Multipurpose Reservoir Operation Research Articles

Simulation of Multipurpose Reservoir Operation with Hedging Rules

Reservoir operation plays an important role in the economic development of a region. The storage reservoirs are not only useful for supplying water for municipal and irrigation purpose, but also act as a protection barrier form flood, and the stored water can be used for generation of electricity power as well. To meet the objectives for which the reservoir was planned, it is vital to formulate guidelines for the operation of reservoir. This can be achieved by systematic operation of the system, and by the use of systematic and simplified rule curve for the operation of reservoir. Hedging rules are popular in drinking and irrigation water supply. Application of hedging is now gaining focus for hydropower power reservoir operation. In the present study, attempt has been made to formulate a new operating rule for multipurpose reservoir using hedging rules and the developed model was applied to a case study of Bargi reservoir in the Narmada basin in India. In order to increase the reliability of water supply for municipal, irrigation and average annual power production, the new operating rule has been developed using Standard Operation Policy (SOP) and hedging rule according to the priority of release for different purposes. The hedging rule based simulation model satisfies 97.5% of municipal water supply which is more than 8.25% of the present operational policy. The spill of the reservoir is decreased by 57 % compared to present policy. The performances of different hedging rules were compared with that of a new standard operating policies and the superiority of the hedging rules are discussed in this paper.

Optimisation of Multipurpose Reservoir Operation by Coupling Soil and Water Assessment Tool (SWAT) and Genetic Algorithm for Optimal Operating Policy (Case Study: Ganga River Basin)

Reservoirs are recognized as one of the most efficient infrastructure components in integrated water resources management. At present, with the ongoing advancement of social economy and requirement of water, the water resources shortage problem has worsened, and the operation of reservoirs, in terms of consumption of flood water, has become significantly important. To achieve optimal reservoirs operating policies, a considerable amount of optimization and simulation models have been introduced in the course of recent years. Subsequently, the assessment and estimation that is associated with the operation of reservoir stays conventional. In the present study, the Soil and Water Assessment Tool (SWAT) models and a Genetic Algorithm model has been employed to two reservoirs in Ganga River basin, India in order to obtain the optimal reservoir operational policies. The objective function has been added to reduce the yearly sum of squared deviation from preferred storage capacity and required release for the irrigation purpose. The rule curves that were estimated via random search have been discovered to be consistent with that of demand requests. Thus, in the present case study, on the basis of the generated result, it has been concluded that GA-derived optimal reservoir operation rules are competitive and promising, and can be efficiently used for the derivation of operation of the reservoir.

Multiobjective Optimization Modeling Approach for Multipurpose Single Reservoir Operation

The water resources planning and management discipline recognizes the importance of a reservoir’s carryover storage. However, mathematical models for reservoir operation that include carryover storage are scarce. This paper presents a novel multiobjective optimization modeling framework that uses the constraint-ε method and genetic algorithms as optimization techniques for the operation of multipurpose simple reservoirs, including carryover storage. The carryover storage was conceived by modifying Kritsky and Menkel’s method for reservoir design at the operational stage. The main objective function minimizes the cost of the total annual water shortage for irrigation areas connected to a reservoir, while the secondary one maximizes its energy production. The model includes operational constraints for the reservoir, Kritsky and Menkel’s method, irrigation areas, and the hydropower plant. The study is applied to Carlos Manuel de Céspedes reservoir, establishing a 12-month planning horizon and an annual reliability of 75%. The results highly demonstrate the applicability of the model, obtaining monthly releases from the reservoir that include the carryover storage, degree of reservoir inflow regulation, water shortages in irrigation areas, and the energy generated by the hydroelectric plant. The main product is an operational graph that includes zones as well as rule and guide curves, which are used as triggers for long-term reservoir operation.

