Application of Entropy Spectral Method for Streamflow Forecasting in Northwest China
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College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling 712100, China
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Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling 712100, China
3
Department of Water Resources Management and Agricultural-Meteorology, Federal University of Agriculture, PMB 2240, Abeokuta 110282, Nigeria
*
Author to whom correspondence should be addressed.
Entropy 2019, 21(2), 132; https://doi.org/10.3390/e21020132
Received: 5 November 2018
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Revised: 20 January 2019
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Accepted: 21 January 2019
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Published: 1 February 2019
(This article belongs to the Special Issue Entropy Applications in Environmental and Water Engineering II)
Streamflow forecasting is vital for reservoir operation, flood control, power generation, river ecological restoration, irrigation and navigation. Although monthly streamflow time series are statistic, they also exhibit seasonal and periodic patterns. Using maximum Burg entropy, maximum configurational entropy and minimum relative entropy, the forecasting models for monthly streamflow series were constructed for five hydrological stations in northwest China. The evaluation criteria of average relative error (RE), root mean square error (RMSE), correlation coefficient (R) and determination coefficient (DC) were selected as performance metrics. Results indicated that the RESA model had the highest forecasting accuracy, followed by the CESA model. However, the BESA model had the highest forecasting accuracy in a low-flow period, and the prediction accuracies of RESA and CESA models in the flood season were relatively higher. In future research, these entropy spectral analysis methods can further be applied to other rivers to verify the applicability in the forecasting of monthly streamflow in China.
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Keywords:
burg entropy; configurational entropy; relative entropy; spectral analysis; streamflow forecasting
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MDPI and ACS Style
Zhang, G.; Zhou, Z.; Su, X.; Ayantobo, O.O. Application of Entropy Spectral Method for Streamflow Forecasting in Northwest China. Entropy 2019, 21, 132. https://doi.org/10.3390/e21020132
AMA Style
Zhang G, Zhou Z, Su X, Ayantobo OO. Application of Entropy Spectral Method for Streamflow Forecasting in Northwest China. Entropy. 2019; 21(2):132. https://doi.org/10.3390/e21020132
Chicago/Turabian StyleZhang, Gengxi, Zhenghong Zhou, Xiaoling Su, and Olusola O. Ayantobo. 2019. "Application of Entropy Spectral Method for Streamflow Forecasting in Northwest China" Entropy 21, no. 2: 132. https://doi.org/10.3390/e21020132
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