Reservoir Operation Rules Research Articles

Effectiveness of Adaptive Operating Rules for Reservoirs

In this paper, a methodological proposal is made to develop an adaptive decision support system for reservoir management. The system is based on an optimization model that determines operating rules that meet certain optimality conditions based on the state of the reservoir at a certain time and on a streamflow forecast, if available. The model is based on Spiliotis et al. in Water Resour Manage 30:5759-5778, where a general methodology was developed to specify static operating rules for reservoir systems. The proposed methodology consists of modifying the optimization procedure developed in the previous work to dynamically update operating rules to adapt management to the changing situation. To evaluate its effectiveness, the methodology was applied to the Pisuerga-Carrión reservoir system, in the Spanish part of the Duero basin. The results obtained with adaptive rules were compared with those obtained applying the same static operating rule for the entire analysis period. Adaptive rules were found to lead to better operating results, particularly if a successful streamflow forecast method is available.

Monitoring Dewatering Fish Spawning Sites in the Reservoir of a Large Hydropower Plant in a Lowland Country Using Unmanned Aerial Vehicles

This paper presents research concerning dewatered areas in the littoral zones of the Kaunas hydropower plant (HPP) reservoir in Lithuania. It is a multipurpose reservoir that is primarily used by two large hydropower plants for power generation. As a result of the peaking operation regime of the Kaunas HPP, the large quantity of water that is subtracted and released into the reservoir by the Kruonis pumped storage hydropower plant (PSP), and the reservoir morphology, i.e., the shallow, gently sloping littoral zone, significant dewatered areas can appear during drawdown operations. This is especially dangerous during the fish spawning period. Therefore, reservoir operation rules are in force that limit the operation of HPPs and secure other reservoir stakeholder needs. There is a lack of knowledge concerning fish spawning locations, how they change, and what areas are dewatered at different stages of HPP operation. This knowledge is crucial for decision-making and efficient reservoir storage management in order to simultaneously increase power generation and protect the environment. Current assessments of the spawning sites are mostly based on studies that were carried out in the 1990s. Surveying fish spawning sites is typically a difficult task that is usually carried out by performing manual bathymetric measurements due to the limitations of sonar in such conditions. A detailed survey of a small (approximately 5 ha) area containing several potential spawning sites was carried out using Unmanned Aerial Vehicles (UAV) equipped with multispectral and conventional RGB cameras. The captured images were processed using photogrammetry and analyzed using various techniques, including machine learning. In order to highlight water and track changes, various indices were calculated and assessed, such as the Normalized Difference Water Index (NDWI), Normalized Difference Vegetation Index (NDVI), Visible Atmospherically Resistant Index (VARI), and Normalized Green-Red Difference Index (NGRDI). High-resolution multispectral images were used to analyze the spectral footprint of aquatic macrophytes, and the possibility of using the results of this study to identify and map potential spawning sites over the entire reservoir (approximately 63.5 km2) was evaluated. The aim of the study was to investigate and implement modern surveying techniques to improve usage of reservoir storage during hydropower plant drawdown operations. The experimental results show that thresholding of the NGRDI and supervised classification of the NDWI were the best-performing methods for the shoreline detection in the fish spawning sites.

Surveying Dewatered Areas in the Fish Spawning Sites during Short-Term Drawdown Operations: Case Study of a Large Hydropower Plant Reservoir in the Lowland Area, Lithuania

This paper presents research on the dewatering areas during drawdown operations in the Kaunas Hydropower Plant (HPP) reservoir situated in the lowland area of Lithuania. It is a multipurpose reservoir primarily used for power generation by two large hydropower plants. Because of the HPP peaking operation and the reservoir morphology—a shallow, gently sloping littoral zone—significant dewatered areas can occur (during drawdown operations). This is especially dangerous during the fish spawning period. Therefore, reservoir operation rules are in force that limit operation of the HPPs and secure other reservoir stakeholder needs. There is a lack of knowledge about the fish spawning locations, how they are changing, and what areas are dewatered at different stages of HPP operation. This knowledge is crucial for decision making and efficient water resources management in order to increase power generation and protect the environment at the same time. A detailed survey of an area containing several potential spawning grounds (about 5 ha) was conducted to track changes in the dewatering areas. The aim of the study is to investigate different surveying methods, gather knowledge about potential fish spawning sites, and investigate the dewatered areas that occur during water level (WL) fluctuations. The methodology and insights of this study can be used in similar lowland countries to assist in improving the usage of water resources while increasing power generation.

