Geospatial Modeling of Urban Flood Susceptibility under Rapid Urban Expansion in Pakistan

Abstract

Rapid urbanization in Pakistan, occurring at an annual rate of approximately 3%, has dramatically increased urban flood susceptibility through uncontrolled sprawl, encroachment on floodplains, blockage of natural drainage networks (nullahs), and widespread conversion of permeable surfaces to impervious cover. This study synthesizes geospatial modeling approaches to map and predict urban flood risk under these dynamic land-use changes, drawing on multi-criteria decision analysis (Analytical Hierarchy Process AHP), machine learning algorithms (Random Forest, XGBoost, CNN), and remote sensing data (Sentinel-1 SAR, NDVI, NDBI, TWI). Key conditioning factors elevation, slope, drainage density, distance to rivers, land-use/land-cover (LULC), and rainfall intensity are integrated to generate high-accuracy susceptibility maps (AUC 0.92–0.99 in validated models). Case studies from major cities (Karachi, Lahore, Islamabad, Quetta) reveal that urban expansion has eliminated critical natural waterways, reduced infiltration capacity, and exacerbated pluvial and flash flooding, as evidenced by record-breaking events in 2010, 2022, and 2025. The analysis highlights the limitations of traditional models in capturing non-stationary climate extremes (cloudbursts, GLOFs) and underscores data gaps (high-resolution DEMs, localized rainfall records). Findings emphasize that unchecked impervious surface growth disproportionately amplifies runoff in low-lying and high-density zones, threatening infrastructure, public health, and economic stability. Policy recommendations include mandatory risk-sensitive urban planning, restoration of natural drainage, separation of stormwater and sewage systems, scaling nature-based solutions (urban green infrastructure, sponge city principles), and integration of real-time AI/GIS monitoring for early warning. Transitioning to resilient, adaptive urban development is essential to mitigate escalating flood risks in Pakistan’s rapidly growing cities amid climate change.