Assessment of flood vulnerability in Jamuna floodplain: a case study in Jamalpur district, Bangladesh

Abstract

Flooding is a recurring event, and Bangladesh is particularly vulnerable to it. This study aimed to assess the Jamuna oodplain's community vulnerability. A concise overview of the literature had performed to identify and nalize the indicators of vulnerability. Expert judgments used to weight the selected indicators. Primary data were collected using a pretested questionnaire throughout the eld, where 400 households have been interviewed. Using multi-stage sampling techniques, ve Upazilas of Jamalpur district, including Dewanganj, Islampur, Madarganj, Melandaha, and Sharishabari, were purposively chosen following extensive ood damage reports. Percentage value was derived using SPSS for each variable collected from the eld survey. The variable vulnerability index (VVI) was derived by dividing the weighting value by the eld percentage value for each variable. Exposure, sensitivity, and adaptive capacity have been calculated using the variable vulnerability index values. Finally, using a widely recognized established index, the vulnerability was assessed for the study area. The calculated vulnerability scores for Dewanganj, Islampur, Madarganj, Melandaha and Sharishabari are 0.86, 0.84, 0.71, 0.70 and 0.65. According to the survey ndings, all the study sites are found highly vulnerable to oods, especially Dewanganj and Islampur Upazilas, due to poor socio-economic conditions, low adaptive capacities, and high exposures. This study recommends resistant materials like brick and concrete in housing construction, sustainable ood-resistant dams and improving their adaptive capacities through socio-economic uplift.the government of the People's Republic of Bangladesh under the NST Fellowship Program in 2018-2019 FY.Cordial thanks are expressed to Md. Kamruzzaman and Md. Asif Bin Alam for their assistance during household survey.

Evaluating Flood Susceptibility in the Brahmaputra River Basin: An Insight into Asia's Eastern Himalayan Floodplains Using Machine Learning and Multi-Criteria Decision-Making

“…It presents a holistic flood-risk analysis across the Brahmaputra basin, utilizing an unprecedented 18 flood-influencing factors. It also scrutinizes spatial variations in the basin's physical settings, highlighting flood risk concentrations, particularly in Assam (Hazarika et al 2018;Pareta 2021;Gupta and Dixit 2022) and Bangladesh (Haque and Nicholls 2018;Haque et al 2023). Additionally, the study advances flood susceptibility literature by integrating recent MCDM methods like EDAS and WASPAS (Ghorabaee et al 2015;Zavadskas et al 2012) within a GIS framework.…”

“…Navigating these complexities to formulate effective management and mitigation measures presents an intricate challenge. However, a communitybased resilience framework, often referred to as the "People-centered model," offers a promising avenue for disaster risk reduction (Haque et al 2023;Huq and Bracken 2015;Haque 2019). Such a comprehensive and integrated approach not only enhances community preparedness and adaptability in the face of uncertain flood risks but also offers a sustainable model for safeguarding both human and environmental resources against flood hazards.…”