Abbas Atapourfard
Abstract
Using one or some specific property to discriminate the sediment of different sources is impossible. Therefore, properties were selected with attention to the type and properties of sedimentary sources. Thus, the efficiency of tracers for identification of sedimentary sources should be evaluated and ...
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Using one or some specific property to discriminate the sediment of different sources is impossible. Therefore, properties were selected with attention to the type and properties of sedimentary sources. Thus, the efficiency of tracers for identification of sedimentary sources should be evaluated and obtained results should be recommended for similar areas. Therefore, in this study, the efficiency of rare earth elements in discrimination sediments of lithological units has been investigated. 69 samples collected from surface soil and active walls of channels in 10 lithological unites of the Chandab watershed basin. The amount of rare element earth was determined by using the neutron activation analysis method. Then, the assumptions of discriminant analysis method (1- the variables are distributed normally, 2- the within-group covariance matrices are equal 3-There is no multicollinearity between variables) were evaluated and then were applied. Based on the results, lithological unites fo Chandab Watehrshed classified into five groups and Yb, Sc, Sm, Th and Eu were selected as sedimentary tracers. According to the F method, for coefficients of discriminate functions, the selected elements can discriminate sediments of lithological groups at 95% confidence level. The ability of Sm, Eu, Yb and Sc to successfully discriminate different sources are the same and more than Th.
Mehdi Sepehri; Seyyed Abbas Atapourfard; Alireza Ildoromi; Hamid Nori; Saba Goodarz; Mohammadmehdi Artimani; Morteza Solgi
Abstract
Peak flow estimation is one of the major issues in water resources and flood management that have basic role in the design of hydraulic structures and biomechanics activities in basins. So that a proper assessment has a basic role in the success of administrative works. In this paper, using artificial ...
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Peak flow estimation is one of the major issues in water resources and flood management that have basic role in the design of hydraulic structures and biomechanics activities in basins. So that a proper assessment has a basic role in the success of administrative works. In this paper, using artificial intelligence methods (MLP Neural Network, the mixture of SOFM with MLP, the mixture of FCM with ANFIS) to estimate Yalfan River’s peak discharge in hydrometer local station. For these models, eight variables have been considered as the inputs that includes rainfall amount in the occurrence time of flood, rainfall of five days ago from occurrence of flood, curve number of the basin (CN), basic discharge and finally peak discharge are considered as the output. In the artificial intelligences after preprocessing of the data, the optimal structure of the models are determined with input and output data, evaluation criteria and trial and error. At the end, the MLP model had better performance compared to ANFIS+FCM, MLP+SOFM, GRNN models.