Journal of Water Resources Planning and Management

Rivers provide multiple water uses and services, including offstream uses that are valued economically and instream uses, such as recreation and ecosystem preservation, that are rarely valued economically. In many countries, water rights allocate water to offstream uses, and dedicated minimum instream flows are the main instrument for instream water allocation. However, minimum instream flows do not ensure continuous reaches for recreation or aquatic habitats. An efficient allocation of water for instream uses requires quantifying the benefits obtained from those uses, so that trade-offs between instream and offstream water uses can be weighed against each other and properly considered. This study develops a generalizable, hybrid economic–engineering method to assess trade-offs between competing instream and offstream uses. Benefit curves measure recreation quality as a function of instream flow, and opportunity costs given by lost benefits of offstream uses generate supply curves for instream water. The method is applied to Chile’s Maipo River. Instream water uses for recreation include kayaking and rafting. The principal offstream water use in the study reach is hydropower generation from the Alto Maipo Hydroelectric Project. Continuous length of boatable reaches and trade-offs between instream and offstream water uses are evaluated for normal and dry months and years. Results show that the opportunity cost of additional boatable reaches is sensitive to both drought and energy price. The cost of maintaining 34 km rather than 26.6 km of continuous boatable river is US$10 million in dry years when energy prices are high, and US$240,000 in normal years when energy prices are low. Results indicate that dry months and years, when water is scarce, have a greater number of optimal solutions between instream and offstream water uses. This is explained by the physical relationship between instream flow and continuous boatable distance for low flow values. The proposed approach could guide negotiation processes between instream and offstream water users, and can be applied elsewhere, provided a physically based assessment of instream water use benefit and an economic representation of offstream opportunity costs is available.

Due to climate change and human activities, the assumption of the stationarity of hydrological variables will no longer hold. Moreover, the stochastic uncertainty of hydrological variables introduces huge challenges for water managers. To address nonstationarity and randomness, a new methodology called the nonstationary stochastic simulation–based water allocation approach is proposed to optimize regional water management. This objective is achieved via four steps. First, the generalized additive model is chosen to analyze the nonstationary probability distribution of the hydrological series. Second, the Monte Carlo method is applied to generate an optimized stochastic sample with many possible inflows according to the probability distribution obtained in the previous step. Third, a preallocated water optimization model is set up to optimize water allocation under each possible inflow. Last, the final water allocation plan can be made through statistical analysis of all optimized water allocation schemes obtained in the previous step. The approach can describe the probability distribution of regional water inflow in the planning year more accurately and reflect more stochastic information, which makes the final water allocation plan more reliable. To demonstrate its applicability, the approach was applied to the Zhanghe Irrigation District to optimize available water allocation for municipality, industry, hydropower, and agriculture in a planning year. The annual inflow of the Zhanghe Reservoir was found to be nonstationary. Moreover, an appropriate final water allocation plan in the Zhanghe Irrigation District in the planning year can be obtained through the nonstationary stochastic simulation–based water allocation method, which provides a foundation to water managers for managing water resources under nonstationary and stochastic conditions.

This exploratory study uses corrosion rates in aging metal pipes to predict the number of holes in drinking water supply systems over time. Using this estimate of the number of holes, it is possible to estimate the volume and number of pathogens introduced by negative-pressure events by Monte Carlo simulation. The probability of an intrusion volume greater than 10 L increases from less than 1% in a 25-year-old pipe to greater than 70% in a 150-year-old pipe. Surprisingly, however, health risks associated with three pathogens increase little with increasing pipe age. Some pathogens, like Giardia, are so abundant that almost any intrusion volume presents a risk, virtually independent of pipe age. Other organisms, such as Cryptosporidium, are present at such low concentrations that the risk remains low. The only evidence of significant increase in health risk (rotavirus) was predicted to occur early in the service life of the pipe (i.e., fewer than 50 years), and many pipes are much older. Because there is little evidence health risk due to intrusion increasing over time, it would seem that controlling intrusion risk is unlikely to be the key factor in developing pipe repair and replacement strategies. A simple model for assessing the overall health risks associated with intrusion is provided, suggesting the number of negative-pressure events and pipe residence time are important risk factors.

