A land use suitability model for rainfed farming by Multi-criteria Decision-making Analysis (MCDA) and Geographic Information System (GIS)

This study was carried out to analyze the land use suitability of Golestan Province, located in the northeast of Iran, for rainfed farming performance using Geographic Information System (GIS) and Multi-criteria Decision-making Analysis (MCDA) in 2016. First, thematic maps of several environmental variables including soil, climate and topographic variables were obtained. After preparing the raster layers, the environmental requirements of rainfed farming were identified from a comprehensive literature review and asking local experts' opinions; then they were classified according to FAO (Food and Agriculture Organization of the UN) requirements. In the next step, AHP (Analytic Hierarchy Process)-acquired weights were assigned to the criteria. Then, digital layers were overlaid using Weighted Overlay Analysis (WOA) in ArcGIS. According to the results of land suitability analysis, development of rainfed farming is possible for up to 56 percent of the current land of Golestan Province (about 396,550.5 ha) in the southern and central areas as a long belt from east to west. The results showed that some climatic variables such as temperature, annual rainfall, and sunshine hours were not limiting factors for rainfed farming in this region. However, other environmental variables such as salinity, organic matter, soil erosion, soil texture classes, and the autumn, spring, May and June rainfalls were identified as limiting factors for rainfed farming performance in the northern and northeastern regions of Golestan Province. We also found that slope was a limiting cause in the southern part of this province. Generally, the use of specific management practices such as increasing soil organic matter, saline reduction of lands, conservation tillage, and supplementary irrigation canimprove the quality class of low capability lands to higher suitability classes and increase the quality of environmental resources.