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

被引：11

作者：

Zhang, Jinping ^{[1
,2
,3
]}

Li, Hongbin ^{[1
]}

Shi, Xixi ^{[1
]}

Hong, Yang ^{[4
]}

机构：

[1] Zhengzhou Univ, Sch Water Conservancy & Environm, 100 Sci Rd, Zhengzhou 450001, Henan, Peoples R China

[2] Zhengzhou Univ, Zhengzhou Key Lab Water Resource & Environm, Zhengzhou 450001, Henan, Peoples R China

[3] Henan Key Lab Groundwater Pollut Prevent & Rehabi, Zhengzhou 450001, Henan, Peoples R China

[4] Univ Oklahoma, Sch Civil Engn & Environm Sci, Norman, OK 73019 USA

来源：

WATER RESOURCES MANAGEMENT | 2019年 / 33卷 / 08期

基金：

国家重点研发计划;

关键词：

Wavelet-nonlinear cointegration prediction; Irrigation water; Rainfall; Crop water requirement; TIME-SERIES; ECONOMIC-GROWTH; NEURAL-NETWORK; RAINFALL; EVAPOTRANSPIRATION; MEMORY;

D O I：

10.1007/s11269-019-02270-3

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

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.

引用

页码：2941 / 2954

页数：14

共 36 条

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