Journal of Water Resources Planning and Management

The design of district metered areas (DMAs) has many factors to be considered to reduce the adverse effect of the closure of valves. A three-step methodology for DMA design is proposed based on spectral clustering algorithm and graph theory. The first step is to calculate the nontrivial eigenvectors based on a weighted graph of the water distribution network. The second step is optimal nodes clustering as DMAs by spectral clustering. The third step is to determine the location of meters and valves by a proposed heuristic method. The multicriteria decision method is then used to determine the best DMAs solution. A simple example network is used to demonstrate the method, and a real-world network, the Wolf-Cordera Ranch, is applied to test the feasibility and effectiveness of the proposed method for DMA design in actual systems. Results show that the proposed method can identify different DMA solutions effectively, and better DMA design can be obtained considering different performance criteria.

The estimation of user demands in water distribution systems is usually based on flow and pressure measurements in the system. Even when the number of measurements is larger than or equal to the number of unknowns, the system may not be observable; i.e., not all unknown variables can be estimated. Common estimation methods (e.g., the weighted least-square error) do not automatically identify an unobservable system and may provide unreliable results. This paper builds on the algebraic approach recently proposed, where the unknown variables considered were the nodal heads, and modifies the approach in order to estimate the demand multipliers of the demand patterns. A comparison between algebraic and finite difference derivatives is also presented and shows that finite differences cannot be used to assess the observability of the system.

Considering all possible input (predictor) variables in a predictive water quality model is impractical owing to computational workload and complexity of the problem. Computational efficiency, as well as complexity of a model, is greatly increased if the most influential variables are determined using an input variable selection technique. In this study, the multilayer perceptron artificial neural network was implemented in order to predict total dissolved solids in the Sufi Chai river (Iran). The research studied the impacts of chemical composition (salinity, potassium, sodium, magnesium, calcium, sulfate, chloride, bicarbonate, carbonate, pH, and sodium adsorption ratio) in source water, climatic variables (rainfall, air temperature, wind speed, and evaporation), and hydrometric variables (river discharge and suspended sediment) on the predictions. Garson’s equation was used to find the relative importance of each input variable and to select the most influential variables. A correlation method was applied and the results were compared with those of the Garson method. A set of 12-year data (1999–2010) was used to calibrate, validate, and test the models. The results indicated that input variable selection before modeling can improve both accuracy and simplicity of the models. Although Garson and correlation methods both improved the accuracy of the models, the Garson method was found to be more accurate. As well, the research showed including climatic and hydrologic variables improved the accuracy of the models with fewer variables considered.

Simplification methodologies for complex water distribution systems (WDS) are essential for better understanding water distribution system behavior. Such methodologies have substantially improved the management and operation of water distribution systems. WDS are complex structures that may consist of thousands to tens of thousands of elements, which makes their optimal management and operation a very large-scale and complex problem. With the objective of improving the network properties, this work uses mathematical methods drawn from graph theory to represent the water distribution system as a directed graph mimicking the original WDS topology and hydraulic properties. The digraph representation uses graph theory algorithms to identify the unique behaviors on the basis of cluster analysis that distinguishes the specific understandings of WDS. The simulation was performed on two case studies, showing results that were very similar to the results that were predicted theoretically.

This paper presents a practical method for estimating the volume of apparent losses in water supply systems, particularly in a developing country context, so that real losses can be calculated from the volume of nonrevenue water (NRW). The method employs the fact that almost all apparent losses reach wastewater treatment plants (WWTPs). The volume of apparent losses can be estimated through establishing a water and wastewater balance using routine measurements of WWTP inflow and routine data of billed consumption. The water and wastewater balance was applied in the water supply system of Sana’a, Yemen, so NRW components were estimated. Sensitivity and uncertainty analyses show that all sources of the errors are small apart from the level of accuracy of measuring the WWTP inflow, and this accuracy can be practically improved. Other parameters and variables are relatively insensitive. The paper discusses the advantages and limitations of the suggested alternative method compared with the other NRW assessment methods.

This paper presents an integrated solution approach for solving the challenge of partitioning a large water-distribution system into district meter areas (DMAs). The solution method is formulated to employ graph algorithms to generate DMA partitions, and apply a high performance genetic algorithm optimizer to optimize DMA partitions, boundary links, system interventions including parallel pipes, replacement pipes, and tank capacities. The solutions are interactively evaluated and fine-tuned by using well-developed modeling software to adjust the boundary link status and place pressure reduction valves (PRVs). Finally, the PRV settings are optimized to reduce the nodal pressures to meet the maximum allowable pressures inside DMAs. The approach has been applied to the Battle of Water Networks DMAs (BWNDMA). Good solutions have been obtained for the case study. In particular, water-balance analysis is carried out to identify which water-supply source is going to supply which DMA region according to the available amount of water that is allowed to be extracted. Link status and settings are adjusted accordingly to optimize the system performance. Throughout the solution process engineering judgment has been employed, together with the simulation and optimization models, to obtain the optimized solutions while meeting the constraints.

