Identification and mapping of flood-prone areas using GIS-based multi-criteria decision-making and analytical hierarchy process: the case of Adama City’s watershed, Ethiopia

Abstract

Adama is one of the fastest growing and second-most populous cities in Ethiopia. It is highly prone to flooding due to its location and rapid urbanization. The city is densely populated in the floodplain areas. It is a low-lying flat terrain surrounded by mountains and ridge topography. The objective of this study was to identify and map flood-prone areas in Adama City’s watershed using a geographic information system (GIS)-based multi-criteria decision-making (MCDM) and analytical hierarchy process (AHP). Distance from sewer drainage, topographic wetness index (TWI), elevation, slope, rainfall, land cover, normalized difference vegetation index (NDVI), distance from the river, distance from the road, drainage density, and soil types data sets were combined to meet the objective of the study. The result of the present study revealed that about 98.69% of the study area is moderate to very highly prone to flooding, whereas the other 1.31% of the area is at low risk. The model-generated flood-prone map matched with the ground control points (GCPs) collected by handheld GPS, Google Earth Satellite Imagery, experts’ opinions, and local community reports. Thus, this model has important implications for decision-makers and professionals in early warning and sustainable flood management systems.