Abstract
Flood vulnerability is estimated by Flood Damage Functions (FDFs), which are crucial for integrated flood risk assessment for developing sustainable flood management, mitigation, and adaptation strategies under global change. However, the FDFs, either empirical or synthetic, are not available in Bangladesh. Therefore, this paper focused on developing the synthetic type of FDFs for agriculture and rural households through the data of a well–structured questionnaire survey conducted in two pilot sub–districts of northeastern Bangladesh in the Meghna River basin. Multiple regression analyses were performed on the collected data, and the best performing models were selected to establish FDFs. The FDF for agriculture (~196 samples) was developed concerning damage to Boro rice, whereas the FDFs for households (~165 samples) were developed concerning damage to the buildings and household property of three house types (Mud, Brick, and Concrete), separately. The results revealed that there were no yield losses when the water levels were lower than 25 cm (~rice tiller height), and the yield losses were ~100% when the water levels were 70–75 cm deep (~rice grain height). Mud houses and their household property were found the most flood–vulnerable and likely to experience total damage when the water levels exceeded 150 cm above the plinth level, whereas the damage to Brick and Concrete houses and their household property was found likely to remain partial even when the water levels exceeded 150 cm above the plinth level. The developed FDFs can be used to assess potential flood risk in the study area for sustainable and effective management of flood disasters and build back better under global change in the future.
Highlights
Bangladesh is a deltaic country located at the confluence of three large transboundary rivers, the Ganges, Brahmaputra, and Meghna; about 92–93% of their total catchment area is situated outside Bangladesh [1,2]
Flood damage for study agriculture and rural households through the datafunctions of a as a first functions attempt, this established a synthetic type of flood damage for structured questionnaire survey conducted in the two sub–districts of the northeastern agriculture and rural households through the data of a structured questionnaire survey region conducted of Bangladesh fortwo assessing potential flood risk in the region
The methodology consisted of the following steps: (1) Conducting a well–structured questionnaire survey in the chosen sub–districts to collect flood damage data based on the calculated minimum sample size for the three damage classes (i.e., Boro rice, house building, and household property); (2) Investigating the similarity and variations of the collected datasets between the two sub–districts for each damage category; (3) Evaluating the consistency of the collected data statistically for each damage category; (4) Performing multiple regression analyses with the data to fit the depth–damage relationship for each damage category; and (5) Identifying the best regression function based on several performance indicators to establish damage curves for the mentioned damage classes
Summary
Bangladesh is a deltaic country located at the confluence of three large transboundary rivers, the Ganges, Brahmaputra, and Meghna; about 92–93% of their total catchment area is situated outside Bangladesh [1,2]. Many researchers and government agencies worldwide have attempted establishing flood damage functions via questionnaire surveys for areas of different content characteristics and established stage–damage relationships of various damage categories (e.g., agricultural or residential damage) to assess flood risk [20,21,27,31,33,34,35,36,37,38,39]. Flood damage for study agriculture and rural households through the datafunctions of a as a first functions attempt, this established a synthetic type of flood damage for structured questionnaire survey conducted in the two sub–districts of the northeastern agriculture and rural households through the data of a structured questionnaire survey region conducted of Bangladesh fortwo assessing potential flood risk in the region. In the sub–districts of the northeastern region of Bangladesh for assessing potential flood risk in the region
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