A Dynamically Dimensioned Search Allowing a Flexible Search Range and Its Application to Optimize Discrete Hedging Rule Curves

The discrete hedging rule for reservoir operation includes time-varying trigger volumes used for the onset and termination of water rationing, which complicates its optimization problems. A dynamically dimensioned search can be easily applied to complex optimization problems, but the performance is relatively limited in constrained optimization problems such as deriving reservoir operation rules. A dynamically dimensioned search allowing for a flexible search range is proposed in this study to efficiently solve constrained optimization problems. The modified algorithm can recursively update the search ranges of decision variables with limited overlaps. The above two algorithms are applied to derive hedging rule curves for three reservoirs. Objective function values are closely converged to optimum solutions, with fewer evaluations using the modified algorithm than those using the traditional algorithm. The modified algorithm restrains an overlapped search range of decision variables and can reduce redundant computational efforts caused by unreasonable candidate solutions that violate inequality conditions.

An adaptive multi-objective reservoir operation scheme for improved supply-demand management

The complex hydrological connectivity of integrated river-reservoir catchment command regions in conjunction with abrupt societal development and population growth impose adverse water availability scenario in the global reservoirs. In this context, to formulate optimal reservoir operation policies, numerous reservoir simulation and optimization models are currently on board. However, lack of combined hydrologic and hydraulic conceptualizations in the existing reservoir operation framework fetches considerable uncertainty; thereby leading to formulation of erroneous reservoir operation rule. This study proposed an integrated Soil and Water Assessment Tool (SWAT) based hydrologic, HEC-ResSim based hydraulic, and genetic algorithm (GA) based optimization framework (SWAT-HEC-ResSim-GA) for formulating the optimal reservoir operation rule of the Kangsabati reservoir located in the eastern India. Unlike the existing reservoir operation rules, the present study incorporates a 10-daily-scale environmental flow estimation approach to quantify the water demand. The proposed reservoir operation framework generated rule curve based HEC-ResSim simulation revealed improved reservoir performance with reservoir time reliability, volume reliability, and resiliency magnitudes of 0.631, 0.736, and 0.591, respectively. Finally, this study endorses to use the developed methodology for supply–demand management, and subsequent, reservoir operation in any global reservoir catchment-command regions with utmost accuracy.

Development of A Two-storage Reservoir Operation Rules for Flood Control Case Study of Wonogiri Multipurpose Reservoir, Central Java, Indonesia

Wonogiri Reservoir, one of the large reservoirs in Indonesia, regulates water for flood control, irrigation, domestic use, and hydropower. It is located at the upper part of Bengawan Solo River Basin, Central Java. A closure dike has recently been constructed as a countermeasure against severe sedimentation that separates the reservoir into two parts, i.e., Sediment Storage Reservoir (SSR) and Main Reservoir (MR). A two-gate spillway was constructed in the SSR to facilitate sediment flushing and sluicing. During flood events, it controls reservoir water level jointly with the MR spillway. This brings the need for an update on the reservoir operation rules, especially on the gates opening of the new spillways to maintain the flood control performance. An assessment of reservoir routing simulation results was carried out by considering the overflow from SSR to MR, or vice versa with two options of Control Water Level (CWL), i.e. +135.8 m and +136.3 m. The flood control performance of the new reservoir operation rules was evaluated by considering the reservoir water level recovery, the maximum total outflow discharge, and the dam safety due to the risk of overtopping. These assessments give a foundation for the selection of CWL and the spillway operation to ascertain an optimal flood control of the reservoir.

