Water Release Policy Research Articles

A Proposed Multi‐Objective, Multi‐Stage Stochastic Programming With Recourse Model for Reservoir Management and Operation

AbstractWe present a multi‐objective, multi‐stage stochastic programming with recourse model for reservoir management and operation, where we use utility theory to select the best compromise solution from the Pareto front. A multi‐stage streamflow scenario tree is generated first by the neural gas method. Then the Pareto front at each stage is produced by a modified constrained NSGA‐II. A single best compromise solution on the Pareto front must be selected for the immediate stage and the model moves forward one stage and is re‐optimized over a moving planning horizon of fixed duration. A key contribution of this study is the selection of the best compromise solution, which is achieved by a proposed linear spline utility function allied with regression. Our proposed utility function has the following advantages: (a) It satisfies the law of diminishing marginal rate of substitution, (b) it does not rely on the pre‐specified weight or goal, and (c) it selects the best compromise solution that is likely to fall in the “knee regions” of the Pareto front. We apply the proposed optimization model to the Three Gorges Reservoir in China. The two conflicting objectives are (a) maximizing the total expected energy output in the planning horizon, and (b) maximizing the average expected ecological benefits in the planning horizon. The results show that the proposed model produces the optimal water release policy successfully under different hydrological scenarios, considering both the inflow uncertainty and the tradeoff between the two conflicting objectives.

Water storage and release policies for all large reservoirs of conterminous United States

Large-scale hydrological and water resource models (LHMs) require water storage and release schemes to represent flow regulation by reservoirs. Owing to a lack of observed reservoir operations, state-of-the-art LHMs deploy a generic reservoir scheme that may fail to represent local operating behaviors. Here we introduce a new dataset of bespoke water storage and release policies for 1,930 reservoirs of conterminous United States. The Inferred Storage Targets and Release Functions (ISTARF-CONUS) dataset relies on a new inventory of observed daily reservoir operations (ResOpsUS) to generate reservoir operating rules for 595 data-rich reservoirs. These functions are developed in a standardized form that allows for extrapolation of operating schemes to 1,335 data-scarce reservoirs—leading to the first inventory of empirically derived reservoir operating policies for all large CONUS reservoirs documented in the Global Reservoir and Dams (GRanD) database. Evaluation of the new scheme in daily simulations forced with observed inflow demonstrates substantial and robust improvement for both release and storage relative to the popular Hanasaki method. Performance of the extrapolation approach for data-scarce reservoirs is evaluated with leave-one-out validation and is shown to also offer modest gains on average over Hanasaki. ISTARF-CONUS may be readily adopted in any LHM featuring large reservoirs of the conterminous United States.

Improving Dam and Reservoir Operation Rules Using Stochastic Dynamic Programming and Artificial Neural Network Integration Model

The simulation elevation-surface area-storage interrelationship of a reservoir is a crucial task in developing ideal water release policies for reservoir and dam operations. In this study, an inclusive (stochastic dynamic programming-artificial neural network (SDP-ANN)) model was established and applied to obtain an ideal reservoir operation strategy for Sg. Langat reservoir in Malaysia. The problems associated with the management of water resources mostly relate to uncertainty and the stochastic nature of the reservoir inflow, and the SDP-ANN model is meant to consider uncertainty in the input parameters such as reservoir inflow and reservoir evaporation losses. The performance of the SDP-ANN model was compared to that of the stochastic dynamic programming-autoregression (AR) model. The primary aim of the model is to decrease the squared deviation from the desired water release, which we determined by comparing the SDP-AR and SDP-ANN model performances. The results indicate that the SDP-ANN model demonstrated greater resilience and reliability with a lower supply deficit. Consequently, the case study results confirm that the SDP-ANN model performs better than the SDP-AR model in obtaining the best parameters for the reservoir operation. Specifically, a comparison of the models shows that the proposed Model 2 increased the reliability and resilience of the system by 7.5% and 6.3%, respectively.

