Kaka Shahedi; mahtab forootan danesh
Abstract
Simulation of the rainfall-runoff process in a watershed is highly important from the point of view of hydrological issues, water resources management, river engineering, flood control structures and its storage. Rainfall-runoff estimation using a distributed hydrological model and the technique of GIS ...
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Simulation of the rainfall-runoff process in a watershed is highly important from the point of view of hydrological issues, water resources management, river engineering, flood control structures and its storage. Rainfall-runoff estimation using a distributed hydrological model and the technique of GIS has become possible, practical and common. The Wetspa model is a distributed model simulating runoff and water balance that is performed at different time scales including hourly or daily basis. In this research, the discharge is simulated using Wetspa model in the Ghorichay watershed. This watershed (as one of the sub-watersheds of Gorganrood) with an area of 2481.5 ha is located in the south of Ramian city in Golestan province. The data used by the model are land use maps, soil texture, digital elevation model, precipitation, evaporation, temperature and discharge (for calibration and validation of the model). Calibration of 13 parameters was performed manually and automatically for 7 years at the beginning of the statistical period and model validation was performed for a period of 5 years. The results of the model evaluation show the accuracy of discharge simulation and very good agreement between the simulated data and observations based on the Nash-Sutcliffe criterion of 67.21% in the calibration period and 76.34% in the validation period. Also, the discharge calculated by the Wetspa model for the whole watershed was 28.31%, which in comparison with the observed discharge of 30.12% indicates a good simulation of the model.
Geomorphology
hojatolah younesi; ahmad godarzi; Masoud Shakarami
Abstract
Today, hybrid models of artificial intelligence are considered as a suitable method for simulating hydrological phenomena, including quantitative estimation of river flow. For this purpose, there are various approaches in hydrology to estimate the flow rate of rivers, of which artificial intelligence ...
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Today, hybrid models of artificial intelligence are considered as a suitable method for simulating hydrological phenomena, including quantitative estimation of river flow. For this purpose, there are various approaches in hydrology to estimate the flow rate of rivers, of which artificial intelligence models are the most important. Therefore, in this study, the performance of support vector-wavelet regression, backup vector-gray wolf regression and bat-support vector regression models to simulate the flow of Kashkan river located in Lorestan province during the statistical period of 2010-2011 in the daily time scale were analyzed. The criteria of correlation coefficient, root mean square error and mean absolute value of error and bias were selected for evaluation and performance of the models. The results showed that the hybrid models have acceptable results in simulating the river discharge. Comparison of models also showed that the support-wavelet vector regression model in the validation stage showed values of R2 = 0.960, RMSE = 0.045, MAE = 0.024, NS = 0.968 and BIAS = 0.001 in predicting daily river flow. . Overall, the results showed that the use of hybrid support-wavelet regression model can be useful in predicting daily discharge.