Water distribution networks have a significant water and energy demand and, therefore, must face the challenge of adopting measures that improve how these resources are used. Previous investigations have demonstrated the potential of micro-hydropower energy recovery in reducing both energy consumption and water leakage in urban water supply networks. In this work, the potential of hydropower energy recovery combined with leakage reduction has been evaluated in eight rural water distribution networks in Ireland. Two scenarios were evaluated. Scenario 1 consisted of replacing the devices currently being used to reduce pressure with a pump as turbine (PAT). In Scenario 2, potential new locations were proposed for existing sites with excess pressure, according to the flow and elevation of the network. The hydropower generated and leakage reduction due to lower pressure at the nodes were both estimated. The results showed that the estimated hydropower could reduce the net energy demand by 21% in Scenario 1 and by up to 23% in Scenario 2 in some of the networks. However, in many of the networks the amount of energy recoverable was low due to the relatively low water demand in these rural settings. In Scenario 1 three out of the eight rural water networks were found to have economically viable micro-hydropower sites. However, in Scenario 2 the significant water savings achieved as a consequence of leakage reduction made the installation of PATs feasible in all the networks evaluated. The results of this investigation highlight that while energy recovery using micro-hydropower in rural water supply networks produces only modest amounts of power in comparison with urban settings, this power can contribute significantly as a proportion of local energy demand. In addition, combining water savings with energy production greatly improves the economic viability of these micro-hydropower installations.

The basin of the Seine River is an extremely important economic region for France and Europe. Four reservoirs are operated to reduce the natural variability of the Seine River, reducing both flood and drought risk. Presently, reservoir operation is not centrally coordinated, and release rules are based on empirical rule curves. This study presents the setting of an optimal and centralized solution to the problem of reservoir operation on the Upper Seine–Aube river system, found by applying the stochastic dual dynamic programming (SDDP) procedure. The novelty of this study lies on the combination of reservoir and hydraulic models in SDDP for flood and drought protection. Including the hydraulic process in SDDP is required for estimating flood and drought at different locations along the river, and for representing the delay between the release from the reservoirs and their effects downstream. The study case covers the Seine basin until the confluence with the Aube River: this system includes two reservoirs, the city of Troyes, France, and, at the confluence of the two rivers, the nuclear power plant at Nogent-Sur-Seine. Results shows that the SDDP solution can be effectively used to optimize the operation of a water system made of multiple reservoirs and multiple hydraulic transfer components, solving a relatively large stochastic dynamic programming problem in an acceptable time. The management obtained from SDDP rules exploits the centralized operation and, compared to the current operational rules, results in more frequent but shorter, less intense, and less severe flood and drought events at Nogent-Sur-Seine.

Challenges abound for water managers attempting to address problems that have cumulative effects. This paper discusses some of these challenges and potential solutions through a case study of farm dam management in the Australian state of Victoria. Farm dams are useful sources of water but also have an impact on the environment because they capture water that might otherwise flow into streams. Responding to this problem, the Victorian government enacted the Farm Dams Act in 2003, which expanded the farm dam licensing system. To measure the outcomes of this law, farm dam maps were analyzed using GIS and dam owners were interviewed. Map analysis showed a 65% reduction in the construction rate of dams used for irrigation after the implementation of the Act, and interviews suggested the revised licensing system made it more difficult for farmers to build new irrigation dams. The combination of direct regulation and economic instruments employed in the Farm Dams Act reduced the rate of dam construction and increased the political acceptability of the changes. Consultation and education complemented the other policy instruments by increasing community support for the policy and compliance with its licensing requirements. The case study suggests that earlier action to expand the licensing system would have resulted in many benefits including savings in public resources, increased certainty of water supply for farmers, and better protection of the environment.

Water distribution systems are becoming increasingly vulnerable to cyber-physical attacks as they are further augmented with otherwise helpful monitoring and control devices. Simulating the hydraulic responses of networks to attacks is an important first step toward understanding and mitigating their potential impacts. To date, the tools available for this have either been small-scale, bespoke models or have relied on demand-driven analysis. In this work, we improve the suite of modeling tools currently available by extending the capabilities of epanetCPA—a Matlab toolbox that uses the demand-driven hydraulic engine of EPANET—to simulate pressure-driven simulations of cyber-physical attacks on water distribution systems. The proposed modeling approach is scalable and, by adding pressure-driven capabilities, vastly increases the range of possible failure scenarios that can be reliably simulated. The approach was tested and verified on a town-scale benchmark network through multiple attack scenarios. These showed that the approach can be used to gain helpful insights into the behavior of networks, including the relative vulnerability of different sections of networks, the suddenness with which supply is fully cut off, and the window of opportunity for responding to attacks. Such insights can then be used to improve network resiliency and aid in the detection of attacks.