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Reservoir operations for single and multi-‎reservoirs ‎of rainwater harvesting systems has been ‎tested to ‎address the ‎deficit in supplying water and electric power for remote rural ‎communities ‎of ‎semi-arid region of AL-Khoser watershed, Iraq. The main basin ‎ was divided into ‎four sub-basins 1B, 2‎B, 3‎B and 4B. The Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) was ‎applied to estimate water volumes of the above proposed reservoirs. To optimize reservoir operations for the objective ‎function ‎of ‎maximized ‎total annual ‎hydropower generation, a technique was ‎used to ‎convert ‎non-linear ‎to linear problems. In which a linear approximation of the ‎non-linear power production term can be expressed ‎linearly by summing the vectors, the ‎release and storage, where the relationship between the ‎head and the storage is ‎directly proportional. Total annual hydropower ‎generation is maximized by ‎ optimized sustainable operation policies for single and ‎multi-‎reservoirs. Dry, average, and wet rainfall seasons were selected for 1985-2020. The ‎annual harvested water in the reservoirs ‎of Main Basin, 1B, 2B, 3‎B and 4B ranged between: 0.7790-4.1788, ‎‎2.1256-11.4010, and ‎‎5.10158-28.1985 ‎MCM for the three seasons. The capacity ‎of hydropower ‎generation was 82.59, ‎‎436.75 and 1034.70 Kw for the three seasons‎. The increase in ‎hydropower generation ‎is ‎achieved with multi-reservoirs operations ‎by 110%, 66% and 41% respectively. The importance of hydropower generation increase is ‎demonstrated by providing hydropower to additional families in the rural ‎community as their ‎primary source of power in addition to an increase in the irrigated areas. [ABSTRACT FROM AUTHOR]

The streamflow process is an crucial information resource for the joint optimal operation of reservoirs. As the length and representativeness of historical streamflow samples are insufficient for practice projects, streamflow stochastic generation approaches are usually used to expand the streamflow series. For the joint operation and management of the multi-reservoir system, the multisite streamflow stochastic generation (MSSG) with high-dimensional temporal-spatial correlation poses a challenge. This paper develops the generative adversarial network as a novel MSSG model. In contrast to the existing literature on MSSG, which solely focuses on a specific case study and provides a comparatively one-sided assessment, this paper evaluates multiple characteristics of streamflow at various time scales from three MSSG models in two instances. Specifically, three MSSG models, namely the seasonal autoregression (SAR) model coupled with the master station method, the Copula model coupled with the master station method, and the deep convolutions generative adversarial network (DCGAN) model, are employed to generate monthly, ten-daily, and daily streamflow series of the two-reservoir and eight-reservoir systems. This study aims to examine the performance of three models and provide recommendations for implementing MSSG approaches in practice. Results show that: (1) the priority should be given to the maximum iterations on the DCGAN model at a large time scale, while at a smaller time scale, the training of the model is directly linked to the setting of batch size; (2) the Copula model is capable for better retaining statistical characteristics of streamflow series for similarity; (3) the SAR model excels in simulating the extremes of streamflow; and (4) the DCGAN model possesses a significant advantage in capturing the temporal-spatial higher-order correlation, especially in systems comprising more than two reservoirs and with small time scales (e.g., daily streamflow). Furthermore, this study presents comprehensive and multi-scale recommendations for selecting MSSG approaches, thereby providing a theoretical foundation and practical value for MSSG in diverse scenarios. [ABSTRACT FROM AUTHOR]

This study investigates the effect of extreme storms on the safety of flood protection dams within complex schemes. A modeling methodology is developed using HEC-RAS 2D and presented on an illustrative case, where nine scenarios are simulated. The impact of climatic shifts on extreme storms and dams’ safety is highlighted. The results showed that, despite multi-reservoir systems can be efficient in flood protection against their design storms, they can cause catastrophic damage when subjected to extreme events that have become evident nowadays due to climatic shifts. This is attributed to the successive failure of the water storage structures in a progressive (“domino-like”) manner. The consequences of such breaches can significantly multiply the hazards. These findings can be linked to storm Daniel that occurred at Wadi Derna in Libya and caused two successive dam breaches, leaving a tragedy. The proposed modeling methodology can be useful for designers in evaluating complex scenarios.

To promote the multi-objective coordination of the three subsystems of water and sediment discharge, ecological and environmental, and social and economy in the Yellow River basin, an overall multi-objective collaborative framework of water and sediment regulation for the Yellow River was proposed. The model was constructed based on the overall coupling coordination degree of the system to achieve a flexible selection of objective functions and constraints, as well as an adaptive adjustment of weight coefficients under different water and sediment conditions and various combinations of engineering. Taking the Sanmenxia and Xiaolangdi reservoirs in the middle reaches of the Yellow River as a case study, the optimal water and sediment regulation of high-flow, normal-flow, and low-flow years was carried out. The results reveal that there is a strong competitive relationship between sediment discharge and power generation targets and a weak competitive relationship between ecological and power generation targets. The schemes with the highest coupling coordination degree of the whole system can achieve high-quality coordination of each target and tend to exert greater power generation benefits. The application results of the model can inspire managers to appropriately increase power generation in actual scheduling and pay attention to increasing the ecological water supply in low-flow years. This research can provide scientific and technological support for the practice of multi-objective optimal water and sediment regulation in the Yellow River. [ABSTRACT FROM AUTHOR]

