جستجوی مقالات مرتبط با کلیدواژه « بهره برداری از مخزن » در نشریات گروه « آب و خاک »

One of the basic steps in water resources management and planning according to population increase and lack of water resources in Iran is to optimize the use of dam reservoirs. In this research, the effect of meteorological droughts on the optimization of the Aydoghmoush dam reservoir in the northwest of Iran was evaluated by applying metaheuristic algorithms under the impact of future climate change. Three models and two scenarios of SSP2-4.5 and SSP2-8.5 of the sixth IPCC report, and the LARS-WG downscaling model were used for Aydoghmoush dam weather station for the base period (1978-2014) and future periods of 2022-2040 and 2070-2100. The inflow and outflow of the dam, as well as the optimal utilization of the dam reservoir, were evaluated using standalone, and hybrid mode of genetic, slime mold, and ant colony algorithms. Results of the best release scenario (SSP2-8.5) showed that the annual rainfall in the future periods will decrease by 8.9 mm, and 14.5 mm, respectively, compared to the base period. The objective function of optimizing the use of the dam reservoir was defined as minimizing the sum of squared relative deficiencies in each month and maximizing the reliability in the statistical period of 2011-2021. The results showed that in terms of time reliability, vulnerability, and stability, the hybrid slime mold-genetic algorithm was better than other algorithms with values of 0.73, 0.32, and 28.78. Prediction of the dam's inflow and outflow using the hybrid slime mold-genetic algorithm indicated high accuracy compared to other models by 13% and 19% errors, respectively.

In this paper, the artificial gorilla troops (GTO) optimizer algorithm with the gray wolf optimizer (GWO) and particle swarm optimization (PSO) algorithms was compared for optimal operation of dam reservoir. The results of the GTO were evaluated with GWO and PSO results which are successful in complex engineering issues and reservoir operation. The objective function of minimizing the total squares of the downstream demand deficit was defined during the operation period. The constraints of the operating equation include the reservoir continuity equation, the reservoir volume, and the release volume. A case study of Jamishan reservoir dam located in Kermanshah province was considered. In this regard, runoff values related to the statistical years 1991-2011 were introduced as input to the reservoir for optimal operation management. The obtained results from optimization algorithms using error estimation indices including mean square root of error (RMSE), mean absolute value of error (MAE), Nash-Sutcliffe criterion (NSE), ratio of root mean square error to standard deviation of observational data (RSR), Reliability, Resiliency, Vulnerability And the minimization values of the objective function were evaluated. The values of these indicators for GTO were 2.86, 1.85, 0.73, 0.52, 69%, 36%, 23% and 4.7, respectively. The results showed that the GTO algorithm had very good accuracy in minimizing the objective function and based on the values of proposed indicators performed better than the GWO and PSO algorithms. Based on this algorithm, the amount of water release volume was brought to the reservoir as a function of the reservoir volume and the amount of water demand volume for the months of the year was determined.

In this paper two models have been written and solved by two approaches: non-linear programming (GAMS/MINOS solver) and simulated annealing methods in order to optimize operational rules in Mahabad reservoir. Because of missing the required eco-system data, these required data were calculated using Tennant method. The objective function was defined to minimize the deference between the amounts of agriculture water demand and the released water from the reservoir during 23 years of flow data (1370-1393) and their performance were evaluated using the operational indexes. Obtained results of both optimization models showed that, the simulated annealing algorithm with objective function value of 22.01, reliability value of 25%, resiliency velocity value of 22.22%, vulnerability value of 41.04% and sustainability value of 0.032, gave relatively better results compared to the non-linear programming method with the objective function value of 88.92, reliability value of 48.18%, resiliency velocity value of 32.86%, vulnerability value of 84.27% and sustainability value of 0.024. Also, it was found that, simulated annealing algorithm took longer running time to achieve the global optimal point in comparison to non-linear programming. However, using simulated annealing algorithm estimated a lower water shortage of 1632.24 MCM compared to the non-linear programming which estimated water shortage of 3351.4 MCM. Simulated annealing algorithm decreased the shortage by distributing shortages in different months and estimated a better performance.

Flexibility indicates the status of water supply, so that by increasing this index, the status of the water supply system will be better and periods of crisis will be going across with the least risk. The purpose of this research is the evaluation of flexibility of Gharanghu reservoir system (East Azerbaijan) in terms of climate change (2040-2069) for the three status’s (100, 85 and 70 % of water demand supply) in order to identify and manage periods of crisis. Climatic pre-processing for the present study is performed by HadCM3 (A2 emission scenarios) that those are as an input to the simulation models of inflow to the reservoir (IHACRES model) as well as water demand model (Cropwat model). The results show that the long-term average annual inflow volume in future (30-year) will decrease about 25 % compared to the baseline period (1971-2000). However, the average annual water demand volume for crops increases by 20 % compared to the baseline. Next, in order to optimize the operation of reservoir for water supply, objective function as minimization of total squared monthly deficiencies is determined. For this purpose, LINGO 11.0 software (NLP method) was used for solving the problem. Results show that in climate change condition for first situation (with supplying 100 % of demand) relative to baseline period, reliability index will be decreased (by 20 %). The declines for the second and third situations are 16 and 2 %, respectively.

