Journal of Water Resources Planning and Management

Water infrastructure-intensive organizations should incorporate sustainability principles when making decisions on infrastructure investments to ensure the long-term resilience of mission-critical equipment and components. A water efficiency evaluation framework to inform infrastructure investments is discussed and applied to three federal campuses. The methodology considered emphasizes the iterative process between data analysis and decision-making; evaluates cost-sharing solution alternatives when making final recommendations; considers both internal and external stakeholder perceptions of project outcomes and future planning; and makes explicit government and community preferences when evaluating projects. Case study findings underscore condition evaluations for infrastructure that are critical to setting a baseline for system performance and determining desired potential upgrades and sustainment strategies. Such a holistic approach has demonstrated effectiveness for understanding, classifying, and recommending innovative water asset solutions that are necessary for the public sector to consider in today’s complex, modern planning environment.

The 2013 Boston Marathon attack demonstrated the complexity of real-time response to such occurrences. The procedures used by the Federal Bureau of Investigation (FBI) at the Boston event to cluster and mitigate the event consequences inspired the development of a method for real-time response to contamination intrusion events in water distribution systems. Similar to the Boston attack, in the event of water contamination events, the shortage of real-time data, coupled with uncertainties in network topology, water consumption, and the event characteristics, set the ground for the need for a real-time response strategy. A methodology that divides the network into separate monitored zones or clusters, often referred to as district metered areas (DMAs), is widely used to cope with water-related problems such as leakage reduction or pressure control. In this study, a water-quality-related criterion called infection delay time (IDT) was introduced to dynamically cluster the network in case of a contamination event. The IDT parameter was combined with the available system resources to meet water quality goals. A coupled DMA-IDT method was developed for real-time response to contamination events. The setup of the DMA-IDT is described and demonstrated on water distribution systems of various complexities.

Using municipal wastewater effluent as a feedstock in algae cultivation is a promising approach for increasing the commercial viability of algal biofuel production. However, differences in site-specific characteristics at municipal wastewater treatment plants (WWTPs) could drive tradeoffs between maximizing the profitability of algae production and minimizing the cost of meeting water quality standards. A complicating factor is how water quality regulations are enforced, namely the potential presence of nutrient trading markets that would monetize removal of nutrients from wastewater effluent. This study develops an analytical framework for optimizing the siting of an algal biofuel production facility within a network of WWTPs. A combined life cycle assessment (LCA) and techno-economic analysis (TEA) model of an algal biofuel production facility is integrated with a simplified watershed model. An evolutionary algorithm is used to identify optimal sites for algal biofuel production and explore financial tradeoffs for algae biofuel producers and wastewater treatment plants. This analytical framework is then applied to a high-priority, impaired watershed in North Carolina, the Neuse River Basin.

Recent years have witnessed a rise in the frequency and intensity of cyberattacks targeted at critical infrastructure systems. This study designs a versatile, data-driven cyberattack detection platform for infrastructure systems cybersecurity, with a special demonstration in the water sector. A deep generative model with variational inference autonomously learns normal system behavior and detects attacks as they occur. The model can process the natural data in its raw form and automatically discover and learn its representations, hence augmenting system knowledge discovery and reducing the need for laborious human engineering and domain expertise. The proposed model is applied to a simulated cyberattack detection problem involving a drinking water distribution system subject to programmable logic controller hacks, malicious actuator activation, and deception attacks. The model is only provided with observations of the system, such as pump pressure and tank water level reads, and is blind to the internal structures and workings of the water distribution system. The simulated attacks are manifested in the model’s generated reproduction probability plot, indicating its ability to discern the attacks. There is, however, need for improvements in reducing false alarms, especially by optimizing detection thresholds. Altogether, the results indicate ability of the model in distinguishing attacks and their repercussions from normal system operation in water distribution systems, and the promise it holds for cyberattack detection in other domains.

Urban water supply networks are important infrastructure to ensure the daily water consumption of urban residents and factories. However, the scope of leakage detection is large and inaccurate using the traditional leakage-detection method based on a sensitivity matrix of the nodal flow. Therefore, this paper proposes a novel leakage-detection method based on a sensitivity matrix of the pipe flow. The sensitivity matrices regarding the pipe flow to nodal pressure and pipe flow are deduced. Then, the least-square method based on the sensitivity of the pipe flow is used to fit the actual leakage state of the pipeline network. Moreover, the leaking pipeline is determined by using the fitting residuals of each pipeline. Finally, the proposed method is applied to fit the leakage detection of water distribution systems. Compared with the traditional leakage-detection method, the results show that the proposed method is more accurate and effective in locating the leaky pipe and improving the utilization rate of water resources.

