Ata Allah Nadiri; Saeed Yousefzadeh
Volume 4, Issue 10 , June 2017, , Pages 21-40
Abstract
An accurate estimation of the hydrogeological parameters such as hydraulic conductivity, which is essential for careful management and protection of groundwater resources, is an important part of hydrogeological studies. Various field and laboratory methods, generally done using hydrogeological data, ...
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An accurate estimation of the hydrogeological parameters such as hydraulic conductivity, which is essential for careful management and protection of groundwater resources, is an important part of hydrogeological studies. Various field and laboratory methods, generally done using hydrogeological data, have already been proposed for estimating hydraulic conductivity. One of the best and the most complete methods is the field pumping test which is very time-consuming and expensive. In addition, hydrogeological parameters estimated by it have an inherent uncertainty. In this study, we tried to use artificial intelligence methods, widely considered in recent years, such as artificial neural network (ANN), mamdani fuzzy logic(MFL), sugeno fuzzy logic(SFL), and adoptive neuro-fuzzy inference system (ANFIS) for the estimation of the hydraulic conductivity. In this study, for the accurate estimation of the hydraulic conductivity in Maraghe-Bonab plain by these models, geophysical and hydrogeological data were used as models' inputs. Their results were compared with the evaluation criteria, and the best model based on the RMSE was selected. Accordingly, the ANFIS model, compared to other models, with an RMSE of 1.12 in the test phase has high power in the estimation of the hydraulic conductivity. Radius of clustering, number of fuzzy rules, and number of clusters are very important in fuzzy and neuro-fuzzy models. Radius of clustering in the ANFIS model, based on the minimum RMSE amount, was equal to 0.4 and the numbers of clusters, based on if-then fuzzy rules, was 9. The methods presented in this study, which demonstrated superior performance in estimating hydraulic conductivity of Maragheh-Bonab plain, can be used in estimating hydraulic conductivity of other plains with similar hydrogeological conditions.
