RESERVOIR OPERATION ANI EVALUATION OF DOWNSTREAM FLOW AUGMENTATION1

ABSTRACT: Operation of a storage‐based reservoir modifies the downstream flow usually to a value higher than that of natural flow in dry season. This could be important for irrigation, water supply, or power production as it is like an additional downstream benefit without any additional investment. This study addresses the operation of two proposed reservoirs and the downstream flow augmentation at an irrigation project located at the outlet of the Gandaki River basin in Nepal. The optimal operating policies of the reservoirs were determined using a Stochastic Dynamic Programming (SDP) model considering the maximization of power production. The modified flows downstream of the reservoirs were simulated by a simulation model using the optimal operating policy (for power maximization) and a synthetic long‐term inflow series. Comparing the existing flow (flow in river without reservoir operation) and the modified flow (flow after reservoir operation) at the irrigation project, the additional amount of flow was calculated. The reliability analysis indicated that the supply of irrigation could be increased by 25 to 100 percent of the existing supply over the dry season (January to April) with a reliability of more than 80 percent.     

OPTIMIZING THE PROBABILITIES OF WATER YIELD FOR THE RIDAURA AQUIFER (SPAIN)1

ABSTRACT: Aquifer pumping represents, in many geographical locations, an alternative and/or a complementary source of water to surface water supplies. Several Catalonian coastal towns in the northeastern corner of Spain are in this situation. Also, since pumped water is used to supply drinking water, the main purpose in managing these water resources is to supply, no matter the cost, the amount needed at every moment. In other words, the managers of these aquifers attempt to optimize firm water yield. If we think of these aquifers as underground reservoirs with fixed storage capacity, most of the techniques which are applied to surface reservoirs can be implemented. In this paper we use a Stochastic Dynamic Programming model to optimize the yield from the aquifer of the Ridaura River. The objective function in this model was chosen with the aim of maximizing the reliability of the target yields in each of four seasons.     

OPTIMAL CAPACITIES OF WATER SUPPLY RESERVOIRS IN SERIES AND PARALLEL1

ABSTRACT: The planning of water supply reservoirs has traditionally been based on the Rippl or sequent peak analysis which applies to the design of a single reservoir. This paper incorporates the sequent peak method as the central feature in establishing a procedure for determining the sizes of several potential reservoirs located in a system of one or more rivers. Separate algorithms are developed for sites on parallel streams and for sites on the same stream. In both cases the approach is to find the combination of reservoirs which can satisfy a given constant monthly demand at a minimum total construction cost. It is shown that both problems can be cast in the form of a dynamic programming problem. A more complex system is then a combination of reservoirs in parallel and in series. An extension is given if the monthly demand is not constant but each reservoir satisfies a constant fraction of the monthly demand.     

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.     

FLEXIBLE PRICING IN WATER SUPPLY PLANNING–FOR FLEXIBLE ENGINEERS1

ABSTRACT. Preliminary results from a digital simulation model designed to test time-varying water pricing policies are presented. Stochastic inflows feeding a water supply reservoir are assumed for a hypothetical community with defined demand functions. Prices are allowed to vary as a function of reservoir level, generally rising as reservoir levels fall. Increasing, decreasing and constant rates are tested. It is concluded that varying the price to reflect the increased value of scarce supplies can greatly reduce the risk of water supply shortages. It is also concluded that varying incremental (conservational) pricing policies not only reduces the risk of shortages, but also lowers the average price to the community while rewarding the low consumption user with lower average rates.     

An imprecise fuzzy risk approach for water quality management of a river system

Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA) problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max–min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga–Bhadra river system in India.     

Multireservoir real-time operations for flood control using balanced water level index method

This paper presents a real-time simulation-optimization operation procedure for determining the reservoir releases at each time step during a flood. The proposed procedure involves two models, i.e., a hydrological forecasting model and a reservoir operation model. In the reservoir operation model, this paper compares two flood-control operation strategies for a multipurpose multireservoir system. While Strategy 1 is the real-time joint reservoir operations without using the balanced water level index (BWLI) method, Strategy 2 involves real-time joint reservoir operations using the BWLI method. The two strategies presented are formulated as mixed-integer linear programming (MILP) problems. The idea of using the BWLI method is derived from the HEC-5 program developed by the US Army Corps of Engineers. The proposed procedure has been applied to the Tanshui River Basin system in Taiwan using the 6h ahead forecast data of six typhoons. A comparison of the results obtained from the two strategies reveals that Strategy 2 performs much better than Strategy 1 in determining the reservoir real-time releases throughout the system during flood emergencies in order to minimize flooding, while maintaining all reservoirs in the system in balance if possible. Consequently, the proposed model using the BWLI method demonstrates its effectiveness in estimating real-time releases.     