A novel Master–Slave optimization algorithm for generating an optimal release policy in case of reservoir operation

Dams and reservoirs provide decision-makers and managers with appropriate control on the available water resources, allowing the implementation of various strategies for the most efficient usage of the available water resources. In areas where water supply exhibits significant temporal variation when compared with the demand, the challenge is to bridge the gap and achieve an optimal match between the water supply and demand patterns. Therefore, the release of water from reservoirs should be controlled to ensure that the operation rule for the available water storage in the reservoir is optimized to satisfy the future water demands. This level of optimal control can only be achieved using an efficient optimization algorithm to optimally derive the operation rule for such a complex water system. Herein, two main methods have been considered to tackle this water resource management problem. First, three different optimization algorithms, namely particle swarm optimization, differential evolution, and whale optimization algorithm, have been applied. In addition, two different optimization algorithms, namely crow search algorithm and master–slave algorithm, have been introduced to generate an optimal rule for water release policy. Further, the proposed optimization algorithms have been applied to one of the most critical dam and reservoir water systems, namely the Aswan High Dam (AHD), which controls almost 95% of Egypt’s water resources. The current operation of AHD using the existing optimization rules resulted in a mismatch between the water supply and water demand. In other words, the water availability could be higher than the water demand during a certain period, whereas it could be less than the water demand during another period. The results denoted that the master–slave algorithm outperforms the remaining algorithms and generates an optimization rule that minimizes the mismatch between the water supply and water demand.

An Ecologically Oriented Operation Strategy for a Multi-Reservoir System: A Case Study of the Middle and Lower Han River Basin, China

Abstract Constructing and operating a multi-reservoir system changes the natural flow regime of rivers, and thus imposes adverse impacts on riverine ecosystems. To balance human needs with ecosystem needs, this study proposes an ecologically oriented operation strategy for a multi-reservoir system that integrates environmental flow requirements into the joint operation of a multi-reservoir system in order to maintain different ecological functions throughout the river. This strategy is a combination of a regular optimal operation scheme and a series of real-time ecological operation schemes. During time periods when the incompatibilities between human water needs and ecosystem needs for environmental flows are relatively small, the regular optimal operation scheme is implemented in order to maximize multiple human water-use benefits under the constraints of a minimum water-release policy. During time periods when reservoir-induced hydrological alteration imposes significant negative impacts on the river’s key ecological functions, real-time ecological operation schemes are implemented in order to modify the outflow from reservoirs to meet the environmental flow requirements of these functions. The practical use of this strategy is demonstrated for the simulation operation of a large-scale multi-reservoir system which located in the middle and lower Han River Basin in China. The results indicate that the real-time ecological operation schemes ensure the environmental flow requirements of the river’s key ecological functions, and that adverse impacts on human water-use benefits can be compensated for by the regular optimal operation scheme. The ecologically oriented operation strategy for a multi-reservoir system that is proposed in this study enriches the theoretical application of the multi-reservoir system joint operation which considers environmental flow requirements.

System performances analysis of reservoir optimization–simulation model in application of artificial bee colony algorithm

In reservoir system operation, optimization is very much essential and the compatibility of different optimization techniques is essential to be checked by some performance checking indices. In this study, various types of performance-measuring index are used and compared to provide a complete knowledge on adopting different approaches. Here, the considered performance-measuring indicators will check the operation policy in terms of three different scenarios—how the method is efficient in achieving best results (reliability); how vulnerable the method is for different critical situation (vulnerability); and how capable it is to handle a failure of the model (resiliency). Therefore, the study proposed the artificial bee colony (ABC) optimization technique to develop an optimal water release policy for the well-known Aswan High Dam, Egypt. Particle swarm optimization, genetic algorithm and neural network-based stochastic dynamic programming are also used in a view of comparing model performances. A release curve is developed for every month as a guidance to the decision maker. Simulation has been done for each method using historical actual inflow data, and reliability, resiliency and vulnerability are measured. All model indicators proved that the release policy provided by ABC optimization outperforms in terms of achieving minimum water deficit, less waste of water and handling critical situations.

An environmental perspective on the water management policies of the Upper Delaware River Basin

Since 1954, the Delaware River has been managed under the framework of a Supreme Court decree and the subsequent concomitant intergovernmental collaboration between New York State, New Jersey, Pennsylvania, Delaware, New York City (NYC) and the US federal government. Taking an environmental perspective, we review the evolution of water release policies for three NYC reservoirs from the issuance of the 1954 decree through the implementation of the Flexible Flow Management Program (FFMP) of 2007–2015 and examine the policies' impact on the upper Delaware River. We describe governmental and institutional constraints on the development of Delaware water policy and show how modifications of release policies have enhanced aquatic habitat and ecological health in the upper Delaware while reliably delivering water to NYC and the Delaware's other principal stakeholders. We describe the development of the FFMP in 2006, its subsequent modification, and its augmentation by NYC's Operations Support Tool in 2012. Finally, we discuss the negative ecological consequences of the 2010–2016 stalemate on Delaware water policy resulting from conflicts between the decree parties about current and future water rights, and how the stalemate derives partially from the decision structure imposed by the 1954 decree and the Good Faith Agreement of 1983.