Optimisation of Multipurpose Reservoir Operation- Bekhme Dam Greater Zab River Basin, Erbil Governorate and Duhok Governorate- Iraq

Optimisation of Multipurpose Reservoir Operation- Bekhme Dam Greater Zab River Basin, Erbil Governorate and Duhok Governorate- Iraq

Optimal multipurpose reservoir operation planning using Genetic Algorithm and Non Linear Programming (GA-NLP) hybrid approach

The major issue in water resource planning and management is determination of the optimal operating policy of a reservoir. In this study, GA-NLP hybrid approach has been applied. Genetic Algorithm (GA) is able to find the near optimal solution easily but for finding global optimal solution it will take too many function evaluations, so hybrid approach is adopted. GA is based on the principle of natural selection, derived from theory of evolution and it is popular for solving optimization problems. Non Linear Programming (NLP) is based on second derivatives of the Lagrangian function. To show practical utility, this approach is applied to an existing reservoir namely, Nagarjuna sagar Reservoir system in India. Maximizing sum of Irrigation releases into left and right main canal from the reservoir while maximizing annual power production is considered as the objective function. The constraints considered for this model are bounds for releases, storage capacity, canal capacity, and power generation capacity. The proposed model derives the optimal rule curves and release policies of the reservoir for different inflow scenario’s and for different priorities. Hence, based on the present case study it can be concluded that GA-NLP hybrid approach has the capability to perform efficiently, if applied in real world reservoir operation problems.

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

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

Optimal reservoir operation using soil and water assessment tool and genetic algorithm

Recent research and literature in the area of water resources demonstrated applications of modern tool of operation research and system analysis for assisting in development, planning, and management of water resources project. This study aims to derive equitable management of water resources from study area to fulfill various demands in command area. GIS-integrated SWAT model has been used to calculate the inflows for case study. The performance of model is evaluated by NS, R2, and RSR which are found to be 0.77, 0.79, 0.48 for calibration and 0.82, 0.83, 0.42 for validation, respectively, using SWAT-CUP. Further the multi-objective reservoir operation model is developed. The reservoir operation model considers two objectives: maximization of releases for irrigation and maximization of releases for hydropower generation. The applicability of model is demonstrated through the case study of Jayakwadi reservoir stage I, Maharashtra State, India. The multipurpose reservoir operation model is solved under MATLAB environment using multi-objective optimization of genetic algorithm solver and optimal Pareto front is generated. Total 33 solution sets are obtained. From these solution sets, decision-maker can choose operating policy as per requirement and acceptance level. In present approach, decision-maker is not required to give any objective function preference.

The multipurpose water uses of hydropower reservoir: The SHARE concept

Abstract The production and use of energy and the capture and use of water are vital to the economy and the health and welfare of all nations, and the wise stewardship of these resources is essential to the protection of the environment. After the 6th World Water Forum held in Marseille (France, 2012), Electricite de France (EDF) and the World Water Council (WWC) have agreed to work on “the multipurpose water uses of hydropower reservoirs”. This framework bridges between 6th Forum in Marseille and the 7th Forum in Daegu/Gyeongbuk in the Republic of Korea and addresses the following issues: (i) how to minimize contradictions/competition among multipurpose water uses of hydropower reservoirs, and (ii) how to set an appropriate governance to allow coordinated/integrated water uses management (in terms of strategy, planning, decision-making and operation). This process was conducted under a participative multi-stakeholder approach with governments, banks, NGOs, international organizations, hydropower utilities, and other sectors. Multipurpose hydropower reservoirs are designed and/or operated to provide services beyond electricity generation, such as water supply, flood and drought management, irrigation, navigation, fisheries, environmental services and recreational activities, etc. While these objectives (renewable and power services, water quantity management, ecosystem services, economic growth and local livelihoods) can conflict at times, they are also often complementary. Although there are no universal solutions, there are principles that can be shared and adapted to local contexts. Indeed the development and/or operation of such multipurpose hydropower reservoirs to reach sustainable water management should rely on the following principles: shared vision, shared resource, shared responsibilities, shared rights and risks, shared costs and benefits. These principles and acknowledgement of joint sharing among all the stakeholders are essential to successful development and management of multipurpose hydropower reservoirs, and should frame all phases from early stage to operation. The SHARE concept also gives guidance. Based on 12 worldwide case studies of multipurpose hydropower reservoirs, the SHARE concept was developed and proposed as a solution to address this issue. A special focus will be presented on the Durance–Verdon Rivers in France.

