Reservoir Operation Rules Research Articles

Reservoir operation under accidental MTBE pollution: A graph-based conflict resolution framework considering spatial-temporal-quantitative uncertainties

Given the hazardous effects of sudden dam reservoir contamination — as might occur upon the intrusion of the fuel additive methyl tert-butyl ether (MTBE) — the contaminant’s effect on the quality of allocated waters requires careful study. Employed to determine optimal reservoir operational rules in the case of sudden MTBE pollution, a risk-based simulation–optimization model was developed to simultaneously minimize unsatisfied water demand, the risk of violations of water quality standards, and the reservoir recovery time. Risks were assessed by considering various often-neglected pollution scenarios as a combination of location, quantity, and the season of pollution intrusion. The appropriateness of operational rules proved to depend upon thermal conditions and MTBE intrusion properties, confirming the necessity of considering location-quantity-season uncertainties. Social and regional conditions also occupied a dominant role in determining the level of satisfaction achieved under different water allocation strategies. Accordingly, by considering environmental conditions and local rules, a graph model for conflict resolution was established and used to reach a set of compromise operational rules. The developed framework could serve as a guide for water utilities to determine efficient reservoir operational rules after a sudden contaminant intrusion.

Sediment Yield Analysis in Tahtaköprü Dam Basin

The determination of the volume of water to be stored is one of the most important criteria for dam and pond planning and operation. This amount is calculated locally prior to planning studies, and a bathymetric map is created following water storage in the reservoir. Because of sedimentation during the operation period, the volume of the reservoir decreases over time, and this situation appears as a problem in the operation of the water structure. In this study, the reservoir storage volume changes and reservoir sediment accumulation rates between the locally produced map before the construction of Tahtaköprü Dam and the hydrographic survey maps prepared during operation period were investigated by using GIS modules. It was determined that the decrease in the storage volume of the dam reservoir at the maximum water level by 9.15% and at the minimum water level by 51.90% was due to sediment accumulation. The effect of the changes in the land cover and forest area in the basin on reservoir sedimentation was examined and it was found that land cover and forest area in the basin have reduced sediment accumulation in the reservoir. Furthermore, sediment thickness change was mapped to compare the decrease in the storage volume capacity of the reservoir at the maximum water level and at the minimum water level by comparing the digital elevation models of 1962, 1980 and 2014 to support the decision-makers on determining reservoir operation rules in order to benefit water resources effectively within the scope of sustainable management of water resources.

Investigation of Forecast Accuracy and its Impact on the Efficiency of Data-Driven Forecast-Based Reservoir Operating Rules

Today, variable flow pattern, which uses static rule curves, is considered one of the challenges of reservoir operation. One way to overcome this problem is to develop forecast-based rule curves. However, managers must have an estimate of the influence of forecast accuracy on operation performance due to the intrinsic limitations of forecast models. This study attempts to develop a forecast model and investigate the effects of the corresponding accuracy on the operation performance of two conventional rule curves. To develop a forecast model, two methods according to autocorrelation and wrapper-based feature selection models are introduced to deal with the wavelet components of inflow. Finally, the operation performances of two polynomial and hedging rule curves are investigated using forecasted and actual inflows. The results of applying the model to the Dez reservoir in Iran visualized that a 4% improvement in the correlation coefficient of the coupled forecast model could reduce the relative deficit of the polynomial rule curve by 8.1%. Moreover, with 2% and 10% improvement in the Willmott and Nash—Sutcliffe indices, the same 8.1% reduction in the relative deficit can be expected. Similar results are observed for hedging rules where increasing forecast accuracy decreased the relative deficit by 15.5%. In general, it was concluded that hedging rule curves are more sensitive to forecast accuracy than polynomial rule curves are.

