A Spatial Decision‐Support Approach to Identifying Optimal Sites for Rainwater Harvesting

ABSTRACT This study develops a spatial decision‐support framework to locate optimal rainwater harvesting (RWH) sites in the semi‐arid Karma Soor Basin, northern Iraq. ArcGIS Pro was coupled with three multi‐criteria decision‐making methods, TOPSIS, SAW, and Weighted Overlay, using nine hydrological, topographic, and infrastructural parameters whose weights were derived with the Analytic Hierarchy Process. Stream order (22.18%) and surface runoff (18.62%) were the most influential criteria. Suitability maps show that highly suitable zones coincide with mid‐ to high‐slopes, well‐developed drainage networks, and loamy soils. Validation using ROC curves and Quality Sum/Density Ratio metrics identified TOPSIS as the most accurate model (AUC = 0.827). TOPSIS produced the most even distribution, highlighting dispersed but hydrologically favorable sites; SAW gave more extensive areas of moderate suitability, whereas Weighted Overlay gave well‐defined high‐suitability areas. Technique‐specific suitability analysis indicates that check dams, terracing, and percolation tanks are the most appropriate RWH interventions, each associated with distinct landform and runoff regimes. The framework is transferable to other data‐scarce semi‐arid basins to prioritize decentralized storage and groundwater recharge under increasing water stress in the region. Check dams were optimally suited across 142.3 km 2 of the basin, predominantly in high stream order valleys; terracing was on sloping cropland; percolation tanks were most suitable on loamy, moderate‐rainfall zones of recharge potential. These results demonstrate that optimal RWH site selection is not solely a function of rainfall, but a complex interplay between topography, land cover, and hydrological connectivity.