Comparison of static and dynamic resilience for a multipurpose reservoir operation

AbstractReliability, resilience, and vulnerability are the traditional risk measures used to assess the performance of a reservoir system. Among these measures, resilience is used to assess the ability of a reservoir system to recover from a failure event. However, the time‐independent static resilience does not consider the system characteristics, interaction of various individual components and does not provide much insight into reservoir performance from the beginning of the failure event until the full performance recovery. Knowledge of dynamic reservoir behavior under the disturbance offers opportunities for proactive and/or reactive adaptive response that can be selected to maximize reservoir resilience. A novel measure is required to provide insight into the dynamics of reservoir performance based on the reservoir system characteristics and its adaptive capacity. The reservoir system characteristics include, among others, reservoir storage curve, reservoir inflow, reservoir outflow capacity, and reservoir operating rules. The reservoir adaptive capacity can be expressed using various impacts of reservoir performance under the disturbance (like reservoir release for meeting a particular demand, socioeconomic consequences of reservoir performance, or resulting environmental state of the river upstream and downstream from the reservoir). Another way of expressing reservoir adaptive capacity to a disturbing event may include aggregated measures like reservoir robustness, redundancy, resourcefulness, and rapidity. A novel measure that combines reservoir performance and its adaptive capacity is proposed in this paper and named “dynamic resilience.” The paper also proposes a generic simulation methodology for quantifying reservoir resilience as a function of time. The proposed resilience measure is applied to a single multipurpose reservoir operation and tested for a set of failure scenarios. The dynamic behavior of reservoir resilience is captured using the system dynamics simulation approach, a feedback‐based object‐oriented method, very effective for modeling complex systems. The results of dynamic resilience are compared with the traditional performance measures in order to identify advantages of the proposed measure. The results confirm that the dynamic resilience is a powerful tool for selecting proactive and reactive adaptive response of a multipurpose reservoir to a disturbing event that cannot be achieved using traditional measures. The generic quantification approach proposed in the paper allows for easy use of dynamic resilience for planning and operations of various civil infrastructure systems.

Application of Integrated Hydrologic and River Basin Management Modeling for the Optimal Development of a Multi-Purpose Reservoir Project

Multi-purpose reservoir development have been always a big challenge for the management of water resources. This paper describes an integrated approach for investigating catchment hydrology in the development of a hydropower and a canal irrigation system based on model analyses. The investigation aims to adequately determine an optimal domestic and irrigation water resources allocation scheme based on an assessment of the reservoir water balance and capacity for hydropower. The soil and water assessment tool (SWAT) which characterizes basin hydrology and the water management and planning model MODSIM which provides a decision support system for water allocation optimization, were used in this study. The integrated approach was applied to Prek Te River basin in Cambodia. The water demand aspect was examined based on domestic water use, irrigation water, environmental flow, and water losses. An operational rule curve was developed for hydropower operation with respect to a power potential of 13 MW. Hydrologic modeling revealed 90 % dependable water of about 2.7 m3/s during the dry season and 214.3 m3/s during the wet season, indicative of a wet-season dependent reservoir for storage. Results from the 26-years simulation period also showed that diversions for domestic water and irrigation water supply were 92.3 % dependable for a 13 MW capacity hydropower development. The integrated approach was shown to be a valuable decision support tool for water resources management with the determination of an optimum policy for multi-purpose reservoir operation based on available basin water supply.

Optimal Operation of Multipurpose Reservoir for Irrigation Planning with Conjunctive Use of Surface and Groundwater

In the present study, a Linear Programming (LP) model is developed for the conjunctive use of surface water and ground water to obtain the optimal operating policy for a multipurpose single reservoir. The objective of the present study is to maximize the net benefit from the command area under consideration. The constraints imposed on the objective function are maximum and minimum irrigation demands, reservoir storages and canal capacity. The model takes into account the continuity constraint which includes inflows in to the reservoir, releases for irrigation, releases for hydro-power generation, evaporation losses, feeder canal releases, initial and final storages in the reservoir in each time period. The developed model is applied to the case study of Jayakwadi reservoir stage-I, built across river Godavari, Maharashtra, India. Initially the model is solved for the availability of surface water which results in net benefit of 3373.45 million rupees with irrigation intensity is 57.07%. Next the model solved by considering the availability of surface water and available potential of groundwater in the area, which results in net benefits of 3590.02 million rupees with an intensity of irrigation 58.48%. The present model takes in to account the socio-economic requirement of growing the essential crops to meet the requirement of the society. The model has also generated the canal wise optimal releases for irrigation and power, monthly utilization of groundwater, storages in the reservoir at the end of every month and corresponding head over the turbine.