Improvement of Downstream Flow by Modifying SWAT Reservoir Operation Considering Irrigation Water and Environmental Flow from Agricultural Reservoirs in South Korea

This study aims to develop a reservoir operation rule adding downstream environmental flow release (EFR) to the exclusive use of irrigation water supply (IWS) from agricultural reservoirs through canals to rice paddy areas. A reservoir operation option was added in the Soil and Water Assessment Tool (SWAT) to handle both EFR and IWS. For a 366.5 km2 watershed including three agricultural reservoirs and a rice paddy irrigation area of 4744.7 ha, the SWAT was calibrated and validated using 21 years (1998–2018) of daily reservoir water levels and downstream flow data at Gongdo (GD) station. For reservoir water level and streamflow, the average root means square error (RMSE) ranged from 19.70 mm to 19.54 mm, and the coefficient of determination (R2) and Nash–Sutcliffe efficiency (NSE) had no effect on the improved SWAT. By applying the new reservoir option, the EFR amount for a day was controlled by keeping the reservoir water level up in order to ensure that the IWS was definitely satisfied in any case. The downstream mean wet streamflow (Q95) decreased to 5.70 m3/sec from 5.71 m3/sec and the mean minimum flow (Q355) increased to 1.05 m3/sec from 0.94 m3/sec. Through the development of a SWAT reservoir operation module that satisfies multiple water supply needs such as IWR and EFR, it is possible to manage agricultural water in the irrigation period and control the environmental flow in non-irrigation periods. This study provides useful information to evaluate and understand the future impacts of various changes in climate and environmental flows at other sites.

Hybridizing ANN-NSGA-II model with genetic programming method for reservoir operation rule curve determination (Case study Zayandehroud dam reservoir)

Hybridizing ANN-NSGA-II model with genetic programming method for reservoir operation rule curve determination (Case study Zayandehroud dam reservoir)

Adapting reservoir operation rules to hydrological drought state and environmental flow requirements

Negligence of environmental flow (e-flow) has severe adverse impacts on wetlands. Additionally, hydrological droughts, compounded by mismanagement of available water resources and anthropogenic activities, lead to water shortage and degrade wetland ecosystem. However, in dealing with reservoir operation/re-operation, a few studies have addressed inflow uncertainty and hydrological drought state to improve the monthly operation performance of an upstream reservoir in coordination with downstream wetland needs. Hence, the study objective is to adopt a linear/nonlinear reservoir operation rule to hydrological drought states and e-flow requirements. So, first, the soil and water assessment (SWAT) model is applied to simulate the natural daily flow regime by eliminating human impacts. Then, using the Tennant e-flow scheme, the intra/inter-annual variability of e-flow and the degree of alteration of the flow are measured. Afterward, using the Standardized Hydrological Drought Index (SHDI), the drought/wet severity and duration are determined. A linear/nonlinear simulation model adopted for the presentation of reservoir policies and the non-dominated sorting genetic algorithm-II (NSGA-II) was employed to determine the optimal monthly operation of the upstream reservoir. The simulated operation policies correspond to each hydrological drought state were evaluated with reliability, resilience, vulnerability, and water-deficit indices. Results indicated that incorporation of hydrological drought state could improve the overall system reliability by 23% over simply enforcing the monthly variable-parameter nonlinear decision rules. Also, the proposed methodology simultaneously maximized the downstream allocated water and e-flow of the terminal wetland. It also implicitly minimized the change in extreme flow metrics that are known to benefit ecosystem diversity. The proposed framework supports reservoir re-operation in regions subject to challenges in supplying water to different sectors while maintaining e-flow during drought periods.

Management of water supply systems from interbasin transfers: case study in the Brazilian semiarid region

ABSTRACT This paper develops a discharge allocation model for public water supply for a set of communities, considering available and planned reservoirs and interbasin transfer projects. Reservoir operation rules were defined for maximum water withdrawals in function of the storage volume over a period of 45 years, and then the discharges to be transported from the different sources to 18 locations were defined, minimizing the costs. Generalized Reduced Gradient and Particle Swarm Optimization algorithms were used in the optimization processes. The model was applied in the Agreste region of the state of Pernambuco, Brazilian semiarid. This region has the worst water balance in the entire country and three interbasin water transfer systems are under construction. Due to the interconnection among the systems, it will be possible to supply the communities from one or another source. The results showed that the optimized operation of the reservoirs can minimize water transfer and costs.

