Journal of Water Resources Planning and Management

While it has become more commonplace as an environmental management strategy, few empirical studies have evaluated the environmental performance of collaborative governance regimes. Using watershed management as an example, this study tests the effectiveness of a collection of collaboration components included in the Integrative Collaborative Governance Regime framework for achieving environmental improvement goals using the EPA’s watershed-based approach. Coupling survey measures of collaboration dynamics with empirical assessments of environmental performance, this research offers evidence on the importance of specific collaborative elements and provides public managers with guidance to improve performance and achieve goals. Correlation analyses revealed the importance of monetary and technical resources to watershed partnerships’ environmental performance, validating previous literary assumptions. This study also uncovered an incongruence between participants’ acceptance of assigned roles and responsibilities within the watershed partnership and achievement of watershed improvement goals. This suggests that it is not enough to get the right people to the table—they must also be assigned the right roles.

Los Angeles, which relies on large infrastructure systems that import water over hundreds of miles, faces a future of reduced imports. Within Los Angeles and its hundreds of water agencies, the capacity to adapt to future changes is influenced by laws, institutions, and hydrogeology. This paper presents a systems analysis of urban water management in metropolitan Los Angeles County to assess opportunities for increasing local water reliance. A network flow model was developed to investigate management tradeoffs across engineered, social, and environmental systems. With an aggressive regional demand target, increased stormwater capture (300%), and prioritized water reuse from existing facilities, imported water supplies can be cut by 30% while maintaining landscapes, economic productivity, and groundwater resources. Further reducing imports (by 40–50%) is possible through actions to promote additional reuse, recharge, conservation, and groundwater access. Reducing imported water without significant conservation results in likely groundwater overdraft. Fragmented networks of agencies in Los Angeles create an uneven landscape of vulnerability to water shortages. The paper discusses model applications, research needs, and policy implications of results for dry-climate cities.

Reducing pressure in a water distribution system leads to a decrease in water leakage, decreased cracks in pipes, and consumption decreases. Pressure management includes an advanced type called remote real-time control. Here pressure control valves are controlled in real time in such a way as to provide set optimal pressures mostly at remote consumer locations. A hydraulic valve is expected to minimize problems with transients, although the study also applies to other valves. The control is done by using a controller that typically depends on tunable parameters, which are laborious to determine. A parameter-less controller is simpler because there are no parameters to tune. Such an existing P-controller, based on the flow in a pressure control valve being known, is enhanced from assuming constant flow to be valid for variable flow. This novel parameter-less controller performs significantly better than the former P-controller. Several recently proposed controllers, which were studied numerically, are compared: two parameter-less controllers, and two parameter-dependent controllers. The new parameter-less controller performs either better or worse than the most optimally tuned parameter-dependent controllers.

To investigate transport of drinking water in topologically complex distribution networks and associated monitoring problems, experimental facilities can provide a relevant complement to numerical models and living laboratoriess or playgrounds. An experimental facility was designed which is a scale model of an existing supply zone serving $\sim \mathrm{100,000}$ customers. The facility was designed for (1) investigating transport of water qualities and potential contaminations; (2) providing a fast and flexible testing ground for networks of real-time water quality and quantity sensors prior to installment in live distribution networks; and (3) training and demonstration purposes. A scale analysis was used to investigate the possibilities including in a single facility the processes turbulence, turbulent diffusion, particle transport mode, and shear stress in a way that represents the real-life network environment, and to determine the facility’s spatial and temporal dimensions. Using hydraulic modeling, it was verified that the main flow patterns in the facility are representative for the real-life network. The final design includes a $4\times 8\mathrm{m}$ model, transparent PVC pipes, and a decentralized fast control system that includes 28 demand and 4 supply locations to simulate complex flow patterns. The setup is currently being prepared for experimentation. This paper describes the theoretical background and the design and construction process.

The management of water flow using reservoirs for the purpose of hydropower production can have significant impacts on solute transport. Reducing the phosphorous load to downstream areas can be of great importance for aquatic habitats associated with recipient waters, as well as for the overall health of coastal and estuary areas. This study demonstrates a combined operation of a network of reservoirs with the objectives of hydropower production and improvement of water quality in downstream areas using a multiobjective approach and incorporating the transport of phosphorous in the watershed. A genetic optimization method was used to determine the trade-off between power production and mitigation of phosphorous discharge in the reservoir network of the Dalälven River, Sweden. The phosphorous export can be reduced ($-5\%$) with a limited loss of power production ($-4.3\%$), but further reduction is associated with a significant loss in total power production. The trade-off between the two objectives is determined using Pareto diagrams and examined for varying particulate conditions.