State-of-the-Art for Modelling Reservoir Inflows and Management Optimization

A multi-purpose reservoir operation requires a good decision from the operator in order to maximize the value of water. Therefore, a good inflows modelling will be very helpful in providing a better optimization solution. By then, perplexing in the selection of the most preferable solution might happen to the operator. A comprehensive review of different computational intelligent models which applied in reservoir inflows modelling and management optimization is presented in this paper. The aim of this study is to review, compare and summarize their attempts along with difficulties in dealing with the water management problem. The benefits derived from such comparison are used to improve the performance of the existing models for future work. Study showed that models based evolutionary algorithm revealing a great potential in the management of reservoir operation. However more research about the most recent self-optimization modelling application needs to be revised.

Detecting Multi-Purpose Reservoir Operation Induced Time-Frequency Alteration Using Wavelet Transform

It is well recognized that natural flow variability is an inherent characteristic of rivers. Altered natural flow regime caused by anthropogenic regulations would threaten ecosystem biodiversity and deteriorate riverine health. Wavelet transform is a newly-developed tool that extracts dominant modes of variability by decomposing a non-stationary series into time-frequency space, which can be used to detect hydrologic alteration at various scales caused by reservoir operation. Continuous wavelet transform is simultaneously applied to recorded hourly inflow and outflow series of 1998–2008 for the Feitsui Reservoir located in northern Taiwan. Differences between wavelet power spectrum obtained for outflow and inflow series denote severity of hydrologic alteration. Greater spectral alteration is observed at less-than-1-day scales due to peak-load hydropower releases. The spectral alteration gradually declines with increasing scales. Different variation patterns for the yearly time-averaged spectral difference also reveal that the altered spectrum depends on hydrologic conditions. The index of spectral alteration (ISA), defined as the mean absolute deviations of power spectrum for all scales over a certain time period, is proposed to quantitatively assess severity of altered natural flow regime. ISA of 5 can be roughly recognized as the division of dry and non-dry years for the Feitsui Reservoir case. The obtained results offer decision makers useful information to adopt adaptive operating strategies to mitigate negative impacts of altered natural flow regime and derive optimal trade-off between human and environmental needs.

New Approach: Integrated Risk-Stochastic Dynamic Model for Dam and Reservoir Optimization

Multiple studies have developed management models to identify optimal operating policies for reservoirs in the last four decades. In an uncertain environment, in which climatic factors such as stream flow are stochastic, the economic returns from reservoir releases that are based on policy are uncertain. Furthermore, the consequences of reservoir release are not fully realized until it occurs. Rather than explicitly recognizing the full spectrum of consequences that are possible within an uncertain environment, the existing optimization models have focused on addressing these uncertainties by identifying the release policies that optimize the summative metric of the risks that are associated with release decisions. This technique has limitations for representing risks that are associated with release policy decisions. In fact, the approach of these techniques may conflict with the actual attitudes of the decision-makers regarding the risk aspects of release policies. The risk aspects of these decisions affect the design and operation of multi-purpose reservoirs. A method is needed to completely represent and evaluate potential consequences that are associated with release decisions. In this study, these techniques were reviewed from the stochastic model and risk analysis perspectives. Therefore, previously developed optimization models for operating dams and reservoirs were reviewed based on their advantages and disadvantages. Specifically, optimal release decisions that use the stochastic variable impacts and the levels of risk that are associated with decisions were evaluated regarding model performance. In addition, a new approach was introduced to develop an optimization model that is capable of replicating the manner in which reservoir release decision risks are perceived and interpreted. This model is based on the Neural Network (NN) theory and enables a more complete representation of the risk function that occurs from particular reservoir release decisions.

