Derivation of Optimal Hedging Rules for a Water-supply Reservoir through Compromise Programming

This study derives optimal hedging rules for simultaneously minimizing short- and long-term shortage characteristics for a water-supply reservoir. Hedging is an effective measure to reduce a high-percentage single period shortage, but at a cost of more frequent small shortages. Thus simultaneously minimizing the maximum monthly shortage and the shortage ratio (defined as the ratio of total shortages to total demands) over the analysis horizon is the operation goal of a water-supply reservoir to derive optimal hedging rules. Two types of hedging are explored in this study: the first uses water availability defined as storage plus inflow, while the second depends on the potential shortage conditions within a specific future lead-time period. The compromise programming is employed to solve this conflicting multiobjective problem. The optimal hedging rules under given reservoir inflow are derived first. Because future inflow cannot be known exactly in advance, the monthly decile inflows are suggested as a surrogate for forecast of future inflows in hedging rules for real-time reservoir operations. The results show that the suggested method can effectively achieve the reservoir operation goal. The merits of the proposed methodology are demonstrated with an application to the Shihmen reservoir in Taiwan.     

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.     

Operating rules of irrigation reservoir under climate change and its application for the Dongwushi Reservoir in China

Since agriculture development would be affected by climate change, the reservoir operation for agricultural irrigation should be adjusted. However, there are to date few literatures addressing how to design adaptive operating rules for an irrigation reservoir. This study aims to analyze the adaption of fixed operating rules and to derive adaptive operating rules under climate change. The deterministic optimization model is established with the solving method of two-dimensional dynamic programming (TDDP), and its optimal trajectory is supplied to derive reservoir operating rules at time intervals of crop growth periods. Then, two alternative operating rules, including fixed operating rules based on historical data and adaptive operating rules based on climate change data, are extracted using the fitting method with the multiple linear regression model. The alteration of reservoir inflow under climate change is calculated by the Budyko formula. A case study of the China’s Dongwushi Reservoir shows that: (1) fixed operating rules are unable to adapt climate change in the future scenario. Thus, adaptive operating rules should be established, (2) adaptive operating rules can reduce profits loss resulting from climate change, and improve field soil water storages, and (3) precipitation reduction by 7%/40a is the major cause for agricultural profits loss, whereas, the decrement of agricultural profits is less than that of precipitation, which indicates agricultural crops have the resilience to resist the adverse influence from precipitation decrease. These findings are helpful for adaptive operation of irrigation reservoirs under climate change.     

Reservoir Operation Incorporating Hedging Rules and Operational Inflow Forecasts

Reservoir operation incorporating a naïve hedging strategy and operational inflow forecasting is studied in this paper. Gridded precipitation forecasts from climate model, ECHAM4.5, are used as potential predictors for reservoir inflow forecasting. In building a statistical predicting model, principal component analysis (PCA) is used to reduce the dimension of the regression model. Performance evaluation indices, including water supply satisfaction ratio, environmental flow satisfaction ratio, end-of-month storage satisfaction ratio and flood prevention capacity index, are defined. Three scenarios where a naïve hedging operation rule under different set of reservoir inflow are investigated. These are evaluated for a water supply reservoir, Falls Lake Reservoir, at Neuse River in the southeast United State. Reservoir simulation with monthly average inflow serves as a benchmark. The utility of operational inflow forecasts is quantified by the improvements of performance indices. Results show that reservoir operation under perfect inflow forecasting has the highest values for most indices. Compared to climatology, operational inflow forecasts result in higher index values. Among all the performance indices, end-of-month storage satisfaction ratio is the most sensitive index to inflow information. Limitation of this study and further work is also discussed.     

Improving the Summer Power Generation of a Hydropower Reservoir Using the Modified Multi-Step Ahead Time-Varying Hedging Rule

This paper aims to improve summer power generation of the Yeywa Hydropower Reservoir in Myanmar using the modified multi-step ahead time-varying hedging (TVH) rule as a case study. The results of the TVH rules were compared with the standard operation policy (SOP) rule, the binary standard operation policy (BSOP) rule, the discrete hedging (DH) rule, the standard hedging (SH) rule, the one-point hedging (OPH) rule, and the two-point hedging (TPH) rule. The Multi-Objective Genetic Algorithm (MOGA) was utilized to drive the optimal Pareto fronts for the hedging rules. The results demonstrated that the TVH rules had higher performance than the other rules and showed improvements in power generation not only during the summer period but also over the entire period.

