Journal of Water Resources Planning and Management

The Battle of Water Networks District Metered Areas (BWNDMA) was the latest of the Battle of Water Networks competition series held at the 18th Water Distribution Systems Analysis Conference (WDSA 2016) as part of ASCE’s Environmental and Water Resources Institute (EWRI) stand-alone conferences in Cartagena, Colombia in July 2016. In these competitions, the main objective was to address a specific problem related to water distribution systems (WDS) regarding how to optimize the design and operation of the system’s main components. This time, the competition was focused on the challenge of WDS network sectorization, that is, determination of the new district metered areas (DMAs) for an existing network. Design requirements involved constraints related to costs, pressure uniformity, and water quality. Changes in valve and pump operations were needed to supply demands at adequate pressures and acceptable water quality for the given supply scenarios: a wet season and a dry season with water shortages. Seven teams from different parts of the world participated in the BWNDMA and presented their solutions at a special session during the 18th WDSA. This article summarizes the BWNDMA teams’ approaches, outcomes, and learned lessons for solving the challenging stated problem. An analysis of some of the decisions that were taken is presented; for instance, some teams ignored the demand similarity criterion, the water age criterion, the pressure restrictions, or the constraints in the water rate that could be extracted from sources. The approaches developed in the BWNDMA represent the state-of-the-art with respect to the analysis of hydraulic conditions in DMAs of real-world water distribution networks for which it is mandatory to make efficient use of available water resources.

Hedging rules for hydropower operation provide optimal decisions to hedge against extreme system loss from an energy shortfall in the future at the price of a small current loss. Aiming at determining optimal end-of-year carryover storage decisions, this paper develops a hedging model for hydropower operation and proposes a corresponding numerical solving procedure to derive optimal hedging rules. The overall solving procedure involves generating possible future inflow sequences, optimizing the hedging model with nonlinear programming (NLP) technique, and plotting the hedging rule with the optimal results in condition–decision forms. Results from a case study demonstrate the correctness and feasibility of the proposed model and procedure. Performance comparison between the generated hedging rule and standard operating policy (SOP) reveals that (1) in a dry period, hedging rules could provide optimal end-of-year carryover storage, which helps achieve more benefit and suffer less system loss compared with SOP; (2) forecast uncertainty greatly affects the operation for it reduces the benefit and increases the system loss; and (3) when water is abundant, hedging becomes trivial and the generated operating rules provide similar benefit and system loss compared with SOP. The proposed procedure and the implications could be applied to determine more rational end-of-year carryover storage decisions for hydropower operation considering inflow uncertainty.

The alteration of a watershed’s hydrologic response due to urban development, population growth, global warming, and sea level rise have increased the frequency and intensity of floods. In order to cope with the new challenges in coastal flood management, many efforts were made after Superstorm Sandy. These efforts call for better understanding of flood hazard, better understanding of the operation of infrastructures in a resilience context, ways to mitigate hazard impacts, rebuilding efforts by adaptive design, and developing a unified scale of resilience for measuring performance. In this paper, attempts have been made to address implementation of these measures. The main purpose of this study is to improve resilience in infrastructures, particularly wastewater-treatment plants (WWTPs), which play a pivotal role in urban lifelines in New York City. To do this, first, a flood inundation map has been generated to evaluate the current response of the study area to a 100-year flood and determine the flood inundation depth at WWTPs. Next, a multicriteria decision-making (MCDM) approach was utilized to quantify the resilience index as a system performance indicator. Afterward, two approaches based on resilience-improving measures have been considered to improve this index. The first approach is to provide redundancies between WWTPs to make a platform for WWTPs’ cooperation to move the sewage between them. The second approach is to implement adaptive hazard mitigation practices such as best management practices (BMPs) based on a proposed framework of a key initiative in New York City. In order to prioritize various groups of BMPs, five methods of flood mitigation practices, namely resist, delay, discharge, store, and retreat, have been ranked using experts’ opinions in a MCDM framework. Thereafter, resilience improvements based on the two aforementioned approaches have been compared by considering financial resources allocation to each WWTP, and the most efficient alternative solutions have been chosen. The methodology outlined in this paper can be utilized in other urban coastal settings to plan for better flood preparedness.

