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1.
Sensitivity of reservoir operation performance to climatic change   总被引:4,自引:2,他引:2  
The potential impacts of changing climatic conditions on the operational performance of water resource systems was investigated in this paper. A multi-site streamflow generation model was used to synthesize potential monthly flow sequences reflecting two different sets of climatic conditions. The generated data were subsequently employed as input to a reservoir operation model that was used to determine the reservoir response to the inflow resulting from the implementation of the reservoir operating policy. The performance of an example reservoir system, the Shellmouth Reservoir located in the Canadian province of Manitoba, was evaluated and compared for the two sets of conditions. The operational performance was evaluated in terms of the reliability of the system for meeting the three purposes of the actual reservoir. The reservoir performance was determined to be sensitive to the inflow data. The results indicate that climatic change has potentially important implications for the operation of the example reservoir system.  相似文献   

2.
A genetic algorithm (GA) and a backward moving stochastic dynamic programming (SDP) model has been developed for derivation of operational policies for a multi-reservoir system in Kodaiyar River Basin, Tamil Nadu, India. The model was developed with the objective of minimizing the annual sum of squared deviation of desired target releases. The total number of population, crossover probability and number of generations of the GA model was optimized using sensitivity analysis, and penalty function method was used to handle the constraints. The policies developed using the SDP model was evaluated using a simulation model with longer length of inflow data generated using monthly time stepped Thomas–Fiering model. The performance of the developed policies were evaluated using the performance criteria namely, the monthly frequency of irrigation deficit (MFID), Monthly average irrigation deficit (MAID), Percentage monthly irrigation deficit (PMID), Annual frequency of irrigation deficit (AFID), Annual average irrigation deficit (AAID), and Percentage annual irrigation deficit (PAID). Based on the performance, it was concluded that the robostic, probabilistic, random search GA resulted in better optimal operating policies for a multi-reservoir system than the SDP models.  相似文献   

3.
Ant Colony Optimization for Multi-Purpose Reservoir Operation   总被引:4,自引:1,他引:3  
In this paper a metaheuristic technique called Ant Colony Optimization (ACO) is proposed to derive operating policies for a multi-purpose reservoir system. Most of the real world problems often involve non-linear optimization in their solution with high dimensionality and large number of equality and inequality constraints. Often the conventional techniques fail to yield global optimal solutions. The recently proposed evolutionary algorithms are also facing problems, while solving large-scale problems. In this study, it is intended to test the usefulness of ACO in solving such type of problems. To formulate the ACO model for reservoir operation, the problem is approached by considering a finite time series of inflows, classifying the reservoir volume into several class intervals, and determining the reservoir release for each period with respect to a predefined optimality criterion. The ACO technique is applied to a case study of Hirakud reservoir, which is a multi-purpose reservoir system located in India. The multiple objectives comprise of minimizing flood risks, minimizing irrigation deficits and maximizing hydropower production in that order of priority. The developed model is applied for monthly operation, and consists of two models viz., for short-time horizon operation and for long-time horizon operation. To evaluate the performance of ACO, the developed models are also solved using real coded Genetic Algorithm (GA). The results of the two models indicate that ACO model performs better, in terms of higher annual power production, while satisfying irrigation demands and flood control restrictions, compared to those obtained by GA. Finally it is found that ACO model outperforms GA model, especially in the case of long-time horizon reservoir operation.  相似文献   

