The application of dynamic and continuous time series has drawn attention due to the complexities of the rainfall-runoff process and the simplification of multiple regression and static methods. On the other hand, forecasting river flow is one of the main topics in flood control. This paper reports the results of applying the SWAT hydrological model to analyze the rainfall-runoff relationship for a 6-year period in the Kahir catchment basin, Sistan and Baluchistan province. The model output was calibrated by the SUF12 optimizer algorithm, and the data entered the model again. Then, the model output was used to forecast future periods using Support Vector Regression (SVR) and essential codes in MATLAB. The acceptable results of the SVR model regarding data prediction can be used as another method to estimate parameters and inputs.
Azhdary Moghaddam, M., Rashki, M., & Sanayee, S. (2020). Runoff simulation and prediction using Support Vector Regression (SVR) and SWAT Hydrological model. Journal of Hydrosciences and Environment, 4(8), 14-20. doi: 10.22111/JHE.2022.6903
MLA
Mehdi Azhdary Moghaddam; Mohsen Rashki; Soroosh Sanayee. "Runoff simulation and prediction using Support Vector Regression (SVR) and SWAT Hydrological model", Journal of Hydrosciences and Environment, 4, 8, 2020, 14-20. doi: 10.22111/JHE.2022.6903
HARVARD
Azhdary Moghaddam, M., Rashki, M., Sanayee, S. (2020). 'Runoff simulation and prediction using Support Vector Regression (SVR) and SWAT Hydrological model', Journal of Hydrosciences and Environment, 4(8), pp. 14-20. doi: 10.22111/JHE.2022.6903
VANCOUVER
Azhdary Moghaddam, M., Rashki, M., Sanayee, S. Runoff simulation and prediction using Support Vector Regression (SVR) and SWAT Hydrological model. Journal of Hydrosciences and Environment, 2020; 4(8): 14-20. doi: 10.22111/JHE.2022.6903
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