An Integrated Water Resources and Economic Approach for Optimizing Water Allocation Policies

Reservoir/river systems analysis models are generally used in the formulation and evaluation of alternative plans for responding to water related problems and needs. One of the main problems is the water resources allocation and the cost associated with pumping, if needed. Taking the appropriate decision is considered as a techno-economic issue. The case study presented in this paper involves a complex system of three dams, two pumping stations and two diversion structures all serving an agricultural production unit. The objective of this research is to determine a suitable and feasible water allocation/pumping policy as a “trade-off” between minimizing the water deficiency and the cost of pumping. To achieve this objective, a water resources model was developed using HEC-5. A multi-criteria decision approach was implemented to determine the most appropriate water release policy and the capacity of the water diversion facilities. The parameters used were subject to a sensitivity analysis to assess their relative impact on the determined policy. The suggested release policy allows a reduction of half the total of the pumping costs with only 3% reduction in the water allocation reliability, as measured by the failure frequency of demand satisfaction and the average shortage index.

A Factorial-based Dynamic Analysis Method for Reservoir Operation Under Fuzzy-stochastic Uncertainties

In this study, a factorial-based fuzzy-stochastic dynamic programming (FFS-DP) method is developed for tackling multiple uncertainties including fuzziness, randomness and their interaction in reservoir operation management (ROM). FFS-DP is framed on the integration of stochastic dynamic programming, fuzzy-Markov chain, vertex analysis and factorial analysis techniques. It can not only deal with the conventional optimization problem for reflecting dynamic and uncertain features in ROM, but also obtain detailed effects of uncertain parameters and their interactions on the system performance. The developed method is applied to a case study of a reservoir operation system, where the local authority is in charge of allocating relative scant water to the downstream municipality. The results obtained can help the local authority identify desired water release policies under uncertain system conditions. Besides, the results simultaneously indicate that significant factors and their interactions can be identified in ROM. Moreover, the results can be further analyzed for generating optimal parameter inputs to obtain maximized system benefits.

Real-Time Operation of Reservoir System by Genetic Programming

Reservoir operation policy depends on specific values of deterministic variables and predictable actions as well as stochastic variables, in which small differences affect water release and reservoir operation efficiency. Operational rule curves of reservoir are policies which relate water release to the deterministic and stochastic variables such as storage volume and inflow. To operate a reservoir system in real time, a prediction model may be coupled with rule curves to estimate inflow as a stochastic variable. Inappropriate selection of this prediction model increases calculations and impacts the reservoir operation efficiency. Thus, extraction of an operational policy simultaneously with inflow prediction helps the operator to make an appropriate decision to calculate how much water to release from the reservoir without employing a prediction model. This paper addresses the use of genetic programming (GP) to develop a reservoir operation policy simultaneously with inflow prediction. To determine a water release policy, two operational rule curves are considered in each period by using (1) inflow and storage volume at the beginning of each period and (2) inflow of the 1st, 2nd, 12th previous periods and storage volume at the beginning of each period. The obtained objective functions of those rules have only 4.86 and 0.44 % difference in the training and testing data sets. These results indicate that the proposed rule based on deterministic variables is effective in determining optimal rule curves simultaneously with inflow prediction for reservoirs.

Optimization Model for Management of Water Quality in a Tidal River Using Upstream Releases

This study deals with the management of water quality in a tidal river through optimal releases of water from an upstream environmental reservoir. A management model is proposed based on the simulation-optimization framework, in which a complete hydrodynamic model for transport of BOD and DO in a tidal river is linked to Simulated Annealing (SA) algorithm for optimization. The proposed management model is used to investigate the effect of tidal variation on the constant minimum in stream discharge that is required to maintain the water quality, for a given pollutant loading. It is demonstrated how the total upstream release volume can be minimized, while still maintaining the desired water quality, by resorting to an optimum temporal variation in releases from the upstream environmental reservoir. The performance of the methodology is evaluated for an illustrative river. The proposed model will be helpful in arriving at best water release policy for maintaining water quality in tidal rivers for given tidal variation and pollutant loading.