     

Evaluation and selection of hedging policies using stochastic reservoir simulation

A hedging policy is characterized by three parameters, namely, starting water availability (SWA), ending water availability (EWA) and hedging factor (HF). The effects of these three parameters on the reservoir performance indicators have been evaluated and discussed for a southwest monsoon-dependent within-year reservoir system in southern India. For the performance evaluation, synthetically generated periodic inflow sequences from a periodic autoregressive model have been used. Quite a number of the 1800 hedging policies considered for the reservoir system, yield a better overall performance compared to the standard operating policy (SOP). Reliability, Resilience and vulnerability are found to increase with SWA for a specified EWA. On the other hand, all these performance indicators are found to decrease with EWA for a specified SWA. Hence, it is desirable to start the hedging at reasonably high SWA. All performance indicators remain practically constant at higher ranges of EWA for a given SWA. If hedging is started when there is enough water in storage, reliability, resilience and average deficit increase with degree of hedging, whereas vulnerability decreases significantly up to a hedging factor of 0.3. An interactive computer program has been developed for the selection of compromising hedging policies, and its usefulness has been discussed.     

A realistic linear decision rule for reservoir management

A generalized linear decision rule is presented which takes into account the aspect of spill in a multi-lag LDR model. The proposed rule incorporates past inflow experience to determine the optimum release rules based on a stochastic (linear) programming optimization model. It also prescribes a procedure of determining spill, should it occur, and the method of adjusting the release policy, accordingly, for the subsequent periods, which are directly affected by the spill of the current period. The use of the rule also makes it possible to produce a specification for a reservoir with a smaller capacity by taking liberal constraints on the reservoir freeboard during the monsoon months. The problem is solved, for the purpose of illustration, using the historical data of a river located in central India. Two synthetic streamflow series of a duration of 50 years each are generated under lognormal flow assumption. The prescribed release rules are applied to a hypothetical reservoir with the optimum capacity determined by the linear programming method, and the generated series as the inflow. The results and findings are quite satisfactory.     

Optimization of Multi-Reservoir Operating Rules for a Water Supply System

To obtain the optimal releases of the multi-reservoir system, two sets of joint operating rules (JOR-I and JOR-II) are presented based on the aggregation-disaggregation approach and multi-reservoir approach respectively. In JOR-I, all reservoirs are aggregated to an equivalent reservoir, the operating rules of which, the release rule of the system is optimized following operating rule curves coupled with hedging rules. Then the system release is disaggregated into each reservoir according to water supply priorities and the dynamic demand partition approach. In JOR-II, a two-stage demand partition approach is applied to allocate the different demand priorities to determine the release from each reservoir. To assess the reliability and effectiveness of the joint operating rules, the proposed rules are applied to a multi-reservoir system in Liaoning province of China. Results demonstrate that JOR-I is suitable for high-dimensional multi-reservoir operation problems with large-scale inflow data, while JOR-II is suitable for low-dimensional multi-reservoir operation problems with small-scale inflow data, and JOR-II performs better than JOR-I but requires more computation time. The research provides guidelines for the management of multi-reservoir system.     

变化环境下水库适应性调度研究进展与展望

在气候变化与人类活动共同驱动的变化环境下,依赖于一致性水文条件所设计的传统水库调度运行策略,将难以满足决策者的需求。为了保障水资源安全与高效利用,水库管理者需对传统水库调度运行策略进行适应性调整。因此,变化环境下水库适应性调度作为当前水库调度领域的一项前沿课题,国内外专家学者已经开展了大量卓越的工作。本文旨在于总结近年来的水库适应性调度研究进展,包括变化环境下水库入库径流预测、水库调度规则编制以及耦合变化环境-入库径流-调度规则的框架等方面,并归纳当前相关研究中存在的问题及不足。进而,未来水库适应性调度研究发展方向,建议更多关注考虑自然-人工互馈影响的入库径流预测、水库调度运行策略的静态衔接与动态调整。     

A Multi-Objective Risk-Based Game Theoretic Approach to Reservoir Operation Policy in Potential Future Drought Condition

In this paper, by using the concept of Conditional Value at Risk (CVaR), a Leader-Follower game (LFG) based multi-objective optimization model is developed to determine the optimum 12-month operation policy of a reservoir in potential future dry periods. The minimization of CVaRs of storage loss and agricultural and environmental deficits along with maximization of planned allocation to agricultural sector are considered as leader’s objectives, while the followers try to maximize their share of water rights using Nash bargaining (NB) method. This framework is then used to model the operation policy of Dorudzan basin in Fars province, southwestern Iran. Water demand and daily climate data in the period of 2003 to 2015 for this basin, as well as future projections from fifteen IPCC-AR4 global circulation models (GCMs) for 2018–2030 under A2, B1 and A1B emission scenarios are considered to evaluate future dam operation policies. Future projections are downscaled using the LARS-WG model, which then feeds the HMETS watershed model to simulate the corresponding reservoir inflow time-series. Thereafter, three-hundred 12-month rainfall, evaporation and inflow time series with least inflow volume are used as input for the optimization model, which is solved using NSGA-II and GA algorithms. The results show while the model can determine the operation policy that keeps the associated risks in the acceptable range, it can satisfy the followers demands with respect to the available resources. The results also show that the agricultural sector of the study area can be hugely affected by potential future droughts.