4.
Today's water systems require integrated water resource management to improve the water supply for conflicting water uses. This research explores alternative policies to improve the water supply for two conflicting uses, hydropower and environmental, using the Leishui River basin and Dongjiang reservoir as a case study. First, the natural flow regime prior to reservoir construction (pre‐1992) was estimated by performing a statistical analysis of 41 years of daily streamflow data (March 1952–February 1993). This natural flow regime was used as a template for proposing environmental flow (e‐flow) requirements. The post‐reservoir flow regime (post‐1992) (March 1993–February 2011) was analysed to estimate the streamflow alteration. Results show that the natural flow regime has been completely transformed; post‐1992 winter normal flows are greater, and summer flows are smaller than pre‐1992 conditions. Also, the occurrence of natural floods has been prevented. Second, a planning model was built of the current operation of the Dongjiang reservoir and used for comparison of four alternative water management policies that considered e‐flow releases from the Dongjiang reservoir. The scenarios that considered combinations of the current operational policy and e‐flow releases performed better in terms of hydropower generation than the current operation. Different volumes of e‐flow requirements were tested, and an annual e‐flow volume of 75% of the pre‐1992 hydrograph was determined to generate the most hydropower while providing for environmental water needs. Trade‐offs are essential to balance these two water management objectives, and compromises have to be made for both water uses to obtain benefits. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

5.
In this study, application of Genetic Algorithms (GA) is demonstrated to optimize reservoir release policies to meet irrigation demand and storage requirements. As it is commonly recognized that accuracy of inflow forecast and operating time horizon affects the optimal policies, a trial-and-error approach is suggested to identify the appropriate trade-off between forecast accuracy and operating horizon. The flexibility offered by GA to set up and evaluate objective functions is exploited towards this end. The results are also compared with Linear Programming (LP) model. It is concluded that forecasts models of high accuracy are desirable, particularly when the system is to be operated for periods of high demand. In such cases, the optimization with longer time horizon ensures achievement of the objective more uniformly over the period of operation. The performance of GA is found to be better than LP, when forecast model of higher accuracy and longer period of operating horizon are considered for optimization.  相似文献   

6.
A generalized linear decision rule is presented which takes into account the aspect of spill in a multi-lag LDR model. The proposed rule incorporates past inflow experience to determine the optimum release rules based on a stochastic (linear) programming optimization model. It also prescribes a procedure of determining spill, should it occur, and the method of adjusting the release policy, accordingly, for the subsequent periods, which are directly affected by the spill of the current period. The use of the rule also makes it possible to produce a specification for a reservoir with a smaller capacity by taking liberal constraints on the reservoir freeboard during the monsoon months. The problem is solved, for the purpose of illustration, using the historical data of a river located in central India. Two synthetic streamflow series of a duration of 50 years each are generated under lognormal flow assumption. The prescribed release rules are applied to a hypothetical reservoir with the optimum capacity determined by the linear programming method, and the generated series as the inflow. The results and findings are quite satisfactory.  相似文献   

7.
The construction and operation of hydropower reservoirs on the Lancang River have drawn worldwide concern, because streamflow changes have occurred in this river since the introduction of dams. To address these concerns, it is necessary to quantitatively assess relative contributions of climatic variations and human activities to these changes. In this research, Mann-Kendall method was used to assess the trends in hydro-climatic data. The streamflow data were divided into a reference period (1956–1985) and a change period (1986–2008) based on hydropower reservoir construction timeline. The Back-Propagation Artificial Neural Network (BP-ANN) model was used to reconstruct natural streamflow. The contributions of climatic variations and human activities were investigated at the yearly, seasonal and monthly time scales. The results indicate that human activities exerted a slightly greater impact on flow changes than did climatic variations, at the yearly time scale (54.6 and 45.4 %, respectively). At the seasonal time scale, climatic variations made a greater contribution (65.8 %) during the wet season, while the contribution of human activities became the dominant factor during the dry season (85.3 %). At the monthly time scale, the contribution of climatic variations in January, June, August, and September was greater than that of human activities, while in the remaining eight months, human activities exerted a greater contribution than did climatic variation. The relative contributions of human activities and climatic variations (RCs) were also determined during the single- and cascade-dam periods; these did not always increase at the three time scales when dam system shifted from single-dam to cascade-dam.  相似文献   

