Flood Susceptibility Mapping of Netrokona District Using a GISbased multi-criteria Analysis

Abstract

Due to geographical location and physiographic conditions, i.e., low elevation, siltation of riverbed, monsoon dominated excessive rainfall at upstream Bangladesh faces most destructive flood events every year, especially Netrokona, a district of north-eastern Bangladesh. Such extreme events not only destroy property and assets but also endanger people’s life and livelihoods. Existing research works have assessed flood risk using several methods but the dynamic interaction between human and climate as well as their inherent community knowledge is ignored. In this study, researchers aim to integrate those by developing a multi-criteria approach in order to mapping flood susceptibility of Netrokona. Subsequent studies lack precise and intricated mapping operations as well as susceptibility indexing that directs flood vulnerability analysis with a view to integrate mitigation strategies and planning. In this research, the socioeconomic factors, i.e., land use, population and drainage are integrated with physical factors, i.e., elevation, slope, rainfall, and drainage using Weighted Linear Combination (WLC) method. To enhance local relevance, the study incorporates expert input and participatory mapping. Weights were derived by the Analytical Hierarchy Process (AHP) using seven essential geographical criteria: elevation, slope, rainfall, soil type, drainage density, land use/cover, and historical flood data. Reliability was ensured through pairwise comparisons and consistency ratios. With zones ranging from extremely low to very high risk, a flood susceptibility index was created by integrating layers into a GIS environment. According to this study, 29.44% of the district is very to extremely susceptible to flooding, primarily along rivers and low-lying areas. This study aims to address these gaps by developing a Multi-Criteria Approach (MCA) for flood susceptibility mapping in Netrokona using Geographic Information Systems (GIS). The methodology employs the Weighted Linear Combination (WLC) method to integrate socioeconomic factors (such as land use, population, and infrastructure) with physical factors (including elevation, slope, rainfall, and drainage). The resulting flood risk and social maps contribute significantly to integrated flood risk management in Bangladesh, supporting early warning systems, disaster resilience planning, and informed decision-making.