Reservoir Rule Curves Research Articles

Optimal Reservoir Operation with Water Supply Enhancement and Flood Mitigation Objectives Using an Optimization-Simulation Approach

Floods are one of the most destructive natural disasters which compensation of their effects inflicts immense costs especially in areas with human developments such as cities. Moreover, supplying water for demands particularly during the drought period is a challenging issue in water resource planning. The aim of this study is to propose a model for optimal operation of a reservoir with enhancing downstream demands supply and flood damage mitigation objectives. The model is developed by coupling MODSIM, river network simulation DSS with the imperialist competitive optimization algorithm (ICA). Gotvand Dam in southwestern Iran is the case of study and amounts of water storage in the reservoir in daily time-steps are the decision variable. Results indicate efficiency of the proposed optimization-simulation approach, suggesting that flood damages can be controlled with proper planning while ensuring that downstream water demands are satisfied. As an instance of results, the optimum reservoir rule curve obtained by the proposed model is able to manage a flood entering to the reservoir 11 times greater than the safe flow in the downstream reach and release it lower than the safe flow rate.

Development of Future Rule Curves for Multipurpose Reservoir Operation Using Conditional Genetic and Tabu Search Algorithms

Optimal rule curves are necessary guidelines in the reservoir operation that have been used to assess performance of any reservoir to satisfy water supply, irrigation, industrial, hydropower, and environmental conservation requirements. This study applied the conditional genetic algorithm (CGA) and the conditional tabu search algorithm (CTSA) technique to connect with the reservoir simulation model in order to search optimal reservoir rule curves. The Ubolrat Reservoir located in the northeast region of Thailand was an illustrative application including historic monthly inflow, future inflow generated by the SWAT hydrological model using 50‐year future climate data from the PRECIS regional climate model in case of B2 emission scenario by IPCC SRES, water demand, hydrologic data, and physical reservoir data. The future and synthetic inflow data of reservoirs were used to simulate reservoir system for evaluating water situation. The situations of water shortage and excess water were shown in terms of frequency magnitude and duration. The results have shown that the optimal rule curves from CGA and CTSA connected with the simulation model can mitigate drought and flood situations than the existing rule curves. The optimal future rule curves were more suitable for future situations than the other rule curves.

Adaptive reservoir rule curves by optimisation and simulation

Effective reservoir operation is achieved using suitable rule curves to control the release of water following the release criteria. Conditional cuckoo search (CCS) algorithms and conditional particle swarm optimisation (CPSO) were linked with a reservoir simulation model to identify adaptive optimal reservoir rule curves. Three cases (normal, dry and wet years) were considered when producing the rule curves depending on the inflow pattern and inflow period. Lampao reservoir in Thailand was used to illustrate application of the method. The results showed that the new rule curve patterns produced by CCS algorithms and CPSO in a normal year were similar to the patterns obtained by conditional ant colony optimisation and current usage patterns. However, the obtained rule curves for wet and dry years were quite different from those for the normal year. Average water shortages using the normal-year inflow were less than using the dry-year inflow by 24·05% and 18·92% for CCS and CPSO models, respectively. Situations of water shortage when using the normal-year rule curves can best mitigate the water situation. In conclusion, the adaptive rule curves were suitable for reservoir operation under all inflow cases.

Optimal reservoir rule curves under climatic and land use changes for Lampao Dam using Genetic Algorithm

The uncertainties of climate and land use changes have directly impacted the inflows and water resource management in reservoirs. The optimal reservoir rule curve is a tool for the mitigation of droughts and floods, which are situations that occur often. This study applied the Genetic Algorithm (GA) to connect with a reservoir simulation model to search optimal reservoir rule curves during the period 2014-2064 for Lampao Reservoir located in the northeast of Thailand. It considered the impact of climate change with the PRECIS model under two emission scenarios: A2 and B2, and created future land use maps using the CA Markov model, including an assessment of the future inflow into the reservoir using the hydrologic model SWAT in the Upper-Lampao Basin, which is the headwater area of the reservoir. The results showed that the new rule curves were improved by the GA connected simulation model and can mitigate the frequency of water shortage situations and the releases of excess water during inflow changes in the future, including a situation where the water demand increased due to the expansion of irrigation areas.