     

Long-Term Planning of Water Systems in the Context of Climate Non-Stationarity with Deterministic and Stochastic Optimization

Seasonal inflow variability, climate non-stationarity and climate change are matters of concern for water system planning and management. This study presents optimization methods for long-term planning of water systems in the context of a non-stationary climate with two levels of inflow variability: seasonal and inter-annual. Deterministic and stochastic optimization models with either one time-step (intra-annual) or two time-steps (intra-annual and inter-annual) were compared by using three water system optimization models. The first model used one time-step sampling stochastic dynamic programming (SSDP). The other models with two time-steps are long-term deterministic dynamic programming (LT-DDP) and long-term sampling stochastic dynamic programming (LT-SSDP). The study area is the Manicouagan water system located in Quebec, Canada. The results show that there will be an increase of inflow to hydropower plants in the future climate with an increase of inflow uncertainty. The stochastic optimization with two time-steps was the most suitable for handling climate non-stationarity. The LT-DDP performed better in terms of reservoir storage, release and system efficiency but with high uncertainty. The SSDP had the lowest performance. The SSDP was not able to deal with the non-stationary climate and seasonal variability at the same time. The LT-SSDP generated operating policies with smaller uncertainty compared to LT-DDP, and it was therefore a more appropriate approach for water system planning and management in a non-stationary climate characterized by high inflow variability.     

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 1^st, 2^nd, 12^th 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.     

Linking Drought Indicators to Policy Actions in the Tagus Basin Drought Management Plan

One crucial aspect of drought management plans is to establish a link between basin drought state and management actions. Basin state is described by a drought indicator system that includes variables like precipitation, streamflow, reservoir inflow, reservoir storage and groundwater piezometric levels. Basin policy consists on a catalogue of management actions, ranging from enforcing demand reduction strategies to establishing priority of users to allocate scarce water or approving emergency works. In this paper, the methodology applied in the Tagus Basin Drought Management Plan to link operational drought indicators to policy actions in regulated water supply systems is presented. The methodology is based on the evaluation of the probability of not being able to satisfy system demands for a given time horizon. A simplified model of every water resources system in the basin was built to evaluate the threshold of reservoir volume that is required to overcome the drought situation without deficit. For each reservoir level, a set of policy actions is proposed with the goal of guaranteeing essential demands during drought conditions. The methodology was validated with a simulation of system behavior for 60 years of historic streamflow series, finding acceptable results in most systems.     

Multi-Objective Operating Rules for Danjiangkou Reservoir Under Climate Change

The natural variations of climatic system, as well as the potential influence of human activity on global warming, have changed the hydrologic cycle and threatened current water resources management. And the conflicts between different objectives in reservoir operation may become more and more challenging because of the impact of climate change. This study aims at deriving multi-objective operating rules to adapt to climate change and alleviate the conflicts. By combining the reservoir operation function and operating rule curves, an adaptive multi-objective operation model was proposed and developed. The optimal operating rules derived both by dynamic programming and NSGA-II method were compared and discussed. The projection pursuit method was used to select the best operating rules. The results demonstrate that the reservoir operating rules obtained by NSGA-II can increase the power generation and water supply yield and reliability, and the rules focusing on water supply can significantly increase the reservoir annual water supply yield (by 18.7 %). It is shown that the proposed model would be effective in reservoir operation under climate change.     

基于随机森林与支持向量机的水库长期径流预报

水库长期径流预报对于研判水文情势变化和指导水库调度管理具有重要意义。针对云南龙江水库年、汛期和枯水期平均入库径流,利用随机森林从环流指数、海温、气压和前期月径流中选取关键预报因子,基于粒子群与交叉验证相结合的算法优选参数,建立随机森林与支持向量机模型,开展龙江水库入库径流预报研究。结果表明:太平洋中北部与西部气候因子对径流预报的影响较大,前期月径流对年、汛期径流的重要性偏低,但对枯水期的影响程度与部分气候因子相当。随机森林与支持向量机模型总体精度较高,模拟与预报的合格率均达到85%以上,平均绝对百分比误差均低于15%,支持向量机的泛化能力强于随机森林,但二者在局部极值流量处的预报精度尚有待提升。     