Water scarcity in arid and semiarid regions of the world is increasing rapidly due to multiple factors, exacerbating competition over alternative water uses. This is especially relevant in the case of so-called closed water bodies, such as the Guadalquivir River Basin in southern Spain. This study tests the environmental Kuznets curve (EKC) hypothesis for urban water uses (i.e., residential and services) based on a wide data set of 336 municipalities in the Guadalquivir Basin, for the period 2005–2014. The analysis includes other water use determinants, such as population density, age, educational level, employment, electricity consumption, and urbanization, which might impact urban water use. The results indicate that income is a main factor and has a positive effect on water use, since a growing water elasticity, with respect to income, is observed. Therefore, no EKC pattern is detected in our case study. This has enormous policy implications for the management of the river basin, as the river basin is hydrologically closed, with all available water resources allocated, and competition over alternative uses is expected to increase.

Decision analysis methods provide opportunities to explore alternatives for drinking water resources in impoverished, rural regions of developing countries. With varying success, southwestern Bangladesh communities currently use multiple drinking water sources, including rainwater harvesting, ponds, pond sand filters, managed aquifer recharge (MAR), and tubewells. This study uses a variety of multicriteria decision analysis (MCDA) methods to assess the probable success of these drinking water sources based on various technical, economic, social, and environmental factors. Data include an assortment of physical and social sources including focus group interviews, surveys, and water quality measurements. Additionally, the MCDA methods (multiple attribute value theory, analytic hierarchy process, ELECTRE I, and ELECTRE III) are informed by preferences from three stakeholders—locals, nongovernmental organizations, and environmental science academics—to ensure proper weighting of criteria for success. Across all MCDA methods, we find that rainwater harvesting is the most likely to succeed as a reliable drinking water source in the region. Conversely, MAR is the least preferred alternative. Sensitivity analyses suggest a robust ranking order that is relatively insensitive to model parameters, including water source performance score and stakeholder weighting, across all criteria categories. This case study demonstrates how decision modeling and alternative assessment can be the first step to reach sustainable solutions in complex water management problems.

Despite decades of operational use, stochastic dynamic programming (SDP) is still a popular method for solving hydropower management optimization problems. From an operational perspective, there are many advantages to using this type of method: it provides a feedback operating policy that can be used for simulation purposes, marginal values of water stored in reservoirs are easy to compute, and it is relatively simple and easy to understand. However, for systems with more than two or three reservoirs, some issues arise that must be resolved in order to create efficient and fast operational software. This paper presents a case study which solved a problem of four reservoirs by sampling SDP (SSDP). Several improvements were proposed, such as using parallelization techniques, efficient discretization of the state space, and piecewise linear approximation of the water value function utilizing a strategy similar to Benders cuts as in stochastic dual dynamic programming, to build fast, efficient, and robust SSDP operational software. Program implementation details and numerical results were presented for a real hydropower system owned by Rio Tinto in Canada.

Commonly used approaches for studying water affordability in developing countries tend to focus on households that pay for their water supply (revealed affordability). A major problem of this approach is that it neglects the significant portion of households in these countries that use free water sources. Given that these free sources often are of questionable quality, we provide an alternative approach, whereby hidden affordability for households that use free water sources is revealed by using the average price of purchased water as a proxy for what these households would have to pay for good quality water at the local market. Our calculation shows that the hidden affordability problem is far more important than the revealed affordability problem and that water affordability problems in developing countries have been significantly masked by studies that focus on households paying for water.

The purpose of this paper is twofold. First, it assesses the efficiency of the drinking water supply in the Spanish municipalities of over 5,000 inhabitants. Second, it examines the hypothesis that this efficiency is conditioned by a group of environmental variables. Unlike monitoring reports based on descriptive methods, this paper uses the double data envelopment analysis bootstrap procedure to ascertain efficiency determinants. The results show that municipalities could improve their efficiency by modifying the scale at which they are operating. Regarding the determinants of efficiency, population density has been found to have a positive effect on the level of efficiency in the public service covered by this study. Moreover, it is shown that most tourist municipalities are more efficient at managing water supply service. These findings also suggest that there is greater efficiency when the provision of drinking water is managed directly by the local government. Finally, no significant impact of citizens’ level of income, political ideology, and strength on drinking water supply efficiency is found.