Open AccessFlood hazard mapping of Sangu River basin in Bangladesh using multi‐criteria analysis of hydro‐geomorphological factors
Author(s) -
Zzaman Rashed Uz,
Nowreen Sara,
Billah Maruf,
Islam Akm Saiful
Publication year - 2021
Publication title -
journal of flood risk management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.049
H-Index - 36
ISSN - 1753-318X
DOI - 10.1111/jfr3.12715
Subject(s) - topographic wetness index , flood myth , drainage density , hydrology (agriculture) , drainage basin , drainage , environmental science , elevation (ballistics) , hazard , land cover , return period , population , land use , water resource management , geography , geology , cartography , civil engineering , remote sensing , ecology , digital elevation model , mathematics , geotechnical engineering , archaeology , sociology , engineering , biology , geometry , demography
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.