Hydrological suitability analysis for rainwater harvesting using GIS-based fuzzy AHP: Mojo watershed, Ethiopia

ABSTRACT Water scarcity is a major challenge in Ethiopia's arid and semi-arid regions, particularly the Mojo watershed in the Awash River Basin. This study identified optimal sites for rainwater harvesting (RWH) using an integrated approach that combined geographic information system, remote sensing, hydrological modeling, and a fuzzy analytical hierarchy process. Eleven spatial and non-spatial criteria, including rainfall, runoff, slope, stakeholder input, and infrastructure proximity, were used to generate thematic layers, standardized and weighted with fuzzy logic. The SWAT model was calibrated and validated using 15 years of streamflow data, showing strong performance (R² = 0.77 calibration, 0.80 validation; NSE = 0.76 calibration, 0.78 validation). Suitability analysis showed 6.61% of the area is very highly suitable for RWH, 21.55% highly suitable, 21.76% moderately suitable, 32.99% low suitability, and 17.09% restricted. The proposed RWH structures include nine farm ponds and three micro dams, selected based on terrain, soil, runoff, and proximity factors. Field surveys and spatial analysis validated the model's reliability. This study highlights the effectiveness of integrating geospatial tools, stakeholder input, and multi-criteria decision-making to promote climate-resilient water management. The findings provide practical guidance for improving water access, agricultural productivity, and ecosystem resilience in the Mojo watershed and similar environments.