Exploring a multi-objective cluster-decomposition framework for optimizing flood control operation rules of cascade reservoirs in a river basin

Multi-objective flood control operation of cascade reservoirs is a vital issue in river basin management. However, traditional multi-objective approaches commonly provide one operation scheme only and fail to offer decision-makers with more Pareto-front options. This study explores a multi-objective cluster-decomposition framework for optimizing the flood control operation rules of cascade reservoirs in a river basin. The proposed framework involves a multi-objective optimization module, a cluster-decomposition module, and an evaluation and sorting module. The multi-objective cluster-decomposition framework simultaneously deals with three objectives: to minimize the flood peaks of flood control points (O1); to minimize the reservoir capacity used for flood control (O2); and to minimize the flood diversion volume of the flood detention area (O3). The complex flood control system composed of two cascade reservoirs, four navigation-power junctions, one flood detection area, and three flood control points in the Ganjiang River basin of China constitutes the case study. The results demonstrate that the proposed framework can significantly improve the comprehensive benefits of the cascade reservoirs, where the maximum reduction in objectives O1–O3 is 2071 m3/s (the improvement rate is 2.64 %), 219 million m3 (the improvement rate is 44.60 %), and 167 million m3 (the improvement rate is 78.13 %), respectively. Furthermore, in contrast to the traditional multi-attribute evaluation method, the proposed framework can effectively identify compromised decisions through a cluster-decomposition module, which provides beneficial trade-off guidance in making a sound decision upon Pareto-front options.

Featured Collection Introduction: Severe Sustained Drought Revisited: Managing the Colorado River System in Times of Water Shortage 25 Years Later — Part I

Featured Collection Introduction: Severe Sustained Drought Revisited: Managing the Colorado River System in Times of Water Shortage 25 Years Later — Part I

Research on Reservoir Operation Rules Extraction Based on Decision Tree and Its Ensemble Model

Reservoir operation rules, as an important tool to guide reservoir operation, are not only the decision-making reference in the period of reservoir planning and design, but also one of the key technologies affecting the comprehensive benefits of the reservoir in the stage of operation and management. Therefore, the reservoir operation rules extraction method based on decision tree and its ensemble model was proposed in this paper. The time index, early water level, inflow, outflow and current inflow were selected to form the input factor set with the reservoir scheduling principle. Comprehensively considering the characteristics of operation data and the principle of decision tree, reservoir water level at the end of period was determined as the model output and then the corresponding simulated water level evaluation index was proposed based on the reservoir regulation capacity. Furthermore, in view of the difficulties in selecting input factors and calibrating the hyperparameters of models, the F test method and mutual information were used as the correlation evaluation index of model input factors, and the Tree-structured Parzen Estimator was introduced. Finally, the proposed methods were applied in Ahai and Ertan Reservoirs, the results showed that the extracted operation rules have high precision, which demonstrated the proposed methods is practicable and effective in the reservoir operation rule extraction.

Reservoir operation rule in semiarid areas: The quantity-quality approach

The increase in water demand in association with the degradation of water quality can result in conflicts between users, especially in semi-arid regions where reduced flow is likely during long periods of drought. In these regions, reservoirs are normally operated to ration water, according to the level of water stored, in order to reserve this water to supply the demands of a future drought, i.e., using the Zone-based Guide Curve method. However, the quality of the water is also important because eutrophication in reservoirs limits the use and availability of water. The aim of this study was to use the quantity-quality approach to define the operating rule for four reservoirs in the semi-arid region of Brazil, with the aim of providing satisfactory supply to users while reducing water scarcity and eutrophication in the reservoirs. Scenarios of supplying the demands were simulated and optimized with the use of the Multiobjective Genetic Algorithm, NSGA-II. The results showed that the application of the Zone Hedging Rule (ZHR), considering only the quantitative approach, was able to guarantee the priority demands and reduce the water scarcity for non-priority requirements. However, by only using the quantitative approach the reservoirs did not meet the quality criteria required by Brazilian legislation. Applying the ZHR with a quanti-qualitative approach considering more favorable water quality conditions, the reservoirs were able to supply the demands with satisfactory quantity and quality; however, when the phosphorus concentration is high, a severe rationing of demands is triggered, which may not be viable, especially in reservoirs with greater demands in relation to the regularized flow and the average annual input flow. Therefore, actions are required to reduce nutrient concentrations in reservoirs, in addition to optimizing operating rules.

