Identification and prioritization of flooding areas using GIS-based analytical hierarchy process, case study: Karun Watershed

Floods are one of the most destructive natural disasters that cause severe injuries and loss of life, major infrastructure damage, significant economic losses, and social unrest worldwide. Due to the fact that flood is a dynamic and multidimensional phenomenon, Geographic Information System (GIS) and Remote Sensing (RS) data are used to a large extent to discover the extent of flooded areas and play a special role in preparing flood risk and susceptibility maps. Flood susceptibility mapping is essential for characterizing flood risk areas and planning flood control schemes.

In this research, the identification of flooded areas in the Karun Watershed based on the Analytical Hierarchy Process (AHP) in the GIS environment and its validation with the NDWI blue index extracted from Landsat 8 satellite images has been considered. For this purpose, first, 15 effective parameters in floods occurrence including slope, aspect, elevation, curvature, rainfall, distance from stream, stream density, distance from fault, fault density, distance from road, road density, lithology, Curve Number (CN), land use, Topographic Wetness Index (TWI) and Stream Power Index (SPI) were selected and the weighting of these parameters was done based on AHP method in the Expert Choice software environment. Finally, by using the command to combine the layers based on the weighting of the AHP method in GIS, the final flood risk zoning map was obtained. NDWI water index was used to validate the flood risk map obtained.

The results of the AHP model showed that the most effective factors in the occurrence of flood risk in the Karun Watershed include rainfall, the amount of slope and the height classes, which should be considered in order to reduce flood damage and provide management solutions for these factors. Also, the results show that the downstream areas of the watershed have the highest risk of flooding and more than half of the watershed's surface (52.24%) has a medium flood potential.

Preparing a map of flood-prone areas is one of the most constructive methods that enable the reduction of flood risk damages and help planners, stakeholders and decision-makers to properly monitor flood-prone areas and ensure appropriate and sustainable socio-economic development.