8.
Assessing potential deviations of the fundamental river basins’ hydrological processes and streamflow characteristics from the “natural trajectory” represents a high-priority objective to understand the biological impact of altered flow regime on river ecosystems. Existing approaches are mainly based on the analysis of daily-based indicators of hydrologic alteration, which requires wide database, including “pre-impact” and “post-impact” daily flow data frequently unavailable. The hydrological modeling is commonly used to face data missing problems or reconstruct natural conditions, even if models, especially at the daily scales, are often complex and computationally intensive. The use of simpler and more parsimonious models results, sometimes, essential for practical applications, also in consideration of the typical scarce availability of some data. This paper proposes an alternative approach for the evaluation of rivers flow regime alterations, based on different monthly hydrological indicators that are first computed and then combined to provide a global index of alteration. The procedure, conceptually derived from the Range of Variability Approach (RVA), is applied and tested on two Sicilian river basins (Italy) subject to anthropogenic influence. Streamflow regime for both the basins results differently disturbed by upstream human pressures. An alteration index is computed using available observations as “post-impact” monthly flow time-series, while time-series relative to “pre-impact” conditions have been reconstructed by the Tri.Mo.Ti.S. model, an innovative monthly and high-performing regional regressive hydrological model. The methodology, easily transferable to other regions, has revealed particularly efficacious in identifying and quantifying the existing human pressures and can be considered as a suitable tool for water resource management and policy planning activities.  相似文献   

9.
River flow simulation is required on water resources planning and management. This paper proposes hierarchical network-copula conditional models to generate two-dimension monthly streamflow matrix aiming at simulating flow both on time and space. HNCCMs develop the simulation generator driven by both temporal and spatial covariates conditioned upon values of a set of parameters and hyper parameters which can be addressed from the three-layer hierarchical system. In the first layer, streamflow time series of the station at the most upstream is generated using bivariate Archimedean copulas and river flow space series in each month at stations down a river in sequence is simulated by nested copulas in the second layer. Last, the seasonal characters of the temporal parameters and covariates are detected as well as the spatial ones are detected using the neural network by fitting them into functions to contribute to the downscaling of space series. A case study for the model is carried on the Yellow River of China. This case (1) detects temporal and spatial relationships which illustrate the capacity of catching the seasonal characterize and spatial trend, (2) generates a river flow time series at Huayuankou station as well as (3) simulates a flow space sequence in January picking out best fitted building blocks for the cascade of bivariate copulas, and finally (4) synthesizes two-dimension simulation of monthly river flow. The result illustrates the essentially pragmatic nature of HNCCMs on simulation for this spatiotemporal monthly streamflow which is nonlinear and complex both on time and space.  相似文献   

10.
In achieving the final objective of the European Water Framework Directive, the evaluation of the ‘hydrological status’ of a water body in a catchment is of the utmost importance. It represents the divergence of the actual hydrological regime from its ‘natural’ condition and may thus provide crucial information about the ecological status of a river. In this paper, a new approach in evaluating the hydrological status of a temporary river was tested. The flow regime of a river has been classified through the analysis of two metrics: the permanence of flow and the predictability of no‐flow conditions that were evaluated on monthly streamflow data. This method was applied to the Candelaro river basin (Puglia, Italy) where we had to face the problem of limited data availability. The Soil and Water Assessment Tool model was used when streamflow data were not available, and a geographic information system procedure was applied to estimate potential water abstractions from the river. Four types of rivers were identified whose regimes may exert a control on aquatic life. By using the two metrics as coordinates in a plot, a graphic representation of the regime can be visualized in a point. Hydrological perturbations associated with water abstractions, point discharges and the presence of a reservoir were assessed by comparing the position of the two points representing the regime before and after the impacts. The method is intended to be used with biological metrics in order to define the ecological status of a stream, and it could also be used in planning the ‘measures’ aimed at fulfilling the Water Framework Directive goals. Copyright © 2014 John Wiley & Sons, Ltd.  相似文献   

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