Optimal Reservoir Release Policy Considering Heterogeneity of Command Area by Elitist Genetic Algorithm

A number of models with conventional optimization techniques have been developed for optimization of reservoir water release policies. However these models are not able to consider the heterogeneity in the command area of the reservoir appropriately, due to non linear nature of the processes involved. The optimization model based on genetic algorithm (GA) can deal with the non linearity due to its inherent ability to consider complex simulation model as evaluation function for optimization. GA based models available in literature generally minimize the water deficits and do not optimize the total net benefits through optimal reservoir release policies. The present study focuses on optimum releases from the reservoir considering heterogeneity of the command area and responses of the command area to the releases instead of minimizing only the reservoir storage volumes. An optimization model has been developed for the reservoir releases based on elitist GA approach considering the heterogeneity of the command area. The developed model was applied to Waghad irrigation project in upper Godavari basin of Maharashtra, India. The results showed that 19% increase in the total net benefits could be possible by adopting the proposed water release policy over the present practice keeping same distribution of area under different crops. The model presented in this study can also optimize the crop area under irrigation. It is found that irrigated area can be increased to 50% of ICA (Irrigable Command Area) from the existing 23% with resulting addition to total net benefits by 31%. The effect of adopting the proposed irrigation schedule and increased irrigation areas would be to increase the net benefits to existing farmers.

A fuzzy-Markov-chain-based analysis method for reservoir operation

In this study, a fuzzy-Markov-chain-based stochastic dynamic programming (FM-SDP) method is developed for tackling uncertainties expressed as fuzzy sets and distributions with fuzzy probability (DFPs) in reservoir operation. The concept of DFPs used in Markov chain is presented as an extended form for expressing uncertainties including both stochastic and fuzzy characteristics. A fuzzy dominance index analysis approach is proposed for solving multiple fuzzy sets and DPFs in the proposed FM-SDP model. Solutions under a set of α-cut levels and fuzzy dominance indices can be generated by solving a series of deterministic submodels. The developed method is applied to a case study of a reservoir operation system. Solutions from FM-SDP provide a range of desired water-release policies under various system conditions for reservoir operation decision makers, reflecting dynamic and dual uncertain features of water availability simultaneously. The results indicate that the FM-SDP method could be applicable to practical problems for decision makers to obtain insight regarding the tradeoffs between economic and system reliability criteria. Willingness to obtain a lower benefit may guarantee meeting system-constraint demands; conversely, a desire to acquire a higher benefit could run into a higher risk of violating system constraints.

Introduction: 2010 Franz Edelman Award for Achievement in Operations Research and the Management Sciences

This special issue of Interfaces is devoted to the finalists of the 39th annual competition for the Franz Edelman Award for Achievement in Operations Research and the Management Sciences, the profession's prestigious award for the practice of operations research. The six finalists this year cover a wide range of industries, functions, and countries around the globe. The winning entry demonstrates the use of operations research (OR) by INDEVAL, Mexico's central financial securities depository, to decrease daily liquidity requirements by $130 billion. One finalist entry describes the OR analyses and the politics that led to the implementation of optimization-based water-release policies by the Delaware River Basin Commission. Another entry shows how OR models were used to increase the brand value of Deutsche Post DHL in Germany by over $1 billion in five years. A fourth reflects the development and deployment of OR-based tools at New Brunswick Department of Transportation to save over $70 million per year in maintaining 18,000 kilometers of roads. Yet another entry discusses the use of single-stage and multiechelon inventory optimization techniques to reduce Procter & Gamble's investment in inventory by $1.5 billion. A sixth entry describes the use of simulation models to save approximately $230 million over a 10-year period at the Sasol Synfuels coal-to-liquids conversion facility in South Africa.

Contributors

Contributors

Optimized reservoir operation to balance human and riverine ecosystem needs: model development, and a case study for the Tanghe reservoir, Tang river basin, China

