Raziyeh Safiyari; Fereydoon Sarmadian; Ahmad Heidari; Shirin Younesi
Abstract
Evaluation soil erosion is an important matter to protecting it from destroying in future due to the excessive use of the inherent capacity of soil and also improper management. Therefore, in this study land vulnerability related to water and wind erosion of Abyek for crops and pasture land has been ...
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Evaluation soil erosion is an important matter to protecting it from destroying in future due to the excessive use of the inherent capacity of soil and also improper management. Therefore, in this study land vulnerability related to water and wind erosion of Abyek for crops and pasture land has been evaluated, using Raizal model as one of the Microleis sub-models. Morphological and physical and chemical analysis data were obtained of studying and evaluating the 32 soil profiles. Agricultural - climatic and management information including temperature and precipitation data were collected from Bagh-e-Kosar climatological station for the last 17 years. To study the effect of climatic changes in the assessment of land area for the year 2080 AD (for 70 future year), the reports of International Panel on Climate Change (IPCC) allocated to West Asia have been used. Utilization types considered for evaluation, including wheat, corn, barley and alfalfa. The results obtained of Land vulnerability evaluation studies related to water and wind erosion using Raizal model part have been prepared as maps in the GIS environment. Information obtained from Land vulnerability models related to wind erosion for crops and pasture land, also implies vulnerability risk fora wide percent of the region lands under the current management, that the results evaluation of the proposed management methods express the improvement of destroying ability classes.
Alireza Amirian Chekan; Ferydoon Sarmadiyan; Ahmad Heydari; Mahmoud Omid; Jahangir Mohammadi; Inakwu Odeh
Abstract
The traditional fuzzy operators, such as t-norms, t-conorms and averaging operators have been used for soil suitability evaluation to aggregate criteria as an overall suitability index. However, such operators do not account for the degree of compensation common to human aggregation criteria, especially ...
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The traditional fuzzy operators, such as t-norms, t-conorms and averaging operators have been used for soil suitability evaluation to aggregate criteria as an overall suitability index. However, such operators do not account for the degree of compensation common to human aggregation criteria, especially in the presence of conflicting criteria. Fuzzy integrals are powerful and flexible aggregation functions that combine the data provided by several information sources based on fuzzy measures. One of the most known fuzzy integrals is the Choquet Integral (CI) that is often used as a nonlinear aggregation tool that takes into account the interactions among the conflicting and interrelated criteria. CI has hardly ever been used in soil suitability evaluation. In this paper, we tested the CI performance as an aggregation operator to evaluate soil suitability for irrigated rice in Lorestan province, western Iran. To conduct standard fuzzy analysis, soil samples were taken from 29 farms under rice cultivation and for the purpose of validation, average dry matters of the three 1×1m quadrates were used to determine the grain yield of rice in each farm. Fuzzy membership values of seven evaluation criteria were combined using CI to obtain a single suitability index in each land unit. In order to validate the results, the soil suitability indices were tested and compared with the results obtained by Lukasiedwicz’s t-norm and t-conorm operator (CLO) by correlation with the measured rice yield. The results show R2 values were fairly high for both aggregated methods, but the soil suitability index obtained by the CI integral has significantly better agreement with rice yield (R2 = 0.83) than those obtained with the CLO (R2 = 0.75). These results call for further investigation of CI as an alternative, and perhaps a better, aggregation operator for soil suitability evaluation.
