Browsing by Author "Behmanesh, J."
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Item Covariance Correction For Estimating Groundwater Level Using Deterministic Ensemble Kalman Filter(University of Eloued جامعة الوادي, 2015-01-01) Behmanesh, J.; Bateni, M. M.The main problem in developing a groundwater model is to determine model parameters, particularly hydrogeologic coefficients, in a precise way. In this research, Deterministic Ensemble Kalman Filter (DEnKF) is described as a modern sequential method for data assimilation and a localization scheme within the framework of DEnKF is applied. Najafabad aquifer (in Iran) with area of 1150 km2, is modeled in the time window of Oct. 2000 to Sept. 2007 to obtain water table level data when its values of hydrogeologic coefficients calibrated and verified. DEnKF assimilated 45 observations of true run into the model with 2, 5, and 10 times of calibrated values of hydraulic conductivity and specific yield. This filter has been run both with and without use of localization. Results show easily-implemented localized DEnKF is favorably robust in groundwater flow modeling.Item Rainfall-runoff Modeling In The Turkey River Using Numerical And Regression Methods(University of Eloued جامعة الوادي, 2015-01-01) Behmanesh, J.; Ayashm, S.Modeling rainfall-runoff relationships in a watershed have an important role in water resources engineering. Researchers have used numerical models for modeling rainfall-runoff process in the watershed because of non-linear nature of rainfall-runoff relationship, vast data requirement and physical models hardness. The main object of this research was to model the rainfall-runoff relationship at the Turkey River in Mississippi. In this research, two numerical models including ANN and ANFIS were used to model the rainfall-runoff process and the best model was chosen. Also, by using SPSS software, the regression equations were developed and then the best equation was selected from regression analysis. The obtained results from the numerical and regression modeling were compared each other. The comparison showed that the model obtained from ANFIS modeling was better than the model obtained from regression modeling. The results also stated that the Turkey river flow rate had a logical relationship with one and two days ago flow rate and one, two and three days ago rainfall values.