Restoring the hydrologic flow regime of urban areas by promoting infiltration, retention, and evapotranspiration on the site is one of the goals of low-impact development (LID). These goals can be achieved through the implementation of stormwater control measures (SCMs) such as green roofs and permeable pavements. The effectiveness of SCMs can be influenced not only by their design but also by their location. The present study applies multi-objective evolutionary optimization and Monte Carlo simulation approaches to help identify near-optimal locations of green roofs and permeable pavements in the catchment scale. The Nondominated Sorting Genetic Algorithm II was connected to the stormwater management model (SWMM) to identify the location of SCMs and characterize the tradeoffs between flow regime alteration and implementation costs. The impact of implementing SCMs is measured by peak flow, runoff volume, and the hydrologic footprint residence (HFR). The HFR is a new stormwater metric that represents dynamics of inundated areas and residence time of flood waves throughout downstream segments. The approach was tested in an illustrative case study of an 11.7-ha urban catchment divided into five subcatchments. The results indicate that locating SCMs in downstream subcatchments can reduce peak flow more effectively, whereas SCMs placed in upstream subcatchments better reduce the HFR. The proposed methodology can help stormwater managers to better assess the combined performance of LID-SCMs in different hydrologic scales and generate guidelines for prioritizing the implementation or retrofitting of urban areas with green infrastructure.

Water resources management is a challenging problem in Iran and in many other locations because of the unbalanced temporal and spatial distribution of available water and demands. Interbasin water transfer, in which water is transmitted from a basin with high water availability to a neighbor basin with high water use, has been proposed as a solution to water scarcity. Because of the various decision-making factors, studies of interbasin water transfer projects have been presented as complex and difficult in the literature. In this paper, an optimum design for the capacities of the Behesht-Abad interbasin water transfer system, from the upstream Karoun basin to the Gavkhooni basin in central Iran, has been studied using a simulation-optimization approach in which particle swarm optimization (PSO) is coupled with the river basin simulation model, to find the optimum values for decision variables. In another approach, by use of multicriteria decision making (MCDM) and quantifying selected criteria in the source and target basins, the most beneficial scenario for water transfer is selected by prioritizing six possible alternatives. Results obtained by both PSO-MODSIM and MCDM approaches are close to each other and show that under conditions consistent with recent drought years, the optimum capacity of the water transfer tunnel is obtained to be a maximum of 45% of the capacity under conditions consistent with long-term historical discharges of the rivers.

Reducing nutrient loadings in urban areas is important for water quality improvement programs in many watersheds. Urban nutrient loadings are expected to increase and become more variable under climate change (CC). In this study, a water quality simulation model (SWMM), land cover data layers, and mathematical programming models were used to compare costs of abating nutrient loads under CC in the Difficult Run Watershed located in Fairfax County, Virginia. Predicted costs of abating mean total nitrogen (TN), total phosphorus (TP), and total suspended sediment (TSS) loadings under current climate conditions were compared with those for CC under certainty with a Cost Minimization Model and under uncertainty with a Safety First Model. Total nitrogen loadings abatement had the highest cost followed by TP and TSS abatement in that order. Costs of controlling TP and TSS increased with CC, whereas there was little change in TN control costs. Introducing uncertainty of loadings caused control costs to increase substantially for all three pollutants. The preferred pollutant control strategy was urban stream restoration. Policy makers seeking to meet water quality goals over a multiyear horizon should consider front-loading supplemental best management practices (BMPs) to offset the changes in nutrient loadings predicted for CC.

This paper investigates the potential of unsteady flow modelling for the simulation of remote real-time control (RTC) of pressure in water distribution networks. The developed model combines the unsteady flow simulation solver with specific modules for generation of pulsed nodal demands and dynamic adjustment of pressure control valves in the network. The application to the skeletonized model of a real network highlights the improved capability of the unsteady flow simulation of RTC compared with the typical extended period simulation (EPS) models. The results show that the unsteady flow model provides sounder description of the amplitude of the pressure head variations at the controlled node. Furthermore, it enables identification of the suitable control time step to be adopted for obtaining a prompt and effective regulation. Nevertheless, EPS-based models allow consistent estimates of leakage reduction as well as proper indications for valve setting under network pressure RTC at a much smaller computational cost.

Partitioning water distribution networks into district metered areas (DMAs) is a challenge for water utilities due to the complexity of network topology, especially for large-scale and highly looped water supply systems. This paper presents a novel approach, using complex network theory and multiobjective optimization, for efficiently partitioning of water distribution networks. In this approach, a water distribution network is first mapped on to a weighted undirected graph, and its strength is measured by an extended modularity by a random walk strategy. Then, the Louvain algorithm is employed for network partitioning based on the modularity. Finally, boundary pipes between DMAs are determined by applying an evolutionary algorithm to minimize the number of boundary pipes and maximize the network pressure and water age uniformity. The approach has been tested on a real-world distribution system to demonstrate the effectiveness of the method. The results indicate that the method is effective at partitioning the network into DMAs with a similar pressure and water age.

