Journal of Water Resources Planning and Management

Residents often encounter water-quality issues in their drinking water systems. If these issues recur or persist, residents may, despite assurances of water safety from utilities, lose trust in the system and seek alternative drinking water sources, including bottled water. This erosion of trust can occur due to breakdowns in communication, perceptions of a utility handling an issue poorly, or misconceptions about the dangers of discolored water. This study analyzed trust as a triangular relationship between water provider, end user, and consequential action an end user takes regarding the use of tap water. We posited an interrelationship between the level of trust individuals put in a water system and how they interact with it. A survey deployed in 21 shrinking cities in November 2019 examined three questions of interest: (1) whether a water provider’s decisions are perceived to align with the best interests of the consumer, (2) whether the tap water provided is perceived to be of adequate quality, and (3) whether consumers feel the water provider promptly informs them of water-quality issues. We tested whether differences in individuals’ consumption of bottled water impacted different aspects of trust. We found that individuals using bottled water as their primary water source responded differently from individuals who do not. In other words, actions and end user interactions with infrastructure are in fact related to trust toward water purveyors. Trust appears to be significantly influenced by sociodemographic parameters, including the ability to pay water bills and the number of water-quality issues one has experienced. In shrinking cities, in which one challenge is that low water use can adversely affect water quality, utilities may encourage residents to use more tap water by implementing strategies or policies that build trust with certain demographics.

Though the magnitude of future rainfall is important in most water resources applications, many applications require its occurrence/nonoccurrence rather than its magnitude such as in agricultural systems management, drought management systems, regulated deficit irrigation for various crops, short-term municipal water demand modeling and management, and reservoir operation. The occurrence of rainfall is a classification problem that also affects day-to-day human activities and management. However, most of the work on rainfall forecasting is for rainfall magnitude, and very few studies on rainfall occurrence forecasting have been carried out in the past. Also, few artificial intelligence and machine learning techniques have been utilized in rainfall magnitude forecasting but not any work registered so far for forecasting rainfall occurrence using these methods. The proposed novel approach in this paper integrates two machine learning methods, artificial neural network (ANN) and decision tree (DT), which are capable of making rainfall occurrence forecasting comprehensible and accurate. For this purpose, the rules have been extracted by generating a DT using the input-output data obtained from an ANN rainfall occurrence forecasting model. Daily climatic data are employed to illustrate the methodology developed in this study. The obtained results show that during training, ANN models learned a fixed set of rules for rainfall occurrence forecasting. The obtained rules are simple and can be used as a tool for rainfall occurrence forecasting.

This article presents a novel response methodology for the operational recovery of a drinking water network after an incident causes an interruption of service. The proposed optimization-based methodology allows computing the optimal set of interventions to be performed in order to mitigate, or even prevent, the impact of the incident on the network operation. Besides, a proof-of-concept scheme has been designed for the automatic generation of failure scenarios and the systematic implementation and validation of the proposed response methodology. Several results are presented to demonstrate the capability of the methodology to mitigate harmful incidents, as well as the performance improvements derived from the application of the obtained interventions.

Abstract

This study aimed to examine the fractal properties of the optimal hydraulic gradient surface (OHGS), a geometrical body that describes the way in which the available energy should be spent within a water distribution network to ensure the calculation of a minimum capital cost design. For this purpose, multiple benchmark and Colombian systems were optimized and then analyzed to compute the fractal dimension of the OHGS and of the underlying structure of each network, which included the examination of randomly generated nonoptimal designs to recognize the differences in the fractal behavior of a least-cost and a more expensive solution. The results showed a dependency between the fractal properties of the OHGS and those of the topological structure, flow, and energy distribution inside the corresponding optimized network. Moreover, it was found that the degree of irregularity of the OHGS tended to be higher compared to a nonoptimal energy dissipation pattern. This suggests the applicability of the fractal analysis in optimization and operational improvement procedures.

