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Multi-Resolution Cointegration Prediction for Runoff and Sediment Load

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  • Jinping Zhang
  • Yong Zhao
  • Weihua Xiao

Abstract

With the wavelet transform method, the multi-resolution analysis of runoff and sediment load at Huaxian hydrological station located in the lower reaches of the Weihe River in China is presented to find the varying quasic-periodic waveforms existing in different decomposed time scales. The cointegration theory is introduced to reveal the long-term balance relationship and short-term fluctuations of the original and decomposed runoff and sediment load time series. Thus, considering the decomposed sediment load components in different time scales as the input data series, and the corresponding decomposed runoff component acting as the output data series, the multi-resolution cointegration method is produced. The results show that the multi-resolution cointegration method has the higher prediction accuracy, and the prediction errors are almost less than 5 %. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Jinping Zhang & Yong Zhao & Weihua Xiao, 2015. "Multi-Resolution Cointegration Prediction for Runoff and Sediment Load," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(10), pages 3601-3613, August.
    • Handle: RePEc:spr:waterr:v:29:y:2015:i:10:p:3601-3613
    DOI: 10.1007/s11269-015-1018-7
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    References listed on IDEAS

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    1. Xia Zhang & Guo Yu & Zhan Li & Peng Li, 2014. "Experimental Study on Slope Runoff, Erosion and Sediment under Different Vegetation Types," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(9), pages 2415-2433, July.
    2. R. Venkata Ramana & B. Krishna & S. Kumar & N. Pandey, 2013. "Monthly Rainfall Prediction Using Wavelet Neural Network Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(10), pages 3697-3711, August.
    3. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
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    Cited by:

    1. Jinping Zhang & Hongbin Li & Xixi Shi & Yang Hong, 2019. "Wavelet-Nonlinear Cointegration Prediction of Irrigation Water in the Irrigation District," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(8), pages 2941-2954, June.

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