GIS-AHP-based site selection for surface rainwater harvesting in the Beshilo sub-basin, Ethiopia

Introduction Water scarcity remains a pressing global problem, influenced by climate variability, limited access to water storage, and considerable reliance on rain-fed agriculture, making rainwater harvesting particularly relevant in drought-prone areas, where this reliance increases vulnerability to water stress. Rainwater harvesting has become a viable adaptation strategy for reducing exposure to dry spells, strengthening resilience to climate fluctuations, and supporting sustainable agricultural practices. Methods Therefore, this study was conducted in the Beshilo sub-basin, Ethiopia, to identify suitable rainwater harvesting sites using geographic information system (GIS) and analytic hierarchy process (AHP), to enhance drought resilience, improve agricultural water availability, supporting climate adaptation planning, and promoting sustainable water resource management in water-stressed areas. Ten parameters were considered: rainfall, soil texture, hydrological soil group, topographic wetness index, land use/land cover, stream order, drainage density, slope, geology, proximity to agricultural land, and proximity to roads. Within the geographic information system environment, spatial datasets were reclassified into suitability classes, standardized to a common resolution and projection, and combined using a weighted overlay technique. Parameter weights were derived through the AHP method, yielding an acceptable consistency ratio (CR = 0.09) based on expert judgment and prior research. Results Rainfall (29%) was the most influential parameter, followed by slope (20%) and land use/land cover (15%). Drainage density, geology, and proximity-related factors exerted a relatively low influence. The sub-basin was classified into four suitability classes: low suitable, moderately suitable, highly suitable, and very highly suitable by the ensuing rainwater harvesting suitability map. Discussion Analysis revealed that very high and very low suitability classes account for 1.89 and 1.63% of the area, respectively, while 58.76% is moderately suitable and 37.72% is highly suitable. The predominance of moderately to highly suitable zones highlights significant potential for implementing rainwater harvesting structures across the basin. Generally, the findings demonstrate that geographic information systems integrated with AHP are reliable and effective tools to assist in making decisions for rainwater harvesting planning. This study aligns with similar studies conducted in semi-arid regions, including Ethiopia, offering valuable spatial insights to advance climate-resilient agriculture and sustainable water resource management in water-stressed areas.