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<p>Flood hazard assessment is a critical component of disaster mitigation studies, particularly within the dynamic and topographically complex Sub-Himalayan landscape. This research applies an integrated modelling framework—encompassing the Analytical Hierarchy Process (AHP), Frequency Ratio (FR), and their fuzzy logic extensions (Fuzzy AHP and Fuzzy FR)—to evaluate flood susceptibility in the Bangri–Mujnai Basin. A suite of 11 topographic, hydrological, and climatic parameters was derived from remote sensing datasets and synthesized to produce thematic layers. These layers were then weighted through pairwise comparison and statistical correlation techniques to generate flood hazard maps for each model variant. Results indicate a predominance of <i>moderate</i> flood hazard zones in all models, with <i>high</i> susceptible areas concentrated primarily near the major stream networks—especially around the alluvial fan–floodplain transition at ~125 m elevation. Of particular note, the Fuzzy FR model identified the least spatial extent of <i>high</i> hazard zones, underscoring its enhanced analytical precision. Validation using historical flood extent data extracted from Sentinel-1A SAR-C imagery revealed strong concordance between the model outputs and field observations. The analysis also highlights the continued influence of the Titi River’s avulsion, where its former confluence with the Bangri remains a significant driver of flood dynamics. Overall, this study demonstrates the utility of integrating fuzzy logic with conventional modelling approaches to improve flood hazard assessments in highly variable environmental contexts. The findings offer valuable insights for policymakers to inform targeted flood mitigation measures and guide sustainable land use planning in the vulnerable Sub-Himalayan regions.</p>

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Flood hazard assessment using AHP–FR–Fuzzy ensemble of a sub-Himalayan catchment in a transboundary piedmont landscape of the Eastern Himalayas

  • 期刊论文

  • 发表日期：

    2026年3月30日

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  • Deepangshu Chandra,
  • Sanchary Debnath,
  • Deeprita Ghosh,
  • Sayantan Das

摘要

Flood hazard assessment is a critical component of disaster mitigation studies, particularly within the dynamic and topographically complex Sub-Himalayan landscape. This research applies an integrated modelling framework—encompassing the Analytical Hierarchy Process (AHP), Frequency Ratio (FR), and their fuzzy logic extensions (Fuzzy AHP and Fuzzy FR)—to evaluate flood susceptibility in the Bangri–Mujnai Basin. A suite of 11 topographic, hydrological, and climatic parameters was derived from remote sensing datasets and synthesized to produce thematic layers. These layers were then weighted through pairwise comparison and statistical correlation techniques to generate flood hazard maps for each model variant. Results indicate a predominance of moderate flood hazard zones in all models, with high susceptible areas concentrated primarily near the major stream networks—especially around the alluvial fan–floodplain transition at ~125 m elevation. Of particular note, the Fuzzy FR model identified the least spatial extent of high hazard zones, underscoring its enhanced analytical precision. Validation using historical flood extent data extracted from Sentinel-1A SAR-C imagery revealed strong concordance between the model outputs and field observations. The analysis also highlights the continued influence of the Titi River’s avulsion, where its former confluence with the Bangri remains a significant driver of flood dynamics. Overall, this study demonstrates the utility of integrating fuzzy logic with conventional modelling approaches to improve flood hazard assessments in highly variable environmental contexts. The findings offer valuable insights for policymakers to inform targeted flood mitigation measures and guide sustainable land use planning in the vulnerable Sub-Himalayan regions.