Assessing land suitability for surface irrigation using geospatial technologies in the Genale Dawa River Basin, Ethiopia
摘要
The escalating pressure on land and water resources necessitates precise tools for identifying suitable irrigation areas, especially in rain-fed agricultural systems vulnerable to climate variability. This study presents a comprehensive, basin-wide land suitability assessment for surface irrigation in Ethiopia’s Genale Dawa River Basin (GDRB), the nation’s third-largest basin with significant untapped potential. We employed a GIS-based Analytic Hierarchy Process (AHP) to integrate 11 biophysical and infrastructural criteria: soil depth, texture, pH, organic matter, cation exchange capacity, water-holding capacity, rockiness, slope, land use/land cover, and proximity to rivers and roads. Factor weights were derived via expert-driven pairwise comparisons (Consistency Ratio = 0.079), and a weighted overlay analysis generated a final suitability map classified into four classes: highly suitable (S1), moderately suitable (S2), marginally suitable (S3), and not suitable (N). The analysis reveals that only 8.32% of the GDRB is highly suitable (S1) for surface irrigation, while a vast 73.29% is moderately suitable (S2). The highly suitable zones are primarily located in the central plains, characterized by deep Vertisols, gentle slopes, and better access to water, whereas moderately suitable lands require targeted interventions to overcome constraints related to soil texture, rockiness, or infrastructure access. The findings advocate for a two-phase development strategy: immediate investment in highly suitable areas for rapid gains, coupled with a long-term program of land improvement and infrastructure development to unlock the potential of moderately suitable lands. This study provides a critical, evidence-based geospatial tool for policymakers to optimize land and water resources, enhance climate resilience, and achieve sustainable agricultural intensification in Ethiopia and similar data-scarce basins.