MULTIPLICATIVE,SEASONAL ARIMA MODELS FOR LAKE ERIE AND LAKE ONTARIO WATER LEVELS1

ABSTRACT: Federal agencies in the U.S. and Canada continuously examine methods to improve understanding and forecasting of Great Lakes water level dynamics in an effort to reduce the negative impacts of fluctuating levels incurred by interests using the lakes. The short term, seasonal and long term water level dynamics of lakes Erie and Ontario are discussed. Multiplicative, seasonal ARIMA models are developed for lakes Erie and Ontario using standardized, monthly mean level data for the period 1900 to 1986. The most appropriate model identified for each lake had the general form: (1 0 1)(0 1 1)₁₂. The data for each lake were subdivided by time periods (1900 to 1942;1 943 to 1986) and the model coefficients estimated for the subdivided data were similar, indicating general model stability for the entire period of record. The models estimated for the full data sets were used to forecast levels 1,2,3, and 6 months ahead for a period of high levels (1984 to 1986). The average absolute forecast error for Lake Erie was 0.049m, 0.076m, 0.091 m and 0.128m for the 1, 2,3, and 6 month forecasts, respectively. The average absolute forecast error for Lake Ontario was 0.058m, 0.095m, 0.120m and 0.136m for the 1,2,3, and 6 month forecasts, respectively. The ARIMA models provide additional information on water level time series structure and dynamics. The models also could be coordinated with current forecasting methods, possibly improving forecasting accuracy.     

A COMPARISON OF STREAMFLOW GENERATION MODELS FOR RESERVOIR CAPACITY-YIELD ANALYSIS1

ABSTRACT: An analysis of four streamflow generation schemes for the use in the estimation of the required conservation storage for a single reservoir is presented. The comparison of the generating schemes should aid in the selection of an appropriate model type for the reservoir sizing problem. The streamflow generation models are compared using two criteria. The first comparison is between the statistics of the generated streamflow sequences and the corresponding statistics from the historical record. The second evaluation compares the median reservoir size determined by each model with the required storage based on the historical flow sequence. The results of a comparative analysis for monthly streamflow data for the Rzav River in Yugoslavia are presented and discussed. The results indicate that both evaluation criteria are required to discriminate between the various options.     

AN APPROXIMATE METHOD FOR SIZING DETENTION RESERVOIRS1

ABSTRACT: The detention reservoir is an effective measure for the management of storm water runoff, but random or unplanned placement may aggravate potential flood hazards. An approximate method for the sizing and placement of detention reservoirs is presented. The procedure is based upon the application of a storage estimation equation. The results show that the procedure closely approximates the results produced by the U.S. Army Corps of Engineers HEC-1 Flood Hydrograph Package in computing reservoir capacities on a hypotehtical watershed. Pending further tests, the use of the procedure is very limited, but it is an initial step to incorporating detention storage into regional storm water management plans.     

SEQUENT PEAK PROCEDURE: MINIMUM RESERVOIR CAPACITY SUBJECT TO CONSTRAINT ON FINAL STORAGE1

ABSTRACT: When the sequent peak procedure is used to size a reservoir, two cycles of inflows and drafts are analyzed. The use of two cycles results in the identification of the minimum reservoir capacity which, when simulated with the design inflows and drafts, will not only meet demands, but will also result in a final storage which equals or exceeds the initial storage. Demonstration of optimality follows from consideration of a method which is equivalent to the sequent peak procedure.     

NPS MODEL PARAMETER UNCERTAINTY ANALYSIS FOR AN OFF-STREAM RESERVOIR1

ABSTRACT: Parameter uncertainties exert a significant effect on nonpoint source pollution (NPS) modeling results. A decision made on the basis of such results may thereby be inappropriate. In this work, the parameter uncertainty is analyzed to explore an improved modeling procedure. Drainage patterns generated from digital elevation data and rainfall are the major parameters examined. A case study for the watershed of the Posan off-stream reservoir is implemented. A significant spatial variation of NPS distribution simulated with a drainage pattern generated from varied methods is observed. The effects of rainfall randomness on the spatial loading distribution are assessed and computed based on a Monte Carlo simulation. The proposed procedure is capable of improving the quality of modeling results and the decision for an appropriate control strategy.     

ESTIMATION OF RECHARGE FROM A RESERVOIR USING TWO WATER BUDGET MODELS1

ABSTRACT: Reservoir water levels, observation well data, and meteorological parameters were collected at a recharge dam site in Central Saudi Arabia. This data, along with other information on the reservoir and the underlying aquifer, were used to estimate the amounts of recharge through the reservoir bed by applying two water budget models. The first is a water budget model for the reservoir only, while the second is for an aquifer reach extending upstream and downstream from the reservoir. The results of the two approaches were discussed and compared.     

