GIS–AHP-based assessment of urban waterlogging susceptibility in Delhi using multi-source geospatial data

Abstract

This study explores challenge of urban waterlogging in Delhi by utilizing a comprehensive methodology that merges geospatial analysis with the Analytic Hierarchy Process (AHP). A Digital Elevation Model (DEM), Landsat imagery and rainfall data were used as input datasets for assessing urban waterlogging susceptibility. Ten conditioning factors, including elevation, LULC, MNDWI, road density, population density, drainage density, distance to drainage channels, NDBI, flow accumulation and rainfall, were derived from multi-source geospatial datasets. Rainfall had the highest AHP weight (24.53%), followed by population density (16.26%) and LULC (11.68%). The study underscores the growing prevalence of impervious surfaces due to urban development, leading to diminished natural water absorption and heightened flooding hazards. Low-lying areas, particularly in the cental, north and west regions, exhibit higher susceptibility to waterlogging due to lower drainage-network density and topographic conditions associated with reduced drainage efficiency.