Mohammad Gholampoor; abdolhalim Ghazali; Ahmad Roodzi; Shahab Araghinezhad
Abstract
In arid regions,like most of the Iran, human is suffering fromwater shortage. Water harvesting can be effective, especially in correct exploitation of existing waters in arid regions. With an average rainfall of less than one-third of the world, there are different climates in Iran, even in southern ...
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In arid regions,like most of the Iran, human is suffering fromwater shortage. Water harvesting can be effective, especially in correct exploitation of existing waters in arid regions. With an average rainfall of less than one-third of the world, there are different climates in Iran, even in southern parts like Minab and the areas around Estaghlal Dam. In current situations, rainfall pattern has been changed and the length of drought periods has been increased in Minab. Last designed standard operating systems for estimating the amount of water entering to reservoirs like Esteghlal Dam are not sufficient. So, it is necessary to use new methods with higher accuracy in estimating and predicting watershed surface runoff. To achieve this objective, the use of numerical models for estimating and predicting is inevitable. In this research, SWAT and artificial intelligence models are used to estimate and forecast surface runoff. Calibration, validation and prediction of surface runoff were computed using soil, land use, topography and hydro-climatic data layers in the yearly and monthly basis. The annual values of evaluation criteria such as Mean Square Error (RMSE) and mean absolute error (MSE) in the calibration of the SWAT model were 6.89, 8.37 and for FTDNN were 5.35, 7.76, respectively, while, the monthly calibration results were 16.29, 32.02 for the SWAT and 9.46, 22.86 for FTDNN models. Linear regression coefficients in monthly calibration of models were 0.96 and 0.60 and in annual calibration of models were 0.94 and 0.98, respectively. Comparing criteria of evaluation of two models concluded that artificial intelligent model (FTDNN) has more accuracy and superior performance compared to SWAT model.
Fatemeh Mirzaie Nodoushan; Shahab Araghinejad; Omid Bozorghaddad
Abstract
One of the most important problems of water resources operation systems, specifically surface reservoirs in confronting hydrologic variability, is considering drought phenomenon effects on operation methods. As well as flow variations relative to average flow, duration of the drought is another ...
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One of the most important problems of water resources operation systems, specifically surface reservoirs in confronting hydrologic variability, is considering drought phenomenon effects on operation methods. As well as flow variations relative to average flow, duration of the drought is another important factor. One way to resist the drought is suitable operation of water resources during drought conditions. There are several models developed for water resources management such as WEAP software. But such models do not have water resources modeling capability during drought conditions. Therefore, developing such capability on WEAP model is highly important for water resources engineers. Developing the hedging rules for operation based on WEAP software was investigated by this research by which an extension program was developed in WEAP software. Developing such model would enable us to jointly optimize and simulate on basins. In order to test the capability of the complementary program, modeling was performed on operation of Gorganrood river reservoirs. Then the results of the developed model were compared to the ordinary WEAP software results. The results indicated 1 to 38 percent increased capability of WEAP software on modeling for hydrologic drought conditions. It is worth mentioning that the complementary model was developed as a general model by which the model can be used on different basins.
