Rainfall-Runoff modelling using Support Vector Regression and Artificial Neural Network models (Case study: SafaRoud Dam Watershed)

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Najibzade N.; QADERI K.; AHMADI M.M.

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Paper Information

Journal: IRANIAN JOURNAL OF IRRIGATION AND DRAINAGE Year:2020 | Volume:13 | Issue:6 Page(s): 1709-1720

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Title

Rainfall-Runoff modelling using Support Vector Regression and Artificial Neural Network models (Case study: SafaRoud Dam Watershed)

Author(s)

Najibzade N. | QADERI K. | AHMADI M.M. | Issue Writer Certificate

Keywords

Rainfall-runoffQ1

Support vector regressionQ1

Safaroud DamQ1

Artificial neural networkQ2

Abstract

Rainfall-runoff modeling is an important and complex aspect in most water resource management and planning projects. In this study, Perespetron multi-layered artificial neural network (MLP), Radial basis function Neural Network (RBF), and support vector machine regression with linear kernel functions (SVR linear) were used to develop some models in SPSS to simulate Rainfall-runoff process in subarea of Safaroud dam, located in Halil Rood watershed. For this porpose, hydrometric data of Hanjan station and rainfall data of Hanjan, Rabor, Cheshme Aroos, and Meidan stations, located in the studied area, were used. 70% of the data were used as training data and 30% were used as test data. After calculating the partial correlation coefficients of the rainfall and discharge, six different patterns were used to model the daily rainfall of Hanjan station. In the best pattern of the test level, for SVR Linear 5 model, Mean Absolute Error (MAE), Root Mean Squared Error (RMSE) and correlation coefficient (r) were equal to 0. 032, 0. 229, and 0. 967, respectively. The results proved the efficient performance of MLP and SVR Linear in Rainfall-runoff modeling in the studied area.

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APA: Copy

Najibzade, N., QADERI, K., & AHMADI, M.M.. (2020). Rainfall-Runoff modelling using Support Vector Regression and Artificial Neural Network models (Case study: SafaRoud Dam Watershed). IRANIAN JOURNAL OF IRRIGATION AND DRAINAGE, 13(6 ), 1709-1720. SID. https://sid.ir/paper/131795/en

Vancouver: Copy

Najibzade N., QADERI K., AHMADI M.M.. Rainfall-Runoff modelling using Support Vector Regression and Artificial Neural Network models (Case study: SafaRoud Dam Watershed). IRANIAN JOURNAL OF IRRIGATION AND DRAINAGE[Internet]. 2020;13(6 ):1709-1720. Available from: https://sid.ir/paper/131795/en

IEEE: Copy

N. Najibzade, K. QADERI, and M.M. AHMADI, “Rainfall-Runoff modelling using Support Vector Regression and Artificial Neural Network models (Case study: SafaRoud Dam Watershed),” IRANIAN JOURNAL OF IRRIGATION AND DRAINAGE, vol. 13, no. 6 , pp. 1709–1720, 2020, [Online]. Available: https://sid.ir/paper/131795/en

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