Journal of Water Resources Planning and Management

Water utilities are urged to decrease their real water losses, not only to reduce costs but also to assure long-term sustainability. Hardware- and software-based techniques have been broadly used to locate leaks; within the latter, previous works that have used data-driven models mostly focused on single leaks. This paper presents a methodology to locate multiple leaks in water distribution networks employing pressure residuals. It consists of two phases: one is to produce training data for the data-driven model and cluster the nodes based on their leak-flow-rate-independent signatures using an adapted hierarchical agglomerative algorithm; the second is to locate the leaks using a top-down approach. To identify the leaking clusters and nodes, we employed a custom-built k-nearest neighbor (k-NN) algorithm that compares the test instances with the generated training data. This instance-to-instance comparison requires substantial computational resources for classification, which was overcome by the use of high-performance computing. The methodology was applied to a real network located in a European town, comprising 144 nodes and a total length of pipes of 24 km. Although its multiple inlets add redundancy to the network increasing the challenge of leak location, the method proved to obtain acceptable results to guide the field pinpointing activities. Nearly 70% of the areas determined by the clusters were identified with an accuracy of over 90% for leak flows above $3.0\mathrm{L}/\mathrm{s}$, and the leaking nodes were accurately detected over 50% of the time for leak flows above $4.0\mathrm{L}/\mathrm{s}$.

This paper presents a multistep approach for the rehabilitation of the deteriorated and intermittently operated water distribution network (WDN) proposed by the organizers of the joint WDSA CCWI 2022 Conference as the case study for the battle. In the rehabilitation, various interventions are considered with the final objective to improve the operation of the WDN in terms of hours of service to users and total volume supplied to meet their demands, including pipe and device (pump/valve) replacements, leak repairs, and extended period optimization of device settings. The multistep approach is proposed to tame the extremely large space of decision variables and includes the following steps: (1) subdivision of the WDN into main chain and district metered areas (DMAs), rehabilitation of (2) the main chain and (3) the DMAs while looking at the final year of the rehabilitation, (4) sequencing of the interventions, and (5) optimization of device settings. Compared to other methodologies in the literature, the main novelty and merit of the present approach consist of the way the rehabilitation interventions are selected, i.e., by using engineering judgment and by maximizing the flow capacity of the main chain and the global resilience–failure index in the DMAs.

We developed an integrated optimization program to design the release strategy for a dam, given a downstream flow target and considering medium-range ensemble forecasts of downstream tributary flows. A strength of the program is its ability to explicitly limit the risk of downstream flooding through chance constraints. Embedded in the program is an advanced hydrological ensemble prediction system (HEPS). Given the ensemble nature of the downstream flow forecasts (in that they comprise sets of individual scenarios), we formulated the chance constraints as discontinuous mixed-integer equations. This makes the integrated program nondeterministic polynomial-time hard (NP-hard) and thus, intractable to be solved by conventional mixed-integer programming methods based on branch-and-bound. Thus, to solve the program, we took a simplified but innovative approach—possible through exploiting certain simplifying aspects of the problem—where we solved first for the integer (binary) variables following a ranking mechanism, then the continuous variables using nonlinear programming. The results for a case study of Hume Dam and Lake Mulwala in the Murray-Darling Basin, Australia, demonstrates the efficacy of the integrated program and our simplified approach to solving it. The results show the integrated program is able to meet the optimization target when the natural flow from tributaries is low. The results also show that when that natural flow is high, the integrated program’s ability to meet the target to increase with the allowable risk of flooding. However, a higher allowable risk may lead to a higher possibility of flooding, depending on the problem specification. We recommend to run the integrated program on a continual basis because its results depend not only on the optimization for the current day, but also previous days. This study addresses a major need: the ability to use all information from an advanced HEPS, e.g., to limit risk in optimizing the operation of a mixed engineered-natural system, and with that, advances the use of ensemble hydrologic forecasts in water management.

The adequacy of existing water supply depends on a number of factors. These factors include water demand and its variations over time, the amount of water supplied on average, and the nature and types of the water supply alternatives available. A significant question with implications for all of these is whether the existing supply is sustainable in the long term. Answering this question becomes more important when demands are increasing to cater to rising human and animal populations and supply sources are changing due to increasing urbanization and a changing climate. This study presents a new basis for assessing water supply sustainability for regions that depend on multiple sources of supply. This new basis is defined using a multivariate water supply index attempting to join the various sources of supply into one. Water demand is ascertained not based on human needs but the water needs of growing vegetation. Use is made of traditional methods for assessing the adequacy of existing water storage using this multivariate supply and the associated demand, with the added consideration of any systematic decrease in the water supply that may be observed over time. This study uses a partly engineered semiarid basin to illustrate the proposed methodology. Upstream subbasins in this basin are anthropogenically unaffected and have natural vegetation demand and supply dependent on a single source (precipitation). Downstream subbasins, though, have demand dependent on the agricultural needs of the region and supply that is both natural and engineered through diversions from elsewhere. The water supply sustainability of the basin is shown to be dependent on the nature of demand and supply in each of the subbasins in focus. In general, the upstream basins are found to be sustainable according to the proposed index, whereas downstream subbasins are markedly unsustainable, requiring the introduction of a new water supply source or a reduction in the water demand for the region. The proposed method requires knowledge of all water sources applicable in a region, which include naturally occurring and engineered sources (such as diversions or groundwater pumping), while relying on remotely sensed vegetation estimates alone to quantify the applicable demand. As a result, it is possible to use this approach in most regions of the world that use water from a combination of naturally occurring and engineered water supply options and where water use is reflected through the vegetation sustained.

Accurate and well-categorized information on water supply, demand, consumption, and withdrawals is necessary for the assessment and management of water resources. In this context, the Water Accounting Plus (WA+) framework is a valuable platform for quantifying water flows. By utilizing remote sensing datasets, WA+ enables it to quantify water flows in a basin and compute hydrological processes while considering the impact of land use. To understand the water inflows, outflows, consumption, withdrawals, and storage variations of water resources, we applied the WA+ framework to a complex river basin, namely the Mahi River basin. Using blue and green water estimation, we segregated the irrigated and rainfed areas and computed the hydrological processes at the pixel level using the WaterPix model. We also calculated performance indicators to illustrate the state of water resources in the basin. Our analysis shows that the Mahi River basin is water-stressed and mainly relies on groundwater (GW) for irrigation. The average exploitable and available water flows from 2012 to 2020 were $34.07\mathrm{B}\mathrm{i}\mathrm{l}\mathrm{l}\mathrm{i}\mathrm{o}\mathrm{n}\mathrm{C}\mathrm{u}\mathrm{b}\mathrm{i}\mathrm{c}\mathrm{m}\mathrm{e}\mathrm{t}\mathrm{e}\mathrm{r}(\mathrm{BCM})/\mathrm{year}$ and $30.38\mathrm{BCM}/\mathrm{year}$, respectively, and the average outflow was $20.65\mathrm{BCM}/\mathrm{year}$. The average vertical recharge and withdrawal of GW were 17.47 and $21\mathrm{BCM}/\mathrm{year}$, respectively, while surface water (SW) withdrawal was very low and concentrated in only a few areas. According to the results of the flow and GW sheets, 95% of the utilized flow came from GW, indicating a high dependency on GW. A 25% depletion of water storage was observed during the study period. These results indicate that overexploitation of GW for irrigation and depletion of water storage are the main problems in the Mahi River basin. Our study can help local and national authorities to identify areas with poor water management practices and develop appropriate water management plans and schemes