Flood Susceptibility Mapping with Integrated GIS and Analytical Hierarchy Process: A Case Study from Mayadevi Rural Municipality, Rupandehi District, Nepal
DOI:
https://doi.org/10.64862/Keywords:
Flood, Flood susceptible maps, Geographic Information System, Analytic Hierarchy Process, Remote sensingAbstract
Flooding is the most frequent natural disaster, affecting millions of people worldwide. Nepal is highly vulnerable to flood risks due to its topography, geological setting, and monsoon-dominated climatic conditions. Floods often hit Terai regions in Nepal due to its flat terrain and proximity to major rivers. Mayadevi Rural Municipality, situated in the Terai region of Rupandehi district, is at significant risk of flooding due to its proximity to the Tinau River and Dano Khola. Mapping flood susceptible zones is highly essential in effective and sustainable flood management.
Integrated Remote Sensing (RS) and Geographic Information System (GIS) tools, together with the Analytic Hierarchy Process (AHP), offer an effective framework for the integration, manipulation, and analysis of data from diverse sources to assess catastrophe and vulnerability more efficiently. For this, ten parameters that are relevant to the hazard of flooding in the areas: Topographic Wetness Index (TWI), elevation, slope, drainage density, Normalized Difference Vegetation Index (NDVI), precipitation, distance from river and distance from road, land use, and soil type were considered in the study. The GIS tool was used to create all the necessary input layers and the AHP technique was adopted to generate normalized weights to each parameter. All parameters were integrated as distinct layers in GIS utilizing the weighted overlay approach to provide a conclusive flood susceptibility map of the area.
The resulting flood susceptible zones were further classified into low, medium and high flood risk zones based on vulnerability to the potential of flood hazard. Sites that had previously seen flood occurrences were then used to validate the flood susceptibility map. These results suggested that RS and GIS-based geospatial analysis, in conjunction with AHP, are effective and reliable methodology for mapping flood risk and plan for disaster mitigation.
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