This research aims to apply optimization techniques using atom search optimization (ASO), genetic programming (GP), and wind-driven optimization (WDO) with a reservoir simulation model for searching optimal rule curves of a multi-reservoir system, using the objective function with the minimum average quantity of release excess water. The multi-reservoir system consisted of five reservoirs managed by a single reservoir that caused severe problems in Sakon Nakhon province, Thailand, which was hit by floods in 2017. These included Huai Nam Bo Reservoir, the Upper Huai Sai-1 Reservoir, the Upper Huai Sai-2 Reservoir, the Upper Huai Sai-3 Reservoir, and the Huai Sai Khamin Reservoir. In this study, the monthly reservoir rule curves, the average monthly inflow to the reservoirs during 2005–2020, the water demand of the reservoirs, hydrological data, and physical data of the reservoirs were considered. In addition, the performance of the newly obtained rule curves was evaluated by comparing the operation with a single reservoir and the operation with a multi-reservoir network. The results showed situations of water shortage and water in terms of frequency, duration, average water, and maximum water. The newly obtained rule curves from the multi-reservoir system case showed an average water excess of 43.722 MCM/year, which was less than the optimal curves from the single reservoir case, where the average water excess was 45.562 MCM/year. An analysis of the downstream reservoir of the multi-reservoir system, which diverts water from the upstream reservoirs, was performed. The results showed that the new optimal rule curves of ASO, GP, and WDO operated as a multi-reservoir system performed better than when operated as a single reservoir. Therefore, this research is suitable for sustainable water management without construction. [ABSTRACT FROM AUTHOR]

• The shifting of extreme design rainfall events due to climate change is discussed. • A methodology for selecting extreme design scenarios is developed. • An efficient technique to model complex systems in HEC-RAS 2D is presented. • Hazard maps of successive/cascade dam failures are presented. This study investigates the effect of extreme storms on the safety of flood protection dams within complex schemes. A modeling methodology is developed using HEC-RAS 2D and presented on an illustrative case, where nine scenarios are simulated. The impact of climatic shifts on extreme storms and dams' safety is highlighted. The results showed that, despite multi-reservoir systems can be efficient in flood protection against their design storms, they can cause catastrophic damage when subjected to extreme events that have become evident nowadays due to climatic shifts. This is attributed to the successive failure of the water storage structures in a progressive ("domino-like") manner. The consequences of such breaches can significantly multiply the hazards. These findings can be linked to storm Daniel that occurred at Wadi Derna in Libya and caused two successive dam breaches, leaving a tragedy. The proposed modeling methodology can be useful for designers in evaluating complex scenarios. [ABSTRACT FROM AUTHOR]

In the real-time flood control operation of multi-reservoir systems, it is of great significance to establish a dynamic operating system with high efficiency based on the spatiotemporal variation of flood control situations. This paper proposes a self-adaptive modeling framework for real-time flood control operation of multi-reservoirs based on the cyber–physical system (CPS) theory. Firstly, the random flood samples considering the randomness of both space and magnitude are generated, and then the multi-reservoir real-time flood control hybrid operation (MRFCHO) model is established based on the dynamic identification of effective reservoirs. Then, the CPS theory is introduced to put forward the multi-reservoir real-time flood control hybrid operation cyber–physical system (MRFCHOCPS), which integrates real-time monitoring, control center, database, computation module, and communication network. Finally, the proposed framework is demonstrated in terms of accuracy, efficiency, and adaptability in real-time flood control operations. A case study of the multi-reservoir system upstream of the Lutaizi point in the Huaihe River basin in China reveals that (1) the equivalent qualified rate of the MRFCHO model is 84.9% for random flood samples; (2) the efficiency of solving the MRFCHO model is much higher than the efficiency of solving the MRFCJO model under the premise of ensuring the flood control effect, so it provides a reliable method for the real-time operation of basin-wide floods; (3) the MRFCHOCPS has good adaptability in real-time dynamic modeling and operation of large-scale multi-reservoir systems. [ABSTRACT FROM AUTHOR]

Stochastic dynamic programming (SDP) is an optimization technique used in the operation of reservoirs for many years. However, being an iterative method requiring considerable computational time, it is important to establish adequate convergence criterion for its most effective use. Based on two previous studies for the optimization of operations in one of the most important multi-reservoir systems in Mexico, this work uses SDP, centred on the interest in the convergence criterion used in the optimization process. In the first trial, following the recommendations in the literature consulted, the difference in the absolute value of two consecutive iterations was taken and compared against a set tolerance value and a discount factor. In the second trial, it was decided to take the squared difference of the two consecutive iterations. In each of the trials, the computational time taken to obtain the optimal operating policy was quantified, along with whether the optimal operating policy was obtained by meeting the convergence criterion or by reaching the maximum number of iterations. With each optimization policy, the operation of the system under study was simulated and four variables were taken as evaluators of the system behaviour. The results showed few differences in the two operation policies but notable differences in the computation time used in the optimization process, as well as in the fulfilment of the convergence criterion. [ABSTRACT FROM AUTHOR]

