Journal of Water Resources Planning and Management

Numerous experiments are performed that characterize the behavior of individual storage reservoirs across the United States. Storage-yield curves based on annual and monthly flow records are compared to show that the standardized net inflow and the coefficient of variation of net inflow C_v completely characterize the refill properties of storage reservoirs. For example, these experiments indicate that for any river with C_v > 0.8, the design capacity of a reservoir is determined by annual fluctuations in streamflow alone, regardless of its size. Two new indices of resilience and vulnerability are derived for reservoirs fed by correlated lognormal inflows. Previous studies document that inflows to reservoirs in the United States may be approximated by correlated lognormal inflows. Combining these results with a recent inventory of thousands of storage reservoirs across the United States, along with regional climate and streamflow databases, we explore the behavior of individual storage reservoirs. We compare the resilience, reliability, yield, and vulnerability of individual storage reservoirs under existing scenarios and one possible future climate scenario.

The July 1997 flood in Fort Collins was caused by the heaviest rains ever documented over an urbanized area in Colorado, and offers a data base and multifaceted set of lessons about flood planning, mitigation, response, and recovery for engineers, flood managers, and urban officials. The storm dropped 10 to 14 inches in 31 hours and some peak discharges greatly exceeded projected 100-year and 500-year flows. Five people died, 54 were injured, about 200 homes were lost, and 1,500 homes and businesses were damaged. Damages at Colorado State University were about $100,000,000, including catastrophic losses to the library. The paper summarizes the flood experience and provides lessons in five categories: urban drainage and flood control, risk management, mitigation, flood response, and public involvement.

Artificial neural networks (ANNs) are new computing architectures in the area of artificial intelligence. The present study aims at the application of ANNs for reservoir inflow prediction and operation. The Upper Indravati multipurpose project, in the state of Orissa, India, has been selected as the focus area. The project has primarily two objectives: To provide irrigation to 128,000,000 ha of agricultural land and to generate 600 MW of electric power. An autoregressive integrated moving average time-series model and an ANN-based model were fitted to the monthly inflow data series and their performances were compared. The ANN was found to model the high flows better, whereas low flows were better predicted through the autoregressive integrated moving average model. Reservoir operation policies were formulated through dynamic programming. The optimal release was related with storage, inflow, and demand through linear and nonlinear regression and the ANN. The results of intercomparison indicate that the ANN is a powerful tool for input-output mapping and can be effectively used for reservoir inflow forecasting and operation.

This paper addresses the problem of efficient and effective interpretation of water distribution network state estimates that are typically calculated on the basis of measurements and pseudomeasurements (consumption estimates) that have significant uncertainties associated with them. The task of the system state interpretation is particularly relevant to the diagnosis of leakages and other operational faults occurring in water distribution networks. A new approach, based on the examination of patterns of state estimates by a general fuzzy min-max neural network (GFMM) has been proposed and evaluated. The GFMM classification and clustering has been incorporated into a two-level fault diagnosis system. The proposed diagnostic procedure builds on the concept of confidence limit analysis of state estimates and estimation residuals. An extensive leakage detection and identification study in a small test system for a complete 24-h period of operation has been carried out. An analogy between the information processing by the GFMM and by human operators has been identified and highlighted in this context.

A decision framework is presented for assessing the value of ground-water sampling within the context of ground-water management under uncertainty. The framework couples two optimization models—a chance-constrained ground-water management model and an integer-programing sampling network design model—to identify optimal pumping and sampling strategies. The methodology consists of four steps: (1) The optimal ground-water management strategy for the present level of model uncertainty is determined using the chance-constrained management model; (2) for a specified data collection budget, the monitoring network design model identifies, prior to data collection, the sampling strategy that will minimize model uncertainty; (3) the optimal ground-water management strategy is recalculated on the basis of the projected model uncertainty after sampling; and (4) the worth of the monitoring strategy is assessed by comparing the value of the sample information—i.e., the projected reduction in management costs—with the cost of data collection. Steps 2–4 are repeated for a series of data collection budgets, producing a suite of management/monitoring alternatives, from which the best alternative can be selected. A hypothetical example demonstrates the methodology's ability to identify the ground-water sampling strategy with greatest net economic benefit for ground-water management.

Software models are important for the evaluation and management of environmental resources. This paper presents a framework for developing a software system for water quality analysis of river ecosystems. A major component of the system is a database that permits inclusion of analytical water quality and sediment data, river geometry and sampling site characteristics, hydrologic measurements, and reference information on water quality parameters and criteria. Associated with the database is software for managing, analyzing, and representing the information in the database. An object-oriented strategy is applied to derive a model of the software system. The resulting object-oriented design is then translated into an entity-relationship model, which is in turn translated into a relational model. The formality of this translation process ensures consistency among the successive design stages. The overall development approach to system design and implementation is described, and an application for evaluating water quality conditions in the lower Mississippi River is presented.

Failures in operation of water supply reservoir systems are often unavoidable during critical hydrologic periods. The failure characteristics of such systems can be represented by performance indicators such as reliability, resilience, and vulnerability. A mixed-integer programming model for the operation of a water supply reservoir during critical periods has been presented in the literature that incorporates these performance indicators. An improved formulation of this model that represents resilience more completely is discussed herein. In addition, a set of constraints with binary integer variables are included to account for reservoir spills. The improvements achieved with the modified model is demonstrated using the same example as presented with the original model.

A technique is proposed for leak detection and evaluation in outfall pipes based on properties of transient pressure waves. Transients are caused by an increase of the piezometric head at the initial section of the outfall pipe. Since high overpressures are not necessary for the success of the technique and simple equipment is required, tests may be repeated periodically to check the state of the pipe. In order to verify the possibility of locating a possible leak on the basis of the results of transient tests, the effects of a leak on wave propagation from the numerical point of view are discussed first. A first-order formula for preliminary evaluation of the discharge behavior of the leak is also given. Results of some laboratory tests carried out on a long pipe are shown in order to confirm the reliability and validity of the proposed technique. Inverse transient calculations are proved to be able to provide precise information about the characteristics of the leak.