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ارزیابی اثرات تغییر اقلیم بر خشکسالی‌های دهه‌های آتی در حوزه آبخیز ارس تحت مدل CMIP6 | ||
| مهندسی و مدیریت آبخیز | ||
| مقاله 4، دوره 17، شماره 1، فروردین 1404، صفحه 44-63 اصل مقاله (1.77 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/ijwmse.2024.364619.2040 | ||
| نویسندگان | ||
| فاطمه وطن‌پرست قلعه جوق1؛ برومند صلاحی* 2 | ||
| 1دانشجوی دکتری آب و هواشناسی، گروه جغرافیای طبیعی، دانشکده علوم اجتماعی، دانشگاه محقق اردبیلی، اردبیل، ایران | ||
| 2استاد آب و هواشناسی، گروه جغرافیای طبیعی، دانشکده علوم اجتماعی، دانشگاه محقق اردبیلی، اردبیل، ایران | ||
| چکیده | ||
| مقدمه حیات انسانی دائماً تحت تأثیر انواع مخاطرات طبیعی قرار دارد که برخی از آن‌ها برآمده از پیشامدهای آب و هوایی و گرمایش جهانی است. ارزشمندی این مسئله به اندازه‌ای است که هیئت بین‌الدول تغییر اقلیم تأسیس‌شده تا دگرگونی‌های اقلیمی را در سطح جهانی مطالعه کند و نقش فعالیت بشر را در این مورد ارزیابی کند. یکی از پیامدهای تغییر اقلیم، وقوع رخدادهای حدی نظیر خشکسالی است. در واقع با رخداد تغییر اقلیم، شدت و فراوانی خشکسالی نیز پیچیده‌تر می‌شود و به‌دلیل نقش حیاتی آب در زندگی انسان، تولیدات کشاورزی و محیط‌زیست، ارزیابی تأثیرات سوء آن بر وقوع و شدت خشکسالی‌ها اهمیت زیادی دارد. دلیل اصلی پدید آمدن خشکسالی‌ها نیز نوسانات در مؤلفه‌های اقلیمی ازجمله کمبود بارش و افزایش دما است. مواد و روش‌‌ها پژوهش حاضر با هدف پیش‌بینی خشکسالی در ایستگاه‌های اردبیل، اهر، پارس‌آباد، جلفا، خوی و ماکو واقع در حوزه آبخیز رودخانه ارس انجام شده است. برای این منظور، دقت مدل گردش عمومی هیئت بین‌الدول تغییر اقلیم (CMIP6) مورد ارزیابی قرار گرفت. مدلهای اقلیمی مورد استفاده در این پژوهش برای پیش‌نگری داده بارش طی دوره آینده (۲۰۴۳-۲۰۲۴) شامل مدلهای CanESM5، NorESM2-MM و MPI-ESM1-2-HR تحت سناریوهای انتشار خوش‌بینانه (SSP1-2.6) و بدبینانه (SSP5-8.5) هستند. آنگاه با استفاده از شاخص بارش استانداردشده (SPI)، ویژگی‌های خشکسالی در مقیاس سالانه طی دوره پایه (۲۰۱۴-۱۹۸۵) با دوره آینده مورد سنجش قرار گرفت. سپس صحت‌‌سنجی مدل‌ها با استفاده از سنجه‌های R2، RMSE و NSE انجام و در نهایت با داده‌های تولید شده بارش، شاخص خشکسالی SPI از لحاظ شدت و فراوانی مورد تجزیه و تحلیل قرار گرفت. نتایج و بحث ارزیابی مدل‌ها با سنجه‌های خطاسنجی مختلف نشان داد که در شبیه‌سازی بارش ایستگاه‌های مورد مطالعه، مدل CanESM5 بهترین عملکرد را نسبت به سایر مدل‌ها دارد. مقایسه مدل‌ها و سناریوهای استفاده شده در این پژوهش نشان داد که بر مبنای خروجی مدل MPI-ESM1-2-HR، شدت خشکسالی‌ها و تحت مدل CanESM5، فراوانی خشکسالی‌ها نسبت به سایر مدل‌ها بیشتر شده است. همچنین نتایج نشان داد که در بدبینانه‌ترین حالت ممکن، تعداد و شدت دوره‌های خشک نسبت به سناریوی خوش‌بینانه افزایش خواهد داشت. طبق نتایج حاصل از این پژوهش، دوره‌های دارای وضعیت نرمال کاهش‌یافته و به تعداد و فراوانی دوره‌های دارای وضعیت خشک افزوده شده که ناشی از پیامدهای تغییر اقلیم در محدوده مورد بررسی است. همچنین، فراوانی و شدت ترسالی‌ها هم به مقدار اندکی نسبت به دوره مورد نظارت افزایش داشته است. بنابراین، تغییرات اقلیمی تا اندازه قابل قبولی بر وضعیت خشکسالی حوزه رود ارس در آینده اثر دارد. نتیجه‌‌گیری در مجموع می‌توان بیان کرد، آگاهی از میزان تغییرات بارش و منابع آب به‌دلیل مصارف گوناگون آن برای کشاورزی، شرب و صنعت از ارزشمندی فراوانی برخوردار است. در حالت کلی می‌توان اظهار داشت که قدرت مدلهای اقلیمی دوره آینده بنا به آب و هوای هر گستره، ماه و متغیر اقلیمی پیش‌نگری شده مختلف است. حوضه رود ارس، به‌علت انجام فعالیت‌های کشاورزی بیش از ظرفیت و مصرف آب در بخش‌های مختلف کشاورزی در معرض کاهش منابع آبی