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Azhdary Moghaddam, Mehdi, Rashki, Mohsen, Sanayee, Soroosh. (1399). Runoff simulation and prediction using Support Vector Regression (SVR) and SWAT Hydrological model. نشریه علمی دانشگاه سیستان و بلوچستان, 4(8), 14-20. doi: 10.22111/JHE.2022.6903
Mehdi Azhdary Moghaddam; Mohsen Rashki; Soroosh Sanayee. "Runoff simulation and prediction using Support Vector Regression (SVR) and SWAT Hydrological model". نشریه علمی دانشگاه سیستان و بلوچستان, 4, 8, 1399, 14-20. doi: 10.22111/JHE.2022.6903
Azhdary Moghaddam, Mehdi, Rashki, Mohsen, Sanayee, Soroosh. (1399). 'Runoff simulation and prediction using Support Vector Regression (SVR) and SWAT Hydrological model', نشریه علمی دانشگاه سیستان و بلوچستان, 4(8), pp. 14-20. doi: 10.22111/JHE.2022.6903
Azhdary Moghaddam, Mehdi, Rashki, Mohsen, Sanayee, Soroosh. Runoff simulation and prediction using Support Vector Regression (SVR) and SWAT Hydrological model. نشریه علمی دانشگاه سیستان و بلوچستان, 1399; 4(8): 14-20. doi: 10.22111/JHE.2022.6903

Runoff simulation and prediction using Support Vector Regression (SVR) and SWAT Hydrological model

Journal of Hydrosciences and Environment
دوره 4، شماره 8، اسفند 2020، صفحه 14-20    اصل مقاله (630.77 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22111/JHE.2022.6903
نویسندگان
Mehdi Azhdary Moghaddam* ؛ Mohsen Rashki؛ Soroosh Sanayee
University of Sistan and Baluchestan
چکیده
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.
کلیدواژه‌ها
SWAT hydrological model؛ Support Vector Regression (SVR)؛ Time-series forecast؛ Kahir River
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تعداد مشاهده مقاله: 324
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