Impact of Climate Change on Reservoir Reliability: A Case of Bhumibol Dam in Ping River Basin, Thailand

Bhumibol Dam is the largest dam in the central region of Thailand and it serves as an important water resource. The dam’s operation relies on reservoir operating rules that were developed on the basis of the relationships among rainfall-inflow, water balance, and downstream water demand. However, due to climate change, changing rainfall variability is expected to render the reliability of the rule curves insecure. Therefore, this study investigated the impact of climate change on the reliability of the current reservoir operation rules of Bhumibol Dam. The future scenarios from 2000 to 2099 are based on EC-EARTH under RCP4.5 and RCP8.5 scenarios downscaled by RegCM4. MIKE11 HD was developed for the inflow simulation. The model generates the inflow well (R2=0.70). Generally, the trend of increasing inflow amounts is expected to continue in the dry seasons from 2000-2099, while large fluctuations of inflow are expected to be found in the wet seasons, reflecting high uncertainties. In the case of standard deviations, a larger deviation is predicted under the RCP8.5 scenario. For the reservoir’s operation in a climate change study, standard operating procedures were applied using historical release records to estimate daily reservoir release needed to serve downstream water demand in the future. It can be concluded that there is high risk of current reservoir operating rules towards the operation reliability under RCP4.5 (80% reliability), but the risk is lower under RCP8.5 (87% reliability) due to increased inflow amounts. The unmanageability occurs in the wet season, cautioning the need to redesign the rules.

Lake Modeling Reveals Management Opportunities for Improving Water Quality Downstream of Transboundary Tropical Dams

AbstractWater quality in tropical rivers is changing rapidly. The ongoing boom of dam construction for hydropower is one of the drivers for this change. In particular, the stratification in tropical reservoirs induces oxygen deficits in their deep waters and warmer surface water temperatures, which often translate into altered thermal and oxygen regimes of downstream river systems, with cascading consequences for the entire aquatic ecosystem. Operation rules of reservoirs, involving water intakes at different levels, could mitigate the consequences for downstream water quality. However, optimized water management of deep reservoirs relies on predictive models for water quality, but such predictive capability is often lacking for tropical dams. Here we focus on the Zambezi River Basin (southern Africa) to address this gap. Using the one‐dimensional General Lake Model, we reproduced the internal dynamics of the transboundary Lake Kariba, the world’s largest artificial lake by volume, created by damming the Zambezi River at the border between Zambia and Zimbabwe. Through this modeling approach, we assessed and quantified the thermal and oxygen alteration in the Zambezi River downstream of the reservoir. Results suggest that these alterations depend directly on Kariba’s stratification dynamics, its water level and the transboundary policies for water withdrawal from the reservoir. Scenario calculations indicate a large potential for mitigating downstream water quality alterations by implementing a hypothetical selective withdrawal technology. However, we show that a different and cooperative management of the existing infrastructure of Kariba Dam has the potential to mitigate most of the actual water quality alterations.

Climate change scenario analysis for Baro-Akobo river basin, Southwestern Ethiopia

