Comparison of different data layers combination models for rain water catchment systems site selection using GIS, case study: Kan Basin

Inadequate temporal and spatial distribution of precipitation in arid and semi-arid regions, cause destructive floods in addition to loss of surface runoff. Therefore, controlling surface runoff and its proper utilization through the construction of rainwater catchment systems can be a good way to prevent water loss. Traditional methods may be time wasting and concise. Geographic information systems provide new methods and models of using huge number of maps and data for analysis in a short time with best results and conciseness. This project was implemented in Kan Basin as a pilot which covers an area about 197 km2. Different maps including slope, land use, precipitation, vegetation cover, soil hydrologic groups and geology were overlayed. Land use maps were extracted from ETM+ 8 satellite images of 2014 along with field controls. Then layers were weighted according to their importance and role of each map. Suitable areas for establishing rainwater catchment systems in each model were determined by overlaying in the frameworks of different models including Boolean logic, Index overlay and Fuzzy logic and compared with control points which were implemented with Ministry of Jihad Agriculture. The results showed that the operators gamma=0.2, gamma=0.3 and Product from Fuzzy logic model had the most overlap with the control areas, the best integrated model for determining the appropriate locations for the construction of rainwater catchment systems in the study region.