Compared to conventional operating rules (CORs) for multiple reservoirs in a basin, joint flood control operation can reduce flood loss in downstream cities. The CORs adopted for most reservoirs ignore among–basin coordination, leading to incomplete consideration of the problem of the compensation effect between the reservoir flood control storage capacity (FCSC) and uneven flood composition distribution. A parameterization–simulation–optimization framework was applied in this study to design reservoir joint optimized flood control operating charts (OFCOCs) and analyse the compensation effect between reservoirs. The non–fixed FCSC nodes method and guaranteed output were respectively adopted to bound the end water levels in reservoirs with low inflow but high FCSC values or those adopting dynamic flood limited water level (DFLWL) return to the flood limited water level (FLWL). Choosing the Xijiang River basin (XRB) as an example, the optimized OFCOC designed in this study achieved a better peak–cutting effect than that of the CORs. The peak–cutting rate of the OFCOC was 5.77%, while that of the CORs was 3.41%. Adoption of the non–fixed FCSC nodes method and guaranteed output could meet the constraint of water level return to the FLWL. Reasonable operating chart design could provide a guideline for scientific flood control. [ABSTRACT FROM AUTHOR]

The concept of conditional value- at-risk (CVaR) is introduced into the field of flood damage assessment, and a joint design method for multi-reservoir system flood storage based on CVaR is then proposed. The purpose of the method is to research on the mutual feedback mode for coordinated flood control among reservoirs by analyzing the degree of influence of each reservoir′s storage capacity on the flood control risk of the reservoir group system as a whole. The five-reservoir system of the Hanjiang River is selected as a case study, and the flood damage assessment index CVaR values corresponding to the present flood storage combination scheme (FSCS) are regarded as upper limit values. The results show that: ① The sensitivity rankings of the five reservoirs, in descending order, are: Sanliping, Yahekou, Danjiangkou, Ankang, and Pankou reservoirs. ② The flood damage assessment index CVaR values corresponding to different FSCSs may not be the same when the total flood storage of the multi-reservoir system is fixed as a constant, and there is a viable FSCS for the multi-reservoir system. ③ If the same CVaR constraint conditions are selected, the Danjiangkou Reservoir has greater flexibility to adjust its flood control capacity in the five-reservoir system than in the two-reservoir system, because the former considers the flood control coordination effect of more reservoirs (such as Pankou, Sanliping, Yahekou reservoirs). [ABSTRACT FROM AUTHOR]

The aim of this study was to show the importance of exploiting the appropriate sites for construction of dams on the borders of riparian countries. To achieve this aim, a multi-reservoir system was designed across the border of two riparian countries. In addition, simulation models that express the possible operating mechanisms for this system were created. This storage system comprises two reservoirs along the border of Iraq and Turkey. One simulation model of a real reservoir was formulated to prove the model's validity by comparing its output with the observed output of the real counterpart. Three simulation models for the proposed reservoirs were developed by adopting the standard operating policy. The first and second of these three models were built to mimic the operation of the two proposed reservoirs separately, while the third simulation model was formulated to operate these two proposed reservoirs simultaneously as united multi-reservoir system. The results indicated the efficiency of the simulation model for an existing reservoir. In addition, the results of the three simulation models of the proposed multi-reservoir system demonstrated the flexibility of these simulation models in imitating the operation of a storage system, whether it was a single or a multi-reservoir system. According to the results of these three simulation models, the two proposed reservoirs could be significantly beneficial to Iraq and Turkey. [ABSTRACT FROM AUTHOR]

In this paper the proposed constrained gravitational search algorithm (CGSA) is extended and used to solve multi-reservoir operation optimization problem. Tow constrained versions of GSA named partially constrained GSA (PCGSA) and fully constrained GSA (FCGSA) are outlined to solve this optimization problem. In the PCGSA, the problem constraints are partially satisfied, h owever, in the FCGSA, all the problem constraints are implicitly satisfied by providing the search space for each agent which contains only feasible solution and hence leading to smaller search space for each agent. These proposed constrained versions of GSA are very useful when they are applied to solve large scale multi-reservoir operation optimization problem. The constrained versions of GSA are formulated here for both possible variables of the problem means considering water release or storage volumes as the decision variables of the problem and therefore first and second formulations of these algorithms are proposed. The proposed algorithms are used to solve the well-known four and ten reservoir operation optimization problems and the results are presented and compared with those of original form of the GSA and any available results in the literature. The results indicate the superiority of the proposed algorithms and especially FCGSA over existing methods to optimally solve large scale multi-reservoir operation optimization problem. [ABSTRACT FROM AUTHOR]

