Optimal design of water quality monitoring network

19^th April 2018, 14:00
Xiaohui Zhu

Abstract

The optimal design of a water quality monitoring network not only minimizes the pollution detection time and maximizes the detection probability in river systems, but also reduces the redundant monitoring locations. In addition, it saves the investment and costs for building and operating the monitoring system as well as satisfies the management requirement.

We use the beneficial features of Multi-objective Discrete Particle Swarm Optimization to optimize the design of water quality monitoring network. Four optimization objectives are used in the algorithm which are minimum pollution detection time, maximum pollution detection probability, maximum centrality of monitoring locations and satisfying the management requirement of reservation for special monitoring locations. In order to guide the convergence process to keep reserved monitoring locations in Pareto frontier, we use a binary matrix to denote the reserved monitoring locations. Moreover, a new particle initialization procedure and the discrete velocity and position functions are also developed to support the reservation for monitoring locations.

We use the Storm Water Management Model (SWMM) to model a hypothetical river network which was studied in the literature for comparative analysis of our work. We define 3 pollution detection thresholds and simulate pollution events respectively to obtain all the pollution detection time for all the potential monitoring locations when a pollution event occurs randomly at any potential monitoring location. Experiment results are confirmed by an enumeration search method and show that our algorithm can obtain the Pareto frontier of optimization monitoring network design as well as satisfy the management requirement of reservation for monitoring locations.