In water distribution systems, pumps are used for supplying water from low points to elevated tanks that supply the network’s demands. The pumps are operated in different ways that could be distinguished by the complexity of the required control system. Such control systems range from pressure and time-based controls, through simple fixed ON-OFF trigger levels (e.g., a bang-bang controller) to complex online pump optimization schemes based on water demand predictions [e.g., the model predictive controller (MPC)]. In this study, we propose an off-line optimization method that utilizes dynamic trigger levels for pump operations. More specifically, these trigger dynamics are optimized according to electricity tariff structure, pump operation conditions, and long demand series in order to allow a more robust operation. We also provide a multiobjective analysis for the optimization problem and analyze the impact of different objectives on the obtained solution. In addition, the methodology is also demonstrated on real-world data.

Optimization modeling can reveal promising multiperiod schedules for adapting to deeply uncertain changes in flooding. We contribute a parsimonious optimization model (mixed integer program) that adjusts the efficacy of property-scale adaptation measures (first-floor elevation, wet floodproofing, permanent retreat, insurance) for different floodwall investments and insurance incentives. After minimizing expected flood-control and damage costs for individual scenarios, we identified adaptation portfolios that minimize underdesign and overdesign regrets under a deeply uncertain future. A near-optimal solutions algorithm also identified diverse solutions with different multistakeholder tradeoffs. A stylized example showed that, when mild damage is tolerated, portfolios combining smaller floodwalls, wet floodproofing of basements, and moderately elevated manufactured (mobile) homes can be more robust to climate uncertainty than larger floodwalls alone. Yet, near-optimal solutions demonstrated that larger floodwalls without any property-scale measures are also feasible. Insurance incentives targeting property-scale measures (elevation, wet floodproofing) suited for permanent homes discourage municipal floodwall investments and force owners of manufactured homes to retreat. The results motivate further research on wet floodproofing, retreat financing, and insurance-based adaptation incentives.

Water distribution systems (WDSs) are among the most essential infrastructure systems for the sustenance of societies. Therefore, their continued reliability is of utmost importance. However, the reliability of WDSs decreases over time due to aging and deterioration of components, especially pipelines. Metallic pipes are subject to external and internal corrosion overtime, which can significantly affect their mechanical strength and hydraulic performance and, consequently, WDS reliability. Existing research on system reliability is typically based on statistical failure prediction of pipelines, which, however, typically assumes a constant failure rate, thereby ignoring time-dependent strength deterioration due to corrosion. This paper proposes a framework for modeling the time-dependent reliability of WDSs with cast iron pipes considering both mechanical and hydraulic reliabilities. Time-dependent failure of pipelines is evaluated through a fragility analysis that considers the decrease of wall thickness over time due to corrosion. The impact of internal corrosion on hydraulic performance is also accounted for with a time-dependent roughness model. A notional WDS is used to demonstrate the proposed framework. The results of the case study show that pipe corrosion can significantly impact the reliability of a WDS as it ages. The proposed framework links the deterioration of pipeline strength and hydraulic performance with system reliability and can, therefore, form the basis of a reliability-based plan for maintenance and rehabilitation.

In recent years, a number of new water distribution system (WDS) solution methods have been developed. These methods have been aimed at improving the speed and reliability of WDS simulations. However, to date, these methods have not been benchmarked against each other in a reliable way. This research addresses this problem by using a newly developed software platform as a fair basis for a detailed comparison of the performance of these methods under different settings. In this work, efficient implementations of four solution methods, namely the global gradient algorithm (GGA), the GGA with the forest-core partitioning algorithm (FCPA), the reformulated co-tree flows method (RCTM), and the RCTM with the FCPA, are compared using eight case-study benchmark networks containing between 934 and 19,647 pipes and between 848 and 17,971 nodes. These simulations were carried out under both a once-off simulation setting and a multiple simulation setting (such as occurs in a genetic algorithm). Timings for these benchmark runs are decomposed into stages so that the performance of these methods can be easily estimated for different settings. The results of this study will help inform the choice of solution methods for given combinations of network features and given design settings.