Practical Applications

The design of a least-cost water distribution network, which refers to the process of calculating appropriate pipe diameters that ensure the fulfilment of water demands and reduce the required investment to a minimum, has been of interest due to its complexity and importance for the viability of water supply infrastructure projects. In this study, the inherent characteristics of a least-cost design were explored by involving fractal analysis, a novel technique that has been used to solve several problems in the management and operation of water supply systems. The results show that the hydraulic features of a minimum-cost water distribution network, analyzed by considering the behavior of pressure and water flow throughout the system, exhibit certain fractal properties that can be used to distinguish it from more expensive alternatives. These findings lead to the recommendation to use fractal analysis in prospective water distribution network planning and management applications, such as new design and operational improvement strategies. Furthermore, fractal analysis may be useful in identifying the proper hydraulic behavior of a water distribution network so as to maximize its reliability, water quality, and other desirable features that improve its performance and level of service.

Accurate forecasting techniques for a stochastic pattern of water demand are essential for any city that faces high variability in climate factors and a shortage of water resources. This study was the first research to assess the impact of climatic factors on urban water demand in Iraq, which is one of the hottest countries in the world. We developed a novel forecasting methodology that includes data preprocessing and an artificial neural network (ANN) model, which we integrated with a recent nature-inspired metaheuristic algorithm [marine predators algorithm (MPA)]. The MPA-ANN algorithm was compared with four nature-inspired metaheuristic algorithms. Nine climatic factors were examined with different scenarios to simulate the monthly stochastic urban water demand over 11 years for Baghdad City, Iraq. The results revealed that (1) precipitation, solar radiation, and dew point temperature are the most relevant factors; (2) the ANN model becomes more accurate when it is used in combination with the MPA; and (3) this methodology can accurately forecast water demand considering the variability in climatic factors. These findings are of considerable significance to water utilities in planning, reviewing, and comparing the availability of freshwater resources and increasing water requests (i.e., adaptation variability of climatic factors).

Strong financial and operational underpinnings reduce risk to drinking water provision in the face of changing population, climate, and regulations. Because responsibility for oversight of drinking water systems in the United States is commonly divided across state agencies or subagencies, decision makers often are unable to assess a water system’s overall condition. Understanding correlations among different dimensions of performance is essential for assessing a water system’s ability to respond to stressors. We present a network-based method for characterizing multiple dimensions of a water system’s operations, combining data from several sources to describe the relationships between the dimensions within and across systems. Applying this method to North Carolina community water systems, we find that water systems face tradeoffs in balancing water affordability against the capacity to deliver drinking water reliably over the long term. Our approach can distinguish isolated water system vulnerabilities from those that signal more systemic challenges and help agencies responsible for water system compliance, funding, and planning coordinate their activities.

In situations of fluctuating water availability, the optimal reservoir operation policy, resulting from classical models, fails to be implemented for political reasons. This paper proposes a collaborative modeling approach to define the hedging rules of a two-basin reservoir system, in which the acceptable risks, rationing ratio, and reasonable transfer values are defined by the water allocation agents for different phases/drought states. An optimization algorithm is then applied to determine a politically viable hedging operation policy. The methodology showed good results for the Jaguaribe–Metropolitan system in Brazil, and the resulting policy could be applied to the real operation, as the simulated rationing frequencies were close to those defined by the managers’ consensus. The proposed methodology guarantees a politically viable alternative with conflict management possibilities. However, the performance of the resulting hedging rules depends on the negotiation capacity and tacit knowledge of the stakeholders. The proposed approach is a good alternative when the implementation of the mathematically optimum policy fails.

