Journal of Water Resources Planning and Management

The first step in effective design of contaminated aquifer site remediation is the accurate characterization of contaminant sources, which requires a large amount of concentration measurement data. However, in real-world scenarios contamination monitoring wells are generally arbitrary in location, monitoring data are sparse in time and space, and there are various uncertainties in predicting the transport process. It is a very challenging problem to optimally design effective monitoring networks intended for accurate unknown contaminant source characterization, with multiple potential source locations. In this study, the local singularity mapping technique is utilized to obtain potential monitoring well locations, which are used as input to the optimal network design model. This set of potential monitoring locations is utilized for selecting the subset of the optimal monitoring locations. This method of selecting the set of potential locations can improve the efficiency of the designed monitoring network for source characterization. The proposed methodology utilizes a multiobjective optimization algorithm for solving a two-objective optimal monitoring network design model. The optimization model is linked to a numerical simulation model simulating flow and transport processes in the aquifer. While constraining the maximum number of permissible monitoring locations, the designed optimal monitoring network improves the accuracy of unknown contaminant source characterization. The designed monitoring network can decrease the degree of nonuniqueness in the measured set of possible aquifer responses to geochemical stresses. The potential application of the developed methodology is demonstrated by evaluating the performance for an illustrative contaminated mine site aquifer. These performance evaluation results show the improved efficiency in source characterization when concentration measurements from the designed monitoring network are utilized.

This work aims to investigate the extent to which demand assessment at fine temporal scales can be useful in the design of a small water distribution network (WDN). To this end, the peak demand assessed thorough the traditional design approach (DA1), based on the amplification of yearly average demand and aimed at obtaining an hourly peak demand estimate, is compared with those obtainable through plumbing system design procedures (DA2) and demand pulse generation models (DA3), both conceived at a fine temporal scale. A further objective of this work is to analyze the WDN hydraulic behavior in the peak hour in terms of nodal pressure heads. In this context, the snapshot steady flow modeling (SFM) with nodal demands assessed through DA1, which is usually adopted for WDN design, is compared with the unsteady flow modeling (UFM) with trend of nodal demands assessed through DA3. Overall, the results of this work show that, when applied to WDNs serving few inhabitants, the hourly demand estimate provided by DA1 can be much smaller than the estimates of DA2 and than the maximum values of DA3, which are instead in quite good agreement. Furthermore, $\mathrm{UFM}+\mathrm{DA}3$ can spot service pressure deficits in peak demand scenarios, which are unidentifiable through $\mathrm{SFM}+\mathrm{DA}1$.

The problem presented in this edition of the Battle of the Water Networks is to define district metering areas (DMAs) in a large network. The problem is addressed in two phases. First, the complexity of the network is simplified by dividing it into three operational areas. Second, an optimization algorithm defines DMAs, looking for the best feasible solution. A preliminary simulation of the network is made. From this, engineering judgment allows for defining an initial set of elements suitable to change. In the second stage, a heuristic algorithm is used to search for the best DMA definition by selecting the locations and settings of the pressure-reducing valves and isolation valves. The network is then divided into two categories: the main pipes and the distribution pipes. Only the distribution pipes can be closed. With these restrictions and those described in the problem, the algorithm looks for the best DMA definition based on both the pressure and demand distribution among all the DMAs.

Among the environmental effects caused by dams, the alteration of flow regimes is one of the most critical to river ecosystems given its influence in long river reaches and its continuous pattern. Provided it is technically feasible, the reoperation of hydroelectric reservoir systems can, in principle, mitigate the effects on degraded freshwater ecosystems by recovering some of the natural flow regime. The typical approach to implement hydropower-to-environment water transfers focuses on the reoperation of the dam located immediately upstream of the environmentally sensitive area, meaning that only one power station will bear the brunt of the benefits forgone for the power sector. By ignoring the contribution of upstream infrastructures to the alteration of the flow regime, the opportunity cost associated with the restoration of a flow regime is not equitably distributed among the power companies in the river basin, therefore slowing the establishment of environmental flow programs. Yet, there is no criterion nor institutional mechanisms to ensure a fair distribution of the opportunity cost among power stations. This paper addresses this issue by comparing five rules to redistribute the costs faced by the power sector when environmental flows (eflows) must be implemented in a multireservoir system. The rules are based on the installed capacity of the power plants; the live storage capacity of the reservoirs; the ratio between the incremental flows; the extent of the storage services (i.e., the volume of water effectively transferred by each reservoir); and the deregulation effect caused by other reservoirs downstream. The analysis is carried out using the Paraná River Basin (Brazil) as a case study.

This paper developed an interval multiobjective two-stage stochastic programming (IMO-TSP) model. The model integrated interval two-stage stochastic programming (ITSP), interval linear multiobjective programming (IMOP), and the analytic hierarchy process (AHP) method. The IMO-TSP model could not only address the conflicts of multiple objectives under uncertainty but could also obtain the optimal allocation results based on the water managers’ experience, knowledge, and local policies. In addition, a solution method was proposed to solve the IMO-TSP model by integrating the Zimmermann’s fuzzy method and the typical ITSP solution method. The developed model was applied to a real-world case for supporting the allocation of limited water resources to various water-use sectors. From the results analysis, the single objective model with a certain indicator can obtain the maximum value of that objective but can hardly take other significant factors into consideration. Conversely, the IMO-TSP model can effectively balance the three objectives of maximizing the system net benefit, minimizing the total COD discharge, and minimizing the water deficit by obtaining the best coordinated satisfaction. The obtained coordination satisfaction by the IMO-TSP model was [0.74, 0.83] in this study, which indicates that the results obtained by the developed model can allocate limited water resources to various water users with a high degree of coordination among the three objectives under different flow levels. The developed model can help the water managers of arid regions to develop the desired and reasonable water resources management policies under uncertainty.