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<p>In recent years, there has been an increase in the frequency and intensity of floods, resulting in substantial damages, particularly in developing nations such as India. Hence, an accurate forecast of flood risk is necessary as the first step in the design of any flood mitigation strategy. In this study, a Multi-Criteria Decision Analysis (MCDA) based on the Geographical Information System (GIS) and Analytical Hierarchy Process (AHP) is presented for forecasting the future flood risk for the entire state of Bihar, India, due to the climate change scenario. The predictive capability of the developed technique is used to forecast Flood Hazard Zonation (FHZ), Flood Vulnerable Zonation (FVZ), and Flood Risk Zonation (FRZ) maps using scenarios based on Representative Concentration Pathways (RCP) and Shared Socioeconomic Pathways (SSP) from the Coupled Model Intercomparison Project (CMIP) climate projections. The model is validated using the Receiver Operating Characteristic (ROC) - Area Under the Curve (AUC) and Synthetic Aperture Radar (SAR) analysis. Analysis of flooded and non-flooded points using historical inundation data yielded a good accuracy of 72.6% for the flood risk model. The predicted FRZ maps indicate 10–20% increase in the very high and high flood-risk areas from the year 2021–2040, especially in dense urban blocks.</p>

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Integrated flood risk prediction and zonation in bihar: observations from climate change projection using GIS-based AHP-Multicriteria approach

  • 期刊论文

  • 发表日期：

    2025年8月21日

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  • Vishwajeet Kumar,
  • Ahmad Rashiq,
  • Om Prakash

摘要

In recent years, there has been an increase in the frequency and intensity of floods, resulting in substantial damages, particularly in developing nations such as India. Hence, an accurate forecast of flood risk is necessary as the first step in the design of any flood mitigation strategy. In this study, a Multi-Criteria Decision Analysis (MCDA) based on the Geographical Information System (GIS) and Analytical Hierarchy Process (AHP) is presented for forecasting the future flood risk for the entire state of Bihar, India, due to the climate change scenario. The predictive capability of the developed technique is used to forecast Flood Hazard Zonation (FHZ), Flood Vulnerable Zonation (FVZ), and Flood Risk Zonation (FRZ) maps using scenarios based on Representative Concentration Pathways (RCP) and Shared Socioeconomic Pathways (SSP) from the Coupled Model Intercomparison Project (CMIP) climate projections. The model is validated using the Receiver Operating Characteristic (ROC) - Area Under the Curve (AUC) and Synthetic Aperture Radar (SAR) analysis. Analysis of flooded and non-flooded points using historical inundation data yielded a good accuracy of 72.6% for the flood risk model. The predicted FRZ maps indicate 10–20% increase in the very high and high flood-risk areas from the year 2021–2040, especially in dense urban blocks.