A GIS-based multi-criteria framework for mapping potential irrigated agricultural zones in newly reclaimed arid...

Geographic assessment of natural resources is a pillar for sustainable agriculture in newly developed agroecosystems. The current work provides a new framework to discriminate agricultural potential zones by integrating the analytical hierarchy process (AHP) with fuzzy logic under the geographic information system (GIS) platform. The study was conducted on 303.54 km2 (30354 ha) in the western Nile Delta fringes, Egypt. Topographic maps, field surveys, and laboratory analyses were employed to specify parameters characterizing terrain, soil, and groundwater qualities. The main criteria and their respective sub-criteria were ranked and weighted using the AHP. The GIS tools were employed to generate raster layers using ordinary kriging geostatistical models, normalize the thematic layers using fuzzy membership functions, and integrate the fuzzified layers with their AHP-derived weights using the weighted sum algorithm. Results revealed that the consistency ratio of all the developed pairwise comparison models did not exceed 10%, indicating the efficacy of AHP in allocating the specific contribution of each criterion. Salinity, sodicity, and depth were key parameters controlling soil performance; meanwhile, potential salinity and infiltration problems primarily determined the feasibility of groundwater irrigation. Among four major criteria, the greatest impact was due to groundwater quality (50%), followed by chemical soil quality (24%) and physical soil quality (21%), while slope had the least contribution (5%). The potentiality analysis indicated that the studied soils are promising since good-quality soils occupied more than 60% of the studied area. Groundwaters with good, marginal, and poor quality occupied 40, 23, and 37% of the total area, respectively. The overall potentiality map showed that 36, 26, and 38% of the studied area displayed high, moderate, and low potential for agricultural expansion, respectively. The integration of AHP with GIS tools (geostatistical analysis and fuzzy set) can enhance insight into sustainable land-use planning and suggest also timely cropping practices. Further investigations are advocated to quantify the suitable cropping patterns in the studied region.