COMPARISON OF STOCHASTIC AND DETERMINISTIC DYNAMIC PROGRAMMING FOR RESERVOIR OPERATING RULE GENERATION1

ABSTRACT: Two dynamic programming models — one deterministic and one stochastic — that may be used to generate reservoir operating rules are compared. The deterministic model (DPR) consists of an algorithm that cycles through three components: a dynamic program, a regression analysis, and a simulation. In this model, the correlation between the general operating rules, defined by the regression analysis and evaluated in the simulation, and the optimal deterministic operation defined by the dynamic program is increased through an iterative process. The stochastic dynamic program (SDP) describes streamflows with a discrete lag-one Markov process. To test the usefulness of both models in generating reservoir operating rules, real-time reservoir operation simulation models are constructed for three hydrologically different sites. The rules generated by DPR and SDP are then applied in the operation simulation model and their performance is evaluated. For the test cases, the DPR generated rules are more effective in the operation of medium to very large reservoirs and the SDP generated rules are more effective for the operation of small reservoirs.     

AN INTERACTIVE SIMULATION OF PUMPED STORAGE RESERVOIR SYSTEMS1

ABSTRACT: A combination pumped storage reservoir system was simulated by modifying the WRE deep reservoir model. Each of the two reservoirs was described by a copy of the WRE model program, the two programs were converted into subroutines and were called upon alternately by a main program. Operationally, the contributing reservoir, i.e., the reservoir from which flow was discharged, was simulated for one execution interval (1 hour), followed by simulating the receiving reservoir for the same execution interval. The main program directed the discharge temperature of the contributing reservoir for each execution interval as input for simulating the receiving reservoir. The two subroutines were run in this interactive mode for a simulation period of one year. Two simulations, labeled “Pump” and “Net,” were effected and differed basically in the distribution of flow volumes exchanged between the reservoirs. In the ‘Pump’ simulation the total hourly flow volumes were distributed into appropriate horizontal layers of the lakes as determined by temperature-density relationships, i.e., the pumped discharges were distributed into the upper lake and the generation discharges were distributed into the lower lake. In the ‘Net’ simulation only the net daily discharges (daily difference between pump-back and generation at the upper dam), distributed uniformly over 24 hours, were mixed into the horizontal layers of the two lakes. Both simulations produced annual thermal regimes that were apparently within reason for the geographical area and the nature of the input data. However, neither accurately reflected a generalized conditions for the reservoirs because the Pump simulation reflected conditions in the forebay and tailrace of the Upper dam while the Net simulation reflected conditions of the remaining parts of the reservoirs.     

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.     

RESERVOIR MANAGEMENT RULES DERWED WITH THE AID OF MULTIPLE OBJECTIVE DECISION MAKING TECHNIQUES1

ABSTRACT: The determination of optimum reservoir operating rules for reservoirs with multiple conflicting objectives is still a difficult task - despite many publications in this field. In this paper a three-step Multi Objective Decision Making (MODM) method is presented, the emphasis of which is placed on the necessity to make the work easy for the decision maker, which many MODM techniques fail to achieve. The method is applied to the development of a compromise optimum operating rule for a multi-purpose reservoir. In the first step of the method stochastic DP is chosen which is combined with the “weighting method” allowing combination of various objectives into one objective function. By systematically varying the weights for the objectives a large number of pareto optimum reservoir operating rules is generated. In the second step of the method the performance of all these operating rules is tested with the aid of a model simulating reservoir operation. The results are statistically analyzed and the reliabilities for attaining the various objectives are computed. The third step of the model applies another MODM technique which allows the decision maker - in a computer dialog - to select his optimum reservoir operating rule from the large number of pareto optimum solutions generated in step 1. Here he can specify his preferences for the various objectives. For this purpose two alternative MODM techniques are offered: Compromise Programming and the SEMOPS method. Their performance is shown along with the generation and selection of operating rules for the multi-objective Wupper reservoir system in Germany.     