BackgroundSeveral water resources projects are under planning and implementation in the Baro-Akobo basin. Currently, the planning and management of these projects is relied on historical data. So far, hardly any study has addressed water resources management and adaptation measures in the face of changing water balances due to climate change in the basin. The main bottleneck to this has been lack of future climate change scenario base data over the basin. The current study is aimed at developing future climate change scenario for the basin. To this end, Regional Climate Model (RCM) downscaled data for A1B emission scenario was employed and bias corrected at basin level using observed data. Future climate change scenario was developed using the bias corrected RCM output data with the basic objective of producing baseline data for sustainable water resources development and management in the basin.ResultThe projected future climate shows an increasing trend for both maximum and minimum temperatures; however, for the case of precipitation it does not manifest a systematic increasing or decreasing trend in the next century. The projected mean annual temperature increases from the baseline period by an amount of 1 °C and 3.5 °C respectively, in 2040s and 2090s. Similarly, evapotranspiration has been found to increase to an extent of 25% over the basin. The precipitation is predicted to experience a mean annual decrease of 1.8% in 2040s and an increase of 1.8% in 2090s over the basin for the A1B emission scenario.ConclusionThe study resulted in a considerable future change in climatic variables (temperature, precipitation, and evapotranspiration) on the monthly and seasonal basis. These have an implication on hydrologic extremes-drought and flooding, and demands dynamic water resources management. Hence the study gives a valuable base information for water resources planning and managers, particularly for modeling reservoir inflow-climate change relations, to adapt reservoir operation rules to the real-time changing climate.

A forecast-driven decision-making model for long-term operation of a hydro-wind-photovoltaic hybrid system

Hydro-wind-photovoltaic (PV) hybrid system has the potential to increase the integration of renewable energy sources into an existing grid. For the long-term operation of the system, due to the non-storable nature of wind and PV power, it is essentially to decide the optimal long-term carryover storage of cascade reservoirs. However, it remains a challenge due to high uncertainties of long-term forecasts and complicated hydraulic/electrical relationships between cascade reservoirs. In this study, a forecast-driven decision-making model is proposed for the hybrid system, which converts the multi-stage long-term operation process into a two-stage operation problem (including current stage and carryover stage) to avoid using longer-horizon forecast information with lower accuracy. First, the carryover stage energy surfaces (CESs) considering the forecast uncertainties of wind, solar and hydro resources are proposed to characterize carryover stage benefit quantitatively. Then a CESs-based forward decision-making optimization model is developed to guide the long-term operation of a hydro-wind-photovoltaic hybrid system. The applications in a hydro-wind-PV hybrid system of Yalong River basin results show that: compared with conventional operation, 1) power generation increases 9.03%; 2) in terms of the carryover storages control, the reservoir impounding and drawdown timing are delayed, and the drawdown depth is increased, which can be used to formulate better reservoir operation rules.

Uncertainties in agricultural water supply under climate change: Aidoghmoush basin, Iran

The planning of future supplies of agricultural water is beset by uncertainties stemming from inaccuracies in general circulation models, assumed greenhouse gases emissions scenarios (GHGESs), imperfect models employed for estimating reservoir inflows and approximate methods for estimating agricultural water demand. The uncertainty of providing agricultural water under climate change was assessed, relying on simulations involving baseline (1971–2000) and future periods (2040–2069 and 2070–2099). Climatic variables were simulated using six atmosphere–ocean general circulation models (AOGCMs) driven by GHGESs A2 and B2 in the Aidoghmoush basin, Iran. Projection of reservoir inflow was performed using the IHACRES model and artificial neural network (ANNs). Agricultural water demand was calculated using the FAO–Penman–Monteith and Hargreaves-Samani (HS) methods. Eight modelling scenarios were considered based on combinations of AOGCMs, GHGESs, reservoir inflow and agricultural water demand projections. Reservoir operation rules were calculated with a particle swarm optimisation algorithm. The results show that agricultural water demand will increase in future periods compared with the baseline period. The operation rule derived from the combination of the HS and ANN models (under GHGES A2) showed the best performance in 2040–2069 by achieving the highest reliability (93%) of water supply. The operation rule derived from the combination of HS and ANN models (under GHGES B2) achieved the highest reliability (95%) of water supply in 2070–2099. The results provide adjusted reservoir operation rules under uncertainty caused by climate change and related impacts on water resources management.

