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This study evaluates flood risk susceptibility in the Larkana district of Sindh, Pakistan, using a combination of the Analytical Hierarchy Process (AHP) and Geographic Information Systems (GIS). Larkana, with its proximity to the Indus River and vulnerability to monsoon rainfall, is particularly flood-prone. The research integrates multiple spatial and environmental datasets—including elevation, slope, rainfall, land use, soil texture, and vegetation—into a structured AHP framework to prioritize their influence on flood susceptibility. Expert judgment and quantitative analysis were applied to weigh these parameters, producing a flood risk map that categorizes the district into five zones from very low to very high risk. The methodology aims to support local disaster management and urban planning efforts by providing a precise, data-driven assessment of flood-prone areas.

The study reveals that rainfall, proximity to rivers, slope, and elevation collectively contribute to over 80% of the flood risk in Larkana. According to the susceptibility map, 63.89% of the district is at high risk, 7.65% at very high risk, and only 0.12% is at low risk. This spatial distribution highlights northern Larkana as particularly vulnerable. The validated model, supported by satellite imagery and flood history from 2010 and 2022, demonstrates the effectiveness of AHP-GIS integration for proactive planning. It offers a vital tool for policymakers to prioritize mitigation efforts and build climate resilience.