نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشیار گروه مهندسی عمران، دانشکده فنی و مهندسی، دانشگاه قم، قم، ایران

2 دانشجوی دکتری، گروه مهندسی عمران، دانشکده فنی و مهندسی، دانشگاه قم، قم، ایران

چکیده

پژوهش حاضر با هدف بهینه‌سازی تخصیص منابع آب سد قرنقو در افق آینده (2099–2070) و ارتقای تاب‌آوری سامانه تأمین آب انجام شد. از مدل‌های اقلیمی CMIP5، GFDL-ESM2G برای دما وNorESM1-M برای بارش به‌عنوان بهترین گزینه‌ها انتخاب شدند. سپس با به‌کارگیری شبکه‌های حافظه‌دار بلندمدت (LSTM)، رواناب ماهانه حوضه شبیه‌سازی گردید که نتایج از دقت مناسبی برخوردار بود. نیاز آبی محصولات نیز با Cropwat برآورد و نشان داد که در آینده نیاز خالص آبیاری 20 درصد افزایش خواهد یافت. در ادامه، عملکرد الگوریتم بهینه‌سازی گله اسب (HHOA) و برنامه‌ریزی ژنتیک (GP) برای توابع معیار راستریجین و روزنبروک نشان داد که HHOA بهتر عمل نموده است. بررسی عملکرد HHOA برای تخصیص آب نشان داد که HHOA توانست کسری آب را تا 22 درصد کاهش و تاب‌آوری مخزن را از 67 به 79 درصد افزایش دهد. هم‌چنین، LSTM با ضریب نش-ساتکلیف (NSE) برابر با 85/0 توانست رواناب ماهانه را با دقت مناسبی شبیه‌سازی کند.

