Water distribution networks (WDNs) need to guarantee that water is delivered with adequate quality. This paper compares the performance of 12 multiobjective procedures to limit water quality deterioration in a WDN through the optimal operation of valves. The first objective (ObF1) is to minimize the water age, chosen as a surrogate parameter of quality deterioration, and the second objective (ObF2) is to minimize the number of valve closures. The 12 procedures are derived from the combination of 4 different optimization algorithms and 3 formulations of ObF1, namely, to minimize the maximum, the arithmetic mean, and the demand-weighted mean water age. The optimization algorithms considered are random search (RS), Loop for Optimal Valve Status Configuration (LOC), and a combination of each of these two with the Archive-based Micro Genetic Algorithm. The procedures are tested on two networks of different complexity. Results show how LOC is able to find near-optimal solutions using a fraction of the computational time required by a brute force search. Furthermore, among the ObF1 formulations, the use of the averages (either arithmetic or demand-weighted) gives better results in terms of impact on the population served by a WDN.

Efficient management of a sewer system includes the control of the conveyed wastewater quality to adequately operate treatment plants and protect the receiving water bodies. Moreover, these systems are vulnerable to either accidental spills or intentional unauthorized discharges. To properly manage them, a limited number of sensors could be placed at different locations to monitor the water quality. In this paper, multiobjective and single-objective optimization procedures to optimally locate sensors in sewer systems are proposed, tested, and compared. The multiobjective procedures include objective functions related to information theory (IT procedure), detection time and reliability (DR procedure), and a combination of them (IT_DR procedure). The single-objective procedures include a greedy-based objective function (GR procedure) and a merged objective function (DR_IT_GR procedure). The procedures show a similar performance when applied on a small network, whereas in a real system, the results show that (1) the IT-based method can be effectively used as a filtering technique(2) the DR_IT_GR procedure outperforms the other multiobjective onesand (3) the GR procedure is very efficient in finding the Pareto extreme solutions.

A core problem associated with the water quality monitoring in the sewer system is the optimal placement of a limited number of monitoring sites. A methodology is provided for optimally design water quality monitoring stations in sewer networks. The methodology is based on information theory, formulated as a multi-objective optimization problem and solved using NSGA-II. Computer code is written to estimate two entropy quantities, namely Joint Entropy, a measure of information content, and Total Correlation, a measure of redundancy, which are maximized and minimized, respectively. The test on a real sewer network suggests the effectiveness of the proposed methodology.