The determination of optimal operation rules for water storage systems will provide a good perception on the ability of these systems to achieve their objective functions. This study aims to identify optimal operation policies by maximizing the annual hydropower generation of a multi-reservoir system that consists of two reservoirs with different functions in flood risk management. These reservoirs, namely, Mosul and Badush, are located in the Tigris River, Northern Iraq. The Mosul Dam was constructed to protect the cities located downstream, and the Badush Dam is building to absorb flood waves in case the Mosul Dam collapses. The particle swarm optimization model for a single reservoir (PSOS) was formulated to determine optimal operation policies during real operation time to maximize annual hydroelectric generation. PSOS was approved during these operations and developed to specify ideal operation rules for a multi-reservoir system (PSOM), which consists of two reservoirs, through three modes of annual inflows. Results of PSOS indicated its superiority during real-time operation. The annual hydropower generation was achieved by the optimal operation rules of PSOM during the three styles of inflows. These optimal policies will provide good insights into the potential of this multi-reservoir system in supplying the national electricity network with hydropower energy, which is considered environmentally friendly, in addition to achieving the original goals of its construction. [ABSTRACT FROM AUTHOR]

In this research, a new meta-heuristic algorithm, named artificial bee colony (ABC) algorithm, is used to solve multi-reservoir operation optimization problem. For this purpose, two improved versions of ABC are proposed by modifying the structure of original standard form of ABC algorithm. Furthermore, in order to increase the performance of proposed algorithms for solving large-scale problems, the constrained versions of original and improved form of ABC algorithms have been proposed in which the problem constraints are explicitly satisfied. Two benchmark text examples, including four- and ten-reservoir operation optimization problems, are solved here using proposed algorithms, and the results are presented and compared. In order to solve these problems, here, two formulations are also proposed in which in the first formulation, the water releases from the reservoir and in the second one the water storage volumes of the reservoir are considered as the decision variables of the problem. Comparison of the results shows that by using the improved ABC algorithm, the better results are obtained with less computational effort in comparison with the original form of ABC algorithm in which the result improvement is notable when the proposed constrained version of the algorithms is used. [ABSTRACT FROM AUTHOR]

Hydropower energy is one of the most economical and cleanest energies in the world. Due to the huge investment in hydropower projects, economic feasibility and determining the main design parameters related to plant sizing of hydro projects are extremely important. In this research, a simulation–optimization model for optimal design of hydropower systems with a systematic view of the basin (which is a complex nonlinear problem) has been developed. For water resources planning and management in the water basin, WEAP model has been used. Despite various capabilities, there are also limitations for hydropower systems modeling in WEAP. In this regard, a hydropower computation module has been employed to resolve these disadvantages. Then, PSO algorithm, linked to the simulation model and the developed optimization-simulation model has been used to solve the problem of optimal design of Garsha, Kuran Buzan, Sazbon and Tange mashoore power plant projects in Karkhe river basin. Objective function has been formulated based on two conventional methods in the economic analysis of hydro projects, i.e. electricity market price method and alternative thermal plant method. The objective function is maximization of net benefits of hydropower projects considering all resources, uses, and demands in the basin. Normal water level (NWL), Minimum Operation Level (MOL), Installed Capacity (IC) of dams and power-plants were chosen as decision variables of the problem. Finally, the results of optimal design of hydropower system have been discussed for both economic objective functions, followed by comparison and analysis of the results. the total generated energy and firm energy of the hydropower system is calculated bigger in alternative thermal plant method compared to market price method. However, the peak generated energy is computed larger in the market price. • Optimal design of hydropower projects is proposed with an integrated approach. • Market price (MP) and alternative thermal plant (ATP) are used as economic methods. • Total and firm energy produced in ATP method is higher than MP method. • In both economic objectives, the amount of firm energy of the system is not significant. [ABSTRACT FROM AUTHOR]

Dongting Lake, a large river-connected lake in the Yangtze River watershed, plays important roles in flood control, drought mitigation, and biodiversity conservation. Its ecosystem has recently been severely affected by upstream water resource development such as reservoir operations. In this study, an optimization model is developed for the operation of a multi-reservoir system, including the Three Gorges Reservoir (TGR) on the upper Yangtze River and 8 major reservoirs on the tributaries to Dongting Lake. The optimal target in pursuit of the ecological objective is to maximize the environmental water demand (EWD) satisfaction of the lake. A support vector regression-based model is used to predict the response of the lake level to reservoir operations. The optimization is carried out under different scenarios for both normal and dry conditions, and the results show that: (i) the existing operation policy could result in significant hydrologic alteration; (ii) in the normal condition, the proposed optimal joint operation policy could increase the general EWD satisfaction rate of Dongting Lake from 85.4% to 95.7%; and (iii) the improvement of EWD satisfaction in the normal condition is mainly affected by the TGR, while in the dry condition, the southern and western lake regions are more sensitive to the tributaries' reservoirs.

