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Wavelet-Nonlinear Cointegration Prediction of Irrigation Water in the Irrigation District

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Listed:
  • Jinping Zhang

    (Zhengzhou University
    Zhengzhou Key Laboratory of Water Resource and Environment, Zhengzhou University
    Henan Key Laboratory of Groundwater Pollution Prevention and Rehabilitation)

  • Hongbin Li

    (Zhengzhou University)

  • Xixi Shi

    (Zhengzhou University)

  • Yang Hong

    (University of Oklahoma)

Abstract

Aiming at revealing the nonlinear relations between rainfall, crop water requirement and irrigation water in the irrigation district, and improving the accuracy of wavelet-cointegration prediction model proposed by the literature (Zhang et al. J Hydrol 544: 343-351, 2017), the nonlinear cointegration theory and wavelet neutral network method are introduced to construct the innovated wavelet-nonlinear cointegration prediction model of irrigation water. The results show that there are nonlinear cointegration relations amongst the decomposed time series of rainfall, crop water requirement and irrigation water. Compared with the wavelet-cointegration prediction model, the wavelet-nonlinear cointegration prediction model has the higher prediction accuracy, and all relative errors of the predicted values are around 2%, except 2004 and 2012.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:waterr:v:33:y:2019:i:8:d:10.1007_s11269-019-02270-3
    DOI: 10.1007/s11269-019-02270-3
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