Water storage change assessment in the Seyhan Reservoir (Turkey) using HEC-ResSim model

Due to the increase in water demand, it is getting more critical to operate reservoirs in an efficient manner in which multiple demands should be sustained. In Turkey, the Seyhan Plain irrigation project has great importance in terms of increasing agricultural production and development. To evaluate the water storage changes considering alternatives, a daily reservoir operation model was developed using the Hydrologic Engineering Center’s Reservoir System Simulation (HEC-ResSim) watershed model with 33 years of data. Four alternatives were created by considering current and projected water usage in the upstream areas and two different flow types, pipe flow and open channel flow. Findings show that Seyhan Reservoir could not meet the irrigation demand considering the worst-case scenario and the minimum water storage amount was found as 240×106 m3. However, with the modernization in the irrigation transmission system which significantly reduces water loss and prevents water ponding on the soil surface, the simulated minimum water storage amount for the same time was found as 380×106 m3. With this study, it was highlighted that the water supply problems for existing reservoir systems can be mitigated by the modernization of the transmission lines via tandem reservoir operation rules.

Assessing the Potential of Agricultural Reservoirs as the Source of Environmental Flow

Excessive nutrient loadings from drainage areas and resulting water quality degradation in rivers are the major environmental issues around the world. The water quality further deteriorates for the large seasonal variation of precipitation and water flow. Environmental decision makers have been exploring affordable and effective ways of securing environmental flow (EF) to improve the water quality, especially in dry seasons, and agricultural reservoirs have attracted the attention of policymakers as an alternative source of EF. This study proposed an analysis framework for assessing the EF supply potential of agricultural reservoirs as alternative sources of EF. A reservoir water balance model was prepared to mathematically represent the reservoir water balance and quantify temporal variations of the amount of water available for the EF supply. The simulation model was designed to explicitly consider inflow from the upstream drainage areas, irrigation water requirement, and hydrological processes happening in the reservoirs. The proposed framework was applied to four agricultural reservoirs located in South Korea to evaluate its efficiency. Results showed that the additional storage capacity added by the dam reinforcement enabled the study reservoirs to satisfy both needs, EF and irrigation water supply. The surplus capacity turned out to be enough to satisfy various EF supply scenarios at the annual time scale. However, the current operation plans do not consider the seasonal variations of reservoir hydrology and thus cannot supply EF without violating the original operational goal, irrigation water, especially in dry months. The results demonstrate that it is necessary to consider the temporal variations of EF when developing reservoir operation rules and plans to secure EF. This study also highlights the unconventional roles of agricultural reservoirs as resources for improved environmental quality. The methods presented in this study are expected to be a useful tool for the assessment of agricultural reservoirs’ EF supply potential.

A method to include reservoir operations in catchment hydrological models using SHETRAN

Reservoir construction and operation have significant impacts on catchment hydrology, flood risk and fluvial processes. However, few available hydrological modelling packages can simulate complex, dynamic, manually-operated reservoir control structures. We present SHETRAN-Reservoir, a physically-based spatially distributed modelling tool to simulate catchment hydrology, including reservoir operations. We also propose a method for deriving parsimonious reservoir operation rules from real-world observations. Application of SHETRAN-Reservoir to the Upper Cocker catchment in the Lake District National Park, UK, is shown to improve modelling of hydrological response. Modelling combined climate change and water resource management scenarios demonstrates the influence of operational control rules on hydrological impacts, especially during droughts. We discuss how SHETRAN-Reservoir can be applied to other reservoir-containing catchments to guide decisions concerning water resources, ecology and flood risk. We also discuss potential future software developments. • Manual reservoir operations should be modelled in dam-containing catchments. • Parsimonious reservoir operation rules can be derived from hydrometric data. • The newly developed SHETRAN-Reservoir software simulates reservoir operations. • Our methods improve model outputs for Crummock Water in the UK Lake District. • This approach supports sustainable water resource management under climate change.

