Journal of Water Resources Planning and Management

An original modeling framework for the assessment of climate variation and change impacts on the performance of a complex flood protection system has been developed for the city of Winnipeg in the Red River basin, Manitoba, Canada. The modeling framework allows for the evaluation of different climate change scenarios generated by the global climate models. Temperature and precipitation are used as the main factors affecting flood flow generation. The main contribution of the reported work is the use of a system dynamics modeling and simulation approach in the development of a system performance assessment model. The assessment-modeling framework is based on flood flows, capacity of flood control structures, and failure flow levels at different locations in the basin. The results of this study (shown only to illustrate the methodology) indicate that the capacity of the existing Red River flood protection system is sufficient to accommodate future climate variability and change.

The calculation of optimized pump schedules is sometimes complicated by the inclusion of a maximum demand charge in the electricity tariff. Maximum demand charges can be as much as 35% of energy costs, and in the United Kingdom they usually apply over a calendar month. In this paper, medium term maximum demand policies are assumed to be represented in daily scheduling by constraints on power use or by penalty costs. Derivation of optimal constraints or penalty costs has been formulated as a stochastic dynamic program in which variations in daily demand for water are modeled as a Markov process, and solved for the case where there is a single maximum demand charge for the system under consideration. A hypothetical case is provided to illustrate the process, and cost functions and optimal constraints for this case are presented graphically. The method has considerable advantages over heuristic techniques because it takes full account of uncertainty in the demand for water, and of the recursive nature of the problem.

Simulation models in conjunction with synthetic multiple hydro-climate replicates provide the most realistic assessment of the performance of urban water supply headworks systems. However, optimization using such models is computationally very demanding. To appreciate the challenge, a simple case study system is presented. The system consists of one reservoir, has three decision variables to be optimized, and uses an objective function based on reservoir costs and economic penalties for water shortages. Enumeration revealed that the objective function surface has piecewise flat regions that arise from operating rule thresholds and the infrequent sampling of severe droughts. Two search methods capable of dealing with such flat regions, the genetic algorithm (GA) and the shuffled complex evolution (SCE) method, were investigated. For the GA to be robust (i.e., avoid premature convergence on flat regions), it was necessary to employ two lesser-known genetic operators, inversion and population selection strategy. The SCE method was found to have comparable robustness, but required fewer evaluations. Nonetheless, the GA method was preferred because of its inherent advantage in parallel computing.

The hydropower unit commitment and loading problem represents a complex decision-making process involving the integrated hourly scheduling of generators in a multiproject hydropower system. Optimal scheduling maximizes basinwide operating efficiency while satisfying power load demands, water demands, reliability constraints, operational restrictions, and security requirements. Often considered as a sequentially static optimization over each operational period, the problem actually embodies a highly dynamic structure when considering realistic operational restrictions on unit commitment and loading. A dynamic programming (DP) optimization model maximizes basinwide operating efficiency subject to (1) plant constraints on total generation requirements, generation shape requirements, and spinning reserve; and (2) operational restrictions on rough zone avoidance, minimum up and down time requirements, and unit outage modes. Application of the DP model to the hydropower system of the Lower Colorado River Basin demonstrates its capabilities for real-time optimal unit scheduling in satisfying complex operational constraints while improving basinwide generation efficiency.

Devils Lake, a terminal, saline lake, of glacial origin, in North Dakota has experienced a 7.5 m rise in lake elevation resulting in the flooding of over $243{\mathrm{km}}^2$ from 1992 to 2002. At lower water surface elevations, Devils Lake functions as a series of connected basins with salinity increasing in an eastward direction due to evaporation. The recent increase in water depth provides an opportunity for increased dispersive exchange flows and mixing between the lake’s basins due to wind and buoyancy forces. This increased mixing will change the future water quality distribution in Devils Lake, and may therefore have an impact on plans for lake level stabilization. In this paper, a model based on energy and conservation of mass principles is applied to estimate the potential redistribution of sulfate within Devils Lake. The rate of redistribution may affect the lake’s ecosystem and the design of a possible water diversion to the Red River of the North for the purpose of stabilizing the water surface elevation. Included in the paper is the selection of model input parameters, model calibration with field measurements, and application of the model to five future scenarios.

Storm-water flow from an impervious surface can lead to stream degradation, habitat alteration, low base flows, and increased toxic loadings from nonpoint sources, a problem that has resisted traditional command and control regulatory approaches. We explore the thesis that a well-designed, tradable runoff allowance system can create economic incentives for landowners to employ low-cost runoff management practices to reduce excess stormwater flow to more ecologically sound levels. Attributes such as percent impervious surface, soil type, and so on, determine a given land parcel’s runoff potential and management alternatives and, by extension, its allowance requirements. Using a small watershed in Cincinnati, Ohio, as a case study, we show that a tradable runoff allowance system carries promise as a low-cost method for attaining reductions in storm-water runoff.

Imperviousness is an important indicator of the impact of urbanization on storm water systems. A hydrologic analysis was performed to evaluate long-term impacts from an apartment area in Miami. The result shows that the directly connected impervious area (DCIA), which covers 44% of the catchment, contributes 72% of the total runoff volume during 52 years. Few studies have actually measured the DCIA with a high level of accuracy for residential areas that constitute the largest proportion of urban land. A detailed analysis of urban imperviousness was performed using geographic information systems and field investigations on a 5.81 ha residential area in Boulder, Colo. For this study area, the total impervious area is 35.9% and the DCIA is 13.0%. Transportation-related imperviousness comprises 97.2% of the DCIA. Hydrologic modeling of this area shows about a 265% difference in estimates of peak discharge with imperviousness measured at five different levels of accuracy. These results suggest the need to focus on DCIA as the key indicator of urbanization’s effect on storm water quantity and quality.

Flooding is a hazard with serious socioeconomic consequences for all activities and infrastructure within an affected floodplain. Accurate delineation of flood extents and depths within the floodplain is essential for flood management officials to make sensible and fair decisions regarding construction, insurance, and other regulated practices on land and property potentially affected by flooding. Traditional methods for manually delineating flood extents from computed hydraulic models are tedious, subjective, and prone to mistakes. With the advent of high-powered computers and accurate digital terrain models, the possibility of automating floodplain delineation is achievable. An improved process is presented for delineating floodplains accurately from a digital terrain model (DTM) and hydraulic model in an automatic environment and providing the flexibility of incorporating professional judgment in the process. The most significant improvements are (1) use of georeferenced water levels from different sources; (2) a refined water levels selection procedure for interpolation such as the use of quadrant, flow path, and flow distance; and (3) incorporating user-defined flood barriers. The outcome of these improvements is a flexible, easy-to-use floodplain delineation process that is independent of hydraulic modeling systems, water-level sources, and DTM data structures and maintains hydraulic connectivity over the floodplain. The use of georeferenced water levels also makes the process capable of integrating 1D and 2D model results in floodplain delineation.