Journal of Water Resources Planning and Management

A hydrometerological study in a river basin was conducted to demonstrate the use of a weather radar for rainfall and flood-flow forecasting. The study region is a Pinioç river subbasin with a drainage area of 2,763 km ² located in central Greece. Six storm events that created flash floods were recorded every 10–30 min, and were analyzed and processed in terms of ground clutter supression, anomalous propagation, beam refraction, and the losses and merging procedures of radar and rain-gauge rainfall data. A rainfall-runoff model for flood-flow forecasting based on the unit hydrograph theory was then applied twice. First, by using as input the mean areal rain-gauge rainfall derived by applying the Thiessen polygon method and second, by applying the mean areal radar rainfall information over the basin. It was found that the model performs better when it uses processed weather radar data as input. Results of using as input oneand two-hour forecasted rainfall for flood forecasting were encouraging.

The weighted-least-squares method based on the Gauss-Newton minimization technique is used for parameter estimation in water distribution networks. The parameters considered are: element resistances (single and/or group resistances, Hazen-Williams coefficients, pump specifications) and consumptions (for single or multiple loading conditions). The measurements considered are: nodal pressure heads, pipe flows, head loss in pipes, and consumptions/inflows. An important feature of the study is a detailed consideration of the influence of different choice of weights on parameter estimation, for error-free data, noisy data, and noisy data which include bad data. The method is applied to three different networks including a real-life problem.

Relatively little of the research on reservoir operating procedures has found its way into actual practice. One reason is that operators are uncomfortable with complex optimization models and reluctant to use procedures that they do not fully understand. Fuzzy logic seems to offer a way to improve on existing operating practices, which is relatively easy to explain and understand. The main concepts in fuzzy logic and a procedure for applying them are explained. These are applied to finding operating procedures for a single-purpose hydroelectric project, where both the inflows and the selling price for energy can vary. Operation of the system is simulated using both fuzzy logic programming and fixed rules. The results are compared with those obtained by deterministic dynamic programming with hindsight. The use of fuzzy logic with flow forecasts is also investigated. The conclusion is that the fuzzy logic approach is promising, but it suffers from the “curse of dimensionality.” It can be a useful supplement to other conventional optimization techniques, but probably not a replacement.

Water managers have been attempting to operate reservoirs in a “best water management strategy” to meet specific project objectives since the first man-made impoundment was constructed. When it was realized, several years ago, that the U.S. Army Corps of Engineers must have the capability to analyze the operation of large multiple reservoir systems for water quality, the Hydrologic Engineering Center (HEC) was funded to develop a computer program to meet this need. “HEC-5Q, Simulation of Flood Control and Conservation Systems” computer model has the unique capabilities to accept user-specified water quantity and quality needs systemwide, and to decide how to regulate a network of reservoirs. The decision criteria are programmed to consider flood control, hydropower, instream flow (municipal, industrial, irrigation, water supply, fish habitat), and water-quality requirements. A brief history and description of the HEC-5Q model is provided along with citations to related case studies and technical reports.

A mathematical model for designing a ground-water-quality monitoring network is developed that links a ground-water pollution-transport simulation model and an optimization model. Tritium is considered as the (radioactive) pollutant. The model is formulated using chance constraints and solved by using a mixed-integer programming algorithm. It incorporates uncertainties in the prediction of pollutant movement in the saturated zone. Nonlinearities due to the inclusion of cumulative distribution functions (CDFs) of actual spatial concentrations are accommodated in the optimization model through a piecewise linearization scheme. The design of the optimal monitoring network is based on the solution of two mathematical models: a simulation model for the prediction of radioactive pollutant transport in the saturated zone, and an optimization model. Constraints of the optimization model are formulated by incorporating results from the prediction-simulation model. The simulation model provides information about pollution transport with respect to time and space. The chance-constrained optimization model solution specifies the optimal location of the monitoring wells subject to the maximum limit on the number of such wells. Performance evaluation of the developed model demonstrates potential applicability of this model for designing ground-water-quality monitoring networks.

