Flood hazard mapping of Sangu River basin in Bangladesh using multi‐criteria analysis of hydro‐geomorphological factors

Abstract

Flood havoc during 2019 in the Sangu River basin caused widespread damage to residents, crops, roads, and communications in parts of hills in Bangladesh. Developing flood hazard maps can play an essential step in risks management. For this purpose, this study assessed 12 hydro‐geomorphological factors, namely, topographic wetness index, elevation, slope, extreme rainfall, land‐use and land‐cover, soil type, lithology, curvature, drainage density, aspect, height above the nearest drainage, and distance from streams. Maps prepared by individual application of the Analytical Hierarchy Process (AHP) and Analytical Network Process (ANP) exhibit validation scores ranging from 0.77 to 0.79. It is found that the ANP‐based model under 1‐day maximum rainfall denotes a reliable hazard map presenting comparable accuracy to the field results. The hazard map under 100‐year return periods shows that a total of 0.71 million population living downstream is prone to “very high” flood because of its lowland morphology, mild slope, and high drainage density. Alarmingly, 39% of roads, 43% of farming lands, and 25% of education buildings are observed to lie in the highest flood‐prone area. Details on subdistrict level exposures have the potential to serve the decision‐makers and planners in site selection for flood management strategies and setting priorities for remedial measures.

MCA and geospatial analysis-based suitable dumping site selection for urban environmental protection: A case study of Shambu, Oromia Regional State, Ethiopia

“…Analytical Hierarchy Process (AHP) is a popular multi-criteria decision technique that is widely used in different fields of studies. AHP technique was intensively applied in water resource development, allocation of water resources ( Hamdani, 2020 ; Zzaman et al., 2021 ; Sisay et al., 2021 ), flood susceptibility analysis ( Rincón et al., 2018 ; Swain et al., 2020 ), groundwater exploration ( Dar et al., 2020 ; Berhanu and Hatiye, 2020 ; Arulbalaji et al., 2019 ), water supply distribution systems, and selection of suitable dumping sites ( Ayaim et al., 2019 ; Chabuk et al., 2019 ; Şener et al., 2011 ; Sk et al., 2020 ). AHP technique has a capability of capturing the non-linear relationships among the key factors of suitable dumping sites selection criteria.…”

Flood Susceptibility Mapping Using an Analytic Hierarchy Process Model Based on Remote Sensing and GIS Approaches in Akre District, Kurdistan Region, Iraq

“…These flooded locations were selected for training and validation of flood-prone areas. A training data set of 91 points -70% of the flooded siteswas randomly selected to produce a flood vulnerability map, and a validation data set of 39 points -30% of the flooded areaswas employed for result validation (Zzaman et al, 2021). In order to facilitate the validation, the area under the curve of the receiver operating characteristic curve (AUC-ROC) technique was used.…”

“…Slope is another topographical factor that affects flood modelling and occurrence since it affects the speed of surface water runoff (Tehrany et al, 2019;Islam et al, 2021). The steeper the slope the less vulnerable it is to flood events; steeper slopes show a lower infiltration rate and higher speed of flow (Das, 2020;Zzaman et al, 2021) . Thus, flat and gently sloping areas have a higher probability of flooding because of accumulation of water runoff (Tabarestani and Afzalimehr, 2021).…”

“…Furthermore, geographic information systems (GIS) are powerful tools for spatially analysing and developing flood susceptibility maps by merging various significant thematic factors and layers with specific mathematical and logical algorithms (Pham et al, 2021;Fatah et al, 2020b). Several arithmetical and probabilistic models based on GIS and remote sensing (RS) techniques have been developed and used at various spatial scales to detect, examine, and evaluate flood-prone areas (Rahmati et al, 2019;Zzaman et al, 2021). Some advanced and sophisticated mathematical models have been employed in conjunction with GIS and RS approaches to assess flood risk, notably for FSM.…”

Novel Hybrid Models by Coupling Support Vector Regression (SVR) With Meta-heuristic Algorithms (WOA and GWO) for Urban Flood Risk Mapping

“…In their study, Lee et al (2012) showed that different units of geology have various susceptibilities to flooding. Lithology greatly influences the hydrological and hydrogeological conditions by controlling the infiltration and surface runoff (Bui et al, 2019) as well as the slope of channel in temporal floods (Waqas et al, 2021;Zzaman et al, 2021).…”