Performance evaluation of implicit stochastic reservoir operation optimization supported by long-term mean inflow forecast

This study applies implicit stochastic optimization (ISO) to develop monthly operating rules for a reservoir located in Northeast Brazil. The proposed model differs from typical ISO applications as it uses the forecast of the mean inflow for a future horizon instead of the current-month inflow. Initially, a hundred different 100-year monthly inflow scenarios are synthetically generated and employed as input to a deterministic operation optimization model in order to build a database of optimal operating data. Later, such database is used to fit monthly reservoir rule curves by means of nonlinear regression analysis. Finally, the established rule curves are validated by operating the system under 100 new inflow ensembles. The performance of the proposed technique is compared with those provided by the standard reservoir operating policy (SOP), stochastic dynamic programming (SDP) and perfect-forecast deterministic optimization (PFDO). Different forecasting horizons are tested. For all of them, the results indicate the feasibility of using ISO in view of its lower vulnerability in contrast to the SOP as well as the proximity of its operations with those by PFDO. The results also reveal that there is an optimal choice for the forecasting horizon. The comparison between ISO and SDP shows small differences between both, justifying the adoption of ISO for its simplified mathematics as opposed to SDP.

A framework for the assessment of reservoir operation adaptation to climate change in an arid region

It is essential to assess the adaptation of reservoir operation to climate change in arid regions. The main objective of this research is to propose a framework for assessment of reservoir rule-curve (RRC) adaptation for climate change scenarios. The framework is applied to an arid zone in Iran and consists of the three models: downscaling, rainfall-runoff and reservoir optimisation models. LARS-WG is tested in 99% confidence level before to using it as downscaling model. Seven artificial neural network models are proposed, examined and compared with IHACRES to find proper rainfall-runoff model for arid zone. Current and adapted reservoir rule curves are derived by dynamic programming optimisation. The results demonstrate capability of proposed framework in assessment of adaptation and show that global warming negatively influences proposed index (water supply index) in normal and wet years, but has positive influence for dry years. It also improves reservoir reliability, but it cannot restore current reliability.

Effect of Hedging-Integrated Rule Curves on the Performance of the Pong Reservoir (India) During Scenario-Neutral Climate Change Perturbations

This study has evaluated the effects of improved, hedging-integrated reservoir rule curves on the current and climate-change-perturbed future performances of the Pong reservoir, India. The Pong reservoir was formed by impounding the snow- and glacial-dominated Beas River in Himachal Pradesh. Simulated historic and climate-change runoff series by the HYSIM rainfall-runoff model formed the basis of the analysis. The climate perturbations used delta changes in temperature (from 0° to +2 °C) and rainfall (from −10 to +10 % of annual rainfall). Reservoir simulations were then carried out, forced with the simulated runoff scenarios, guided by rule curves derived by a coupled sequent peak algorithm and genetic algorithms optimiser. Reservoir performance was summarised in terms of reliability, resilience, vulnerability and sustainability. The results show that the historic vulnerability reduced from 61 % (no hedging) to 20 % (with hedging), i.e., better than the 25 % vulnerability often assumed tolerable for most water consumers. Climate change perturbations in the rainfall produced the expected outcomes for the runoff, with higher rainfall resulting in more runoff inflow and vice-versa. Reduced runoff caused the vulnerability to worsen to 66 % without hedging; this was improved to 26 % with hedging. The fact that improved operational practices involving hedging can effectively eliminate the impacts of water shortage caused by climate change is a significant outcome of this study.

