Water Quality Evaluation and Influencing Factor Analysis of Nanwan Reservoir with a Bayesian Model Based on AHM-CRITIC Combination Weighting - SUN Geyao; DUAN Jingjing; ZHAO Jing (Renmin Zhujiang)
In a traditional Bayesian model,equal weights are assigned to different evaluation factors,and the difference in their contributions to water quality is thereby ignored.To address this problem,this paper introduces the attribute hierarchy model-criteria importance through intercriteria correlation (AHM-CRITIC) combination weighting on the basis of a traditional Bayesian model and constructs a Bayesian model for water quality evaluation based on AHM-CRITIC combination weighting.The water quality of Nanwan Lake and the water quality grades of the main tributaries inflowing into Nanwan Reservoir are quantitatively analyzed with the model by using measured monthly water quality data of reservoir sections and main inflow tributaries from 2012 to 2020,and the results are compared with those of other methods.The following findings are obtained.① From 2012 to 2015,Nanwan Lake basically maintained the water quality at the Class III standard.However,from 2016 to 2020,the water quality did not meet the Class III standard occasionally,with water of Class Ⅳ even appearing.The water quality of the Dongjiahe section was poor,while the water quality of the Xiaoshihe,Tanjiahe,Wudaohe,and Xijiahe sections was good.② The results of the Bayesian model with combination weighting for water quality evaluation are more consistent with those of the single factor index method and the improved Nemerow index method.Overcoming the shortcomings of the subjectively weighted Bayesian method,the proposed model can reflect the water quality of the reservoir more realistically and provide a technical basis for similar water quality evaluation.