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

Jinping Zhang (), Hongbin Li, Xixi Shi and Yang Hong
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Jinping Zhang: Zhengzhou University
Hongbin Li: Zhengzhou University
Xixi Shi: Zhengzhou University
Yang Hong: University of Oklahoma

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2019, vol. 33, issue 8, No 20, 2954 pages

Abstract: 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.

Keywords: Wavelet-nonlinear cointegration prediction; Irrigation water; Rainfall; Crop water requirement (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s11269-019-02270-3

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