The advent of smart metering is set to revolutionize many aspects of the relationship between water utilities and their customers, and this includes the possibility of using time-varying water prices as a demand management strategy. These dynamic tariffs could promote water use efficiency by reflecting the variations of water demand, availability, and delivery costs over time. This paper relates the potential benefits of dynamic water tariffs, at the utility and basin scale, to their design across a range of timescales. On one end of the spectrum, subdaily peak pricing shifts use away from peak hours to lower a utility’s operational and capital expenses. On the other end, scarcity pricing factors in the variations of the marginal opportunity cost of water at weekly or longer timescales in the river basin from which water is withdrawn. Dynamic pricing schemes that act across timescales can be devised to yield both types of benefits. The analysis estimates these benefits separately for Greater London (United Kingdom) and its 15 million inhabitants. Scarcity pricing implemented on a weekly timescale equates the marginal cost of residential water with estimates of the marginal economic values of environmental-recreational flows derived from tourism, property values, etc. Scarcity pricing during droughts could result in a 22–63% average reduction in environmental flow shortage while residential price increases would be capped at 150% of base levels. Yet, its ability to protect environmental flows could decrease in extreme shortage situations. The net present value of savings from peak pricing is conservatively evaluated at approximately £10 million for each initial percentage point in daily peak-hour price increase.

Water supply utilities need to properly manage their systems to guarantee a quality supply. One way to manage large systems is through division into district metered areas (DMAs). Graph clustering with an unknown number of subdivisions, as in social network theory, has proven highly efficient in this sectorization problem. Several physical and hydraulic features may easily be used as criteria to suitably divide the network. This paper uses social network community detection algorithms to define several DMA scenarios. Configurations mainly depend on nodal demand and elevation, but adaptations may be needed to guarantee full supply in future scenarios related to system growth—and rehabilitation actions may also be required. The problem associated with pipes and valves is first solved with three optimization methods. The best solutions then enter a new optimization process, in which tank dimensions and valve set points are defined. This complex optimization-segregation approach enables an improvement in the hydraulic efficiency of the E-Town network at an affordable cost, and this approach also determines the measures needed to meet the dry season requirements.

The Eastern Nile riparian countries are currently developing several reservoir projects to contribute to the needs for energy and food production in the region. In the absence of formal mechanisms for collaboration, the transboundary nature of the Eastern Nile basin makes water resources development challenging. The large seasonal and interannual variability of the river flow increases those challenges. This paper assesses the implications of water resources development in the Eastern Nile basin on water availability for hydropower generation and irrigation demands at country and regional levels, using simulation and scenario analysis methods. Twelve scenarios are used to test developments of several dams and irrigation demands, Grand Ethiopian Renaissance Dam (GERD) operation options, and unilateral (status quo) versus integrated transboundary management of dams. A RIBASIM model that included 20 dams and 21 irrigation schemes was built, using a complete data set of 103 years at a monthly time step. Four indicators have been used for evaluating the performance of the system: hydroenergy generation ($\mathrm{MWh}/\mathrm{year}$), reliability of irrigation supply (%), reservoir net evaporation (${10}^6{\mathrm{m}}^3/\mathrm{year}$), and flow regimes of rivers (${\mathrm{m}}^3/\mathrm{s}$). The results show that in case of managing the system in an integrated transboundary manner and without new irrigation development projects, GERD would increase the hydroenergy generation in Ethiopia by $+\mathrm{1,500}\%$ and in Sudan by $+17\%$, with a slight reduction in Egypt of $-1\%$. Supply reliability of existing and planned irrigation schemes in Sudan would not be practically influenced by the GERD, but the reliability will be reduced by about 8% when upstream development and new irrigation expansion materialize. Full development of the Eastern Nile basin would reduce the irrigation supply reliability in Egypt to 92% compared to the base scenario (100%). Compared to integrated management, unilateral management would increase the hydroenergy generation in Ethiopia ($+16\%$), increase the rate of evaporation losses in the basin ($+15\%$), and reduce the irrigation supply reliability in Sudan after full development of dams and irrigation projects ($-10\%$). Water resources development would have considerable but varying effects on the countries.