FORECASTING OF MEAN DAILY RUNOFF DISCHARGE OF BEHESHT-ABAD RIVER USING WAVELET ANALYSIS

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ABDOLLAHI ASADABADI S.; DINPASHOH Y.; MIRABBASI R.

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Journal: Journal of Water and Soil Year:2014 | Volume:28 | Issue:3 Page(s): 534-545

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Title

FORECASTING OF MEAN DAILY RUNOFF DISCHARGE OF BEHESHT-ABAD RIVER USING WAVELET ANALYSIS

Author(s)

ABDOLLAHI ASADABADI S. | DINPASHOH Y. | MIRABBASI R. | Issue Writer Certificate

Keywords

FORECASTINGQ2

RIVER DISCHARGEQ2

CROSS WAVELETQ2

ARTIFICIAL NEURAL NETWORKQ2

Abstract

FORECASTING of RIVER DISCHARGE is a key aspect of efficient water resources planning and management. In this study, two models based on Wavelet Analysis and ARTIFICIAL NEURAL NETWORKs (ANNs) were developed for FORECASTING discharge of Behesht-Abad River. For this purpose, mean daily discharge data of mentioned river as well as precipitation data of 17 meteorological stations were used in the period 1999-2008. In the first method, called CROSS WAVELET (CW), complex Morlet wavelet was used as analyzer function. Wavelet analyzing was performed for every daily rainfall and average discharge time series, separately. The model equation derived for 1, 2, 3 and 7 days ahead FORECASTING horizon. In the second method, called Wavelet Neural Networks conjunction (WNN), a preprocessing was done on the initial input matrix using Meyer wavelet. Then the elements of the initial input matrix were normalized and the second input matrix was created. A three layer Feed Forward Back Propagation (FFBP) was formed based on the second input matrix and target matrix. After training the model using Levenberg-Marquardt (LM) algorithm, the RIVER DISCHARGEs were predicted for short term time horizons.The results showed that the WNN method had higher accuracy in short-term FORECASTING of RIVER DISCHARGE in comparison with CW and ANN methods. In testing stage, in CW model when FORECASTING horizon reduced from 7-days to 1day, the R2 value increased from 0.5113 to 0.9388, and RMSE decreased from 17.9171 to 8.3226 m3/s. In ANN model when FORECASTING horizon reduced from 7-days to 1day, the R2 value increased from 0.6705 to 0.9166, and RMSE decreased from 5.9828 to 2.5600 m3/s. Whereas, in WNN model, when FORECASTING horizon reduced from 7-days to 1day, the R2 value increased from 0.8424 to 0.9927, and RMSE decreased from 3.4678 to 0.8145 m3/s.

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APA: Copy

ABDOLLAHI ASADABADI, S., DINPASHOH, Y., & MIRABBASI, R.. (2014). FORECASTING OF MEAN DAILY RUNOFF DISCHARGE OF BEHESHT-ABAD RIVER USING WAVELET ANALYSIS. JOURNAL OF WATER AND SOIL (AGRICULTURAL SCIENCES AND TECHNOLOGY), 28(3), 534-545. SID. https://sid.ir/paper/141913/en

Vancouver: Copy

ABDOLLAHI ASADABADI S., DINPASHOH Y., MIRABBASI R.. FORECASTING OF MEAN DAILY RUNOFF DISCHARGE OF BEHESHT-ABAD RIVER USING WAVELET ANALYSIS. JOURNAL OF WATER AND SOIL (AGRICULTURAL SCIENCES AND TECHNOLOGY)[Internet]. 2014;28(3):534-545. Available from: https://sid.ir/paper/141913/en

IEEE: Copy

S. ABDOLLAHI ASADABADI, Y. DINPASHOH, and R. MIRABBASI, “FORECASTING OF MEAN DAILY RUNOFF DISCHARGE OF BEHESHT-ABAD RIVER USING WAVELET ANALYSIS,” JOURNAL OF WATER AND SOIL (AGRICULTURAL SCIENCES AND TECHNOLOGY), vol. 28, no. 3, pp. 534–545, 2014, [Online]. Available: https://sid.ir/paper/141913/en

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