Flood Susceptibility Mapping and Mitigation Plan in Punjab, Pakistan: A Case Study of the 2025 Flood Using GIS and Remote Sensing

Flooding remains a recurring and damaging hazard in South Punjab, Pakistan, largely due to intense monsoon rains, flat terrain, and the complex Indus River system. This study evaluates flood susceptibility for the 2025 flood event using an integrated approach that combines remote sensing, GIS-based analysis, the Analytical Hierarchy Process (AHP), and machine learning techniques. Key flood-influencing factors considered include elevation, slope, rainfall, land use and land cover (LULC), drainage density, soil characteristics, proximity to rivers, and spectral indices such as NDVI, NDMI, and MNDWI. Satellite data from Sentinel-1 SAR, Sentinel-2, and Landsat were processed to derive hydrological and environmental indicators, allowing reliable identification of flood-affected areas. A weighted overlay method based on AHP was applied alongside a Random Forest model to produce a flood susceptibility map. The study area was classified into five risk categories: very low, low, moderate, high, and very high. The results show that nearly 23% of the region falls within high-to-very-high flood risk zones, particularly along the Indus and Chenab river corridors. Model validation using observed inundation data from 2025 indicates strong agreement, supporting the robustness of the approach. The total flooded area was estimated at around 6,180 km², with agricultural land suffering the greatest impact. In addition, a GIS-based flood mitigation and management plan was developed for Tehsil Alipur and Head Panjnad, where flood risk is especially severe due to low elevation and river confluence. The plan identifies flood extent, safe evacuation zones, and priority areas for intervention. Overall, the study offers a practical and scalable framework that can support more informed decision-making, improve disaster preparedness, and guide sustainable land-use planning in flood-prone regions.