A COMPLEMENTARY TOOL TO WATER QUALITY INDEX: FUZZY CLUSTERING ANALYSIS1

ABSTRACT: A general methodology for fuzzy clustering analysis is developed and illustrated with a case study of water quality evaluation for Dianshan Lake, Shanghai, China. Fuzzy clustering analysis may be used whenever a composite classification of water quality incorporates multiple parameters. In such cases, the technique may be used as a complement or an alternative to comprehensive assessment. In fuzzy clustering analysis, the classification is determined by a fuzzy relation. After a fuzzy similarity matrix has been established and the fuzzy relation stabilized, a dynamic clustering chart can be developed. Given a suitable threshold, the appropriate classification is worked out. The methodology is relatively simple, and the results can be interpreted to provide valuable information to support decision making and to aid water quality management.     

Conversion of a Missouri River Dam and Reservoir to a Sustainable System: Sediment Management1

Abstract: A present and future challenge for water resources engineers is to extend the useful life of our dams and reservoirs. Ongoing reservoir sedimentation in impoundments must be addressed; sedimentation in many reservoirs already limits project benefits and effective project life. Sustainability requires that incoming sediment be moved downstream past the impounding dam. We use Lewis and Clark Lake, the most downstream of the six Missouri River main stem reservoirs, to demonstrate how a reservoir in advanced stages of its project life could be converted to a sustainable system with local benefits exceeding costs by a factor of 1.5. Full consideration of benefits would further enhance project justification. The proposed strategy involves four phases that will take about 50 years to complete. Cost estimates for this potential project range from the quantitative to the plausible, but it is clear that the results justify a full engineering, environmental, and economic study of this model project. If implemented, the project will create scientific knowledge and develop technologies useful for achieving sustainability at many other reservoirs in the Mississippi River basin and beyond.     

A stochastic fuzzy chance-constrained programming model for energy–environment system planning and management in the City of Beijing

A stochastic and fuzzy chance-constrained programming (SFCCP) model was developed in this study for supporting energy–environment management in the city of Beijing, China. SFCCP was capable of tackling the variables in constraints as fuzzy random variables, which were integration of randomness and vagueness. SFCCP was applied to an energy–environment management system in the city of Beijing. The study results indicated that SFCCP was useful in helping decision makers gain in-depth insights into proposed management system and establish environment-friendly energy allocation alternatives. The application of SFCCP is expected to provide a good demonstration to energy–environment management problems under complex uncertainties.     

OPTIMAL CONTROL OF RESERVOIR RELEASES TO MINIMIZE SEDIMENTATION IN RIVERS AND RESERVOIRS1

ABSTRACT: An optimal control methodology and computational model are developed to evaluate multi‐reservoir release schedules that minimize sediment scour and deposition in rivers and reservoirs. The sedimentation problem is formulated within a discrete‐time optimal control framework in which reservoir releases represent control variables and reservoir bed elevations, storage levels, and river bed elevations represent state variables. Constraints imposed on reservoir storage levels and releases are accommodated using a penalty function method. The optimal control model consists of two interfaced components: a one‐dimensional finite‐difference simulation module used to evaluate flow hydraulics and sediment transport dynamics, and a successive approximation linear quadratic regulator (SALQR) optimization algorithm used to update reservoir release policies and solve the augmented control problem. Hypothetical two‐reservoir and five‐reservoir networks are used to demonstrate the methodology and its capabilities, which is a vital phase towards the development of a more robust optimal control model and application to an existing multiple‐reservoir river network.     

BUFFER STRIPS TO PROTECT WATER SUPPLY RESERVOIRS: A MODEL AND RECOMMENDATIONS1

ABSTRACT: Buffer strips are undisturbed, naturally vegetated zones around water supply reservoirs and their tributaries that are a recognized and integral aspect of watershed management. These strips can be very effective in protecting the quality of public potable water supply reservoirs by removing sediment and associated pollutants, reducing bank erosion, and displacing activities from the water's edge that represent potential sources of nonpoint source pollutant generation. As part of a comprehensive watershed management protect for the State of New Jersey, a parameter-based buffer strip model was developed for application to all watersheds above water supply intakes or reservoirs. Input requirements for the model include a combination of slope, width, and time of travel. The application of the model to a watershed in New Jersey with a recommended buffer strip width that ranges from 50 to 300 feet, depending upon a number of assumptions, results in from 6 to 13 percent of the watershed above the reservoir being occupied by the buffer.     