DECISION SUPPORT SYSTEM FOR RESERVOIR OPERATION1

ABSTRACT: A decision support system to determine reservoir releases in an uncertain environment during the dry season was developed. A key characteristic of the decision support system is its recursive procedure that processes observations to obtain the most feasible estimate. The system consists of three components: (1) a hydrologic model; (2) an optimization model, and (3) a fuzzy decision model. This methodology was applied to the operation of the Techi reservoir in central Taiwan. Three criteria (public water supply, irrigation, and hydropower) were taken into account within the operation process. Simulation results show that the decision support system can successfully assist government officials in determining operating policy for the Techi reservoir during the dry season. Also, the system is simple enough to lead to a rapid transfer of theoretical knowledge into practice.     

MODELS FOR WATER AND POWER SCHEDULING FOR THE CALIFORNIA STATE WATER PROJECT1

ABSTRACT: A large-scale simulation/optimization model provides schedules for operation of water and power for the California State Water Project (SWP). The SWP consists of a series of reservoirs linked by rivers, pumping plants, canals, tunnels, and generating plants and is operated by the California Department of Water Resources. The Department provides water to municipal and agricultural users, and manages its electrical loads and resources. The model, therefore, performs hydraulic and electrical computations leading to optimal operation of the entire system. It consists of hydraulic network programming components to meet the storage objectives at all the reservoirs, a linear programming component to determine the schedules at pumping and generating plants, an electrical network programming component to balance electrical loads and resources, and a number of other simulation components. It operates on yearly, weekly, and daily bases. It is primarily used for real-time operation of the SWP and can provide hourly detail schedules which are implemented by the SWP staff via a computerized system.     

STOCHASTIC DYNAMIC PROGRAMMING FOR OPTIMUM RESERVOIR OPERATION1

ABSTRACT. For a multipurpose single reservoir a deterministic optimal operating policy can be readily devised by the dynamic programming method. However, this method can only be applied to sets of deterministic stream flows as might be used repetitively in a Monte Carlo study or possibly in a historical study. This paper reports a study in which an optimal operating policy for a multipurpose reservoir was determined, where the optimal operating policy is stated in terms of the state of the reservoir indicated by the storage volume and the river flow in the preceding month and uses a stochastic dynamic programming approach. Such a policy could be implemented in real time operation on a monthly basis or it could be used in a design study. As contrasted with deterministic dynamic programming, this method avoids the artificiality of using a single set of stream flows. The data for this study are the conditional probabilities of the stream flow in successive months, the physical features of the reservoir in question, and the return functions and constraints under which the system operates.     

COMPUTER-AIDED PLANNING FOR MULTIPLE-PURPOSE RESERVOIR OPERATING POLICIES1

ABSTRACT: Computer-aided planning (CAP) for multiple-purpose reservoir operations involves use of state-of-the-art simulation and optimization methods, color graphic displays, and interactive computing interfaces. These technologies were integrated into a coherent system that has user-friendly interfaces to help the process of communicating reservoir system operations, solicit planning participant preferences and valuation judgments, and provide understandable feedback of system performance. The CAP system was imbedded in a comprehensive public involvement program that paralleled the reservoir operating policy modeling process, as part of multipurpose reservoir operations planning on the Great Plains Reservoirs in Colorado. Experience with the approach indicates the involved publics can quickly learn of reservoir system limitations and opportunities, and can indeed participate in the operations planning process.     

COMPARISON OF TWO AUTOREGRESSIVE MODELS FOR MONTHLY STREAM FLOW GENERATION1

ABSTRACT: Two autoregressive models for monthly stream flow generation are compared based on the reproduction of the historical record in terms of several important statistics such as the mean, standard deviation, skewness coefficient, correlation coefficient, and the reservoir storage components. In the comparison, both theoretical considerations and practical applications are employed to evaluate the performance of each model.     

MULTIOBJECTIVE DECISION MAKING TECHNIQUES FOR RESERVOIR OPERATION1

ABSTRACT: Six applications of multiobjective decision making techniques for finding optimal or satisfying operating rules for reservoir systems are presented. The examples include situations with hydropower vs. water supply (for irrigation), flood control vs. low flow augmentation, selection of an operating rule, low-flow vs. reliability, and low flow and recreation vs. water quality. The techniques applied include the constraint method, compromise programming, goal programming, Tchebycheff approach (max-mm), Consensus, and ELECTRE I and II.     

A HANDY DECISION SUPPORT SYSTEM FOR RESERVOIR OPERATION IN TAIWAN1

A user-friendly decision support system (DSS) for long-term reservoir operation has been introduced with an eye to practical use. The system can assist reservoir managers to work out applicable rules for real-time reservoir operation. The DSS model has already been applied experimentally to the main reservoirs in Taiwan with success. In this study, Tsengwen Reservoir, the largest reservoir in Taiwan, was chosen to test the applicability of the model. The simulation results show that the DSS is not only well suited to long-term reservoir operation, but also very easily applied. A handy DSS was designed for user-friendly computer interaction with Microsoft Excel in the Windows system. Users can survey on-line reservoir operation with a browser on the World Wide Web (WWW). The uniform resource locator of the DSS is http://wrm.hre.ntou.edu.tw. . So users may easily access the DSS via the Internet.     

