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Forecast of Irrigation Water Demand Considering Multiple Factors : Volume 368, Issue 368 (07/05/2015)

By Wang, X.

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Book Id: WPLBN0003992449
Format Type: PDF Article :
File Size: Pages 6
Reproduction Date: 2015

Title: Forecast of Irrigation Water Demand Considering Multiple Factors : Volume 368, Issue 368 (07/05/2015)  
Author: Wang, X.
Volume: Vol. 368, Issue 368
Language: English
Subject: Science, Proceedings, International
Collections: Periodicals: Journal and Magazine Collection, Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


APA MLA Chicago

Lei, X., You, J., Guo, X., Wang, H., & Wang, X. (2015). Forecast of Irrigation Water Demand Considering Multiple Factors : Volume 368, Issue 368 (07/05/2015). Retrieved from

Description: China Institute of Water Resources and Hydropower Research, Beijing, 100038, China. Many factors influence irrigation water requirement on the basin scale, which make it difficult to obtain comprehensive data. Despite the advantage of less needing historical data, the prediction precision of traditional trend prediction methods is hard to guarantee. For water scarce basins, the artificial influence on irrigation requirement should be thought of as important impact factors. In this paper, the PCA (principal component analysis) method is used to identify the main influencing factors, such as precipitation, irrigation area, water saving technology and so on. Based on that, an irrigation water demand prediction model considering multiple factors is developed for water shortage regions. The method is applied in the Haihe River basin as an example. The study results show that the irrigation water demand forecasting method considering multiple factors in this paper can achieve higher modelling accuracy, compared with the traditional trend prediction method and the method that does not consider the human influence. In view of the small average relative error, 1.32%, it has good values for application.

Forecast of irrigation water demand considering multiple factors


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