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Application of GIS-based analytical hierarchy process for assessment and mapping of flood risk zone in the lower Ramganga River Basin, Western Gangetic Plain, India

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Abstract

The Indo-Ganga–Brahmaputra plain is one of the world’s most vulnerable areas to catastrophic flood events. The severity and frequency of floods in this region have grown dramatically during the last few decades. As a result, an authentic map providing detailed spatial information on floods is required for reducing future flood disasters. This sort of map can be an invaluable tool for displaying flood-prone areas and determining the magnitude of flood risk. The Ramganga river (~ 200 km length) flowing in the western Gangetic plain was chosen for this investigation. This river is well known for its channel movement and flood hazards. The analytical hierarchy process model in GIS ambiance was used in this work to quantify and map flood risk in the lower Ramganga river basin. Six hazard-forming factors, namely relief, distance from active channel, slope, geomorphology, rainfall, and vegetation, and seven vulnerability factors, namely population density, household density, female density, road density, land use/land cover, female literacy, and total literacy, were chosen to determine flood risk zone (FRZ). According to the findings, about 35.29 per cent of the basin’s total area is in a high to very high flood risk zone, where flooding occurs at one- to three-year recurring intervals. The flood risk map has been validated using ground truth data, and the Kappa index has been computed, indicating a high degree of accuracy for the FRZ thematic classes.

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  1. Department of Geography, Samsi College, Samsi, Malda, West Bengal, India

    Rameswar Mukherjee

  2. Department of Geography, Visva-Bharati, Santiniketan, West Bengal, India

    Pamela Deb

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  1. Rameswar Mukherjee
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Mukherjee, R., Deb, P. Application of GIS-based analytical hierarchy process for assessment and mapping of flood risk zone in the lower Ramganga River Basin, Western Gangetic Plain, India. Environ Dev Sustain 26, 6163–6193 (2024). https://doi.org/10.1007/s10668-023-02957-z

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