Flood hazard assessment and mapping using GIS integrated with multi-criteria decision analysis in upper Awash River basin, Ethiopia

Abstract

Floods have destroyed people’s lives as well as social and environmental assets. Flooding is becoming more severe and frequent as a result of climate change and an increase in human-induced land-use changes, which puts pressure on river channels and causes changes in river morphology. The study was aimed to assess flood danger and map inundation areas in Ethiopia’s Teji watershed, which is prone to flooding. The basic flood-producing factors in this study were derived from soil, slope, elevation, drainage-density and land use land cover data. The opinions of public institutions and expert decisions were gathered to determine the weight of the factors in the analytic hierarchy process. The collected data were processed using the ArcGIS environment and the analytic hierarchy method to produce a flood danger map. According to the findings of this study, approximately 43.28 and 13.09% of the area were vulnerable to high and very high flood risk zones, respectively. As a result, flood prediction, early warning and management practices could be implemented on a regular and sustainable basis.

Potential flood-prone area identification and mapping using GIS-based multi-criteria decision-making and analytical hierarchy process in Dega Damot district, northwestern Ethiopia

“…Model validation is essential to check whether the model output adequately represents the actual conditions on the ground/field or not. Model validation can be performed by comparing the model output with the observed flood event on the ground (Hagos et al 2022;Mahmoud and Gan, 2018;Ogato et al 2020;Tadesse et al 2022). In this study, to validate the reliability of the model output, the historical flood events on the field collected from the study area Agricultural Office were compared with the locations of flood susceptible areas on the produced flood susceptibility map, and the point data collected from Google Earth were superimposed on the flood susceptibility map generated by the model.…”

“…It is known that river plains are highly susceptible to flood and the data collected from the river plains/flood plains must be placed over the highly susceptible classes on the flood susceptibility map generated by the model. Superimposing the point data collected on the output flood susceptibility map is one of the methods to validate the model output which was also employed by previous studies (Hagos et al 2022;Ogato et al 2020).…”

“…The fine texture composition of the soil reduces infiltration and increases surface runoff. Hence, areas covered by fine soil texture are more likely to be flooded than areas with coarse soil texture (Allafta and Opp 2021;Hagos et al 2022;Hong et al 2018a, b). As shown in Fig.…”

“…Flood is one of the natural disasters that causes massive destruction such as enormous infrastructural damages, substantial economic losses, and social disturbances across the world (Dang and Kumar 2017;Das and Gupta 2021;Farhadi and Najafzadeh 2021;Hong et al 2018a, b). The destruction due to floods has increased in recent years in several countries around the world because of climate change and environmental degradation caused by improper land use management (Das and Gupta 2021;Hagos et al 2022;Kanani-Sadat et al 2019;Ozkan and Tarhan 2016).…”

“…Desalegn and Mulu (2021) employed the integration of GIS-based multi-criteria decision analysis with AHP to assess and map flood vulnerability in the Fetam watershed, upper Abay basin of Ethiopia. Similarly, Hagos et al (2022) employed the combination of GIS-based multi-criteria decision analysis and AHP to combine seven flood-controlling factors to assess and map flood-prone areas in the upper Awash River basin of Ethiopia. Furthermore, other researchers (Ajibade et al 2021;Allafta and Opp 2021;Astutik et al 2021;Das and Gupta, 2021;Dash and Sar, 2020;Hadipour et al 2020;Karymbalis et al 2021;Mahmoud and Gan, 2018;Ogato et al 2020;Wubalem et al 2021;Zzaman et al 2021) also integrated multi-criteria decision analysis (MCDA) and analytical hierarchy process (AHP) with Geographic Information System to identify and map areas prone to flood.…”