its resources and well-being of settlement areas. Policymakers and other stakeholders are working to address environmental impacts on the coast, but there is still a need for a comprehensive approach to monitor and manage flood impacts. This research has three objectives. The first is to analyze flood frequency events from 2021 to 2023 using multi-temporal satellite image processing from Sentinel-1 SAR (Synthetic Aperture Radar). The second is to generate a Coastal Flood Vulnerability Index (CFVI) for floods using a geospatial multi-criteria analysis approach based on exposure, sensitivity, and adaptive capacity components. The third objective is to assess the mitigation strategy for floods in settlement areas based on an integrated analysis of CFVI and stakeholder perception. The research methodology uses a multi-criteria analysis regarding settlement areas and ranking each component by expert opinion in an equation derived from Intergovernmental Panel on Climate Change (IPCC) assessment report at district level. The CFVI indices rely on secondary data acquisition from national and global datasets or referenced works. Interviews were conducted to better understand the stakeholder’s perspectives that are at a strategic or governing level, and to evaluate the existence of flood early-warning and other adaptation capabilities. A flood mitigation strategy is then suggested for the most vulnerable district by CFVI score.