In this paper, alternative reservoir operation models under different environmental operating conditions were developed to analyze the impacts of applying different policies in a multi-reservoir system in order to balance human and environmental requirements. Three scenarios/models were developed under four sub-scenarios/operating conditions. The scenarios were: (1) an optimization model to maximize the hydropower production, (2) an optimization model to minimize the squared of the difference between the release and need, (3) a simulation model under the Hydropower Standard Operating Policy. The sub-scenarios were developed as follows: (i) no environmental flow, (ii) minimum environmental flow, (iii) environmental flow bounded by the minimum and maximum flow, and (iv) maximum environmental flow. Hydropower production and system performance criteria were calculated and compared in all cases. Moreover, the Range of Variability Approach was used to assess the hydrological alterations of each of the 12 cases. The results in a two reservoir cascade of Seimare-Karkheh, located within the Karkheh River Basin in Iran, showed that subscenario 3 performed best in all three scenarios. Further comparison indicated that scenario 1, under sub-scenario 3, was a good compromise solution, as it provided adequate hydropower production and performance criteria and the least hydrological alterations. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Graphical abstract Key findings (1) DC-WCA is faster in finding better solutions for benchmark problems, compared to the other reported optimizers. (2) The performance of DC-WCA is highly competitive with the other reported optimizers for the multi-reservoir optimization. Fig. 1 Comparison of ICGA, CPSO, WCA, and DC-WCA: (a) Benchmark problems; (b) Case study for multi-reservoir optimization. Highlights • A modified water cycle algorithm based on diversity evaluation and chaos theory (DC-WCA) is proposed. • The performance of DC-WCA is validated by six benchmark problems. • DC-WCA is applied for a long-term multi-reservoir optimization. • DC-WCA is faster in finding better hydropower generation for multi-reservoir system, compared to other reported optimizers. Abstract Hydropower generation is a common consideration for reservoir operations. Due to the characteristic of high dimensionality, multi-reservoir optimization for hydropower generation is challenging. Although the original water cycle algorithm (WCA) outperforms other metaheuristic optimization algorithms in solving constrained and unconstrained problems, it still gets trapped in the local optima in the case of some high-dimensional problems. For multi-reservoir optimization problems, this paper provides a modified WCA based on the diversity evaluation and chaos theory (DC-WCA) to avoid premature convergence. Six benchmark problems are examined using DC-WCA, WCA, improved chaos genetic algorithm (ICGA) and chaotic particle swarm optimization algorithm (CPSO) to evaluate the efficacy of DC-WCA. To investigate the application of DC-WCA for multi-reservoir optimization, a serially linked reservoir system located in the upper reach of the Yangtze river of China is used as a case study. After sensitivity analyses of the parameters, the four algorithms are used for long-term multi-reservoir optimization for hydropower generation. The optimization results show that 1) the annual hydropower generation optimized using DC-WCA is superior to those optimized using the other reported optimizers, and 2) the convergence rate of DC-WCA is faster than those of the other reported optimizers. This case study indicates that the application of DC-WCA for multi-reservoir optimization not only improves the calculation accuracy but also reduces computation time. [ABSTRACT FROM AUTHOR]

Continuous droughts and water scarcity have led to the need for optimal exploitation of dams’ reservoirs. Thus, the new meta-heuristic algorithm, spider monkey, is suggested for complex modeling of the multi-reservoir system in Iran with the aim of decreasing irrigation deficiencies. Golestan and Voshmgir dams’ operations are optimized with the spider monkey algorithm. The algorithm based on the exchange of information between local and global leaders with the other monkeys which improves the convergence speed. Average deficiencies for Golestan dam is computed as 2.1 and 1.9 MCM by spider monkey algorithm while it is respectively computed as 6.7, 16.4, 11.1, 4.1, 14.6, 19 MCM by particle swarm algorithm, harmony search algorithm, imperialist competitive algorithm, water cycle algorithm, genetic algorithm, and standards operation policy method. Also, the computation time of the spider monkey algorithm is 50 and 47 s for the Golestan and Voshmgir dams while the genetic algorithm optimizes the problem in 172.6 s and 112 s and the particle swarm algorithm needs 117.4 s and 100 s for the Golestan and Voshmgir, respectively. Also, root means square error (RMSE) and mean absolute error between demand and released water for the spider monkey algorithm have the least values among the applied evolutionary algorithms. Thus, the spider monkey algorithm is suggested as an appropriate method for optimizing the operation policy for the dam and reservoir systems. [ABSTRACT FROM AUTHOR]

Optimizing a multi-reservoir system is complicated, since the operation of one reservoir depends on other reservoir and may also have conflicting multiple objectives. The conflicting purposes of a multi-reservoir system requires a systematic multi-objective study. Recently, multi-objective evolutionary algorithms (MOEAs) have been widely used for the multi-objective analysis of the reservoir systems. However, the simple MOEAs result in premature convergence and local optimal solution for complex non-linear multi-objective optimization problems. To improve the performance and maintain the diversity in the population, chaos is being combined with the evolutionary algorithms for optimizing complex problems. In the present study, the chaos algorithm is coupled with MOEAs such as non-dominated genetic algorithm-II (CNSGA-II) and multi-objective differential evolution algorithm (CMODE) to derive an optimal crop planning for a multi-reservoir system having intra-basin water transfer. The model is developed with the objective of maximizing the net benefits and maximizing the crop production, subject to various physical, land and water availability constraints. The resulted optimal policy is further assessed using a simulation model and its performance is evaluated using various statistical indices. It is found that CMODE has resulted in slightly higher net benefits of Rs. 1921.77 Million and 1201.55 thousand tons of crop production with an irrigation intensity of 106.29% compared to other techniques used in this study. It has also resulted in an optimal spatial and temporal intra-basin water transfer from the upstream reservoirs to the downstream reservoir. The simulation of optimal results showed that the optimal policies obtained from CMODE performed well for longer period with less irrigation deficits. All the reservoirs in the system achieved more than 95% reliability in meeting the irrigation demands and intra-basin water transfer. [ABSTRACT FROM AUTHOR]

