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Integrated Flood Hazard Assessment Using AHP-GIS in the Pallikaranai Marshland, Buckingham Canal Corridor, India
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Integrated Flood Hazard Assessment Using AHP-GIS in the Pallikaranai Marshland, Buckingham Canal Corridor, India
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Journal Article
Integrated Flood Hazard Assessment Using AHP-GIS in the Pallikaranai Marshland, Buckingham Canal Corridor, India
2026
Overview
The resultant impact of climate change and urbanization has caused extensive disruption to natural hydrological processes, thus enhancing the flood risk in susceptible areas. This study evaluated flood processes in the Pallikaranai Marshland–Buckingham Canal corridor using detailed flood inundation modeling and risk assessment methodology. Important geospatial factors and variables, such as rainfall, Digital Elevation Model (DEM), slope, Land Use Land Cover (LULC), river distance, flow length, and Normalized Difference Water Index (NDWI), were weighed and ranked. These weighted parameters were assimilated to estimate the Flood Hazard Index (FHI), which was subsequently applied to create an intricately mapped flood hazard. The analysis and testing of the involved parameters by assessing flood susceptibility has been facilitated with hydrological modeling, Geographic Information System (GIS), as well as with remote sensing procedures. Deep-learning frameworks, particularly convolutional neural networks, have also shown high predictive capability for regional flood susceptibility (Kalantar et al. 2021). The findings suggest that urban growth has resulted in extensive wetland degradation, elevated surface runoff, and more frequent flooding, particularly during intense rainfall. The FHI-based flood hazard map identifies critical areas at risk of flooding, highlighting the explicit role of land cover changes in flood intensity and frequency. This study underscores the urgent need for sustainable urban planning, wetland conservation, and climate-resilient infrastructure to mitigate flood hazards and enhance longterm urban flood resilience in the region. These results help to better understand urban flood hazards and offer a scientific foundation for future flood management.
