| تعداد نشریات | 286 |
| تعداد نشریات سازمان | 84 |
| تعداد شماره‌ها | 2,856 |
| تعداد مقالات | 32,385 |
| تعداد مشاهده مقاله | 41,498,814 |
| تعداد دریافت فایل اصل مقاله | 18,697,323 |
شبیه‌سازی و بهینه سازی تغییر حجم آبگیر سد هرسین بر اثر حالت‌های ممکن اقلیمی | ||
| پژوهش های آبخیزداری | ||
| مقاله 5، دوره 34، شماره 4 - شماره پیاپی 133، دی 1400، صفحه 53-73 اصل مقاله (2.26 M) | ||
| نوع مقاله: پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/wmrj.2021.353516.1387 | ||
| نویسندگان | ||
| فاطمه سلیمی مستعلی1؛ مریم حافظ پرست مودت* 2؛ فرهنگ سرگردی2 | ||
| 1کارشناس ارشد منابع آب دانشگاه رازی | ||
| 2استادیار گروه علوم و مهندسی آب، دانشگاه رازی | ||
| چکیده | ||
| تغییر اقلیم بر بیش‌تر جنبه های زندگی انسان تأثیر گزارده است به طوری که گاه پژوهش تاثیرهای مختلف تغییر اقلیم مهمتر از شناسایی و پژوهش خود تغییر اقلیم است. در این پژوهش با آورد40 ساله‌ی (2017-1978) رودخانه‌ی کمیش در مدل WEAP به شبیه‌سازی آبگیر سد هرسین پرداخته شد. بهینه‌سازی با هدف کمینه‌‌کردن کمبود نیازهای پایین‌دست سد و اثر حالت‌های ممکن اقلیمی در مدل LINGO بررسی‌شد. نتیجه‌ی کاربرد حالت‌های ممکن اقلیمی RCP نشان‌دهنده‌ی کاهش آورد ورودی آبگیر سد هرسین بود و خروجی دو مدل اقلیمیHADGEM2-ao و FGOALS-G2 افزایش بیشینه‌ی 5 و کمینه‌ی °C 3 دما در دوره های آینده است. برپایه‌ی حالت ممکن RCP8.5 مقدار روان‌آب پیش بینی‌شده در دوره های آینده 2059-2020 و 2099-2060 کم‌تر از روان‌آب پیش بینی‌شده با حالت ممکن RCP2.6 است. کاربرد روان‌آب خروجی با مدل بارش-روان‌آب با حالت ممکن RCP2.6 و RCP8.5 در مدل WEAP موجب شد شاخص اطمینان‌پذیری نیازهای پایین‌دست سد به کم‌تر از 80% برسد. بیش‌ترین مقدار شاخص اطمینان‌پذیری با کاربرد حالت ممکن اقلیمی با مدل HADGEM2-ao با حالت ممکن RCP2.6 در نیاز صنعت است، که در حالت شبیه سازی 77/08% بود، درحالی‌که در مدل بهینه به 88/42 % افزایش یافت. کم‌ترین مقدار شاخص اطمینان‌پذیری در مدل WEAP نیز 32/19% برآورد شد، که در مدل LINGO به 52/71% رسید. | ||
| کلیدواژه‌ها | ||
| ایهکرس؛ حالت ممکن اقلیمی 2/6 و 8/5؛ لینگو؛ ویپ | ||
| عنوان مقاله [English] | ||
| Simulation and Optimization of Changes in the Harsin Storage Reservoir as Influenced by the Climate Scenarios | ||
| نویسندگان [English] | ||
| Fatemeh Salimi Mastali1؛ Maryam Hafezparast Mavadat2؛ Farhang Sargordi2 | ||
| 1Master of Water Resources Engineering, Razi University | ||
| 2Assistant Professor, Department of Water Science and Engineering, Razi University | ||
| چکیده [English] | ||
| The side effects of climate change have affected most aspects of human life; Therefore, the study of the various effects of climate change is more important than the identification of the climate change itself. Using the 40-year discharge (1978-2017) of the using Kamish River in the WEAP model. The reservoir of the Harsin Dam has been simulated the LINGO model, optimization was performed with the aim of minimizing the shortage of the downstream needs and the effects of climatic scenarios. By applying the RCP climate scenarios, the results indicated a decrease in the inflow of the Harsin Reservoir; however, the output of the two climate models HADGEM2-ao and FGOALS-G2 increased the maximum temperature by 5 and at least by 3 degrees Celsius in future periods. According to the RCP8.5 scenario, the volume of runoff predicted in the periods 2020-2059 and 2060-2099, is less than the runoff predicted under the RCP2.6 scenarios. Application of the runoff prediction by the precipitation-runoff model under the RCP2.6 and RCP8.5 scenarios in the WEAP model caused the reliability index of downstream demands to fall below 80%. The highest value of reliability index by applying the climate scenarios using the HADGEM2-ao model under the RCP2.6 scenario is related to the industry demand, which in the simulation mode is equal to 77.08%, while this index in the optimal model is 88.42%. The lowest value of the reliability index in the WEAP model was estimated at 32.19%; it attained 52.71% using the LINGO model. | ||
