AUTHOR=He Min , Zhang Yibo , Ma Zhaoxi , Zhao Qin 

TITLE=Intelligent optimal layout of drainage pipe network monitoring points based on information entropy theory

JOURNAL=Frontiers in Environmental Science

VOLUME=Volume 12 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/environmental-science/articles/10.3389/fenvs.2024.1401942

DOI=10.3389/fenvs.2024.1401942

ISSN=2296-665X

ABSTRACT=With the rapid development of the economy, the scale of urban drainage pipe networks is expanding continuously. The pipes used to discharge urban domestic sewage, rainwater and industrial sewage are complex, which makes it difficult for the urban drainage pipe network system to realize efficient and accurate monitoring and management, resulting in various illegal discharges and leakage. Therefore, a reasonable layout of drainage pipe network monitoring points is the premise of efficient management. However, the existing research on the optimal layout of monitoring points in drainage pipe networks is limited. The main methods adopted are fuzzy clustering and dynamic closeness, only considering the relationship between relevant pipe network nodes and depending on manual analysis and understanding of pipe network topology, resulting in the layout of monitoring points being greatly affected by human factors, and monitoring data being invalid. Therefore, based on the information entropy index, and the integration of Bayesian reasoning, Monte Carlo method and stormwater management model (SWMM), a coupling model for the optimization of drainage pipe network monitoring point is proposed to realize the automatic layout of drainage pipe network nodes. Results indicate that (1) the relative mean error of the parameter inversion simulation results of the pollution source tracking model is linearly fitted with the information entropy. The calculation shows that there is a positive linear correlation between them, which verifies the feasibility of the information entropy algorithm in the field of monitoring node optimization; (2) the information entropy algorithm can be well applied to the optimal layout of single monitoring nodes and multiple monitoring nodes, and can well correspond to the inversion results of tracking model parameters; (3) The constructed monitoring point optimization model can realize the optimal layout of monitoring points of drainage pipe network. Finally, the pollution source tracking model is used to verify the effectiveness of the optimal layout of monitoring points and the whole process has less human participation and a high degree of automation. The results of this study will provide technical support for the monitoring system management of urban drainage pipe network, and have great significance in water environment quality.