Application of Analytical Hierarchy Process Model for Flood Risk Zonation of Sunamganj, Bangladesh: A GIS and Remote Sensing Based Study - Iqbal, Mehedi; Oyshi, Mithila Singha (The Jahangirnagar Review, 2024)
Flood is one of the most common and destructive natural hazards in Bangladesh. It is the most frequent hazard in Sunamganj District and occurs once or twice in every year. It wreaks havoc on people and property in the area. Remote sensing and geographic information systems are powerful tools for assessing hydrological studies and hazard management in today’s environment. Analytical Hierarchy Process is a time-consuming and cost-effective decision-making approach. In order to model and estimate the flood risk zones in Sunamganj District, Bangladesh, an integrated Analytical Hierarchy Process (AHP) and Geographic Information System (GIS) analysis technique is used in this research. Total eight spatial factors were assessed using GIS and AHP model to investigate the flood risk zones in Sunamganj. The factors such as slope, elevation, topographic weighted index (TWI), drainage density and distance from river were derived from SRTM DEM using Arc map. Landuse land cover (LULC), normalized difference vegetation index (NDVI) were assessed using landsat 8 imageries. The LULC map was created using supervised image classification method. The lithology of Sunamganj district was generated using world geological shapefiles from USGS Certmapper. In the final map, flood susceptibility of Sunamganj was categorized in five zones including Very High, High, Moderate, Low and very Low flood risk zones. As a result, about 4.827% of the total area is found to be very high flood risk zone, 17.584% of total area of high flood risk zones and 27.126% of total area of moderate flood risk zones are found. On the other hand, 33.786% of low flood risk zones and 16.321% of extremely low flood risk zones are detected. It is concluded that the integration of AHP and GIS in flood risk assessment can give useful comprehensive outputs and information for flood risk management.