AbstractReservoirs impose many negative impacts on riverine ecosystems. To balance human and ecosystem needs, we propose a reservoir operation method that combines reservoir operating rule curves with the regulated minimum water release policy to meet the environmental flow requirements of riverine ecosystems. Based on the relative positions of the reservoir and the water intakes, we consider three scenarios: water used for human needs (including industrial, domestic and agricultural) is directly withdrawn from (1) the reservoir; (2) both reservoirs and downstream river channels and (3) downstream river. The proposed method offers two advantages over traditional methods: First, it can be applied to finding the optimal reservoir operating rule curves with the consideration of environmental flow requirement, which is beneficial to the sustainable water uses. Second, it avoids a problem with traditional approaches, which prescribe the minimum environmental flow requirements as the regulated minimum environmental flow releases from reservoirs, implicitly giving lower priority to the riverine ecosystem. Our method instead determines the optimal regulated minimum releases of water to sustain environmental flows while more effectively balancing human and ecosystem needs. To demonstrate practical use of the model, we present a case study for operation of the Tanghe reservoir in China's Tang river basin for the three above‐mentioned scenarios. The results demonstrate that this approach will help the reservoir's managers satisfy both human and environmental requirements. Copyright © 2009 John Wiley & Sons, Ltd.

Water Release Policy Effects on the Shortage Characteristics for the Shihmen Reservoir System during Droughts

Drought-induced shortages are inevitable because of unexpected abnormal dry weather and the increasing need for water resources. Therefore, assessment of possible shortage conditions for a specific water supply system is an essential component in water resources planning and management. In this study, the shortage characteristics for the Shihmen Reservoir in Taiwan are investigated. A description of the reservoir yield in terms of the shortage frequency, magnitude, and duration is developed first. The derived reservoir yield description under a given operating policy and demand includes the reliability, total shortage rate, frequency, single period shortage, event shortage duration and magnitude, and interarrival time of shortage events. Hedging is a common measure adopted in reservoir operation that involves accepting a small current deficit to reduce future severe shortages. The reservoir supply index is then developed to trigger hedging in this study. The shortage characteristics for different lead-time hedging rules show that the derived reservoir supply index is a useful indicator for triggering hedging and the differences among reservoir performance for various release policies are easily compared using the derived reservoir yield description in terms of probabilistic shortage characteristics.

Geomorphological impacts of Inanda Dam on the Mgeni estuary, north of Durban, South Africa)

Completed in 1988 at a site some 32 km from the Mgeni river mouth, the Inanda Dam may have influenced bed load transport and deposition. The aims of this study were to ascertain whether the dam had affected fluvial sediment delivery to the lower channel, whether the sediment characteristics and bedform of the estuary had been modified and, within this context, to predict the likely effects of continued sand mining on the Mgeni estuary. Re-examination of estuarine cross sections originally surveyed prior to dam completion, comparison of present estuarine sediment characteristics with those of pre-dam sediments and a bottom survey of the Inanda Dam itself were key elements in the analysis. Mean annual discharge of the Mgeni river has reduced by 4% since dam construction and changes in discharge regime caused by the water release policy resulted in an increase in competent discharge events. Retention of sediment behind the dam wall had led to reduction in available downstream sediment. Sediment volume in the estuary had not changed significantly since 1989, although sediment calibre is now much finer. These changes will probably signal the end of sand mining in the lower river and will ultimately cause the estuary to deepen as residual pre-dam sediment is flushed through and not replaced by new material from upstream. Since Mgeni sediment is a source of material for natural beach nourishment, it is likely that beaches will become narrower.

Reservoir operation policies for optimizing energy generation at the Shiroro Dam

Reservoir water release policies are computed for the Shiroro Dam hydroelectric power scheme in Northern Nigeria, using a probabilistic dynamic programming model. The state variable is the reservoir storage volume, while the uncertain nature of the inflow process is accounted for in the model by considering different possible inflow volumes and their inflow probabilities. Simulation of the reservoir operations with the derived policies show that on the average the hydrosystem has acceptable reliability when two units are in use, at 45% design power plant factor. At 70% power plant factor, which is the desired optimum for the power system in Nigeria, system failures are frequent and, in most cases, severe. For normal operation of the Shiroro Dam hydroelectric power system, two or three generating units, running at 40–50% power plant factor is recommended.

Optimal Cropping Pattern for Basin in India

Optimization techniques can be used for deciding cropping pattern for an agricultural land. In the present study an alluvial tract between two rivers in Northern India is considered for such a study. Total water resources of the basin, i.e., surface water and ground water, are used in determining an optimal cropping pattern and optimal water release policy from canals and tubewells during various months in a year for maximizing the net benefits. Linear programming is used for this optimization. Sensitivity analysis is carried out by varying the parameters that affect the optimal solution such as quantity of ground water pumped, area irrigated, operating costs of canals and tubewells, a fixed variation in the rainfall, and value of crops.