Seeking the optimal strategy of a multi-reservoir system is an important approach to develop hydropower energy, in which the Genetic Algorithm (GA) is commonly used as an effective tool. However, when the traditional GA is applied in solving the problem, the constraints of water balance equation, hydraulic continuity relationship and power system load demand might be violated by the crossover and mutation operator, which decreases the efficiency of the algorithm in searching for a feasible region or even leads to a convergence on an infeasible chromosome within the expected generations. A modified GA taking stochastic operators within the feasible region of variables is proposed. When determining the feasible region of constraints, the progressive optimal approach is applied to transform constraints imposed on reservoirs into a singular-reservoir constraint, and a joint solution with consideration of adjacent periods at crossover or mutation points is used to turn the singular-reservoir constraints into singular variable constraints. Some statistic indexes are suggested to evaluate the performances of the algorithms. The experimental results show that compared to GA adopting a penalty function or pair-wise comparison in constraint handling, the proposed modified GA improves the refinement of the quality of a solution in a more efficient and robust way.

Optimal utilization of available water resources has become more urgent due to the rapid growth of the economy and population. The joint operation of the Three Gorges cascade and Qingjiang cascade reservoirs in China was studied in this paper. Choosing maximization of hydropower generation and hydropower revenue as objective functions respectively, optimal models were established for individual and joint operation of the cascade reservoirs. The models were solved by the progressive optimality algorithm. The storage and electric compensation benefits among cascade reservoirs were analyzed. The daily inflow data of consecutive hydrological years of 1982–1987 were selected for a case study. Compared with the design operation rule, the joint operation of the multi-reservoir system can generate 5.992 billion kWh of extra power or an increase of 5.70% by the objective function of maximum hydropower generation. Through reservoir storage compensation, the spilled water of the Three Gorges and Qingjiang cascade reservoirs was decreased by 78.741 and 5.384 billion m3, respectively.

The pollution, changing according to various standards, is directly proportional to water quality in rivers. In this study, data and restrictions prescribed for standards of water quality such as Turkish Standards Institute (TSI), European Commission (EC), and the World Health Organization (WHO) were used to determine water pollution. For this purpose, correlation analysis was made to identify strong relationships between data. Regression analysis and Artificial Neural Networks (ANN) models are developed based on these standards by data obtained from correlation analysis. The Lower Sakarya River is selected as application area, and measurement of the water quality values of this river is used in these models. Pollution control flows in the river are obtained by the ANN models and regression analysis. The obtained results are compared with regard to these standards. [ABSTRACT FROM AUTHOR]

This paper evaluates the combined impacts of climatic and demographic changes on a multipurpose reservoir system in the Harz mountains in northern Germany. For this purpose, the spatially distributed hydrological model PANTA RHEI was firstly calibrated and validated with gridded observational data. Secondly, the hydrological model was forced with data from two regional climate models. The possibilities and limitations of using current regional climate models as an input for hydrological modelling in very high resolution in space and time were evaluated. Their applicability in reservoir operation optimization on an hourly time step was demonstrated. For an increase in extreme events, indicated by one regional climate model, the impact of an adaptation of operation rules with respect to flood protection on the other uses of the system was assessed. Furthermore, a new method was presented, how economic information from national accounting in combination with demographic scenarios can be used in exposure analysis. The paper ends with a demonstration of the importance of combining the impacts of climatic and demographic change, while developing sound and cost-efficient water resources management strategies for the near and distant future. [ABSTRACT FROM AUTHOR]

This study introduces a mixed integer linear fractional programming (MILFP) method to optimize conjunctive use of future surface water and groundwater resources under projected climate change scenarios. The conjunctive management model maximizes the ratio of groundwater usage to reservoir water usage. Future inflows to the reservoirs were estimated from the future runoffs projected through hydroclimate modeling considering the Variable Infiltration Capacity model, and 11 sets of downscaled Coupled Model Intercomparison Project phase 5 global climate model projections. Bayesian model averaging was adopted to quantify uncertainty in future runoff projections and reservoir inflow projections due to uncertain future climate projections. Optimized conjunctive management solutions were investigated for a water supply network in northern Louisiana which includes the Sparta aquifer. Runoff projections under climate change scenarios indicate that runoff will likely decrease in winter and increase in other seasons. Results from the developed conjunctive management model with MILFP indicate that the future reservoir water, even at 2.5% low inflow cumulative probability level, could counterbalance groundwater pumping reduction to satisfy demands while improving the Sparta aquifer through conditional groundwater head constraints. [ABSTRACT FROM AUTHOR]

