Integrating AHP and Land Change Modeling to Assess Urban Expansion-Induced Flood Susceptibility in Islamabad, Pakistan

Rapid and unplanned urban expansion has intensified flood hazards in many developing regions, yet few studies quantitatively disentangle the relative effects of land-use change and climate variability on flood susceptibility. This study examines the interplay between urban sprawl, land cover transformation, and hydrological risk in Islamabad, Pakistan, using an integrated Remote Sensing (RS), Geographic Information System (GIS), Analytical Hierarchy Process (AHP), and Land Change Modeler (LCM) framework. Multi-temporal Landsat imagery (1990–2024) was used to map land-use transitions, while the AHP quantified flood susceptibility weights for topographic, hydrological, and anthropogenic factors. The LCM simulated projected 2030 land-use scenarios, which were integrated into the flood susceptibility model to evaluate baseline, climate change, and urban sprawl scenarios. Results show that built-up area expansion at a rate of 7% per year drives a 41% increase in high-risk flood zones by 2030, exceeding the 35% increase attributed to climate-induced precipitation extremes. The coupled RS-GIS-AHP-LCM approach enhances the dynamic predictive capacity of flood risk modeling and supports anticipatory, spatially informed decision-making. This study is among the first to dynamically integrate AHP and LCM for assessing the coupled impacts of land-use change and climate variability on flood susceptibility in a South Asian megacity.