Water Environment Random Evaluation Model based on the improved TOPSIS method and Bayesian Theory and its Application
- Authors: Jinchao Xu 1, Chen Y.2, Zhao J.3, Hang Q.4, Li X.5
- 
							Affiliations: 
							- School of Hydrology and Water Resources, Nanjing University of Information Science and Technology, Key Laboratory of Navigation Structure Construction Technology, Ministry of Transport
- Protection Institute
- School of Hydrology and Water Resources, Nanjing University of Information Science and Technology, China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Jiangsu Key Laboratory of Agricultural Meteorology, Nanjing University of Information Science & Technology
- Yancheng Branch Office, Jiangsu Provincial Hydrology and Water Resources Investigation Bureau
- School of Hydrology and Water Resources, Nanjing University of Information Science and Technology
 
- Issue: Vol 46, No 3 (2019)
- Pages: 344-352
- Section: Water Resources and the Regime of Water Bodies
- URL: https://journals.rcsi.science/0097-8078/article/view/175109
- DOI: https://doi.org/10.1134/S0097807819030102
- ID: 175109
Cite item
Abstract
Under the background analysis of water issues, water environment random evaluation model based on Bayesian theory is put forward to universally describe and physically analyze the uncertainty information. Guided by the viewpoint of sustainable development, this study applies water conservancy science, intelligence science and information science to discuss about risk indexes from three aspects of water quantity, water quality, and water ecology with the evolution mechanism of water environment. The evaluation index system is selected by qualitative analysis and quantitative calculation, and index weight is determined by the improved TOPSISI method. The Bayesian theory is employed to set up the random evaluation model. The process is to obtain posterior distribution by prior distribution with sample information. Then, the evaluation levels of water environment are given by the principle of probability maximization with advancing the control policy. Taihu Basin, China is taken as an example. It shows that the proposed model is rigorous with theory, flexible with method, and reasonable with results, providing a new way for studying water resources shortage, water pollution prevention, and water ecology protection, which can be widely applied to water environment management.
About the authors
Jinchao Xu
School of Hydrology and Water Resources, Nanjing University of Information Science and Technology, Key Laboratory of Navigation Structure Construction Technology, Ministry of Transport
							Author for correspondence.
							Email: xujinchao301@foxmail.com
				                					                																			                												                	China, 							Nanjing, 210044						
Yaqian Chen
Protection Institute
							Author for correspondence.
							Email: Cowry-5268663@163.com
				                					                																			                												                	China, 							Guangzhou, 510611						
Jun Zhao
School of Hydrology and Water Resources, Nanjing University of Information Science and Technology, China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters/Jiangsu Key Laboratory of Agricultural Meteorology, Nanjing University of Information Science & Technology
							Author for correspondence.
							Email: zsmzyq@126.com
				                					                																			                												                	China, 							Nanjing, 210044						
Qingfeng Hang
Yancheng Branch Office, Jiangsu Provincial Hydrology and Water Resources Investigation Bureau
							Author for correspondence.
							Email: hqf_1107@126.com
				                					                																			                												                	China, 							Yancheng, 224005						
Xuechun Li
School of Hydrology and Water Resources, Nanjing University of Information Science and Technology
							Author for correspondence.
							Email: lxcnuist@163.com
				                					                																			                												                	China, 							Nanjing, 210044 						
Supplementary files
 
				
			 
					 
						 
						 
						 
						 
				 
  
  
  
  
  Email this article
			Email this article  Open Access
		                                Open Access Access granted
						Access granted Subscription Access
		                                		                                        Subscription Access
		                                					