Modeling crop suitability under micro irrigation using a hybrid AHP-GIS approach

Abstract

Abstract Crop suitability analysis using novel models is a pillar for sustainable land-use planning. In this work, the analytical hierarchy process (AHP) was integrated with GIS to produce suitability maps for wheat and maize under sprinkler irrigation and broad bean under drip irrigation. The study was conducted in an arid area, west Nile Delta of Egypt. The characteristics of local climate, landscape, and groundwater quality were matched with crop requirements and assigned scores. A GIS-based model was implemented to integrate scores and AHP weights and generate crop suitability maps. The climate conditions fitted optimum crop requirements; however, slight slope limitations affected wheat and maize. The electrical conductivity (EC), exchangeable sodium percentage, and CaCO3 were the most important soil factors affecting broad bean, and these factors besides coarse fragments affected wheat and maize. The EC, Na+, and Cl– were the most influential factors for wheat and maize irrigation, while EC and sodium adsorption ratio had the greatest priority for broad bean irrigation. Irrigation water quality had the highest specific weight (0.38) followed by soil (0.36), slope (0.15), and climate (0.10). The final suitability maps showed that 97 and 3% of the total area were suitable (S2) and moderately suitable (S3) for wheat, respectively. Moreover, 85 and 15% of the total area fitted the S2 and S3 classes for broad bean. For maize, 36 and 64% of the total area fitted the S2 and S3 classes. Integrating AHP and GIS would provide effective land-use planning and also suggest proper management practices in arid areas.