Combined Fuzzy AHP-GIS for Agricultural Land Suitability Modeling for a Watershed in Southern Iran.

Abstract

Modeling agriculture land suitability at a regional scale plays an important role in designing the best sustainable management systems. The aim of this study was to derive a land suitability map for wheat farming by combining the Geostatistics and analytic hierarchy (AHP)-Fuzzy algorithm in geographic information system (GIS) in calcareous and saline-sodic soils, southern Iran. The local expert's opinions were used to make a decision on the weighting of climate, terrain, and soil data by applying an AHP method. The input data were transformed to a fuzzy-set data. The Spherical and Gaussian semi-variogram models had the best performance for fitting the soil parameters. The results revealed that soil texture (w = 0.207), pH (w = 0.121), slope (w = 0.120), electrical conductivity (w = 0.113), and exchangeable sodium percentage (w = 0.111) had the highest specific weighting for wheat production, respectively. The land suitability map indicated that 25.65% (48306.6 ha) of the studied area was for highly suitable, 38.2% (71939.7 ha) was moderately suitable, and 27.63% (52017.2 ha) was marginally suitable. Only 8.52% (16042.4 ha) of the studied area was not suitable for wheat farming. In conclusion, a combination of AHP, Fuzzy, and GIS could be a potential approach for site-specific soil management, land-use planning, and protection of the environment.