erfan bahrami; Ali Shahidi
Abstract
were prepared as seven raster layers, and after ranking and weighing, the obtained DRASTIC index ranged between 45 and 115. Yet, as far as the model's major problem is applying expert opinions in ranking and weighing the variables, the main purpose of this study is to improve the DRASTIC model by using ...
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were prepared as seven raster layers, and after ranking and weighing, the obtained DRASTIC index ranged between 45 and 115. Yet, as far as the model's major problem is applying expert opinions in ranking and weighing the variables, the main purpose of this study is to improve the DRASTIC model by using the gene expression model, which as an intelligent model has shown a desirable performance. Also, in a mixed form, it can cope with other models to provide acceptable results. Thus, DRASTIC variables of a 20- year statistical period (1999-2009) were defined as the model input, and nitrate concentration was defined as its output. Data in GEP model were divided into two categories: training and experimentation. Moreover, using the statistical parameters (R2, RMSE, MAE and r), the simulation results of the gene expression model were evaluated. The results indicate the model's high ability in estimating nitrate concentration and its high capability in improving DRASTIC model. For validation and improvement of DRASTIC model, statistical parameters, R2 and r, were used, which were specified according to the error of the range model. Also, for each time combining the parameter with the GEP model, a score was gained during different stages and repeated performances of the weight ranking model using weighing rank model of each parameter. Finally, by removing two parameters, S and T, the modified formula of the DRASTIC index which was obtained based on weighing was 5D, 4R, 5A, 5I, and 4C.
hydrogeology
Hadi Nayyeri; Mamand Salari; Zhila Chardawli
Abstract
The soil erosion issue and lands' degradation is one of the most important issues in natural sciences. Soil erosion is the predominant geomorphic process on many land surfaces. In order to assess the environmental and economic consequences of soil erosion, quantitative data are needed. In this research, ...
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The soil erosion issue and lands' degradation is one of the most important issues in natural sciences. Soil erosion is the predominant geomorphic process on many land surfaces. In order to assess the environmental and economic consequences of soil erosion, quantitative data are needed. In this research, soil erosion is studied with of morphometric parameters. For this aim, Gheshlagh river basin iin Kurdistan province, was studied. Areas with a rating of more than 2 that entered directly into the main river were plotted as sub-basins for morphometric calculations. These areas included 47 sub-basins. The number of 16 morphometric parameters were calculated to determine the morphometric conditions of the basin and were considered as the input layer. Then, the results of these parameters were aggregated by four multi-criteria decision models TOPSIS, VIKOR, SAW and CF. In all four, the northern sub-basins were classified as areas with low and very low susceptibility to erosion. These basins are often located in volcanic rocks. In a general view, according to all four models studied, the basins in the lithology of dark gray shale (Sanandaj shale). Their sensitivity to erosion have been classified from moderate to very high. the final results showed that the multi-criteria decision-making methods, by presenting a classification, divide the region into several classes in terms of the degree of erosion sensitivity, and the VIKOR method, due to the greater coefficient of variation, has more accurate than the others.
