**Background:** Agriculture is the primary driver of Ethiopia's economic growth and food security, supporting about 85% of the population and contributing 43% of GDP. However, agriculture in Ethiopia is traditionally rain-fed and subsistence-based, suffering from spatial and temporal rainfall unpredictability. Only 190,000 ha (5.3%) of Ethiopia's 3.7 million hectares of irrigable land have been irrigated. The Belessa Districts in the northwestern highlands are particularly affected by drought and food insecurity due to rainfall variability. No prior land suitability assessment for surface irrigation had been conducted in this area, despite the presence of permanent rivers such as Fota, Mena, Zana, and Bahir Libo. This study aimed to fill that gap using a GIS-based Analytical Hierarchy Process (AHP) method.
**Methods:** The study area covers the East and West Belessa Districts in the central Gondar Zone of Amhara Regional State, with altitudes ranging from 1,169 m to 2,821 m. Eight factors were selected based on literature, data availability, and expert opinion: slope, land use/land cover (LULC), elevation, soil depth, soil texture, soil type, soil drainage, and distance to rivers. Soil data were obtained from the Ethiopian Ministry of Water, Irrigation, and Energy and the Harmonized World Soil Database (HWSD) V:12. The SRTM DEM (30 m resolution) was used to derive slope and elevation. Land use/land cover was prepared from Landsat 8 imagery using ERDAS and ArcGIS 10.3. Distance to rivers was calculated using Euclidean distance in ArcGIS. An 8×8 pairwise comparison matrix was constructed using Saaty's 1–9 scale to assign weights to each criterion. Consistency was evaluated using the consistency ratio (CR), calculated as CR = CI/RI, where CI = (λmax − n)/(n − 1). With λmax = 8.977, n = 8, and RI = 1.41, the CR was 0.098987 (<0.1), confirming acceptable consistency. Weighted parameters were summed using the weighted overlay method in ArcGIS to produce a land suitability index, classified into four categories using the natural break method: highly suitable (S1), moderately suitable (S2), marginally suitable (S3), and not suitable (S4/N1).
**Key Results:** The normalized pairwise comparison matrix yielded the following weights: distance from water source (44%), slope (18%), elevation (13%), soil texture (13%), soil drainage (5%), soil depth (4%), LULC (3%), and soil type (2%). The final land suitability map showed that 12.3% (334.7 km² or 33,466.7 ha) of the study area was highly suitable (S1), 22.1% (598.9 km² or 59,890.7 ha) was moderately suitable (S2), 37.6% (1,020.3 km² or 102,033.3 ha) was marginally suitable (S3), and 28.0% (761.6 km² or 76,164.7 ha) was not suitable (S4). Among individual parameters: 68.2% of the area was within 5 km of a water source (S1 for distance); 3.2% had 0–2% slope (S1), 12.7% had 2–5% slope (S2), 11% had 5–8% slope (S3), and 73.1% had >8% slope (S4); clay soil texture (S1) covered 15.9% (433.0 km²), loam (S2) covered 62.5% (1,697.6 km²), and sandy loam (S3) covered 21.6% (586.2 km²); well-drained soil (S1) covered 42.5% (1,156 km²); and cropland (S1) covered 38.8% (1,053.2 km²). The model was validated by overlaying pre-existing irrigation schemes, which fell within highly and moderately suitable areas, confirming model accuracy.
**Clinical Implications:** This study provides a practical, evidence-based framework for identifying priority areas for surface irrigation development in the Belessa Districts. By mapping 34.4% of the study area as suitable (S1 + S2) for surface irrigation, the results can guide agricultural planners and land-use officers in targeting investments to increase crop production during dry seasons, reduce food insecurity, and transform low-productivity rain-fed agriculture. The findings support progress toward Sustainable Development Goals (SDGs) 1 (ending poverty), 2 (zero hunger and food security), and 3 (healthy lives and well-being). The authors recommend that future work should also evaluate water availability, soil chemical properties, and socioeconomic parameters to complement these physical suitability assessments.