کلیدواژه‌ها

موضوعات

Akbari-Alashti, H., Bozorg-Haddad, O., Fallah-Mehdipour, E., and Mariño, M. A. (2014). Multi-reservoir real-time operation rules: A new genetic programming approach. Proceedings of the Institution of Civil Engineers: Water Management, 167 (10), 561-576. https://doi.org/10.1680/wama.13.00021.
Akbarifard, M., & Zounemat-Kermani, M. (2024). New hybrid optimization approaches for the optimal management of surface water resources systems. Water Resources Management, 38(2), 341–359. https://doi.org/10.1007/s11269-024-03941-6.
Akbarifard, S., Sharifi, M. R., & Qaderi, K. (2020). Data on optimization of the Karun-4 hydropower reservoir operation using evolutionary algorithms. Data in brief, 29, 105048.. https://doi.org/10.1016/j.dib.2019.105048.
Behroozi, A.H., Nazem Al Sadat, S. M. J., & Pishvaei, M. (2023). Evaluating the trend of rainfall changes in the long-term time series of Shiraz. Journal of Drought and Climate Change Research, 1(1), 19-32. https://doi.org/10.22077/JDCR.2023.5856.1001.
Bhavya, K., & Elango, L. (2023). Ant-inspired metaheuristic algorithms for combinatorial optimization problems in water resources management. Water, 15(9): 1762. https://doi.org/10.3390/w15091762.
Dabral, R., Sharma, A., & Verma, S. (2025). Optimal operation of reservoir for sustainable water resource management using multi-objective algorithms and EMCP approach. Journal of Hydroinformatics, 27(5): 878–892. https://doi.org/10.2166/hydro.2025.064.
Doorenbos, J., & Pruitt, W. O. (1977). Guidelines for predicting crop water requirements. https://openknowledge.fao.org/handle/20.500.14283/f2430e.
Hashimoto, T., Stedinger, J. R., & Loucks, D. P. (1982). Reliability, resiliency, and vulnerability criteria for water resource system performance evaluation. Water Resources Research, 18(1), 14–20. https://doi.org/10.1029/WR018i001p00014.
Helmi, M., Neyshabouri, S. Z., Amirabadizadeh, M. & Yaghoobzadeh, M. (2024). Evaluation of SDSM, LARS-WG, and ANN methods in downscaling of temperature and precipitation for two different climates. Journal of Drought and Climate Change Research (JDCR), 1(4), 105–118. [In Persian]. https://doi.org/10.22077/JDCR.2023.6996.1049.
Hınçal, O., Altan-Sakarya, A. B., and Ger, A. M. (2011). Optimization of multireservoir systems by genetic algorithm. Water Resources Management, 25 (5), 1465-1487. https://doi.org/10.1007/s11269-010-9755-0.
IPCC, 2014, Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, Pachauri, R.K., and Meyer, L.A., (eds.)]. IPCC, Geneva, Switzerland; 151 pp.
Karami, H. Ehteram, M. Mousavi, S.F. Farzin, S. Kisi, O., and El-Shafie, A. (2019). Optimization of energy management and conversion in the water systems based on evolutionary algorithms. Neural Computing and Applications, 31(10), 5951-5964. https://doi.org/10.1007/s00521-018-3412-6.
Kousali, M., Salarijazi, M., & Ghorbani, K. (2022). Estimation of non-stationary behavior in annual and seasonal surface freshwater volume discharged into the Gorgan Bay, Iran. Natural Resources Research, 31, 835–847. https://doi.org/10.1007/s11053-022-10010-5.
Koza, J. R. (1992). Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT Press.
Loucks, D. P., & van Beek, E. (2017). Water resource systems planning and management: An introduction to methods, models, and applications. Springer.
McMahon, T. A., Adeloye, A. J., & Zhou, S. L. (2006). Assessment of storage requirements for water supply reservoirs. Journal of Hydrology, 324(1–4), 1–15. https://doi.org/10.1016/j.jhydrol.2005.08.006.
MiarNaeimi, F., Azizyan, G., & Rashki, M. (2021). Horse herd optimization algorithm: A nature-inspired algorithm for high-dimensional optimization problems. Knowledge-Based Systems, 213, 106711. https://doi.org/10.1016/j.knosys.2020.106711.
Ming, B., Chang, J.-X., Huang, Q., Wang, Y.-M., and Huang, Sh.-Z. (2015). Optimal operation of multi-reservoir system based-on cuckoo search algorithm. Water Resources Management, 29, 5671-5687, https://doi.org/10.1007/s11269-015-1140-6.
Modabber-Azizi, S., Salarijazi, M., and Ghorbani, K. (2023). A novel approach to recognize the long-term spatial-temporal pattern of dry and wet years over Iran. Physics and Chemistry of the Earth, Parts A/B/C, 131, 103426. https://doi.org/10.1016/S1474-7065(23)00070-0.
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., et al. (2011). Scikit-learn: Machine Learning in Python — train_test_split documentation.
Ramezani Etedali, H., & Koohi, S. (2024). Investigating the impact of climate change on the aridity in Iran with population exposure approach. Journal of Drought and Climate Change Research (JDCR), In Press. [In Persian]. https://doi.org/10.22077/jdcr.2024.8258.1079.
Salarijazi, M., Ghorbani, K., Mohammadi, M., Ahmadianfar, I., Mohammadrezapour, O., Naser, M. H., & Yaseen, Z. M. (2023). Spatial-temporal estimation of maximum temperature high returns periods for annual time series considering stationary/nonstationary approaches in Iran urban area. Urban Climate, 49, 101504.https://doi.org/10.1016/j.uclim.2023.101504.
Salarijazi, M., Ahmadianfar, I., and Mundher Yaseen, Z. (2024). Prediction enhancement for surface water sodium adsorption ratio using limited inputs: Implementation of hybridized stacked ensemble model with feature selection algorithm. Physics and Chemistry of the Earth, Parts A/B/C, 134, 103561, https://doi.org/10.1016/j.pce.2024.103561.
Yilmaz, A. O., Kose, E. I., & Demir, A. (2025). Defining the most appropriate water network management plan with different optimization algorithms. Water Resources Management, 39(1), 115–132. https://doi.org/10.1007/s11269-025-04221-7.
Zhou, X., Leng, Y., Salarijazi, M., Ahmadianfar, I., Ahsan Farooque, A. (2024). Development of forecasting of monthly SAR time series in river systems: A multivariate data decomposition-based hybrid approach. Process Safety and Environmental Protection, 188, 1355-1375, https://doi.org/10.1016/j.psep.2024.06.050