Sampling/stochastic dynamic programming for optimal operation of multi-purpose reservoirs using artificial neural network-based ensemble streamflow predictions

Due to limited water resources and the increasing demand for agricultural products, it is significantly important to operate surface water reservoirs optimally, especially those located in arid and semi-arid regions. This paper investigates uncertainty-based optimal operation of a multi-purpose water reservoir system by using four optimization models. The models include dynamic programming (DP), stochastic DP (SDP) with inflow classification (SDP/Class), SDP with inflow scenarios (SDP/Scenario), and sampling SDP (SSDP) with historical scenarios (SSDP/Hist). The performance of the models was tested in Zayandeh-Rud Reservoir system in Iran by evaluating how their release policies perform in a simulation phase. While the SDP approaches were better than the DP approach, the SSDP/Hist model outperformed the other SDP models. We also assessed the effect of ensemble streamflow predictions (ESPs) that were generated by artificial neural networks on the performance of SSDP/Hist. Application of the models to the Zayandeh-Rud case study demonstrated that SSDP in combination with ESPs and the K-means technique, which was used to cluster a large number of ESPs, could be a promising approach for real-time reservoir operation.

Flood Control in the Cuiabá River Basin, Brazil, with Multipurpose Reservoir Operation

Periodic flooding in the Cuiaba River Basin (CRB), which is located in the upper Pantanal region, in central-western Brazil, led to the construction of the Manso multipurpose reservoir and power plant. This study evaluates the influence of the Manso reservoir on the attenuation of downstream flooding specifically in the metropolitan area of Cuiaba, which is the capital city of the state of Mato Grosso. The flood routing provided by the Manso reservoir was simulated by means of the Puls modified method (level-pool routing method), and the translation of the flood wave during floodplain passage was calculated with the CLiv hydrodynamic model for critical hydrological events. It is demonstrated that the reservoir reduces the frequency of flood risk to downstream communities for return periods between 50 and 100 years. Despite the flood attenuation, other measures should be undertaken in addition to the reservoir operation to mitigate the impacts of flooding in a comprehensive and appropriate way. In particular, measures related to floodplain land use planning and management are important to ensure that the safety of the population does not exclusively depend on the upstream reservoir.

Goal Programming을 이용한 홍수기 저수지 최적 운영

홍수기 다목적댐 운영의 목적은 홍수조절용량을 최대한 이용하여 하류 주요 지점의 첨두홍수량을 저감시키거나, 계획홍수량을 초과하지 않도록 방류량과 방류시점을 조절함으로써 홍수피해규모를 최소화하는 것이다. 따라서 홍수기 다목적댐 운영에 있어 가장 중요한 것은 최적의 방류시점과 방류량의 결정이며 이를 통해 홍수기말 이수용량을 최대로 확보 하는 점이다. 본 연구에서는 다목적 최적화기법의 하나인 goal programming을 이용하여 홍수기 저수지 최적운영을 실시하였다. goal programming은 선형계획법 또는 비선형계획법을 이용하여 두 개 이상의 목적을 가진 문제의 최적 대안을 구하기 위해, 목표값으로부터의 편차의 합을 최소화하여 최적화하는 기법이다. 홍수기 다목적댐 운영에서 goal programming의 적용성을 검토하기 위해 실제 홍수 사상을 이용하여, 단일저수지 운영과 저수지 연계운영을 실시하였다. 단일저수지 운영을 적용하기 위한 시험유역으로는 충주댐 유역을 선정하였고 저수지 연계운영을 적용하기 위한 시험유역으로는 안동댐과 임하댐 유역을 선정하였다. goal programming의 결과 분석을 위해 저수지 모의운영 모형인 HEC-5 모형의 결과와 비교, 분석하였다. 검토 결과 goal programming을 이용할 경우 홍수기 말에 저수지 수위를 홍수기제한수위로 유지할 수 있었으며 주요 지점의 홍수량을 매 시간 적절히 계획홍수량 아래로 유지할 수 있었다. goal programming을 이용한 최적 운영의 경우 전 구간의 유입량을 알고 있다고 가정한 점에서 실제 저수지 운영과는 차이가 있으나, 적절한 제약조건을 적용하고 홍수예경보를 이용하여 예보된 유입량을 활용하면 최적의 방류량 시점과 방류량을 산정하여 홍수기 다목적댐을 효율적으로 운영할 수 있으며 주요 지점의 홍수량도 저감할 수 있을 것으로 판단된다. The purpose of multipurpose reservoir operation in flood season is to reduce the peak flood at a control point by utilizing flood control storage or to minimize flood damage by controlling release and release time. Therefore, the most important thing in reservoir operation for flood season is to determine the optimal release and release time. In this study, goal programming is used for the optimal reservoir operation in flood season. The goal programming minimizes a sum of deviation from the target value using linear programming or nonlinear programming to obtain the optimal alternative for the problem with more than two objectives. To analyze the applicability of goal programming, the historical storm data are utilized. The goal programming is applied to the reservoir system operation as well as single reservoir operation. Chungju reservoir is selected for single reservoir operation and Andong and Imha reservoirs are selected for reservoir system operation. The result of goal programming is compared with that of HEC-5. As a result, it was found that goal programming could maintain the reservoir level within flood control level at the end of a flood season and also maintain flood discharge within a design flood at a control point for each time step. The goal programming operation is different from the real operation in the sense that all inflows are assumed to be given in advance. However, flood at a control point can be reduced by calculating the optimal release and optimal release time using suitable constraints and flood forecasting system.