Application of ANN, Fuzzy Logic and Decision Tree Algorithms for the Development of Reservoir Operating Rules

Optimal use of scarce water resources is the prime objective for water resources development projects in the developing country like India. Optimal releases have been generally expressed as a function of reservoir state variables and hydrologic inputs by a relationship which ultimately allows the policy/water managers to determine the water to be released as a function of available information. Optimal releases were obtained by using optimal control theory with inflow series and revised reservoir characteristics such as elevation area capacity table, zero elevation level as input in this study. Operating rules for reservoir were developed as a function of demand, water level and inflow. Artificial Neural Network (ANN) with back propagation algorithm, Fuzzy Logic and decision tree algorithms such as M5 and REPTree were used for deriving the operating rules using the optimal releases for an irrigation and power supply reservoir, located in northern India. It was found that fuzzy logic model performed well compared to other soft computing techniques such as ANN, M5P and REPTree investigated in this study.     

Sensitivity of reservoir operation performance to climatic change

The potential impacts of changing climatic conditions on the operational performance of water resource systems was investigated in this paper. A multi-site streamflow generation model was used to synthesize potential monthly flow sequences reflecting two different sets of climatic conditions. The generated data were subsequently employed as input to a reservoir operation model that was used to determine the reservoir response to the inflow resulting from the implementation of the reservoir operating policy. The performance of an example reservoir system, the Shellmouth Reservoir located in the Canadian province of Manitoba, was evaluated and compared for the two sets of conditions. The operational performance was evaluated in terms of the reliability of the system for meeting the three purposes of the actual reservoir. The reservoir performance was determined to be sensitive to the inflow data. The results indicate that climatic change has potentially important implications for the operation of the example reservoir system.     

Assessment of Water Resources Development Projects under Conditions of Climate Change Using Efficiency Indexes (EIs)

The purpose of this study is to evaluate Gharanghu multi-purpose reservoir system (East Azerbaijan, Iran) using efficiency indexes (EIs) affected by climate change. At first, the effects of climate change on inflow to the reservoir, as well as changes in the demand volume over a time interval of 30 years (2040–2069) are reviewed. Simulation results show that inflow to the reservoir is decreased in climate change interval compared to the baseline interval (1971–2000), so that comparison of long-term average monthly inflow to the reservoir in climate change interval is reduced about 25% compared to the baseline. Also, water demand in climate change interval will increase, namely volume of water demand for agricultural, drinking and industrial, and environmental in climate change interval is expected to increase by 20%. The simulation results of the water evaluation and planning (WEAP) model is used to determine EIs of multi-purpose reservoir system. Next, three scenarios of water supply for climate change interval are introduced to WEAP model, keeping variable of parameter related to water demand volume (based on different percentages of supply) and keeping constant of the parameter related to the volume of inflow to the reservoir. Results show that system EIs in climate change interval will have a disadvantage compared to the baseline. So that, reliability, vulnerability, resiliency and flexibility indexes in climate change interval based on 100% of water supply compared to the baseline will decrease 18%, increase 150%, decrease 33%, and decrease 47%, respectively. These indexes based on 85% of supply compared to the baseline will decrease 12%, increase 75%, decrease 30%, and decrease 39%, respectively. Also, those based on 70% of supply compared to the baseline will decrease 1%, will be without change, decrease 18%, and decrease 18%, respectively. Changes in indexes in future interval indicate the need to manage water resource development projects in the basin.     

Optimal Reservoir Operation for Flood Control Using Folded Dynamic Programming

Folded Dynamic Programming (FDP) is adopted for developing optimal reservoir operation policies for flood control. It is applied to a case study of Hirakud Reservoir in Mahanadi basin, India with the objective of deriving optimal policy for flood control. The river flows down to Naraj, the head of delta where a major city is located and finally joins the Bay of Bengal. As Hirakud reservoir is on the upstream side of delta area in the basin, it plays an important role in alleviating the severity of the flood for this area. Data of 68 floods such as peaks of inflow hydrograph, peak of outflow from reservoir during each flood, peak of flow hydrograph at Naraj and d/s catchment contribution are utilized. The combinations of 51, 54, 57 thousand cumecs as peak inflow into reservoir and 25.5, 20, 14 thousand cumecs respectively as peak d/s catchment contribution form the critical combinations for flood situation. It is observed that the combination of 57 thousand cumecs of inflow into reservoir and 14 thousand cumecs for d/s catchment contribution is the most critical among the critical combinations of flow series. The method proposed can be extended to similar situations for deriving reservoir operating policies for flood control.