To address the decision-making problem for real-time multi-objective flood operations in multi-reservoir system, this paper develops a multi-objective best compromise decision model (MoBCDM). Utility function is used to quantitatively express the preference of decision maker, and also fuzzy analytic hierarchy process (FAHP) and segmentation and averaging (Seg/Ave) are adopted together with the preferences of decision participants (hydrologist and reservoir manager) to convert the problem into a scalar optimization. The differential evolution (DE) algorithm is implemented for obtaining the best compromise solution. The multi-objective flood operation problem in Shiguan River Basin (in China), which contains two reservoirs and three flood control points, is used as a case study. The analyses are performed to compare four historical flood operations scenarios, this model and current operating rules. The results of the analyses show that the MoBCDM outperforms all operational scenarios in terms of peak flow reduction at three flood downstream control points. In addition, the MoBCDM execution is very efficient in real-time implementation, and also weighting coefficients for the use by the MoBCDM can get high resolution calculated by FAHP. [ABSTRACT FROM AUTHOR]

A Genetic Algorithm (GA) method for optimization of multi-reservoir systems operation is proposed in this paper. In this method, the parameters of operating policies are optimized using system simulation results. Hence, any operating problem with any sort of objective function, constraints and structure of operating policy can be optimized by GA. The method is applied to a 3-reservoir system and is compared with two traditional methods of Stochastic Dynamic Programming and Dynamic Programming and Regression. The results show that GA is superior both in objective function value and in computational speed. The proposed method is further improved using a mutation power updating rule and a varying period simulation method. The later is a novel procedure proposed in this paper that is believed to help in solving computational time problem in large systems. These revisions are evaluated and proved to be very useful in converging to better solutions in much less time. The final GA method is eventually evaluated as a very efficient procedure that is able to solve problems of large multi-reservoir system which is usually impossible by traditional methods. In fact, the real performance of the GA method starts where others fail to function.

The paper will describe the algorithm based on adaptive optimization of multi reservoir control, which the medium-term water flow predictions into the reservoirs for several months ahead repeatedly use. Hydrological prediction model was created using ANN method and values of control outflows are searching by optimization based on evolutionary algorithms optimization technique. The objective function was descripted as the sum of squares deviations between required and actual controlled water outflow from reservoirs where objective function is minimized. The algorithm of adaptive control is applied to the operation storage control of selected reservoir system, which open water reservoirs Vir and Brno are created. [ABSTRACT FROM AUTHOR]

Efficient utilization of water resources by reservoir operation in arid and semi-arid regions has been a traditional and important approach to mitigate water and energy scarcity. As the complexity of water resources system increases, there are urgent needs to apply effective optimization techniques to derive better operation rules. The meta-heuristic algorithms have been an alternative to the optimal operation of multi-reservoir system (OOMRS) for their parallel search capabilities. This paper presents the application of the cuckoo search (CS) algorithm to OOMRS with the objective to maximize the energy production. The penalty method was used to handle the physical and operational constraints. To make the CS more efficient, the optimized parameters of the CS were selected based on the parameter sensibility analysis. Finally, the performance of the CS was accessed by comparison with the genetic algorithm (GA) and the particle swarm optimization (PSO) under the same objective function evaluations (FEs). A case study of China's Wujiang multi-reservoir system reveals that the CS can provide better and more reliable optimal results with average energy production of 12.31 billion kW∙h, 10.43 billion kW∙h, and 10.02 billion kW∙h for three different scenarios, which are approximately 0.52, 0.32, and 1.64 % higher than that of the GA, respectively. Meanwhile, the convergence performance of the CS is also satisfying. Therefore, it can be concluded that the CS is quite promising in handling complex reservoir operation optimization problem in terms of its simple structure, excellent search efficiency, and strong robustness. [ABSTRACT FROM AUTHOR]

• Defining the risk of multi-reservoir flood control operation considering model structure and hydrological uncertainties. • Establishing a risk analysis model based on the Bayesian network theory. • Quantitatively analyzing the risk under double uncertainties and its spatial characteristics. In the real-time flood control operation of a multi-reservoir system, the multi-reservoir real-time flood control hybrid operation (MRFCHO) model with reduced structure is an effective way to improve the efficiency, but the reduction of the model structure may cause greater flood risk. This paper focuses on this scientific problem and evaluates the reliability of the MRFCHO model in real-time flood control operation through risk analysis. Firstly, the flood risk is defined. Then, the Bayesian network risk analysis model is established through four parts: Bayesian network structure construction, training samples generation, parameter learning, and inference. This paper takes the flood control system in upstream of the Lutaizi point in the Huaihe River basin as a case study. The flood risk of the MRFCHO model caused by the model structure reduction is quantitatively described, the spatial distribution and propagation characteristics of flood risk are evaluated, and the flood risk caused by the double uncertainties of the model structure and flood forecasting is analyzed. Besides, the factors affecting the risk of the public flood control point are diagnosed. The results show that (1) the model structure reduction does not significantly increase the flood risk at the public flood control point, and there is no obvious propagation law of flood risk in space; (2) compared with only considering the model structure reduction, considering the double uncertainties of flood forecasting and model structure reduction has a 65% probability of increasing the risk; (3) Runoff from the Runheji point in the upper reaches of main stream and the lateral inflow of Lutaizi point are the main reasons for the risk of Lutaizi point. [ABSTRACT FROM AUTHOR]

