Land evaluation approaches comparing TOPSIS and SAW with parametric methods for rice cultivation

Population growth has resulted in an increase in land exploitation on a large scale. Therefore, to increase crop yield and sustainable use of soil, it is necessary to exploit the land according to its potential. Due to land suitability assessment's multifactor nature, it needs a method for evaluating the factors simultaneously; in this case, multi-criteria decision models can be used. Therefore, this study aimed to compare the efficiency of the parametric method (square root) with multi-criteria decision-making approaches (technique for order of preference by similarity to ideal solution (TOPSIS) and simple additive weighting (SAW)) for evaluating land suitability in some rice cultivated areas in Khuzestan province, southwest Iran. A total of 28 rice farms were selected in the study area, and a pedon was dug, examined, and sampled in each. Several physicochemical land characteristics were used for the evaluation process, such as soil, climate, and topographical factors. According to the results, soil texture is the main limiting factor for rice farming in the study region, and organic carbon, salinity, and alkalinity ranked next. The range of land index for rice cultivation calculated by the square root method was from 19.3 to 70.9, from 49 to 95.3 by TOPSIS, and from 3.57 to 74.7 by SAW. The calculated explanatory coefficients between the actual yield and land indices for rice products estimated by the square root method, the TOPSIS approach, and the SAW method were 0.44, 0.63, and 0.60, respectively. This result confirms the high accuracy of TOPSIS method compared to SAW and square root methods. TOPSIS is therefore the ideal method for prioritizing options based on the simulation of the ideal answer because it is highly technical and robust in its decision-making approach. Furthermore, it uses the standardization method, equations, mathematical matrices, and suitable weights. Overall, it can be recommended as a suitable efficiency approach for land suitability evaluation.