Journal of Water Resources Planning and Management

Much research effort has been dedicated to the development of optimal strategies for rehabilitation and/or replacement of water mains. Some of the methods are intended for high-level planning of groups or cohorts of pipes, while others address low-level scheduling of individual water mains. This paper focuses on the latter aspect. An approach is proposed for the efficient scheduling of individual water mains for replacement in a short to medium predefined planning period and subject to various budgetary constraints. This approach also accounts for economies of scale considerations as well as harmonization with other known infrastructure works. A multiobjective genetic algorithm scheme is used as a tool to search a vast combinatorial solution space, comprising various combinations of pipe replacement schedules.

The implementation of local water recycling and reuse practices is considered as a possible approach to managing issues of water scarcity. The sustainable design and implementation of a water recycle/reuse scheme has to achieve an optimum compromise between costs (including energy) and benefits (potable water demand reduction). Another factor that should be taken into account is the influence of potential changes in climatic conditions to the scheme’s efficiency. These issues were assessed in this study using the urban water optioneering tool. Two water-recycling schemes, a rainwater harvesting and a combination of rainwater harvesting and local greywater recycling, were assessed. The trade-off between potable water demand reduction, capital/operational cost, and energy consumption of the two schemes was derived under three basic climatic conditions (oceanic, Mediterranean, and desert) using evolutionary optimization. Furthermore, the impact of changing climatic conditions on the suggested schemes was analyzed to assess the robustness of the proposed design choices to climatic changes. The results indicate that schemes that are efficient in their use of local greywater are less susceptible to changes in climatic conditions, while schemes based exclusively on rainwater harvesting are more susceptible to changes the more efficient they become.

Water deficits often occur during the drought season and may cause water conflicts among various water use sectors. The reservoir rule curve operation is commonly used to avoid extreme water shortage during droughts in Taiwan. When applying the rule curve operation, the water supply discounting ratio for different sectors implies a trade-off of water deficit impact among sectors. This study therefore develops a multiobjective water resource management model to evaluate the trade-off curve of water deficit impact between irrigation and public sectors to facilitate negotiation between the sectors for obtaining acceptable discounting ratios. The study uses the shortage index to assess water deficit impact. The proposed model integrates operating rules, the stepwise optimal water allocation model, and the convex hull multiobjective genetic algorithm to solve the multiobjective regional water allocation planning problem. The computed trade-off curve, noninferior solutions, provides relevant information to facilitate negotiating water-demand transfer. The results reveal that when decision makers prefer specified water use, the discounting ratio of another competing water use at the low buffer zone should be limited on the lower bound.

Urban flooding has become a very important and growing issue around the world. In order to maintain an acceptable performance of urban drainage systems, early rehabilitation plans must be developed and implemented. The allocation of funds to support rehabilitation works should be in a certain sense “optimal” in providing value for money. However, this is a highly demanding and not easily achievable task due to the multidimensional nature of the rehabilitation process, especially taking into account conflicting interests. In this respect, multiobjective optimization using hydrodynamic urban drainage models appears to be promising and more reliable than the traditional engineering approaches. Such optimization is used in this paper to evaluate urban drainage rehabilitation scenarios contrasting investment against flood damages. A small-scale rehabilitation problem is posed and solved. The approach has demonstrated the potential use and combination of multiobjective optimization and hydrodynamic models to analyze urban drainage rehabilitation, providing valuable information for decision makers.

Previous research has demonstrated that there are significant trade-offs between the competing objectives of minimizing costs and greenhouse gas (GHG) emissions for water distribution system (WDS) optimization. However, upon introduction of an emission trading scheme, GHG emissions are likely to be priced at a particular level. Thus, a monetary value can be assigned to GHG emissions, enabling a single-objective optimization approach to be used. This raises the question of whether the introduction of carbon pricing under an emission trading scheme will make the use of a multiobjective optimization approach obsolete or whether such an approach can provide additional insights that are useful in a decision-making context. In this paper, the above questions are explored via two case studies. The optimization results obtained for the two case studies using both single-objective and multiobjective approaches are analyzed. The analyses show that the single-objective approach results in a loss of trade-off information between the two objectives. In contrast, the multiobjective approach provides decision makers with more insight into the trade-offs between the two objectives. As a result, a multiobjective approach is recommended for the optimization of WDSs accounting for GHG emissions when considering carbon pricing.