Optimal Operation of Nashe Hydropower Reservoir under Land Use Land Cover Change in Blue Nile River Basin

Changes in LULC (land use land cover), which significantly influence the spatial and temporal distribution of hydrological processes and water resources in general, have a substantial impact on hydropower generation. The utilization of an optimization approach in order to analyze the operation of reservoirs is an important concern in the planning and management of water resources. The SWAT (Soil and Water Assessment Tool) and the HEC-ResPRM (Hydrologic Engineering Center reservoir evaluation system Prescriptive Reservoir Model) were combined to model and optimize the Nashe hydropower reservoir operation in the Blue Nile River Basin (BNRB). The stream flow into the reservoir was determined using the SWAT model, considering the current and future impacts of LULC changes. The HEC-ResPRM model has been utilized in order to generate the optimal hydropower reservoir operation by using the results of the SWAT calibrated and validated stream flow as input data. This study proposes a method for integrating the HEC-ResPRM and SWAT models to examine the effects of historical and future land use land cover change on the watershed’s hydrological processes and reservoir operation. Therefore, the study aimed to investigate the current and future optimal reservoir operation scenarios for water resources management concerning hydropower generation under the effect of LULC changes. The results reveal that both the 2035 and 2050 LULC change scenarios show the increased operation of hydropower reservoirs with increasing reservoir inflows, releases, storage, and reservoir elevation in the future. The effects of LULC change on the study area’s hydrological components reveal an increase in surface runoff until 2035, and its decrease from 2035 to 2050. The average annual reservoir storage and elevation in the 2050 LULC scenario increased by 7.25% and 2.27%, respectively, when compared to the current optimized scenario. Therefore, changes in LULC have a significant effect on hydropower development by changing the total annual and monthly reservoir inflow volumes and their seasonal distribution. Reservoir operating rule curves have been commonly implemented in the operation of hydropower reservoirs, since they help operators to make essential, optimal decisions with available stream flow. Moreover, the generated future reservoir rule curves can be utilized as a reference for the long-term prediction of hydropower generation capacity, and assist concerned authorities in the successful operation of the reservoir under the impact of LULC changes.

A conflict resolution model for reservoir operation in dry seasons under channel alteration

The increases in extreme drought events and channel alteration challenge the existing reservoir operation rules. Therefore, reservoir operation should be reconsidered to accommodate these challenges. A conflict resolution model for reservoir operation considering the decision-makers’ preference is developed for the conflict between hydropower generation and navigation in dry seasons under channel alteration, to achieve the goal of meeting minimum environmental flow, landslide stability, and river–lake connection constraints. This model with a nondominated sorting genetic algorithm-II (NSGA-II) is applied to the Three Gorges Reservoir (TGR) on the Yangtze River. The results show that minimum navigation discharge for the post-dam period is greater than that for the pre-dam period, indicating channel alteration. Both average hydropower generation benefit and navigation reliability decrease with modification of the post-dam minimum navigation discharge, signifying the adverse effect of damming. The total benefits of navigation and hydropower generation decrease with the exceedance probability. A higher hydropower generation benefit leads to a smaller navigation benefit, reflecting the conflict of interest. This study demonstrates the feasibility of the proposed conflict resolution model, as well as the navigation benefit-quantifying method and applicability to similar water resources management problems.

