Integrating remote sensing and GIS-based AHP for flood hazard assessment in the Damodar River Basin, India

Abstract

Flooding is one of the most catastrophic natural hazards in India, causing significant socio-economic losses annually. Despite the widespread application of GIS-based Analytical Hierarchy Process (AHP) methods for flood hazard assessment, limitations remain in capturing fine-scale hydrological variability. Addressing this gap, the present study advances existing frameworks by integrating additional hydrological indicators specifically the Normalized Difference Water Index (NDWI) and surface roughness to enhance the spatial precision of flood hazard mapping in the Damodar River Basin. This study employs a GIS-based Analytic Hierarchy Process (AHP) within a multi-criteria decision-making (MCDM) framework to delineate flood hazard zones in the Damodar River Basin by assigning relative weights to key influencing factors. Parameters such as elevation, slope, roughness, land-cover, drainage density, topographic wetness index (TWI), (NDWI), annual rainfall, and proximity to rivers were analyzed to evaluate the spatial distribution of flood hazard regions. Thematic maps of these parameters were derived using remote sensing data, including SRTM Digital Elevation Model (DEM) and other scientific datasets. The primary purpose of this study is to develop a robust GIS–AHP framework for flood hazard assessment in the Damodar River Basin, providing scientific evidence to guide targeted mitigation and policy interventions. Weighted values for factors were computed, with elevation (0.2099), slope (0.1894), and rainfall (0.1459) being the most critical contributors, while roughness (0.0265) had the least impact. The calculated consistency ratio (CR) of 0.0562, well below the threshold of 0.1, validates the robustness of the weight assignments. The results reveal that approximately 2.42% (1015 km²) of the basin is categorized as low hazard level, 31.01% (12,997 km²) as moderate hazard level, 56.25% (23,571 km²) as high hazard level, and 10.32% (4326 km²) as very high hazard level. This analysis provides a critical foundation for targeted flood mitigation strategies and resource allocation, emphasizing the need to address high and very high hazard zones to minimize future flood impacts effectively.