| کلیدواژه‌ها [English] | ||
| IHACRES, LINGO, RCP2.6, 8.5, WEAP | ||
| مراجع | ||
|
Aghabeigi N, Esmali Ouri A, Mostafazade R, Golshan M. 2019. The effects of climate change on runoff using IHACRES Hydrologic Model in some of watersheds, Ardabil Province, Irrigation and Water Engineering. 10(2): 178–189. doi: 10.22125/iwe.2019.100750 Ashofteh P, Bozorg-Haddad O. 2015. A new approach for performance evaluation of AOGCM Models in simulating runoff, Journal of Water and Soil Conservation, 22(2): 95–110. (In Persian). Ashofte PS, Rajaee T, Golfam P. 2017a. Assessment of water resources development projects under conditions of climate change using efficiency indexes. Water Resources Management, 31: 3723–3744. Ashofteh PS, Bozorg Haddad O, Miguel A, Marino. 2014. Climate change impact on reservoir performance indexes in agricultural water supply. Journal of Irrigation and Drainage Engineering. 139)2). Ashofte PS, Bozorg Haddad O, Loaiciga HA. 2017b. Logical genetic programming (LGP) development for irrigation water supply hedging under climate change conditions. Irrigation and Drainage, 66 (4): 530–541. Ashofteh P, Massah Bouani AR. 2010. Impact of climate change on maximum discharges: Case study of Aidoghmoush Basin, East Azerbaijan. JWSS. 14 (53):28–38. URL: http://jstnar.iut.ac.ir/article-1-1330-en.html. (In Persian). Ardakani A, Sabaghi phirozabadi MH, Sabaghi phirozabadi P. 2014. Virtual water, a way to manage water resources crisis, National Conference on Solutions to the Water Crisis in Iran and the Middle East, Shiraz. (In Persian) .https://civilica.com/doc/369158. Binaman J, Shoemaker CA. 2005. An analysis of high-flow sediment event data for evaluating model performance. Journal of Hydrological Processes, 19(3): 605–620. Hafezparast M, Pourkheirollah Z. 2018. 'The effect of RCP scenarios on hydrological parameters, case study: Doiraj Dam catchment', Watershed Engineering and Management, 10(2): 231–248. Doi: 10.22092/ijwmse.2017.110468.1296. (In Persian). Jamshidi Pei A, Shorian M. 2017. Planning the optimal allocation of water for agriculture using the simulation-optimization approach under climate change conditions. First International Conference on Climate Change. Tehran. 28–29 February. (In Persian). Kheirfam H, Mostafazadeh R, Sadeghi SH. 2013. Estimation of daily discharge using IHACRES model in some watersheds of Golestan province. Journal of Watershed Management Research, 4(7):114–127 (In Persian). Kia I, Emadi A, Gholami MA. 2018. Efficiency of different optimization methods in the operation of Haraz Dam reservoir, Iranian Journal of Irrigation and Water Engineering, 8 (4):184–196. (In Persian). Kermanshah Regional Water Company .2012. Studies of the first phase of Harsin Reservoir Dam. Report on Water Resources Planning Studies. (In Persian). Khosravi M, Esmailnejad M, Nazaripour H .2010. Climate change and its impact on water resources in the Middle East, 4th International Congress of Geographers of the Islamic World, Zahedan, Sistan and Baluchestan University Archive of the Meteorological Organization.159 (28): 1–8. (In Persian). Li Z, Quan J, Li X, Wu X, Wu H, Li Y, Li G. 2016. Establishing a model of conjunctive regulation of surface water and groundwater in the arid regions. Agricalture Water Management. 174: 30–38. Lotfirad M, Adib A, Haghighi A. 2018. 'Estimation of daily runoff using of the semi- conceptual rainfall-runoff IHACRES model in the Navrood watershed (a watershed in the Gilan province', Iranian Journal of Ecohydrology. 