Systems Approach for Optimal Operation of Water Resources Schemes in Kuttiadi River Basin, Kerala

An optimal operation plan has been developed for the reservoirs in Kuttiadi river basin in Kerala using systems approach. A system consists of three reservoirs namely; Banasurasagar in Wayanad district,Kakkayam and Peruvannamuzhi in Kozhikode district has been taken for the study. Banasurasagar reservoir is in Kabbini river basin, which is an east flowing river and the remaining two are in Kuttiadi river basin, which is a west flowing river. They serve different purposes such as irrigation, domestic water supply and hydropower generation. These purposes were fulfilled based on the Standard Linear Operation Policy (SLOP) developed during the early stages of project formulation. Considering the deficit of water in the region, a system study has been done using multi-reservoir multi-purpose simulation technique, in which reservoir rule curve- based policy to optimally utilize the conservation storage of these three reservoirs have been developed. The generalised simulation model developed at the National Institute of Hydrology has been used to derive the rule levels and simulation of the system. The simulation studies reveal that the Banasurasagar reservoir and Peruvannamuzhi reservoir always serve the purposes of water supply without fail. For Banasurasagar reservoir, irrigation and water supply reliability is found to be 86% where as for Peruvanannamuzhi reservoir, it is 77%. The demand for power generation can be met with 90% dependability. Reservoir linked water supply can be thought of from Banasurasagar reservoir to Wayanad district like water supply from Peruvannamuzhi reservoir to Kozhikode district.

Multi-reservoir joint operating rule in inter-basin water transfer-supply project

The joint operation of inter-basin water transfer-supply (IBWTS) project can be more complex when there is joint water demand in multi-reservoir system and multi-importing reservoirs simultaneously transferring water from exporting reservoir. In this study, a joint operating rule is proposed for the purpose of solving such complex operation problem. This rule is composed of a set of sub-rules, including hedging rule curves of virtual aggregation reservoir (i.e. equivalent reservoir) and other individual reservoirs, water-transfer rule curves of each individual reservoir, as well as some of important assisted rules. These assisted rules refer to allocation models for water transfer-supply. In the proposed rule, an equivalent reservoir is established to determine under what condition the water supply should be reduced and specify the total supplied water for joint water demand (i.e. aggregation method). Allocation models are developed to distribute the total transferred water into each importing reservoir and determine the water releases for joint water demand by each member reservoir of the aggregation system (i.e. decomposition method). And these models are integrated with a set of influence factors such as hydrologic characteristics, reservoir storage or vacant storage, regulating ability, water-supply pressure, and so on. The aggregation of multi-reservoirs and the disaggregation of water quantities are taken into a whole consideration to reduce the complexity in reallocation of water target storage or water release. Finally, the proposed rule is applied to the North-line IBWTS Project in Liaoning Province, China. The results indicate that the proposed rule can take full advantage of hydrologic compensation in basins and capacity compensation in reservoirs. Thus it can improve the utilization efficiency of water resources in system.

Environmental Flows in a Human-Dominated System: Integrated Water Management Strategies for the Rio Grande/Bravo Basin

Water management in the transboundary Rio Grande/Bravo (RGB) Basin, shared by the US and Mexico, is complicated by extreme hydrologic variability, overallocation, and international treaty obligations. Heavy regulation of the RGB has degraded binationally protected ecosystems along the Big Bend Reach of the RGB. This study addresses the need for integrated water management in Big Bend by developing an alternative reservoir operation policy to provide environmental flows while reducing water management trade-offs. A reach-scale water planning model was used to represent historical hydrology (1955–2009), water allocation, and reservoir operations, and key human water management objectives (water supply, flood control, and binational treaty obligations) were quantified. Spatially distributed environmental flow objectives and an alternative reservoir rule curve were developed. We simulated current and alternative water management policies and used an iterative simulation–evaluation process to evaluate alternative policies based on water system performance criteria with respect to specified objectives. A single optimal policy was identified that maximized environmental flows while maintaining specified human objectives. By changing the timing but not the volume of releases, the proposed reservoir re-operation policy has the potential to sustain key ecological and geomorphic functions in Big Bend without significantly impacting current water management objectives. The proposed policy also improved water supply provisions, reduced average annual flood risk, and maintained historical treaty provisions. Copyright © 2014 John Wiley & Sons, Ltd.