Optimization of ecological reservoir operation rules for a northern river in China: Balancing ecological and socio-economic water use

With the conspicuous contradiction between water use inside and outside rivers, ecological reservoir operation has become a feasible approach to coordinate the relationship between socio-economic water use and ecological water use in rivers. However, ecological water demand in rivers remains difficult to be satisfied in areas facing serious water shortages, resulting in an imbalance between ecological and socio-economic water use. To satisfy the instream ecological water demands in water shortage areas, efforts were made on seeking an optimal reservoir operation scheme to balance the water supply for ecology and socio-economy. This study applied the index of guarantee rate of ecological water (GREW) to ecological river management, improved the previous reservoir operation rules, and constructed an optimization model of ecological reservoir operation rules based on dual-control management indexes. The Dagu River in Qingdao City, China, was selected as a study area to apply this model. The results showed that both the recommended scheme and the scheme without considering ecology could meet the socio-economic water demands, but the satisfaction degree of ecological water demand of the recommended scheme was significantly higher than that of the scheme without considering ecology. The scheme without considering ecology cannot ensure the ecological water demand in the Dagu River, especially for the non-flood season. Comparisons between the recommended scheme and the operation results without considering ecology demonstrated that the optimization model of ecological reservoir operation rules could effectively balance the ecological and socio-economic water use. In conclusion, the optimization model of reservoir operation rules with GREW can solve the problem of competitive water use inside and outside rivers, providing an important scientific basis for water resources management.

Estimating Reservoir Inflow and Outflow From Water Level Observations Using Expert Knowledge: Dealing With an Ill‐Posed Water Balance Equation in Reservoir Management

AbstractQuantifying reservoir water balance is an essential process for the efficient management of water resources. Water level records are often the only data available for reservoir analysis, which causes an ill‐posed problem in water resource system planning. This study proposes an analytical framework to estimate reservoir inflow and outflow from water level observations using hydrological models and reasoning carefully derived from expert knowledge and soft data. Partial reservoir inflow hydrographs were constructed from water level observations using a continuity equation and knowledge‐based constraints developed for periods of no spillway discharge. A bucket‐type rainfall‐runoff model was then calibrated to the partial inflow hydrographs. Finally, a complete reservoir inflow hydrograph was constructed using the calibrated models, which were then employed to estimate detailed reservoir outflow components under a full water balance relationship between inflow, outflow, water levels, and reservoir operation rules. The proposed solution for the ill‐posed water balance equation outperformed conventional (benchmark) approaches in accuracy and uncertainty in its application to agricultural reservoirs. This study demonstrates how hydrological modeling and reasoning, which are discreetly designed based on expert knowledge, can help to solve the ill‐posed water balance equation by creating supplementary information regarding the problem. The proposed framework is expected to assist in reconstructing reservoir routing processes using water level observations for hydrological analysis and water resource management planning.

Hybrid methods for reservoir operation rule curve determination considering uncertain future condition

In this research, simple and practical methods have been proposed to determine the reservoir operation rule curves considering uncertain water inflow values at future conditions based on the concept of comparative reservoirs management. For this purpose, two methods are proposed. In the first method named His-Inf, by considering the historical water inflow values, a mathematical optimization model is proposed for defining the reservoir operation rule curves determination problem and solved using nonlinear programming (NLP) method. However, in the second method, three different approaches named Pre-Inf1, Pre-Inf2 and Pre-Inf3 are proposed. In the Pre-Inf1 method, at first, water inflow values into the dam reservoir are predicted using neural network (ANN) model. Then, the predicted water inflow values are used to determine and update the reservoir operation rule curves using NLP method. In the Pre-Inf2 method, the ANN model is used to simulate and update the constant coefficients of the reservoir operation rule curves considering the water demand, water inflow values into the reservoir, water release values form reservoir and time index (T) as data set. For this purpose, two different framework and structure are proposed for sorting and providing data set leading to two different cases. Finally, in the Pre-Inf3 method, at first, water inflow values, reservoir storage volumes, water demand values and time index (T) are used to simulate and predict water releases values from the reservoir. Then, the linear regression method is used to determine the reservoir operation rule curves and policies. Here, both static and dynamic ANN models are used for simulating and predicting the water inflow values and reservoir operation rule curves and policies. In order to investigate the performance of proposed methods, here, the Sefidrood dam reservoir is considered as a case study in which it is located at the intersection of the QezelOzan River and Shahroud River near the city of Manjil in the north of Iran. Finally, the obtained results are presented and compared by calculating the reliability, residency, vulnerability and sustainability indexes. Comparison of the result indicates the superiority of the proposed Pre-Inf3 method for determining the reservoir operation rule curves at uncertain future condition in which the results of the His-Inf, Pre-Inf1 and Pre-Inf2 methods are almost similar. In other words, the sustainability index of His-Inf, Pre-Inf1, Pre-Inf2 and Pre-Inf3 are 63%, 63%, 63% and 74%, respectively, in which the corresponding value of Pre-Inf3 is 17.5% bigger than other proposed methods.