Quantifying the Risks that Propagate from the Inflow Forecast Uncertainty to the Reservoir Operations with Coupled Flood and Electricity Curtailment Risks

Substantial uncertainty is inherent in reservoir inflow forecasting, which exerts a potential negative impact on reservoir risk. However, the risk propagation from the inflow forecast uncertainty (IFU) to reservoir operations remains elusive. Thus, a new integrated assessment framework was developed in this study to characterize the risk coupling with flood and electricity curtailment risks that propagate from the IFU to the reservoir operations. First, to incorporate the IFU, an improved Gaussian mixture distribution (IGMD) and Markov chain Monte Carlo (MCMC) algorithm were constructed to model the measured forecast errors and generate ensemble inflow forecasts, respectively. Next, to assess the reservoir risk, the flood risk induced by the IFU overestimation and the electricity curtailment risk related to the IFU underestimation were identified according to the reservoir operation rules. The sub-daily inflow forecast at the Jinping First Stage Hydropower Plant Reservoir of Yalong River, China (Jinping I Reservoir) was selected. The results indicated that the IGMD-based MCMC was capable of deriving robust ensemble forecasts. Furthermore, there was no flood risk (risk rate was zero) induced by the IFU when taking designed reservoir floods with a ≥10-year return period as the benchmark. In contrast, the electricity curtailment risk rate significantly increased up to 41% when considering the IFU. These findings suggested that compared with the flood prevention pressure, the IFU would more likely result in severe electricity curtailment risk at the Jinping I Reservoir.

Review on Dam and Reservoir Optimal Operation for Irrigation and Hydropower Energy Generation Utilizing Meta-Heuristic Algorithms

In engineering and scientific disciplines, there are extensive Optimization Application Problems (OAPs) such as economic dispatch, structural design, and water resources. One of the major OAPs is the operation of dams and reservoirs to minimize the gap between water supply for irrigation and demand patterns such as hydropower generation. Drawing optimal operation for dams and reservoirs is often categorized as discontinuity, multimodality, non-differentiability and non-convexity. Classical mathematical programming-based methods for optimization might be inappropriate or unrealizable in drawing optimal operation rules for dam and reservoir operation. During the last two decades, new optimization methods-based on nature-inspired meta-heuristic algorithms (MHAs) have motivated hydrologists to investigate MHAs as better alternative optimization tools for identifying the optimal dam and reservoir operation rules. To solve the dam and reservoir-optimization applications better, this review presents the past, present, and prospective research directions using MHAs. The problem of dam and reservoir optimization requires a fundamental shift of focus towards enhancing not only the problem formulation and decomposition but also the computational efficiency of MHAs.

Reliability analysis for reservoir water supply due to uncertainties in hydrological factors, rainfall-runoff routing and operating rule curves

This study aims at developing a reliability-analysis model (RA_WS_RES) to quantify the effect of variations in uncertainties factors regarding the reservoir inflow and outflow at various 10-day periods on the reliability of water supply from the reservoir. The uncertainty factors considered are classified into three types: the hydrological factors (rainfall, baseflow, and initial water level of the reservoir), the reservoir operation rules for the water-allocation model (RIBASIM), and the parameters of rainfall-runoff model (i.e. Sacramento Soil Moisture Accounting, SAC-SMA). In the proposed RA_WS_RES model, the reliability of the water supply attributed to the uncertainty factors considered can be quantified by collaborating the multivariate Monte Carlo simulation (MMCS) methods and uncertainty-risk (advanced first order and second moment, AFOSM) analysis. Shihmen Reservoir watershed in Northern Taiwan is selected as the study area and four associated demand nodes are regarded as the study nodes; the hourly rainfall data from 1987 to 2014 and other hydrological data (i.e. rainfall, baseflow, and initial water level of the reservoir) as well as the operation rule curves are adopted in the model development and application. The results from the numerical experiences indicate that among the uncertainty factors concerned, the average rainfall depth at the current 10-day period and the range between the lower and critical levels are more sensitive to the estimation of water supply from Shihmen Reservoir. Additionally, the impact of variation in baseflow on the reliability of the water supply from Shihmen Reservoir should be taken into account, especially in the dry season. In addition to rainfall and baseflow, the initial water level should be an important source for the water supply, and its effect gradually reduces with the 10-day period. Furthermore, the reliability of water supply is obviously impacted by the uncertainty in the range between the lower and critical rule level, especially in the dry season, due to its range being adversely related with the water supply. Eventually, the proposed RA_WS_RES model can effectively and reasonably quantify the reliability of water supply attributed to variations in uncertainty factors at different 10-day period under the consideration of climate change.

