Designing an optimal water quality monitoring network

Xiaohui Zhu, Yong Yue*, Yixin Zhang, Prudence W.H. Wong, Jianhong Tan

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review


The optimal design of water quality monitoring network can improve the monitoring performance. In addition, it can reduce the redundant monitoring locations and save the investment and costs for building and operating the monitoring system. This paper modifies the original Multi-Objective Particle Swarm Optimization (MOPSO) to optimize the design of water quality monitoring network based on three optimization objectives: minimum pollution detection time, maximum pollution detection probability and maximum centrality of monitoring locations. We develop a new initialization procedure as well as a discrete velocity and position updating function to optimize the design of water quality monitoring network. The Storm Water Management Model (SWMM) is used to model a hypothetical river network which was studied in the literature for comparative analysis of our work. We simulate pollution events in SWMM to obtain all the pollution detection time for all the potential monitoring locations. Experimental results show that the modified MOPSO can obtain steady Pareto frontiers and better optimal deployment solutions than genetic algorithm (GA).

Original languageEnglish
Title of host publicationIntelligence Science I - 2nd IFIP TC 12 International Conference, ICIS 2017, Proceedings
EditorsZhongzhi Shi, Ben Goertzel, Jiali Feng
PublisherSpringer New York LLC
Number of pages9
ISBN (Print)9783319681207
Publication statusPublished - 2017
Event2nd IFIP TC 12 International Conference on Intelligence Science, ICIS 2017 - Shanghai, China
Duration: 25 Oct 201728 Oct 2017

Publication series

NameIFIP Advances in Information and Communication Technology
ISSN (Print)1868-4238


Conference2nd IFIP TC 12 International Conference on Intelligence Science, ICIS 2017


  • Closeness centrality
  • Multi-objective optimization
  • Optimal water quality monitoring network
  • SWMM

Cite this