• Multi-reservoir system's flood damage assessment incorporating CVaR is established. • Proposed optimal model deduce the flood storage combination scheme's feasible area. • The sensitivity of each reservoir to the system's flood loss has been analyzed. • Optimal model helps to trade-off between flood control and power generation benefits. The joint design and operation of multi-reservoir systems is a vital issue for reservoir management. Existing studies mostly focus on determining the optimal scheme by establishing an optimization model and relying on intelligent algorithms. However, the research on the mutual feedback mechanism between the flood control capacity of each reservoir has not been adequately addressed. The overall aim of this paper is to propose a new joint optimization method for design and operation of multi-reservoir systems considering the conditional value-at-risk (CVa R α). In the proposed method, the flood damage assessment with CVa R α for a multi-reservoir system is constructed firstly, and then the feasible flood storage combination scheme (FSCS) of reservoirs in the system is deduced. Finally, the tradeoffs between the hydropower generation benefit and flood damage loss have been analyzed. Selecting China's Ankang-Danjiangkou Cascade Reservoirs as a case study, the results indicate that (1) the CVa R α value is more sensitive to changes in the flood storage of Danjiangkou reservoir (larger and downstream) than that of Ankang reservoir (smaller and upstream); (2) the feasible area of the FSCSs can be described as a triangle, and the boundary of this feasible interval is determined by the allowable minimum flood storage (AMFS) value of each reservoir; and (3) the relationship between the hydropower generation benefit and the flood damage assessment index CVa R α is not monotonic. These findings are helpful for understanding the relationship between flood storage values of each reservoir from the perspective of the entire multi-reservoir system. [ABSTRACT FROM AUTHOR]

• A new reservoir sediment management routine ResSMan was developed for SWAT. • ResSMan allows for system-wide coordinated sediment management. • Uncoordinated flushing of multiple reservoirs in the 2S basin ineffective for sediment removal. • Loss of energy production for individual reservoirs can be significant. Sedimentation is one of the major challenges for the long-term sustainable operation of a hydropower reservoir. Trapping of sediment reduces its storage capacity and consequently diminishes hydropower production. Here first the development of a REServoir Sediment MANagement routine (ResSMan) and its integration into a hydrological model, the Soil and Water Assessment Tool (SWAT) is presented. ResSMan has functions to determine sediment accumulation in multiple reservoirs, and its impacts on the storage capacity and hydropower production under user-specified operation policies. It allows to compute the restoration of storage capacity due to the removal of sediment by flushing, i.e. the removal of sediment from a reservoir by passing water and sediment through the low-level outlets, and sluicing, i.e. passing sediment before suspended sediment solids have settled down in the reservoir. The capabilities (flushing and sluicing) of ResSMan were evaluated through a comparison with the Sediment Simulation Screening (SedSim) model, a well-tested sediment management simulation model and the resulting R2 values of 0.99 validated its capabilities. Subsequently, ResSMan was applied to assess and manage reservoir sedimentation using different management strategies in a complex system of 19 reservoirs (12 currently existing) in the Sesan and Srepok (2S) basin of the Mekong River for 2021–2120. The unregulated mean annual sediment yield at the outlet of the 2S basin was estimated as 7.24 million tonnes/year (Mt/y) and it will be reduced to 0.11 Mt/y due to the operation of the 19 reservoirs. In total 924 Mt of sediment will accumulate in these 19 reservoirs over 100 years, resulting in an average trapping efficiency of 74% (ranging from 11% to 97%). System-wide sediment management coordination simulations demonstrated that bi-annually and 5-yearly flushing of alternate reservoirs are effective options for efficiently releasing sediment in the 2S basin. However, the use of frequent flushing (annual or bi-annual) may be more favourable to minimize adverse impacts due to release of higher sediment loads on downstream ecosystems. The analysis is an initial step towards the coordination of sediment management plans and policies for the multi-reservoirs system in the Mekong basin. [ABSTRACT FROM AUTHOR]

This paper presents an online optimization scheme for combined use of Artificial Neural Networks (ANN), hedging policies and harmony search algorithm (HS) in developing optimum operating policies for Tehran water resources system. Past efforts in this area are concentrated on using an offline approach. In that approach, an optimization method is first used to derive a long-term set of optimum reservoir releases. These releases are then used as the target vector for training the ANN model. The online method simultaneously uses the optimization and ANN methods and can adopt objective functions other than minimizing the error indices. Therefore, it requires methods other than the backpropagation for training the ANN model. Hence, under the proposed online approach the application of a heuristic method, such as HS, is inevitable for training the network. This is accomplished by using an optimization-simulation procedure where different objective functions and system constraints could be easily handled. The proposed approach is a novel and efficient method for finding the parameters of hedging policies where earlier methods suffered from high computational costs and the curse of dimensionality. The results show the superiority of the proposed online scheme. Moreover, a surrogate model for the hedging policy is presented, which by adhering to the principle of parsimony is more efficient in large scale systems involving many decision variables. [ABSTRACT FROM AUTHOR]