Deriving Optimal Refill Rules for Multi-Purpose Reservoir Operation

This paper focuses on deriving optimal refill rules for a multi-purpose reservoir, and aims to maximize utilization benefits under the condition of flood control safety. The entire flood season is divided into multiple sub-seasons (i.e. pre-flood season, main-flood season and post-flood season). By advancing the start of the refill period to the beginning of the post-flood season, seasonal design flows during the new refill period are estimated. A multi-objective refill operation model is proposed by combining flood control and conservation together. The simulation–optimization-test framework and hybrid multi-objective genetic algorithms are developed and used to optimize the rule curves. China’s Three Gorges Reservoir is selected as a case study and the application results show that the proposed model can increase the hydropower generation by 17.4%, decrease spilled water by 43.9%, and improve the refill probability greatly without decreasing the flood control standard and navigation probability during the refill period.

Differential Evolution Algorithm with Application to Optimal Operation of Multipurpose Reservoir

This paper includes an application of Differential Evolution (DE) for the optimal operation of multipurpose reservoir. The objective of the study is to maximize the hydropower production. The constraints for the optimization problem are reservoir capacity, turbine release capacity constraints, irrigation supply demand constraints and storage continuity. For initializing population, the upper and lower bounds of decision variables are fixed. The fitness of each vector is evaluated. The mutation and recombination is performed. The control parameters, i.e., population size, crossover constant and the weight are fixed according to their fitness value. This procedure is performed for the ten different strategies of DE. Sensitivity analysis performed for ten strategies of DE suggested that, De/best/1/bin is the best strategy which gives optimal solution. The DE algorithm application is presented through Jayakwadi project stage-I, Maharashtra State, India. Genetic algorithm is utilized as a comparative approach to assess the ability of DE. The results of GA and ten DE strategies for the given parameters indicated that both the results are comparable. The model is run for dependable inflows. Monthly maximized hydropower production and irrigation releases are presented. These values will be the basis for decision maker to take decisions regarding operation policy of the reservoir. Results of application of DE model indicate that the maximized hydropower production is 30.885 × 106 kwh and the cor-responding irrigation release is 928.44 Mm3.

Non-dominated archiving multi-colony ant algorithm for multi-objective optimization: Application to multi-purpose reservoir operation

Multi-objective optimization using heuristic methods has been established as a subdiscipline that combines the fields of heuristic computation and classical multiple criteria decision making. This article presents the Non-dominated Archiving Ant Colony Optimization (NA-ACO), which benefits from the concept of a multi-colony ant algorithm and incorporates a new information-exchange policy. In the proposed information-exchange policy, after a given number of iterations, different colonies exchange information on the assigned objective, resulting in a set of non-dominated solutions. The non-dominated solutions are moved into an offline archive for further pheromone updating. Performance of the NA-ACO is tested employing two well-known mathematical multi-objective benchmark problems. The results are promising and compare well with those of well-known NSGA-II algorithms used in real-world multi-objective-optimization problems. In addition, the optimization of reservoir operating policy with multiple objectives (i.e. flood control, hydropower generation and irrigation water supply) is considered and the associated Pareto front generated.