USE OF THE DELPHI METHOD IN RESOLVING COMPLEX WATER RESOURCES ISSUES1

ABSTRACT: The tri‐state river basins, shared by Georgia, Alabama, and Florida, are being modeled by the U.S. Fish and Wildlife Service and the U.S. Army Corps of Engineers to help facilitate agreement in an acrimonious water dispute among these different state governments. Modeling of such basin reservoir operations requires parallel understanding of several river system components: hydropower production, flood control, municipal and industrial water use, navigation, and reservoir fisheries requirements. The Delphi method, using repetitive surveying of experts, was applied to determine fisheries' water and lake‐level requirements on 25 reservoirs in these interstate basins. The Delphi technique allowed the needs and requirements of fish populations to be brought into the modeling effort on equal footing with other water supply and demand components. When the subject matter is concisely defined and limited, this technique can rapidly assess expert opinion on any natural resource issue, and even move expert opinion toward greater agreement.     

Water Supply Planning Considering Uncertainties in Future Water Demand and Climate: A Case Study in an Illinois Watershed

Ensuring an adequate, reliable, clean, and affordable water supply for citizens and industries requires informed, long-range water supply planning, which is critically important for water security. A balance between water supply and demand must be considered for a long-term plan. However, water demand projections are often highly uncertain. Climate change could impact the hydrologic processes, and consequently, threaten water supply. Thus, understanding the uncertainties in future water demand and climate is critical for developing a sound water supply plan. In Illinois, regional water supply planning attempts to explore the impacts of future water demand and climate on water supply using scenario analyses and hydrologic modeling. This study is aimed at developing a water supply planning framework that considers both future water demand and climate change impacts. This framework is based on the Soil and Water Assessment Tool to simulate the watershed hydrology and conduct scenario analyses that consider the uncertainties in both future water demand and climate as well as their impacts on water supply. The framework was applied to water supply planning efforts in the Kankakee River watershed. The Kankakee River watershed model was calibrated and validated to observed streamflow records at four long-term United States Geological Survey streamflow gages. Because of the many model parameters involved, the calibration process was automated and was followed by a manual refinement, resulting in good model performance. Long-range water demand projections were prepared by the Illinois State Water Survey. Six future water demand scenarios were established based on a suite of assumptions. Climate scenarios were obtained from the Coupled Model Intercomparison Projection Phase 5 datasets. Three representative concentration pathways (RCPs), RCP2.6, RCP4.5, and RCP8.5, are used in the study. The scenario simulation results demonstrated that climate change appears to have a greater impact on water availability in the study area than water demand. The framework developed in this study can also be used to explore the impacts of uncertainties of water demand and climate on water supply and can be extended to other regions and watersheds.     

Comparison of Machine Learning Models Performance on Simulating Reservoir Outflow: A Case Study of Two Reservoirs in Illinois,U.S.A.

Reservoir outflow is an important variable for understanding hydrological processes and water resource management. Natural streamflow variation, in addition to the streamflow regulation provided by dams and reservoirs, can make streamflow difficult to understand and predict. This makes them a challenge to accurately simulate hydrologic processes at a daily scale. In this study, three Machine Learning (ML) algorithms, Random Forest (RF), Support Vector Machine (SVM), and Artificial Neural Network (ANN), were examined and compared to model reservoir outflow. Past, current, and future hydrologic and meteorological data were used as model inputs, and the outflow of next day was used as prediction. Simulation results demonstrated that all three models can reasonably simulate reservoir outflow. For Carlyle Lake, the coefficient of determination and Nash–Sutcliffe efficiency were each close to one for the three models. The coefficient of determination, relative mean bias, and root mean square error indicated that the SVM performed better than the RF and ANN, but the SVM output displayed a larger relative mean bias than that from RF and ANN. For Lake Shelbyville, the ANN model performed better than RF and SVM when considering the coefficient of determination, Nash–Sutcliffe efficiency, relative mean bias, and root mean square error. The study results demonstrate that the three ML algorithms (RF, SVM, and ANN) are all promising tools for simulating reservoir outflow. Both the accuracy and efficacy of the three ML algorithms are considered to support practitioners in planning reservoir management.     

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.