Nowadays, along with an increase in water needs, there is no balance between water demand and water supply in most regions of the country. Therefore, planning an appropriate policy to strike a balance between a declining water supply and an increasing demand to prevent a crisis is of utmost importance. The use of optimization methods in this context can be useful. Evolutionary algorithm methods are known as appropriate methods in this regard, and their suitable performance have been reported. Biogeography-based optimization (BBO) is a new evolutionary algorithm which its high performance in some aspects has been proved. The main objective of this study was to assess the performance of BBO in water resources management for the first time. Firstly, BBO was used for finding optimal points of three benchmark function including Sphere, Rosenbrock, and Bukin6; secondly, it was applied for an optimal operation of the Karon4 Reservoir with the aim of hydropower generation. In order to evaluate the performance of BBO, in addition to this method, the genetic algorithm (GA) and the nonlinear programming (NLP) were employed. The results of benchmark function showed that BBO delivered a better performance than the GA in finding the optimal points of three functions. Moreover, BBO reached an optimal solution with a higher degree of accuracy. In operation of the Karon 4 Reservoir, the results also indicated the high efficiency of BBO in extracting optimal operational policies in such circumstances; the objective function value of BBO at the best performance was 1.223, and, that for GA was 1.535. Furthermore, the global optimal solution obtained from NLP for this problem was 1.213.

Sometimes the pollution occurs as a sudden event, either intentionally or unintentionally and it may become a water quality crisis. Despite the damage that can occur due to the sudden pollution, little research has been done in this area. Damage caused by the entered pollution in reservoirs can affect the water resource system in two ways: (1) Damages that are caused due to lack of water allocation, and (2) damages that are caused due to consumption of polluted water. Those damages are in contrast with each other. Thus, the crisis should be managed in a way that the least damage occurs in the water resource system. This paper investigates the crisis management due to the sudden entrance of a 30 m3 MTBE load to the Karaj dam. To simulate MTBE advection, dispersion, and vaporization, the latest process is added to the CEQUAL- W2 model. After that, the multi-objective optimization hybrid algorithm, NSGAIIALANN, is used to extract the best set of decisions. According to the results, if pollution enters the reservoir in the summer, by using one of the driven policies, by a 36% reduction in demand meeting, allocated pollution decreases by 60% and also maximum concentration decreased by 76%. These results for winter are 38%, 51% and 67%, respectively. Similar results are extracted for other seasons.

Watershed system configuration and conditions change as newer water supply، irrigation، industry and municipal development projects are constructed. In such a new condition، applying the current operating rules for reservoirs، aside from not being optimum، will produce different economic and social costs، too. Therefore، it is necessary to coordinate the operation in the new condition and update reservoirs operating rules. Coordinating the hydro-system operation and updating the reservoirs، operation rules at different stages of the basin development are studied in this research. Therefore، a long-term optimization model is developed، which takes into account the upstream operation impacts on the downstream performance، and coordinates operation of different hydro-system components in a manner to maximize satisfaction of different stakeholders’ targets as much as possible. Application of the model to the Karkheh’s hydro-system analysis at different development stages for an assessment of coordination and updating of operation impacts shows that after construction of the Karkheh، Saymareh and Sazbon Dams، 60% of water demand targets will not be met in comparison with the updated rule curves application if the primary rule curves of dams that are determined for each dam are used individually in practice. Besides، non- coordination of the Karkheh’s hydro-system operation and updating reservoirs operation rules will reduce water supply reliability by 50% in a 20 year planning horizon in comparison with a coordinated and updated operation of the Karkheh’s hydro-system.

Reservoir operation optimization is one of the most important issues in water resources management. In this study, reservoir operations of Doroodzan dam were carried out using SA optimization algorithm, yield model and Standard Operation Policy (SOP). For each method, a computer model was developed using FORTRAN. The decision variables in the SA model were the amount of water release in different months. The objective function is deficit of water requirement which was investigated as minimization form. Yield model was defined as an amount of water which in addition to supply drinking and industry demands, reservoir can supply agriculture water demand with a reliability of at least 80 percent. Results showed that all three methods fully supply drinking and industrial demands. The performances of SA algorithm and yield model in agricultural uses were better than the standard operation policy. Also the yield model supplies much more water for agricultural use than SA model. SA algorithm and yield model decreased water deficit 33.74 and 83.86 percent, respectively. Therefore, the yield model passes the best performance and the SA algorithm and the standard operation policy obtained the next positions, respectively

Using of a hedging rule during drought periods is a usual approach in water resource management. In this method, although may be possible to satisfy all of demands, occasionally, portions of demands are met. This policy saves water with imposing a little deficit in the current period instead of a severe water shortage in future, which is effective for social and economical aspects. One of the key points in this regard, is to calculate optimal rationing factors for different purposes and optimum trigger volume for each reservoir to start hedging rule. For this purpose, in the present study, a coupled simple genetic algorithm to the simulation model (ARSP) including flow network penalty structure and linear programming model is used. The capabilities of the model are investigated in the Zohreh water resource system as a case study located in west southern of Iran. The results show that the combination model improves intensity of water shortages in comparison with the situation of without hedging rule. Moreover, the model provides the possibility of considering more details for the water resource systems.

Regarding temporal variation of rivers discharge and demands, for suitable use of dam reservoirs stored water, application of operation rule curves is necessary. Operation rules are expressed with rule curves. Application of yield model is one of the methods of operation curve preparation, which correlates reservoir operation with reservoir storage volume in first period. In this study after description Standard Operation Policy and yield model, based on these models two computer programs in FORTRAN language were prepared for reservoir operation. Then based on yield model, Doroodzan dam rule curve achieved based on yield model and results were compared with SOP model. Results showed that sum square of deficit in yield model was significantly 73.27 percent less than SOP model, which expresses model ability in derivation of dam reservoir operation rule curve. Yield model in addition to decrease of water deficiency, supplies absolute demands and distributes deficit uniformly in more years.