Journal of Water Resources Planning and Management

This paper addresses the problem of appropriate location of control valves in a water supply pipe network and their settings via genetic algorithm (GA) to obtain maximum leakage reduction for given nodal demands and reservoir levels. Embedded in this optimization is the problem of determination of optimal control-valve settings in terms of minimization of system leakage for a given location of valves. It is shown through an example water distribution network that the optimally located valves are much more effective at producing maximum leakage reduction in the network. On the basis of multiple simulations of demand patterns, it was found that the expected value of leakage in a network provided with optimally placed control valves is practically independent of total demand. A study of the effect of varying demands on the optimal location of valves indicated distinct combinations of valve-locations for the different spatial patterns of nodal demands and for different total demands.

This paper presents a Bayesian Stochastic Dynamic Programming (BSDP) model to investigate the value of seasonal flow forecasts in hydropower generation. The proposed BSDP framework generates monthly operating policies for the Skagit Hydropower System (SHS), which supplies energy to the Seattle metropolitan area. The objective function maximizes the total benefits resulting from energy produced by the SHS and its interchange with the Bonneville Power Administration. The BSDP-derived operating policies for the SHS are simulated using historical monthly inflows, as well as seasonal flow forecasts during 60 years from January 1929 through December 1988. Performance of the BSDP model is compared with alternative stochastic dynamic programming models. To illustrate the potential advantage of using the seasonal flow forecasts and other hydrologic information, the sensitivity of SHS operation is evaluated by varying (1) the reservoir capacity; (2) the energy demand; and (3) the energy price. The simulation results demonstrate that including the seasonal forecasts is beneficial to SHS operation.

Detention basins are the most popular structural measure for urban flood control and have proven effective for both water quantity and quality management. Integrated, watershed-level planning of the layout and sizing of detention systems is essential because localized solutions may actually aggravate the negative impacts of urban drainage. Successive reaching dynamic programming (SRDP) is applied to minimize detention system costs of maintaining ranges of desired downstream peak flow attenuation, with basin and channel routing imbedded within the algorithm. A multiobjective genetic algorithm (MOGA) is also applied to generating nondominated solutions for system cost and detention effect for a watershed-level detention system. These algorithms are applied to the layout and design of a stormwater detention system in the Pazam watershed located in southern Taiwan. The case study confirms the robustness and computational efficiency of the SRDP algorithm, and the MOGA generates a wide range of nondominated solutions for trade-off analysis using a proposed elite solutions conservation procedure.

The need for effective water sharing agreements between sovereign states is increasing as more people and industries compete for use of that finite resource. To prevent conflict the affected parties must enter into an effective and efficient water sharing agreement for equitable sharing of the water. States entering into the transboundary water sharing agreement are obligated to perform four duties: (1) The duty to cooperate and negotiate in good faith; (2) the duty to prevent unreasonable harm; (3) the duty of equitable utilization; and (4) the duty to exchange data and information.

This paper compares four different methods for estimating the yield of a multiple reservoir system. These include simulation, a combined simulation-optimization model (WATHNET), a full optimization model, and a simplified optimization model called the yield model. Simulation is used widely in practice and provides a good approximation of the behavior of the system but requires a set of operating rules to be specified. The optimization methods automatically determine operating rules and are therefore quite useful in estimating the yield of a new system that has not yet been operated. The four methods are used to estimate the safe historical yield of the Canberra water supply system (Australia). It was found that the full optimization model and the yield model provide high estimates of the system yield because they assume perfect knowledge of future inflows. WATHNET presents a reasonable compromise in estimating the system yield using implied operating rules that are achievable in practice.

A method of random resampling of residuals from stochastic models is used to generate a large number of 12-month-long traces of natural monthly runoff to be used in a position analysis model for a water-supply storage and delivery system. Position analysis uses the traces to forecast the likelihood of specified outcomes such as reservoir levels falling below a specified level or streamflows falling below statutory passing flows conditioned on the current reservoir levels and streamflows. The advantages of this resampling scheme, called bootstrap position analysis, are that it does not rely on the unverifiable assumption of normality, fewer parameters need to be estimated directly from the data, and accounting for parameter uncertainty is easily done. For a given set of operating rules and water-use requirements for a system, water managers can use such a model as a decision-making tool to evaluate different operating rules.