5(2): 449–460. doi: 10.22059/ije. 2017.234237.614. (In Persian). Marabi S. 2018. Evaluation of changes in quantitative and qualitative parameters of the river due to climate change under radiation induction scenarios. Ms.C Thesis. Faculty of Water Engineering, Razi University. 166 p. (In Persian). Mohammadi M, Mousavi S, Farzin S, Karami H .2019. Optimal operation of dam reservoir using whale optimization algorithm and its hybrid with genetic algorithm based on multi-criteria decision making. Iranian Journal of Ecohydrology. 6(2): 281–293. doi: 10.22059/ije.2019.270039.990. (In Persian). Panahi E, Bafkar A, Hafezparast M. 2017. 'Assessment of management alternatives for maintaining watershed sustainability in the climate scenarios'. Iran-Water Resources Research. 13(1):139–152. (In Persian). Rui-chao X, yu-jie G. 2018. Analysis and research on the optimal allocation of regional water resources, 4th International Conference on Energy Materials and Environment Engineering (ICEMEE 2018). 25-27 February, Da Nang, Vietnam. 38(4):1–4. https://doi.org/10.1051/e3sconf/20183803055. Salimi Masteali F, hafezparast M, Sargordi F. 2020. Simulation and optimization of dam operation under changing cultivation pattern scenario (Case study: Harsin Dam), Iranian Journal of Soil and Water Research, 51(1): 1–12. doi: 10.22059/ijswr.2019.282440.668221. (In Persian). Santhi , Arnold JG, Williams J, Dugas WA, Hauck L. 2001. Validation of the SWAT model on a large river basin with point and nonpoint sources. The American Water Resources Association, 37 (5): 1169–1188. Schluter M DC, Savitsky, Mckinney D, Lieth H .2005. Optimizing long-term water allocation in the Amudarya River Delta: A water management modal for ecological impact assessment. Environmental Modaling and Software. 20(5):529–545. Song P, Wang C, Zhang W, Liu W, Sun J, Wang X, Lei X, Wang H. 2020. Urban multi-source water supply in China: Variation Tendency, Modeling Methods and Challenges. Water. 12(4): 1199. https://doi.org/10.3390/w12041199. Soojin M, Hyun S, Kang B. 2015. Future flow duration projection of bayesian ensemble model using the IHACRES model E-proceedigs of the 36th IAHR World Congress. 28 June – 3 JulyThe Hague, the Netherlands, pp. 1–3. Taghian M. 2016. 'Estimation of reliable discharge in water resources systems using linear optimization', Irrigation Science and Engineering, 40 (1): 73–82. doi: 10.22055 / jise.2017.12668. (In Persian). Taghian M. 2016. Estimating the optimal capacity for reservoir dam based on reliability level for meeting demands. Water and Soil. 30(3): 672–684. doi: 10.22067/jsw.v30i3.34436. (In Persian). Wang B, Li W, Huang G, Liu L, Ji L, Li Y. 2015. Urban water resources allocation under the uncertainties of water supply and demand: A case study of Urumqi, China. Environmental Earth Science. 74: 3543–3557. Xu Y, Li W, Ding X. 2017. A stochastic multi-objective chance-constrained programming model for water supply management in Xiaoqing River Watershed. Water. 9(6). 378. https://doi.org/10.3390/w9060378. Yates D, Sieber J, Purkey D, Huber-Lee A. 2005."WEAP21--A demand-, priority-, and preference-driven water planning Model: Part 1, Model Characteristics." Water International. 30: 487–500. Zayn al-Dini S, Anvari S, Bagheri MH, Zahmatkesh Z .2017. Using WEAP model to evaluate different management scenarios under climate change conditions, 14th National Conference on Irrigation and Evaporation Reduction, Kerman, Department of Water Engineering, Shahid Bahonar University, Kerman. (In Persian). Zhang S, Yang J, Wan Z, Yi Y. 2018. Multi-water source joint scheduling model using a refined water supply network: Case study of Tianjin. Water. 10(11). 1580. https://doi.org/10.3390/w10111580. | ||
|
آمار تعداد مشاهده مقاله: 759 تعداد دریافت فایل اصل مقاله: 669 |
||