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

• Published in: Journal of flood risk management Vol. 14; no. 3
• Main Authors: Zzaman, Rashed Uz, Nowreen, Sara, Billah, Maruf, Islam, Akm Saiful
• Format: Journal Article
• Language: English
• Published: Oxford, UK Blackwell Publishing Ltd 01.09.2021; John Wiley & Sons, Inc; Wiley
• Subjects: Analytic hierarchy process; analytical hierarchy process; analytical network process; Bangladesh; Crop damage; Drainage density; Elevation; Extreme weather; Flood control; flood hazard map; Flood hazards; Flood management; Flood mapping; Floods; Geomorphology; hydro‐geomorphological factors; Lithology; Maximum rainfall; Morphology; Rain; Rainfall; Risk management; River basins; Rivers; Roads; sentinel data; Site selection; Slopes; Wetness index; Bangladesh
• ISSN: 1753-318X; 1753-318X
• DOI: 10.1111/jfr3.12715

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.