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<p>The Sylhet district in Bangladesh experiences frequent flooding due to its geographic setting and heavy monsoon rainfall, further intensified by human-driven activities, including rapid urban expansion, land-use/land-cover alterations, and river encroachment, which collectively cause significant damage to communities, infrastructure, and agriculture. This study aims to delineate flood risk in the district by integrating flood hazard and vulnerability maps using an enhanced GIS-AHP (Analytical Hierarchy Process) approach that incorporates 14 hazard and 8 vulnerability factors. Employing AHP, influencing weights were assigned to hazard and vulnerability defining factors, thereafter mapped in GIS to assess the spatial characteristics of the flood hazard index (FHI) and flood vulnerability index (FVI), thus collectively producing the flood risk index (FRI). Validation of the FHI map was conducted through Receiver Operating Characteristic curve analysis, yielding an Area Under the Curve of 0.858. The results also indicated a high level of correspondence with the flood inundation maps for 2004 and 2022. The FVI map was validated by qualitative analysis, confirming its contextual reliability. The assessment reveals that moderate flood hazard dominates across the district, with upazilas like Companiganj, Gowainghat, Bishwanath, and Balaganj having moderate hazard levels above 80%. However, vulnerability levels are higher in densely populated settlement areas, particularly in Sylhet Sadar, Golapganj, Dakshin Surma, and Biswanath upazilas. Moreover, 74.26% of Sylhet falls within the moderate-risk category. The high-risk zones are mainly clustered in Sylhet Sadar, Biswanath, Dakshin Surma, and Golapganj, where over 40% of the land area is classified as high-risk. The FRI map’s performance was further evaluated using recent flood event information, revealing that flooded areas mostly correspond to moderate- and high-risk zones.</p>

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An enhanced approach for flood risk assessment using the Analytical Hierarchy Process (AHP) and Geographical Information System (GIS) in Sylhet district of northeastern Bangladesh

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月3日

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  • Md. Mahfuzar Rahman,
  • Asif Ahmed,
  • Iftakhar Ahmed,
  • Mahfuja Khandaker,
  • B. M. Rabby Hossain,
  • Md. Zillur Rahman,
  • Md. Shakhawat Hossain

摘要

The Sylhet district in Bangladesh experiences frequent flooding due to its geographic setting and heavy monsoon rainfall, further intensified by human-driven activities, including rapid urban expansion, land-use/land-cover alterations, and river encroachment, which collectively cause significant damage to communities, infrastructure, and agriculture. This study aims to delineate flood risk in the district by integrating flood hazard and vulnerability maps using an enhanced GIS-AHP (Analytical Hierarchy Process) approach that incorporates 14 hazard and 8 vulnerability factors. Employing AHP, influencing weights were assigned to hazard and vulnerability defining factors, thereafter mapped in GIS to assess the spatial characteristics of the flood hazard index (FHI) and flood vulnerability index (FVI), thus collectively producing the flood risk index (FRI). Validation of the FHI map was conducted through Receiver Operating Characteristic curve analysis, yielding an Area Under the Curve of 0.858. The results also indicated a high level of correspondence with the flood inundation maps for 2004 and 2022. The FVI map was validated by qualitative analysis, confirming its contextual reliability. The assessment reveals that moderate flood hazard dominates across the district, with upazilas like Companiganj, Gowainghat, Bishwanath, and Balaganj having moderate hazard levels above 80%. However, vulnerability levels are higher in densely populated settlement areas, particularly in Sylhet Sadar, Golapganj, Dakshin Surma, and Biswanath upazilas. Moreover, 74.26% of Sylhet falls within the moderate-risk category. The high-risk zones are mainly clustered in Sylhet Sadar, Biswanath, Dakshin Surma, and Golapganj, where over 40% of the land area is classified as high-risk. The FRI map’s performance was further evaluated using recent flood event information, revealing that flooded areas mostly correspond to moderate- and high-risk zones.