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Water Resources Management

Erschienen in:

14.05.2019

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

verfasst von: Jinping Zhang, Hongbin Li, Xixi Shi, Yang Hong

Erschienen in: Water Resources Management | Ausgabe 8/2019

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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.

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Titel: Wavelet-Nonlinear Cointegration Prediction of Irrigation Water in the Irrigation District
verfasst von: Jinping Zhang
Hongbin Li
Xixi Shi
Yang Hong
Publikationsdatum: 14.05.2019
Verlag: Springer Netherlands
Erschienen in: Water Resources Management / Ausgabe 8/2019
Print ISSN: 0920-4741
Elektronische ISSN: 1573-1650
DOI: https://doi.org/10.1007/s11269-019-02270-3

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