4.2 Article

Analysis and simulation of the influencing factors on regional water use based on information entropy

Journal

WATER POLICY
Volume 14, Issue 6, Pages 1033-1046

Publisher

IWA PUBLISHING
DOI: 10.2166/wp.2012.066

Keywords

Information entropy; Mutual information; Water use proportion

Funding

  1. China Scholarship Council of China, UNESCO-IHE of the Netherlands
  2. Ministry of Science and Technology of China [2011AA100502]
  3. Ministry of Water Resources of China [201201003]

Ask authors/readers for more resources

With regional socio-economic development, the gap between water use demand and available water resources in arid and humid semi-arid areas becomes increasingly serious. In this study, the size of regional water use in the Guanzhong region and Shiyang river basin in northwest China are analyzed to identify important factors affecting it, with the aim of providing better and optimal development planning for the region. Information entropy is used to measure and characterize the diversity of regional water use. Agricultural development and meteorological factors are found to be the main issues affecting regional water use in both regions. A multiple-linear regression (MLR) model was built by applying correlation coefficient (R) and mutual information (MI) scores in the process. Results show that the low value of information entropy of water use in the Shiyang river basin is due to the high proportion of agriculture water use. Using input factors chosen by MI score was found to be the best model to simulate the change of regional water use in both regions. A method using an MLR model together with MI is shown to be able to quantify the relationship between the influencing factors and water use diversity with limited available data.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.2
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available