Water Environment Random Evaluation Model based on the improved TOPSIS method and Bayesian Theory and its Application

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.