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Showing 2 results for Reservoir Operation
Determining the Operating Rules Of Doroodzan Reservoir Using the Adaptive Network Fuzzy Inference System (ANFIS)
M. H. Tarazkar, M. Zibaei, G.r. Soltani, M. Nooshadi,
Volume 22, Issue 2 (9-2018)
Abstract
Nowadays, water resource management has been shifted from the construction of new water supply systems to the management and the optimal utilization of the existing ones. In this study, the reservoir operating rules of Doroodzan dam reservoir, located in Fars province, were determined using different methods and the most efficient model was selected. For this purpose, a monthly nonlinear multi-objective optimization model was designed using the monthly data of a fifteen-year period (2002-2017). Objective functions were considered as minimizing water scarcity index in municipal, industrial, environmental and agricultural sectors. In order to determine the operating rule curves of reservoir, in addition to the nonlinear multi-objective optimization model, the methods of ordinary least-squares regression (OLS), fuzzy inference system and adaptive network fuzzy inference system (ANFIS) were used. Also, the reliability, resiliency, vulnerability and sustainability criteria were used to compare the different methods of reservoir performance rules. The results showed that ANFIS model had the higher sustainability criterion (0.26) due to its greater reliability (0.7) and resilience (0.42), as well as its lower vulnerability (0.13), thereby showing the best performance. Therefore, ANFIS model could be effectively used for the creation of Doroodzan reservoir operation rules.

Optimization of Dam Reservoir Operation Using Metaheuristic Algorithms under Meteorological Drought Conditions (Case Study: Aydoghmoush Dam)
E. Taheri, F. Mousavi, H. Karami,
Volume 27, Issue 2 (9-2023)
Abstract
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.

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