Constructing Reservoir Area-Volume-Elevation Curve from TanDEM-X DEM Data.

Area–volume–elevation (AVE) curves are critical for reservoir operation rules. However, such curves are not publicly available for most global reservoirs. Here, we present a framework to derive reservoir AVE curves from TanDEM-X data, using Lake Mead (~600 km2) as an example. First, the maximum water extent from 1984 to 2018—provided by the global surface water (GSW) dataset—was used as a mask to obtain the TanDEM-X data. Then, the TanDEM-X water indication mask (WAM) was applied to the extracted TanDEM-X data to obtain the visible bathymetry, which represents the topography between the maximum extent (according to GSW) and the water extent from WAM. Last, the AVE curve was generated by integrating the volume values from the top to bottom layers. TanDEM-X also captures the elevation values of the transitional waters, which are defined as the difference between the highest and lowest water levels. The transitional waters were obtained by thresholding amplitude and coherence images, and their elevations were then added to the visible bathymetry to extend the AVE curves with an elevation range extending from 344–369 m to 341–369 m. Validation results against in situ lidar survey values suggest a high-accuracy of elevation–area (E-A) relationships with R2 values of >0.99 and NRMSE values from 2.11% to 2.45%, and elevation–volume (E-V) relationships with R2 values of 1 and NRMSE values from 1.11% to 1.29%. Results also show that TanDEM-X data can capture the interannual variations due to multiple acquisitions, and that the elevation measurements for the lake shore areas are reliable.

Reservoir optimal operation to adapt the non-stationary hydrological series<sup>*</sup>

为完善变化环境下水库防洪调度方案，建立了集水文非一致性诊断、水文模型还现、设计洪水计算与水库调度规则优化于一体的水库适应性调控方法体系，并应用于沂沭泗水系仕阳水库.结果表明，仕阳水库入库洪水变异点发生在1975年；利用新安江模型对水文序列还现处理，得到满足一致性的设计洪水，其洪峰、最大24 h和最大72 h洪量均值，较原设计分别增大了19.7%、14.5%和10.0%；建立了以防洪效益最大为目标函数的水库优化调度模型，采用动态规划进行求解.提出的适应性调度方案在20年、100年、1000年和5000年一遇设计洪水条件下，较水库现行设计方案最高洪水位分别降低了0.32、0.11、0.19和0.11 m.;To improve reservoir operation rules under changing environment, this paper proposed adaptive operation methodologies that include the hydrological series inconsistent testing→backwards restore by hydrological model→design flood calculation→optimal operation of reservoir for flood control safety. The proposed methodologies were applied to the Shiyang Reservoir, which located at the Yi-Shu-Si river system. The results have shown that the change-point of this reservoir inflow flood is 1975. The inflow flood that satisfies the assumption of hydrological stationery were calculated by the Xin'anjiang model, and the hydrological consistent design floods acquired based on it. Compared with the original design, the mean values of flood peaks, maximum flood volume during 24 hours and 72 hours of the new design floods increased 19.7%, 14.5% and 10.0%, respectively. The optimal reservoir operation model based on the objective function of maximizing the flood control benefit is established and solved by dynamic programing. Under design flood with 20-year, 100-year, 1000-year and 5000-year return periods, the maximum flood level of Shiyang Reservoir decrease by 0.32, 0.11, 0.19 and 0.11 m, respectively, compared with the current design scheme.