A generic integrated watershed management optimization model was developed to efficiently screen a broad range of technical, economic, and policy management options within a watershed system framework and select the optimal combination of management strategies and associated water allocations for designing a sustainable watershed management plan at least cost. The watershed management model integrates both natural and human elements of a watershed system including the management of ground and surface water sources, water treatment and distribution systems, human demands, wastewater treatment and collection systems, water reuse facilities, nonpotable water distribution infrastructure, aquifer storage and recharge facilities, storm water, and land use. The model was formulated as a linear program and applied to the upper Ipswich River Basin in Massachusetts. Our results demonstrate the merits of integrated watershed management by showing (1) the relative efficacy and economic efficiency of undervalued or underutilized management options such as incentive pricing; (2) the value of management strategies that serve several functions such as the benefits of increased infiltration for meeting both storm water and water supply management objectives; and (3) that both human and environmental water needs can be met by simultaneously implementing multiple diverse management tools, which in this case study led to achieving 70% of the recommended in-stream flow with only 25% decrease in net benefits.

This paper presents a phosphorus budget and modeling case study for Big Platte Lake Michigan and the Platte River watershed. These analyses are a necessary component of a credible total maximum daily load (TMDL) for Big Platte Lake and may be more broadly applicable to similar systems and other water quality management issues. A calibrated Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) model is used to simulate total phosphorus loads from the watershed. A nonsteady state lake model is developed to predict total phosphorus concentrations in both the water column and the sediments. Temperature and dissolved oxygen models are used to predict the anoxic periods in the lake hypolimnion to facilitate calculation of the internal phosphorus loading due to sediment release. Following calibration, the models were used to determine allowable total phosphorus loads for Big Platte Lake for typical hydraulic conditions. Current measured total phosphorus loads exceed model calculated allowable loads. Therefore various nonpoint remediation alternatives were evaluated as a means to reduce the excess loading. The credibility of the analyses was enhanced because of the availability of laboratory measurements of sediment phosphorus release rates and an extraordinarily comprehensive database of current and historical lake and tributary water quality measurements.

If a chemical or biological agent is released into a water distribution system, sensors that are installed in the pipe network may detect the contamination as it travels through the system. To minimize the adverse impact of the contaminant release, the source must be characterized to determine the extent of the contamination and to remediate the contaminated area. We present a backward modeling approach that uses the data collected by the sensors to obtain probability density functions that describe the random time in the past that the observed contamination was at a particular upgradient position. These probability density functions can be used to identify the source node and release time. The approach is developed for steady flow conditions with known system demands and for a single, instantaneous source of contamination. Using a hypothetical water distribution system and release scenario, we demonstrate that the backward model is an efficient and effective approach for identifying the source node and the release time.

Several modern multiobjective algorithms are compared with respect to the biobjective optimization of water distribution systems’ design, considering the objectives of cost minimization and reliability maximization. A new unbiased algorithmic comparison strategy is suggested using hypervolume convergence. A recent hyperheuristic named AMALGAM, which dynamically combines the strengths of multiple metaheuristics, is applied to this problem for the first time, demonstrating superior performance. The shortcomings of a novel multiobjective greedy algorithm are also demonstrated.

A physics-based, distributed hydrologic model (Vflo) was used to evaluate the effects of urbanization and detention storage on watershed stream flows with grid cells as small as $0.09{\text{km}}^2$ (22 acres). The analysis was performed for the Little Cypress Creek watershed in Houston, Texas. Hypothetical development and flood mitigation scenarios in the upstream, midstream, and downstream portions of the creek were analyzed for their impacts on peak flows for the 100-year design storm. Local ponds and regional reservoirs were compared for their ability to bring downstream flows back to existing conditions at all points along the creek. Analysis showed that downstream flows would be most effectively mitigated when storm water detention volumes and release rates are imposed with an awareness of locations relative to watershed headwaters or a referenced outlet point. This is in contrast to many existing policies that are uniformly applied across a watershed.