One of many important features of blue-green infrastructure is the ability to lower flood risks by detention of stormwater. This ability of flood risk reduction has for the first time been evaluated with empirical data in this study. In 2014, Malmö, Sweden, was hit with extreme precipitation corresponding to a return period of 50–200 years that led to severe pluvial flooding. This and other large events presented the opportunity to evaluate the efficiency of the 15-year-old stormwater system retrofit in the Augustenborg area (30 ha). Blue-green infrastructure is widely promoted for climate change adaptation, making this unique case important in the discussion of the capabilities of the related technical solutions. The long-term trends showed less flood damage in Augustenborg than in similar neighborhoods that have conventional sewer systems (combined or separate), indicating a direct effect of the retrofit with stormwater control measures. Even though a few properties were flooded in Augustenborg, it was shown that the retrofitted stormwater system performed successfully during the extreme event in 2014.

Unsustainable groundwater use has led to the lowering of groundwater levels and the degradation of groundwater-dependent ecosystems worldwide. Integrated hydrologic-ecological-economic models have been developed to simulate and optimize the coupled human and groundwater systems, and address the issue of unsustainable groundwater use. However, a lack of understanding of the heterogeneity of groundwater users undermines the performance of the integrated models. In this paper, an agent-based model is developed using a two-stage optimization strategy with the goal of optimizing the decision making of heterogeneous farmers on crop choice and groundwater irrigation. The performance of the optimization strategy is evaluated under the influence of four behavioral factors. The results illustrate that the optimization strategy can lead to higher crop profits or a slower rate of groundwater depletion in comparison with the observations, but does not necessarily guarantee the optimal solution in balancing these two objectives. In order to achieve sustainable groundwater use, the roles that behavioral factors play in farmers’ decision making need to be better understood, and better accounted for in groundwater policy.

Municipalities in the Kingdom of Saudi Arabia (KSA) are putting serious efforts into reducing the water losses to around 8% (i.e., national benchmark) of supplied water through active leakage control (ALC). In this research, a framework is conceptualized and developed to establish economic level of leakage (ELL), keeping in view the specific conditions of arid regions. In general, water loss control actions, including ALC, passive leakage control, pressure management, and infrastructure asset management, are performed by the municipalities up to the service connections until the cost of these actions becomes equal to the cost of the water lost. For the explicit scenario of KSA, the framework also investigates the possibilities of water losses beyond the property line where water is intermittently supplied for a certain duration in a week and stored in underground tanks to ensure a continuous supply within the house. Night flow analyses were conducted to establish the relationship between pressure and water losses. The framework is implemented on a case study in the Alryan neighborhood of Buraydah (Qassim, KSA) to evaluate its practicality. Scenario analyses are conducted to appraise the economic viability of different management actions for establishing ELL. The study results reveal that conventional ALC can reduce the infrastructure leakage index from around 20 to 7.28, and an additional 43% decrease can be economically achieved by implementing pressure management and control measures on the homeowner side. Environmental valuation analysis demonstrates that upgrading the effectiveness of ALC with a small increase in water prices could further improve the ELL.

Home to one of the world’s most biodiverse and productive freshwater fisheries, the Mekong River basin provides food and economic security to some 60 million people. The extensive hydropower development planned for the river basin has the potential to degrade this ecosystem. The basin’s potentially most impactful and downstream-most proposed main stem dam, the 18-km-long Sambor Dam is to be located just upstream of critical nursery and fishery habitats of the Tonle Sap Lake and the Mekong Delta and just downstream of major spawning areas. We explore the potential to modify Sambor’s siting, design, and operation (SDO) to balance hydropower and ecological outcomes. Our results demonstrate that there are opportunities to achieve more balanced ecology–energy outcomes. We use probabilistic seasonal measures of fish life cycle processes, energy production, and sediment passage to explore alternative SDO options. We consider both ecological concerns and energy production on equal footing prior to any power purchase agreements or fixed designs for Sambor, which is a first among any of the world’s large dams. The Sambor Ecological Alternative (Sambor EA) dam considered in this study includes a combination of design and operational features to improve sediment and fish passage that do not exist at any of the world’s large hydropower dams. Yet Sambor EA still poses a significant risk to the Mekong fishery and the millions who depend on it, given the appreciable uncertainty surrounding its potential ecological outcomes. Our results emphasize the need to address ecological concerns in advance of signing power purchase agreements that would otherwise limit the site-specific and integrated SDO modifications needed to achieve them. Our results also emphasize the importance of, and challenges in, carefully defining ecological performance measures and criteria, as well as the importance of carefully sampling reservoir operation possibilities.