Title: Eutrophication research of Dongting Lake: an integrated ML-SEM with neural network approach

Authors: Xiaodong Li; Zhihua Gao; Zuo Chen; Guangming Zeng; Tomás León; Jie Liang; Fei Li; Wu Liu; Haipeng Wu; Chungyan Du; Ren Chen

Addresses: College of Environmental Science and Engineering, Hunan University, Changsha, Hunan, 410082, China; Key Laboratory of Environmental Biology and Pollution Control, Ministry of Education, Hunan University, Changsha, Hunan, 410082, China ' College of Environmental Science and Engineering, Hunan University, Changsha, Hunan, 410082, China; Key Laboratory of Environmental Biology and Pollution Control, Ministry of Education, Hunan University, Changsha, Hunan, 410082, China ' College of Information Science and Technology, Hunan University, Changsha, Hunan 410082, China ' College of Environmental Science and Engineering, Hunan University, Changsha, Hunan, 410082, China; Key Laboratory of Environmental Biology and Pollution Control, Ministry of Education, Hunan University, Changsha, Hunan, 410082, China ' School of Public Health, University of California, Berkeley, California, 94720, USA ' College of Environmental Science and Engineering, Hunan University, Changsha, Hunan, 410082, China; Key Laboratory of Environmental Biology and Pollution Control, Ministry of Education, Hunan University, Changsha, Hunan, 410082, China ' College of Environmental Science and Engineering, Hunan University, Changsha, Hunan, 410082, China; Key Laboratory of Environmental Biology and Pollution Control, Ministry of Education, Hunan University, Changsha, Hunan, 410082, China ' College of Environmental Science and Engineering, Hunan University, Changsha, Hunan, 410082, China; Key Laboratory of Environmental Biology and Pollution Control, Ministry of Education, Hunan University, Changsha, Hunan, 410082, China ' College of Environmental Science and Engineering, Hunan University, Changsha, Hunan, 410082, China; Key Laboratory of Environmental Biology and Pollution Control, Ministry of Education, Hunan University, Changsha, Hunan, 410082, China ' School of Hydraulic Engineering, Changsha University of Science and Technology, Changsha, Hunan 410114, China ' North China University of Water Resources and Electric Power, Zhengzhou, Henan, 450011, China

Abstract: It is pressing to investigate the influence factors of eutrophication in Dongting Lake, which is the second largest freshwater lake in China and is faced with more and more serious eutrophication problems by natural and man-made factors in recent years. In this study, a new multivariate analysis approach integrating the maximum likelihood estimation structural equation modelling (ML-SEM) with neural network method is proposed. Twenty-seven variables indicating water quality from 2005 to 2012 were derived from the Dongting Lake Ecological Environment Monitoring Center of Hunan Province. The results showed that: (1) temperature (T) and hydraulic gradient (HG) had the most positive influence on chlorophyll-a (Chl-a) with a sensitivity ratio of 1.218 and 1.039, respectively, (2) transparency (SD) had the most negative effect on Chl-a concentration and (3) Chl-a increased quickly and reached the highest level when total phosphorus (TP) levels were from 0.08 mg/L to 0.12 mg/L. These results would provide guidance for eutrophication control strategies for Dongting Lake. By combining ML-SEM with artificial intelligence technique such as neural network, this study examined the causal and nonlinear relationships involved in the eutrophication process.

Keywords: eutrophication; modelling; structural equation modelling; SEM; neural network; Dongting Lake; environmental pollution.

DOI: 10.1504/IJEP.2017.088180

International Journal of Environment and Pollution, 2017 Vol.62 No.1, pp.31 - 52

Available online: 23 Nov 2017 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article