Sedimentation in East Coast Hilly Terrain Reservoirs; Balimela, Odisha

Globally reservoirs behind dams are changing their hydrologic cycle under a shifting climate. Sediment, the flagship for water resources projects provide negative impact on environment and dam benefits. Sedimentation behind dams is continuous, regular through sequential paths that comprises of erosion, entrainment, transference from upper basin and deposition within the reservoirs. Present study envisages the morphometric study of the Balimela Reservoir active from 1972. The downloading of Geographic Information System (GIS), Remote sensing (RS) data from LANDSATS and making Stream order, Contour, slope and aspect maps by constructing Digital Elevation Model using the various Arc-GIS tools. The average bifurcation ratio is safe.. Considering the water-spread areas at various elevations of the years 2000, 2002, 2013, 2016, 2019 and 2022, the sediment deposits and reduction of storage volume by 29.945% by Jan 2022 since first impounding. The dam housed in hilly terrains, so there is less increase of catchment erosion except deforestation. The water from the dam optimally used by both the states Odisha and Andhra Pradesh. Preparation and strict adherence of concrete reservoir operation rule, upstream proper upstream maintenance and best catchment treatment plans shall increase the dam’s longevity and utilities.

Codes and Data of Satellite Observations Reveal 13 Years of Reservoir Filling Strategies, Operating Rules, and Hydrological Alterations in the Upper Mekong River Basin

Codes and Data of Satellite Observations Reveal 13 Years of Reservoir Filling Strategies, Operating Rules, and Hydrological Alterations in the Upper Mekong River Basin

Projection of climate change impacts on hydropower in the source region of the Yangtze River based on CMIP6

The source region of the Yangtze River located on the Qinghai-Tibet Plateau is very sensitive to climate change. The impact of climate change on the source region of the Yangtze River has been detected from multi-aspect, but limited research has been conducted on the hydropower impact of important water system, especially for the Yalong River, which is the longest tributary in the upper reaches of the Yangtze River and rich in hydropower reserves with a value of approximately 33.72 million kilowatts. In this study, we performed statistical downscaling of 10 Coupled Model Intercomparison Project Phase 6 (CMIP6) models and used the Bayesian weighted ensemble method to analyze the Yalong River basin. The interdecadal climate characteristics of the region were analyzed and drive the variable infiltration capacity (VIC) hydrological model coupled with reservoir operation module to obtain the spatiotemporal changes in water-energy resources in the future. The results showed the precipitation in the Yalong River basin showed an increasing trend (12.38 mm/10a, 25.65 mm/10a) under the shared socioeconomic pathways 2–4.5(SSP2-4.5) and socioeconomic pathways 5–8.5 (SSP5-8.5) scenarios. Coupled with reservoir operation rules, the excess water during the wet season could be transferred to the dry season. Even so, it was estimated the overall power generation of the basin would be reduced by 4% to 6% compared to the baseline period. This change will largely affect the energy of Chongqing and Sichuan Provinces, which rely heavily on the Yalong River for hydropower generation. Our framework and research results are expected to provide useful information for other river systems in the Qinghai-Tibet Plateau and can be used to re-examine the research results of related river basins.