There is now evidence that many long-standing international plumbing codes significantly overestimate the peak water demand in multilevel residential buildings. The overestimation of this design value may have adverse effects on construction cost, energy consumption, water quality, and safe operation. This research aims to assess the performance of the current Australian and New Zealand cold water plumbing standard in peak demand design for multilevel residential buildings. A literature review was conducted on the international development of residential water demand estimation models. The Australian practice of peak demand design is compared against selected international plumbing codes and some newly proposed approaches using a fixed apartment layout as a benchmark. Following this, the paper compares the actual water demand of four Australian multilevel residential buildings with the designed peak demand (99th percentile flow) from the Australian and New Zealand standard and selected international plumbing codes. Results show that the adjusted 99th percentile flow rates (adjusted from raw measurements to count for the impact of sampling interval) are only 23%–28% of the nominal design values from the Australian and New Zealand standard. None of the international peak demand design standards considered in this research can be readily applied to Australian multilevel residential buildings. Research needs are identified, including the impact of the sampling interval, the practical definition of the 99th percentile flow, the implications of reduced pipe sizes, and other limitations in current plumbing system design practices. This research serves as an informative reference for researchers, industry, and regulatory bodies working on improving their existing plumbing design standards.

Variations in water fixtures and appliances coupled with different routines and preferences of users result in high levels of variability in residential water consumption. This study assessed differences in residential water use in terms of the timing and distribution of end uses across residential properties. Past studies analyzing residential end use of water have collected data for periods of time that may prevent the observation of temporal variations in indoor and outdoor water use practices. We examined indoor and outdoor residential water use at the household level by analyzing four to 23 weeks of 4-s resolution water use data at 31 single family residential properties in Logan and Providence, Utah, between 2019 and 2021. We identified and classified end uses of water for each property and analyzed monthly water use records to understand how water use varied for users at different levels of consumption. Our results indicated that indoor water use is influenced more by frequency of use than by the characteristics of water fixtures. At sites with longer data collection periods, indoor water use volume, timing, and distribution across end uses varied across homes and across weeks for which we collected data, indicating that short duration data collection intervals used by past studies may not have adequately characterized these variables. The paper presents opportunities to conserve water indoors and outdoors by adopting more efficient fixtures (particularly toilets) and promoting conservation behaviors. All the data and tools used in this study are freely available online for reuse.

Drinking water utilities are vulnerable to both human-caused and natural disasters that can impact the system infrastructure and the delivery of potable water to consumers. Analyzing system performance and resilience can help utilities identify areas of high risk or concern, understand the impacts on consumers, and evaluate response actions during disasters. In this case study, the Water Network Tool for Resilience (WNTR) was used to investigate the performance and resilience of a drinking water system in New York during increased demands due to firefighting, pipe damage, and loss of the source water emergencies. This case study introduced a new combined performance index (CPI) resilience metric, which served to quantify system resilience as a ratio of system performance during an emergency to normal operations. The results revealed that this drinking water system was able to maintain service to most of the consumers during these emergencies due to high redundancy within the system, and conservation efforts extended water service for an additional 20 h. The analysis in this paper can be used by other drinking water utilities to understand their vulnerabilities and evaluate resilience-improving actions in similar disaster scenarios.

Sewage systems are built to carry contaminated wastewater from domestic discharge points to collection points for treatment. However, their capacity can be reduced by obstructions, displaced pipe joints, or broken pipes, creating abnormal hydraulic conditions. Wastewater overflows are a potential consequence of these abnormal conditions, which pose a direct threat to the environment and human health. This paper describes a permanent continuous monitoring system of a real sewage network using ultrasonic water level sensors for the purpose of blockage/choke detection, as installed in the suburb of Stonyfell, South Australia. From 62 available data sets collected over 1 year, two distinctive features of growing chokes were identified, including irregular peaks and durations that the water level remains irregularly high in the sewer maintenance holes. An early choke detection method was formulated based on the later feature, which continuously scans the near-real-time data to find time periods containing these abnormal water levels. Application of the methodology showed that the proposed method is effective in detecting possible chokes and overflow events before they occur. In most cases, the warning from the first detection is early enough to allow proactive maintenance attendance to be scheduled by the water utility.