This paper presents a procedure for sampling the most representative contamination events in the framework of optimal sensor placement with two objective functions to be minimized, namely, sensor redundancy and contaminated population. Compared to other sampling methods present in the scientific literature, it is based on practical considerations of network topology and operation. This aspect confers upon the procedure lightness from a computational viewpoint. Sampling was carried out on four variables, namely, injection location, starting time, mass rate, and duration. The injection location was sampled as a function of distance from the source based on network connectivity. A single starting time was selected inside each network operating phase, during which pipe-water discharges were quite constant. One single mass rate was selected as significant, considering the linearity of the contaminant advection-reaction equation under specific conditions. In fact, owing to this linearity, the results of quality simulations associated with a generic mass rate can be easily derived from those associated with the selected mass rate. Finally, a single (small) duration was sampled. In fact, a long duration event can be simply regarded as the sum of various short-duration events. The procedure was tested in two case studies of different complexity. As evidence of the sampling effectiveness, the results of the optimal sensor placement did not vary significantly when the sampled contamination events were used inside the optimization, instead of the totality of possible contamination events.

Integrated urban water management (IUWM) considering alternative water supply options is attracting increasing attention from water resources managers due to its efficiency and flexibility in addressing water scarcity problems. Adelaide, the capital of South Australia, is an example of a city where water supply security has come under increasing pressure due to population growth, climate variability, and climate change, as well as emerging environmental needs. In order to address this issue, the South Australian government has committed to implementing IUWM principles through a number of actions including an initiative to integrate alternative water source options for metropolitan Adelaide, called the Urban Water Blueprint. This study is part of the optimal water resources mix (OWRM) project, which was initiated by the South Australian government through the Goyder Institute for Water Research to inform the development of the Urban Water Blueprint. In this study, a multiobjective optimization-based IUWM approach is applied to Adelaide to identify its optimal water supply portfolios and, in turn, to inform policy aimed at prioritizing the development of different types of potential water resources. These sources include traditional water sources, such as surface water from reservoirs and rivers, as well as alternative water sources, such as desalinated sea water, harvested stormwater, and reclaimed wastewater. In addition to the traditional objectives of minimizing economic cost and energy consumption (or the associated greenhouse gas emissions) and maximizing reliability, the impact of stormwater and wastewater discharge on receiving waters is also considered. The results demonstrate that for Adelaide, the optimal mix of sources contains water from traditional surface water sources, harvested stormwater, and reclaimed wastewater. Traditional surface water is a low-cost and low-energy source; reclaimed wastewater is likely to have significant environmental benefits in the long term.

A stochastic optimization model for urban drainage design (SODD) was proposed in this study to help analyze the trade-off between investment and acceptable flood damage in urban drainage designs considering effects of both uncertainty and climate change. The simulation model [i.e., Storm Water Management Model (SWMM)], driven by designed rainfall either from existing intensity-duration-frequency (IDF) curves or future ones subjected to climate-change conditions, was used to simulate flooding scenarios. The generalized uncertainty analysis estimation (GLUE) and Monte Carlo simulation methods were employed to quantify the system reliability, which was adopted in the constraints of the optimization model. The results from a case study showed that the deterministic optimization was computationally efficient, with no randomness encountered in hydrological simulation, although its solution was hardly reliable in achieving the target for flood mitigation. The stochastic version, on the other hand, could offer richer information on system reliability and help managers make a more robust decision. The results also revealed that the rainfall extremes under the impact of climate change could significantly affect system investment. The proposed method is advantageous in facilitating cost-effective planning toward a risk-based drainage design in light of various complexities.

As watersheds are urbanized, the amount of impervious surfaces will be increased. As such, water infiltration will be reduced, and the volume of surface runoff will be increased. By retaining stormwater, best management practices (BMPs) are used to mitigate the hydrologic effects of urbanization. Using the Ludlow watershed in northern Kentucky as a case study, the main objective of this paper was to identify the most cost-effective arrangement of BMPs in reducing surface runoff. A simulation program was employed to model the hydrologic conditions in the Ludlow watershed under the current and future climate conditions and to identify the most cost-effective BMP arrangement. The results show that the simulation program is an effective tool in simulating a small watershed. Indeed, BMPs are instrumental in reducing surface runoff even when the future climate becomes drier. The most cost-effective BMP arrangement is to install two infiltration trenches and one bioretention in the watershed. These findings can be useful in watershed management in areas with similar hydroclimatic conditions.