Determination of cost coefficients of a priority-based water allocation linear programming model – a network flow approach

Abstract. This paper presents a method to establish the objective function of a network flow programming model for simulating river–reservoir system operations and associated water allocation, with an emphasis on situations when the links other than demand or storage have to be assigned with nonzero cost coefficients. The method preserves the priorities defined by rule curves of reservoir, operational preferences for conveying water, allocation of storage among multiple reservoirs, and transbasin water diversions. Path enumeration analysis transforms these water allocation rules into linear constraints that can be solved to determine link cost coefficients. An approach to prune the original system into a reduced network is proposed to establish the precise constraints of nonzero cost coefficients, which can then be efficiently solved. The cost coefficients for the water allocation in the Feitsui and Shihmen reservoirs' joint operating system of northern Taiwan was adequately assigned by the proposed method. This case study demonstrates how practitioners can correctly utilize network-flow-based models to allocate water supply throughout complex systems that are subject to strict operating rules.

A New Functional Approach for Searching Optimal Reservoir Rule Curves

Rule curves are guidelines for long term reservoir operation. An efficient optimization technique is required to find the optimal rule curves that can mitigate water shortage in long-term operation. A new functional approach was proposed to search the optimal rule curves of reservoir. The results indicated that the situations of water shortage and excess release water of using the new approach are smaller than the situations of using the existing rule curves.

Coupled-operations model and a conditional differential evolution algorithm for improving reservoir management

This paper proposes a flexible methodology for finding the optimal control of reservoir operations, which is adopted for simulating a storage system including a large reservoir simulation model and a numerical search method for searching decision variables. The optimization model used was a conditional differential evolution algorithm (CDE). The model was connected to reservoir simulation model for searching the decision variables in reservoir management. The reservoir management model was applied to Lampao reservoir in Kalasin province located in the northeast of Thailand. This study considers the criteria of minimum water shortages and downstream flood control. There were synthetic inflow data for evaluating the performance of the reservoir operating rule curves. It was found that the reservoir operating rule curves from the CDE showed a lower frequency and quantity of water shortage than the existing reservoir operating rule curve. In addition, the flood frequency and the flood quantity were reduced. The results also demonstrated that the CDE provided better reservoir operation in any probability of inflow situations. Further, it indicated that the reservoir operating rule curves obtained from this research could effectively support the increasing water requirements to a growing population. Key words: A conditional differential evolution algorithm (CDE), simulation model, optimization technique, reservoir rule curves

Evaluating changes to reservoir rule curves using historical water-level data

Flood control reservoirs are typically managed through rule curves (i.e. target water levels) which control the storage and release timing of flood waters. Changes to rule curves are often contemplated and requested by various user groups and management agencies with no information available about the actual flood risk of such requests. Methods of estimating flood risk in reservoirs are not easily available to those unfamiliar with hydrological models that track water movement through a river basin. We developed a quantile regression model that uses readily available daily water-level data to estimate risk of spilling. Our model provided a relatively simple process for estimating the maximum applicable water level under a specific flood risk for any day of the year. This water level represents an upper-limit umbrella under which water levels can be operated in a variety of ways. Our model allows the visualization of water-level management under a user-specified flood risk and provides a framework for incorporating the effect of a changing environment on water-level management in reservoirs, but is not designed to replace existing hydrological models. The model can improve communication and collaboration among agencies responsible for managing natural resources dependent on reservoir water levels.

Optimal Reservoir Rule Curves Considering Conditional Ant Colony Optimization with Simulation Model

Optimal Reservoir Rule Curves Considering Conditional Ant Colony Optimization with Simulation Model

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.