Optimization of multipurpose reservoir system operation (Case study: Sefidrud and Shahryar reservoir dams)

Nowadays, effective water management becomes more vital all over the worlds. Due to the effect of climate change and population growth, reservoirs play a more important role in water resources management. Reservoirs can be used for multiple purposes such as irrigation, industrial water supply, hydropower generation, flood protection, water quality management, recreation and so on. In this paper, an optimized model have been considered and solved based on the goal programming method for the optimal operation of a multi-objective two reservoir systems in Sefidrud watershed. Release for irrigation demand and environment, flood controlling and recreation are represented as objectives. Then, to consider uncertainties and also for achieving the general method for reservoirs operation, because of the considerable advantages of linguistic rules in better inferring and interpretation of systems, an adaptive neuro based fuzzy inference system (ANFIS) approach is used to construct operation rules for these multipurpose reservoirs. The results of the ANFIS models show that they can be applied successfully to provide high accuracy for the management of the reservoirs system.

OPTIMAL OPERATION OF MULTIPURPOSE RESERVOIRS IN SERIES: ROSEIRES AND SENNAR CASE STUDY

The Roseires-Sennar Dams System (RSDS) at lower part of Blue Nile River play a vital role in water supply to the irrigation schemes in Sudan. The existing rule curves for this system belong to 1925 and 1966 for Sennar and Roseires reservoirs, respectively. Introduction of new irrigation schemes, approved climate change impacts on Blue Nile River flow and upstream developments in Ethiopia as well as the heightening of the Roseires Dam from elevation 480 to 490 m.a.s.l have shown the RSDS is losing its efficiency in terms of fully supplying the water demands. The literature addresses the simulation of Roseires and Sennar dams, and tries to find the best coordinated rule curves through a limited number of operation rules to find optimal operating rules for reservoirs that minimize the impacts of new developments, water demand growth and climate change on water supply to various demands on Blue Nile River. Such decisions are locally optimal in best condition since they do not consider the storage and carry-over capability of reservoirs that can transfer the non-optimal (locally optimal) decisions to other time steps of planning horizon and creat shortages in other time steps. Therefore, aim of this research is to find optimal coordinating operation rules for Roseires and Sennar dams that through a non-linear multi-period optimization model that considers the conditions of climate change, flow regime and water demand as scenarios. Model is validated by comparison with observed reservoir operation during November 1999 till May 2000. Eighteen scenarios that cover the normal, dry and very dry flow regimes, along with three suggested crop patterns and climate change impact are analyzed. Results shows in normal conditions of flow, crop pattern 2 is the most recommended with more than 11 Billion USD marginal profit and fully supplying the water demand and 1530 GWh energy generation per annum. The coordinated rule curves have a totally different pattern of emptying and filling compared with existing ones. Rule curves change from one flow regime to another, which proves how change in conditions of the system has influence on optimal operation rules. Comparison of marginal profits with crop pattern 2 shows in three inflow conditions of normal, dry and very dry years multi-period optimization model could keep the marginal profits above 11 Billion USD, let’s say, 11,050, 11,056 and 11,042 Billion USD, respectively, which shows the robustness of model in dealing with all conditions and keeping the marginal profits not affected. However, the Roseires rule curves are different in these three condition, while Sennar rules curves are almost the same. Without climate change impact, model can manage to supply the water demands fully in all flow conditions. However, water supply reliability is affected by climate change with all crop patterns. Roseires-Sennar Dams system in a normal year under climate change can produce 10,688 Billion USD marginal profit and 1371 GWh per year energy. It shows that model could manage the system performance so that climate change decrease the marginal profit by 3.27%, while inflow is reduced by 25% and water demands and evaporation increased by 19%. Energy generation under climate change has decreased by 10.5%, which is the most affected sector. Crop pattern 2 and 3 are not suitable for climate change conditions since up to 65% deficit in water supply can happen if very dry year realizing with climate change. In very dry conditions crop pattern 1 is more suitable to be practiced.