Analyses on the development of lake complex ecosystem health based on entropy theory
XU Guo-bin1, REN Wang1, GUQ Shu-ying2, WANG Yi-zhen3
1. State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300072, China; 2. Haihe Water Resources Protection Bureau, Tianjin 300170, China; 3. Haihe River Water Environmental Monitoring Center, Tianjin 300170, China
Abstract：To evaluate the development of the lake systems, based on Schrodinger's theory about the relationship between entropy change and life, this paper introduced the concept of information entropy and established a quantitative model which could evaluate health development of the Lake ecosystem. The analysis method adopted is based on the state of the indicators. At the meantime, the indicators were sorted into positive indicators and negative indicators, both the indicator property and entropy flow direction were being identified. And then to determine the indicators' weight, balanced the health and development. The entropy calculation results based on the monitoring data in 2012 of each water areas of Baiyangdian Lake indicated that the entire eco-system of Baiyangdian Lake was in the sub-health situation, without significant treatment measures, the condition would be last for years. To be specific, the degradation trend of hydrology and water resources as well as the "bio" criterion layer was much more serious. Based on the analysis of the stability of the indexes, and through the analysis of related indexes of the two criterion layers, it was easily to get the conclusion that the main factor influenced the health of Baiyangdian Lake. And its ecological water level could not be satisfied for such a long time, which leaded to a series of biology and water quality declined. The subsequent field visit also confirmed this.
徐国宾, 任旺, 郭书英, 王乙震. 基于熵理论的湖泊生态系统健康发展评估[J]. 中国环境科学, 2017, 37(2): 795-800.
XU Guo-bin, REN Wang, GUQ Shu-ying, WANG Yi-zhen. Analyses on the development of lake complex ecosystem health based on entropy theory. CHINA ENVIRONMENTAL SCIENCECE, 2017, 37(2): 795-800.
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