Dynamic Modelling of the Impact of Climate Change and Power Flow Management Options using STELLA: Application to the Steephill Falls Reservoir, Ontario, Canada

This paper presents a dynamic modelling framework for evaluating the impact of climate change and flow management options on a hydroelectric power reservoir. The model couples the HBV (Hydrologiska Byrns Vattenbalansavdelning) rainfall-runoff model to a generic reservoir routing model. The efficacy of the model was tested on the Steephill Falls hydropower facility located in the Magpie River watershed in Northern Ontario. Both the impact of climate change and future energy demands were evaluated. Using a statistical downscaling approach, future climate under Intergovernmental Panel on Climate Change (IPCC) A1B and A2 emission scenarios was projected from the Canadian Global Circulation Model 3 (CGCM3). Both scenarios suggest a significantly increasing trend in air temperature (p < 0.001) corresponding to a 1.7C increase by the middle of the century and a 2.9C to 3.7C increase by the end of the century relative to the baseline period (19702000). The model performed well in simulating the inter-annual seasonal dynamics of the reservoir. Plausible climate-induced increase in runoff input into the reservoir might be counterbalanced by increased drawdown caused by increasing energy demands and water users, resulting in increased pressure to adjust lower reservoir rule curves, in-stream flow requirements downstream, or a combination of both.

Multi-tier interactive genetic algorithms for the optimization of long-term reservoir operation

Genetic algorithms (GAs) are well known optimization methods. However, complicated systems with high dimensional variables, such as long-term reservoir operation, usually prevent the methods from reaching optimal solutions. This study proposes a multi-tier interactive genetic algorithm (MIGA) which decomposes a complicated system (long series) into several small-scale sub-systems (sub-series) with GA applied to each sub-system and the multi-tier (key) information mutually interacts among individual sub-systems to find the optimal solution of long-term reservoir operation. To retain the integrity of the original system, over the multi-tier architecture, an operation strategy is designed to concatenate the primary tier and the allocation tiers by providing key information from the primary tier to the allocation tiers when initializing populations in each sub-system. The Shihmen Reservoir in Taiwan is used as a case study. For comparison, three long-term operation results of a sole GA search and a simulation based on the reservoir rule curves are compared with that of MIGA. The results demonstrate that MIGA is far more efficient than the sole GA and can successfully and efficiently increase the possibility of achieving an optimal solution. The improvement rate of fitness values increases more than 25%, and the computation time dramatically decreases 80% in a 20-year long-term operation case. The MIGA with the flexibility of decomposition strategies proposed in this study can be effectively and suitably used in long-term reservoir operation or systems with similar conditions.

Optimal reservoir rule curves using simulated annealing

Reservoir rule curves are basic guides for the long-term operation of reservoir systems. This paper presents a simulated annealing (SA) algorithm connected with a simulation model to determine optimal reservoir rule curves. The proposed model was applied to the Bhumibol and Sirikit reservoirs in Thailand. The pattern of the obtained rule curves was similar to existing rule curves and the rule curves obtained using genetic algorithms (GAs). The obtained rule curves were used to simulate the Bhumibol and Sirikit reservoir systems with synthetic inflows and these results were compared with the GA-obtained rule curves. The results from the two techniques, in considering both water shortage and excess release of water, were analogous. This indicates that the proposed SA algorithm is effective in determining optimal rule curves for reservoirs.

Applying Multiobjective Genetic Algorithm to Analyze the Conflict among Different Water Use Sectors during Drought Period

Water deficits often occur during the drought season and may cause water conflicts among various water use sectors. The reservoir rule curve operation is commonly used to avoid extreme water shortage during droughts in Taiwan. When applying the rule curve operation, the water supply discounting ratio for different sectors implies a trade-off of water deficit impact among sectors. This study therefore develops a multiobjective water resource management model to evaluate the trade-off curve of water deficit impact between irrigation and public sectors to facilitate negotiation between the sectors for obtaining acceptable discounting ratios. The study uses the shortage index to assess water deficit impact. The proposed model integrates operating rules, the stepwise optimal water allocation model, and the convex hull multiobjective genetic algorithm to solve the multiobjective regional water allocation planning problem. The computed trade-off curve, noninferior solutions, provides relevant information to faci...