قرارگرفته است. بنابراین، پژوهش حاضر تلاشی به‌منظور بررسی تأثیر تغییر اقلیم بر شدت و فراوانی خشکسالی حوزه رود ارس بود که می‌تواند سیاست‌های هوشمندانه در مورد مدیریت با پابرجا منابع آب و زمین را ساده نماید. نتایج این پژوهش بر مبنای مدلهای اقلیمی مورد استفاده، وقوع تغییر اقلیم و به‌خصوص تکرار خشکسالی‌ها را در ایستگاه‌های مورد بررسی تأیید میکند. استفاده از مدلهای اقلیمی متعدد، به‌عنوان معتبرترین ابزار تولید سناریوهای اقلیمی، پیش‌بینی‌ها و مهم‌تر از آن عدم قطعیت‌ها را در شرایط اقلیمی آینده بهتر ارزیابی میکند و به برنامه‌ریزان و تصمیم‌‌گیران کمک میکند تا برای مقابله با اثرات سوء خشکسالی در بخش‌های مختلف منابع آب و کشاورزی نظارت بهتری داشته باشند و نیز برنامه‌ریزی‌های قبل از وقوع بحران جهت کاهش خسارات در منطقه را آسان‌‌تر میکند. | ||
| کلیدواژه‌ها | ||
| اقلیم؛ دره رود ارس؛ شاخص خشکسالی SPI؛ گرمایش جهانی؛ مدلهای GCM | ||
| عنوان مقاله [English] | ||
| Assessing the effects of climate change on droughts in the coming decades in aras watershed under the CMIP6 model | ||
| نویسندگان [English] | ||
| Fatemeh Vatanparast Ghaleh Juq1؛ Bromand Salahi2 | ||
| 1Ph.D. Student of Climatology, Department of Physical Geography, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran | ||
| 2Professor of climatology, Department of Physical Geography, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran | ||
| چکیده [English] | ||
| Introduction Human life is constantly affected by various natural hazards, some of which result from climate events and global warming. This issue is so significant that the Intergovernmental Panel on Climate Change (IPCC) was established to study climate change on a global scale and assess the role of human activity in this matter. One of the consequences of climate change is the occurrence of extreme events such as drought. In fact, with climate change, the intensity and frequency of droughts are becoming more complex. Given the vital role of water in human life, agricultural production, and the environment, it is crucial to assess its adverse effects on the occurrence and severity of droughts. The primary cause of droughts is fluctuations in climatic components, such as decreased precipitation and increased temperature. Materials and methods This study aimed to predict drought conditions in Ardabil, Ahar, Parsabad, Jolfa, Khoi, and Maku stations, located within the Aras River watershed. To achieve this, the accuracy of the General Circulation Models (GCMs) from the IPCC’s CMIP6 dataset was evaluated. The climate models used for forecasting precipitation in the future period (2024–2043) include CanESM5, NorESM2-MM, and MPI-ESM1-2-HR under both optimistic (SSP1-2.6) and pessimistic (SSP5-8.5) emission scenarios. Then, using the Standardized Precipitation Index (SPI), drought characteristics on an annual scale during the historical period (1985–2014) were compared with those in the future period. Model validation was performed using R², RMSE, and NSE parameters. Finally, the SPI drought index was analyzed in terms of intensity and frequency based on the generated precipitation data. Results and discussion Model evaluation using different error metrics indicated that the CanESM5 model outperformed the others in simulating precipitation for the studied stations. A comparison of the models and scenarios revealed that, according to the MPI-ESM1-2-HR model, drought