Simulation of flow discharge based on monthly precipitation values as inputs is one of the important issues in hydrology and water resources studies, especially in areas where data with the shorter time scales are not available. In this study, the applicability of support vector regression (SVR) model optimized by Ant colony and Copula-GARCH algorithms was investigated and compared to simulate the flow discharge based on total monthly rainfall in Talezang Basin, Iran. Entropy theory was used to select a suitable meteorological station corresponding to a hydrometric station. The vector autoregressive model was also used as the base model in Copula-GARCH simulations. The correlation results of the studied paired variable confirmed the possibility of using copula-based models. The simulation results were evaluated using R2, Nash-Sutcliffe Efficiency (NSE) and root mean square error (RMSE) statistics. According to the 99% confidence intervals of the simulations, the accuracy of both models was confirmed. The simulation results showed that the Copula-GARCH model was more accurate than the optimized SVR (OSVR) model. Considering the 90% efficiency (NSE = 0.90) of Copula-GARCH approach, the results show a 36% improvement of RMSE statistics by Copula-GARCH model compared to OSVR model in simulating the flow discharge on a monthly scale. The results also showed that by combining nonlinear ARCH models with the copula-based simulations, the reliability of the simulation results increases, which was also confirmed using the violin plot. The results also showed an increase in the accuracy of the Copula-GARCH model at the minimum and maximum values of the data.

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Posted 03 Jun, 2021
On 02 Mar, 2022
Received 01 Jun, 2021
Invitations sent on 31 May, 2021
On 18 Apr, 2021
Posted 03 Jun, 2021
On 02 Mar, 2022
Received 01 Jun, 2021
Invitations sent on 31 May, 2021
On 18 Apr, 2021
Simulation of flow discharge based on monthly precipitation values as inputs is one of the important issues in hydrology and water resources studies, especially in areas where data with the shorter time scales are not available. In this study, the applicability of support vector regression (SVR) model optimized by Ant colony and Copula-GARCH algorithms was investigated and compared to simulate the flow discharge based on total monthly rainfall in Talezang Basin, Iran. Entropy theory was used to select a suitable meteorological station corresponding to a hydrometric station. The vector autoregressive model was also used as the base model in Copula-GARCH simulations. The correlation results of the studied paired variable confirmed the possibility of using copula-based models. The simulation results were evaluated using R2, Nash-Sutcliffe Efficiency (NSE) and root mean square error (RMSE) statistics. According to the 99% confidence intervals of the simulations, the accuracy of both models was confirmed. The simulation results showed that the Copula-GARCH model was more accurate than the optimized SVR (OSVR) model. Considering the 90% efficiency (NSE = 0.90) of Copula-GARCH approach, the results show a 36% improvement of RMSE statistics by Copula-GARCH model compared to OSVR model in simulating the flow discharge on a monthly scale. The results also showed that by combining nonlinear ARCH models with the copula-based simulations, the reliability of the simulation results increases, which was also confirmed using the violin plot. The results also showed an increase in the accuracy of the Copula-GARCH model at the minimum and maximum values of the data.

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The full text of this article is available to read as a PDF.
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