A RISK-BASED APPROACH FOR FLOOD CONTROL OPERATION OF A MULTIPURPOSE RESERVOIR1

ABSTRACT: Many approaches are available for operation of a multipurpose reservoir during flood season; one of them is allocation of storage space for flood control. A methodology to determine a reservoir operation policy based on explicit risk consideration is presented. The objective of the formulation is to maximize the reservoir storage at the end of a flood season while ensuring that the risk of an overflow is within acceptable limits. The Dynamic Programming technique has been used to solve the problem. This approach has been applied to develop operation policies for an existing reservoir. The performance of the policy was evaluated through simulation and was found to be satisfactory.     

RESERVOIR SEDIMENTATION WITH RANDOM DEPOSITS1

ABSTRACT: The accumulated volume of sediment in reservoris is investigated in this paper using a statistical method. Based on the fact that sediment load and river discharge are highly correlated, a relationship between them is established. With longer records of stream flows, this relationship will serve either as a data generation mechanism which produces a sediment S-sequence having the same length as the river discharge Q-sequence, or as a transformation of variables, by which the distribution of S is transferred from the distribution of Q. The mean and variance of the sediment volume accumulated in the design life of a reservoir are then derived, assuming the S- and Q-sequences follow the log-normal distribution. Finally, case studies are given for illustrating the proposed method.     

A NEW METHOD FOR ESTIMATING FUTURE RESERVOIR STORAGE CAPACITIES1

ABSTRACT: A new method has been developed for estimating future reservoir storage capacities, allowing for sediment deposition and compaction. Reservoir sedimentation surveys for 117 reservoirs, conducted by the Illinois State Water Survey over the past 60 years, were used to determine regional constants K to represent the severity of sediment deposition in the reservoirs. More than half of the 82 water supply reservoirs investigated had records of reservoir sedimentation surveys, and their K values were calculated by using data from those sediment surveys. The average K values of the remaining non-surveyed water supply reservoirs were estimated from the regional distribution of the K values. Other important factors considered in the estimation of future reservoir storage capacities are the trap efficiency of the reservoirs and the variation of density of sediment deposits due to compaction. The model can also be used for analyzing the economics of alternative sites and of design features that can be incorporated in dams for reducing reservoir sedimentation.     

ALTERNATIVE FUTURES USING THE WOLLMAN-BONEM MODELS1

Alternative futures are defined to be mutually consistent alternative combinations of assumed sets of future conditions. Alternative futures are employed in conjunction with the Wollman-Bonem model to project future water use. The model solutions under different alternative futures provide an indication of the direction and relative magnitude of changes in water use, both in quantity and quality, that may result from changes in policy-influenced variables, technology, and other data. The Wollman-Bonem model is employed in this paper as a tool to illustrate the alternative futures concept. The model can best be cast as an economic model. The model solutions are not given as a set of formal projections, but as various possible water-use-over-time curves. This should aid in disspelling the erroneous idea that it is possible to make distant projections of water use as a single curve. Multiple curves suggest that water use is really a function of many variables.     

A NONLINEAR PROGRAMMING ALGORITHM FOR REAL-TIME HOURLY RESERVOIR OPERATIONS1

ABSTRACT: The optimization of real-time operations for a single reservoir system is studied. The objective is to maximize the sum of hourly power generation over a period of one day subject to constraints of hourly power schedules, daily flow requirement for water supply and other purposes, and the limitations of the facilities. The problem has a nonlinear concave objective function with nonlinear concave and linear constraints. Nonlinear Duality Theorems and Lagrangian Procedures are applied to solve the problem where the minimization of the Lagrangian is carried out by a modified gradient projection technique along with an optimal stepsize determination routine. The dimension of the problem in terms of the number of variables and constraints is reduced by eliminating the 24 continuity equations with a special implicit routine. A numerical example is presented using data provided by the Bureau of Reclamation, Sacramento, California.     

TWO-DIMENSIONAL DAM-BREAK FLOOD-FLOW ANALYSIS FOR ORANGE COUNTY RESERVOIR1

ABSTRACT: A two-dimensional dam-break model was used to predict the inundated area on an alluvial fan downslope from the Orange County Reservoir. The model is based upon a diffusion form of the continuity and momentum equations for long waves in shallow water, and the governing equation is solved by an explicit numerical scheme. In a comparison with a one-dimensional model, the two-dimensional model predicts a wider inundated area.     

A COMPARATIVE STUDY OF LINEAR AND NONLINEAR TIME SERIES MODELS FOR WATER QUALITY1

ABSTRACT: Surface water quality data are routinely collected in river basins by state or federal agencies. The observed quality of river water generally reflects the overall quality of the ecosystem of the river basin. Advanced statistical methods are often needed to extract valuable information from the vast amount of data for developing management strategies. Among the measured water quality constituents, total phosphorus is most often the limiting nutrient in freshwater aquatic systems. Relatively low concentrations of phosphorus in surface waters may create eutrophication problems. Phosphorus is a non-conservative constituent. Its time series generally exhibits nonlinear behavior. Linear models are shown to be inadequate. This paper presents a nonlinear state-dependent model for the phosphorous data collected at DeSoto, Kansas. The nonlinear model gives significant reductions in error variance and forecasting error as compared to the best linear autoregressive model identified.