Water resources analysts recognize that water resources planning should be comprehensive and multiply objective in nature, in contrast to planning centered on a single objective, such as flood control or irrigation. Despite this agreement, two basic approaches have emerged over time, each with its own theoretical rationale. One is generally used by the Corps of Engineers and other construction agencies, and the other by the U.S. Environmental Protection Agency (EPA) and other regulatory agencies; neither is really comprehensive. These two approaches, although in theory quite separate since the passage of the Clean Water Act in 1972, have caused relatively little conflict until the last few years, because they have been applied to different aspects of water resources. Now, however, the requirements of the various regulatory approaches are making it almost impossible to construct major facilities for any purpose, and are raising questions about the operation of existing structures for their authorized purposes. This problem has not been properly addressed, because environmentalists have felt no need to question an arrangement that vested them with such power, and water resource analysts were reluctant to challenge environmental interests. Now, however, reflective individuals of both groups are aware that a more complete planning approach would be better. This paper explains the situation we are in and the principles involved; it also explores alternative methods of arriving at better results.

The Garrison diversion unit is a canal system designed to distribute water from the Missouri River basin into western and eastern North Dakota. Canada has opposed the completion of the Garrison diversion unit because of a concern that the water sent to eastern North Dakota may degrade Canadian fisheries when it reaches Hudson Bay. To address this concern, a research project was done to evaluate the use of three different disinfection processes to inactivate harmful microorganisms in Garrison diversion unit water. The processes considered were chlorination, ozonation, and ultraviolet light. The objective was to identify a cost-effective means for inactivating bacteria and viruses that cannot be efficiently removed by broad-brush physical processes such as direct filtration or screening. The main criteria used to evaluate the three disinfection processes were reliability, cost, and potential adverse effects. The results indicated that chlorination was the most reliable and least expensive process but that ozone had fewer potential adverse effects. Ozone would also be a reliable process if the water were filtered before disinfection.

To assess the potential effects of climatic changes on water resources, it is important to incorporate predictions of future climatic trends into hydrologic planning models. Disaggregation models can be used to produce a time series at one resolution from a parent series at a different scale. In this study, a disaggregation approach is used to generate a time series simulating surface air temperature and precipitation. An annual series is generated using a 70-year record from Sacramento, California, and each year is disaggregated into 24 seasonal values. The output series from this modeling process are compared with the historical record. It is found that the statistical and correlation characteristics of the historical series are well maintained. The synthetic and historical series are applied to a reservoir-sizing model, and optimal reservoir sizes are found to be statistically similar. The results indicate the potential usefulness of this technique for generating synthetic temperature and precipitation to use in hydrologic planning based on future climate scenarios.

When a nodal demand is excessive as in a fire-flow condition or when a pump fails or a pipe breaks, a water distribution system (WDS) may temporarily become deficient and unable to satisfy all nodal demands. However, the prediction of the performance of a WDS under a temporarily-deficient condition is necessary for simulation-based reliability analysis and design of WDSs. Available methods for such prediction are reviewed herein. When the actual outlets are considered as demand nodes the methods which simultaneously consider the nodal flows and heads give fairly accurate and similar results. However, when the demands of secondary networks are assumed concentrated at the nodes of the primary WDSs, the prediction of the deficient-condition performance of a primary WDS is rather approximate. For reliability purposes, however, the method using parabolic head-discharge relationship (no flow at minimum head to required flow at desirable head), is the best for prediction of deficient-network performance.

Under most circumstances, dispersive processes can be neglected in water distribution systems due to high velocities and low dispersion coefficients that ensure that advective transport dominates constituent spreading. However, during periods of low flow, dispersive effects may become important if the velocities are significantly decreased (e.g., during the night). Thus, the question that arises during a 24-h simulation is whether dispersive processes may dominate the transport of chlorine in a water distribution system. Given that advective transport models (e.g., EPANET, PICCOLO, NET, and DWQM) cannot account for dispersive transport, it is likely that these models would underpredict the required concentration of chlorine at locations behind the advective front and overpredict the required concentration at locations in advance of the advective front. Therefore, when is a purely advective transport model an appropriate solution for contaminant transport in a water distribution system? Two constraining equations are presented to aid the user in assessing the applicability of an advective transport model.

Using a generalized network formulation, the nonlinear evaporation loss function of a reservoir is directly incorporated in a water-supply-optimization model. The nonlinear function is first piecewise-linearized and the resulting line segments are represented by a series of arcs. An appropriate arc-flow multiplier is used to reflect the slope in each line segment. A convex penalty function is then used to preserve the order of arc-flow fulfillment. The proposed formulation can be applied to model other forms of losses in a water-supply system and it eliminates iterative solutions as required by a pure network formulation. The overall management model is solved by an embedded generalized network algorithm (EMNET), which is designed to solve a linear-programming problem with an embedded generalized network substructure. Together with our previous study EMNET is proven to be an efficient tool in solving general water-supply-optimization problems.