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<p>Flood hazard in Himalayan mid-hill basins is intensifying due to increasing monsoon variability and expanding valley settlements. This study develops a process-informed GIS-based Multi-Criteria Decision-Making framework integrated with the Analytical Hierarchy Process (AHP) to assess flood susceptibility in Lamjung District, Nepal. Nine conditioning factors—elevation, slope, rainfall, distance to river, drainage density, Topographic Wetness Index (TWI), land use/land cover, soil type, and NDVI—were structured to represent precipitation forcing, runoff production, terrain-driven moisture accumulation, and hydrological exposure at 10&#xa0;m resolution. AHP weighting (Consistency Ratio = 0.037) identified distance to river (0.156), rainfall (0.151), and TWI (0.152) as dominant controls. The resulting Flood Susceptibility Index indicates that 604.54&#xa0;km² (35.73%) of the district falls within high and very high susceptibility classes, primarily along the Marsyangdi River corridor. Validation was conducted using a qualitative approach based on documented flood events and spatial agreement with known flood-prone areas, as the lack of spatially explicit flood inventory data constrained formal quantitative validation. The spatial distribution of susceptibility shows strong correspondence with river corridors and reported flood impacts, providing qualitative support for the spatial plausibility of the model outputs. While the proposed framework provides a physically interpretable and adaptable approach for flood susceptibility assessment in data-constrained mountainous regions, its transferability is subject to limitations associated with AHP-based subjective weighting and data availability.</p>

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Flood susceptibility mapping in a Himalayan mountain basin using GIS and multi-criteria analysis: a case study from Lamjung District, Nepal

  • 期刊论文

  • 发表日期：

    2026年7月14日

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  • Bibash Dhakal,
  • Yojana Rimal,
  • Barsha Gautam,
  • Andrea Petroselli

摘要

Flood hazard in Himalayan mid-hill basins is intensifying due to increasing monsoon variability and expanding valley settlements. This study develops a process-informed GIS-based Multi-Criteria Decision-Making framework integrated with the Analytical Hierarchy Process (AHP) to assess flood susceptibility in Lamjung District, Nepal. Nine conditioning factors—elevation, slope, rainfall, distance to river, drainage density, Topographic Wetness Index (TWI), land use/land cover, soil type, and NDVI—were structured to represent precipitation forcing, runoff production, terrain-driven moisture accumulation, and hydrological exposure at 10 m resolution. AHP weighting (Consistency Ratio = 0.037) identified distance to river (0.156), rainfall (0.151), and TWI (0.152) as dominant controls. The resulting Flood Susceptibility Index indicates that 604.54 km² (35.73%) of the district falls within high and very high susceptibility classes, primarily along the Marsyangdi River corridor. Validation was conducted using a qualitative approach based on documented flood events and spatial agreement with known flood-prone areas, as the lack of spatially explicit flood inventory data constrained formal quantitative validation. The spatial distribution of susceptibility shows strong correspondence with river corridors and reported flood impacts, providing qualitative support for the spatial plausibility of the model outputs. While the proposed framework provides a physically interpretable and adaptable approach for flood susceptibility assessment in data-constrained mountainous regions, its transferability is subject to limitations associated with AHP-based subjective weighting and data availability.