A coupling methodology of the analytic hierarchy process and entropy weight theory for assessing coastal water quality

Xiao, Kai; Tamborski, Joseph; Wang, Jerry H. C.; Feng, Xiaobo; Wang, Sichen; Wang, Qianqian; Lin, Debei; Li, Hailong

A coupling methodology of the analytic hierarchy process and entropy weight theory for assessing coastal water quality

2022

Rapid economic development in coastal areas has gradually increased the risk of coastal water quality deterioration. The assessment methods of coastal water quality are multifarious, but many depend on either subjective judgment or objective calculation. We proposed a weighted sum methodology by integrating the subjective analytic hierarchy process and objective entropy theory (AHP-entropy weight methodology) to obtain an overall evaluation of coastal water quality. The mathematical models to transform the biochemical and physical parameter values and soluble substance concentrations into index scores have been formulated in comparison to the national water quality classification scheme. The application of the AHP-entropy weight methodology was demonstrated in the nearshore area of Yangjiang city, China, based on 23 seawater sampling stations in autumn 2017 and spring 2018. Datasets including biochemical and physical parameters, nutrients, and heavy metals have been converted into water quality index scores based on the proposed mathematical model. Results revealed that the overall water quality fell into the “good” class in both sampling seasons. The spatial distribution of the water quality index scores demonstrated that the relatively worse water quality occurred in estuarine and nearshore areas, signifying the negative effect of coastal anthropogenic activities. The statistical analyses like the hierarchical cluster analysis interpreted that the river input acted as a main source of pollutants in the study area. The AHP-entropy weight methodology could be a preferred way to assist decision-makers in properly evaluating the current state of coastal water quality in an unbiased, objective manner.

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