Grade evaluation of black-odorous urban rivers in the Greater Bay Area of China using an improved back propagation (BP) neural network

Abstract

With the rapid development of urbanization, the urban water environment is receiving continuous attention. It is necessary to understand water quality in a timely manner and make a reasonable comprehensive evaluation. However, existing black-odorous water grade evaluation guidelines are not sufficient. Understanding the changing situation of black-odorous water in urban rivers is a growing concern, especially in real-world scenarios. In this study, a BP neural network combined with the fuzzy membership degree was applied to evaluate the black-odorous grade of urban rivers in Foshan City, which is within the Greater Bay Area of China. The optimal 4 × 11 × 1 topology structure of the BP model was constructed by taking the dissolved oxygen (DO), ammonia nitrogen (NH₃-N), chemical oxygen demand (COD), and total phosphorus (TP) concentrations as input water quality indicators. There was almost no occurrence of black-odorous water in the two public rivers outside the region in 2021. Black-odorous water was most significant in 10 urban rivers, with grade IV and grade V occurring over 50% of the time in 2021. These rivers had three features, i.e., parallel with a public river, beheaded, and close proximity to Guangzhou City, the provincial capital of Guangdong. The results of the grade evaluation of the black-odorous water found basically matched those of the water quality assessment. The existence of some inconsistencies between the two systems justified the necessity to expand and extend the number of employed indicators and grades in the present guidelines. The results confirm the capability of the BP neural network combined with the fuzzy-based membership degree in the quantitative grade evaluation of black-odorous water in urban rivers. This study makes a step forward in understanding the grading of black-odorous urban rivers. The findings can provide a reference for local policy-makers regarding the priority of practical engineering projects in prevailing water environment treatment programs.

Keywords: BP neural network; Black-odorous water; Fuzzy membership degree; Grade evaluation; Greater Bay Area; Urban rivers.