Abstract
In order to assess feasibility of ley farming system performance in the Aq-Qala township, a semi-arid region in north of Iran, Multi-Criteria Analysis (MCA) method and Geographic Information System (GIS) techniques were integrated to evaluate the suitability of wheat, barley and annual alfalfa cultivation. The agronomic and ecological requirements of three crops were identified from available scientific literatures. In this study, environmental variables were included: 1) average, minimum and maximum temperatures, 2) precipitation, 3) slope, 4) slope aspects, 5) elevation and 6) soil characteristics such as organic matter, pH, electrical conductivity (EC), texture, nitrogen, phosphorus, potassium, calcium, iron, and zinc. Weights of these variables were extracted from analysis of Analytical Hierarchy Process (AHP) questionnaires. The suitability analysis was based on matching between land qualities/characteristics and crop requirements. It was done by the weighted overlay technique (WOT) in GIS. In order to assess the land suitability of ley farming system performance, the digital suitability layers of three crops were overlaid and integrated in GIS media by raster calculator functions, then zoning of region was done in 4 classes, including: Highly suitable, moderately suitable, marginally suitable and non-suitable. Our results indicated that 35.1% (35495.20 ha) of total areas of studied region is suitable for ley farming system. According to the generated agricultural suitability map, it was determinate that 15.2% (20681.77 ha) of the region is non-suitable for ley-farming performance, 19.5% (23245.74 ha) is marginally suitable and, 30.2% (33725.6 ha) is moderately suitable. Highly suitable, moderately suitable and marginally suitable lands were expected to have a crop yield of 80–100%, 60–80% and 40–60% of the yield under optimal conditions with practicable and economic inputs, respectively. It was found that the most areas of the southern and central parts of Aq-Qala are the highly and moderately suitable regions. The results demonstrated that the high EC, low OM and low rainfall are the key limiting factors in non-suitable areas.