severity is projected to increase, while the CanESM5 model suggests a rise in drought frequency. The results also indicate that under the most pessimistic scenario, both the number and intensity of dry periods will increase compared to the optimistic scenario. Furthermore, normal conditions are expected to decrease, while the number and frequency of dry periods will rise due to the consequences of climate change in the study area. Additionally, the frequency and intensity of wet years have shown a slight increase compared to the historical period. Overall, climate change is expected to have a significant impact on the future drought conditions in the Aras River watershed. Conclusion In summary, understanding changes in precipitation and water resources is crucial due to their various applications in agriculture, drinking water supply, and industry. The accuracy of future climate models varies depending on the climate of each region, the month, and the predicted climate variable. The Aras River Basin is facing a decline in water resources due to agricultural activities exceeding capacity and high water consumption in different agricultural sectors. This study aimed to assess the impact of climate change on drought severity and frequency in the Aras River Basin, providing insights for developing intelligent policies for sustainable water and land resource management. The findings confirm the occurrence of climate change and, in particular, the recurrence of droughts in the studied stations. Using multiple climate models, as the most reliable tool for generating climate scenarios, not only allows for more accurate forecasts but also helps evaluate uncertainties in future climate conditions. These insights assist planners and decision-makers in better monitoring the adverse effects of drought on water resources and agriculture, enabling proactive planning to mitigate regional losses before a crisis occurs. | ||
| کلیدواژه‌ها [English] | ||
| Aras River Valley, Climate, GCM Models, Global Warming, SPI Drought Index | ||
| مراجع | ||
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Abdolalizadeh, F., Mohammad Khorshiddoust, A., Jahanbakhsh, S., 2022. Assessment of the performance of CMIP6 model for analysis of temperature and precipitation in Urmia Lake basin. Climate Change Res. 3(11), 17-30 (in Persian). Asgari, E., Norouzi Nazar, M.S., Baaghideh, M., Entezari, A., 2023. Assessing the impacts of climate change on the future droughts in Gorganroud Watershed under CIMP6 models. Climate Change Res. 4(14), 27-42 (in Persian). Ashrafzade, A., Salehpoor, J., Sharifi, A., 2022. Investigating the effects of climate change on meteorological drought characteristics of Hablehrood Basin using the HADCM3 general circulation model and the SPI and DI inde. Human Environ. 20(2), 217-233 (in Persian). Babaeian, I., Giuliani, G., Modirian, R., Karimian, M., 2024. Projection of Iran’s precipitation during 2026-2075 by dynamical downscaling by RegCM4.7 under SSP scenarios. J. Agricul. Meteorol. 12(1), 20-34 (in Persian). Babaeian, I., modiriyan, R., Karimian, M., javanshiri, Z., 2021. Annual to decadal prediction of precipitation over Iran during 2019-2023 using statistical downscaling of DCPP models. Climate Change Res. 2(6), 63-78 (in Persian). Babolhakami, A., Gholami Sefidkouhi, M.A., Emadi, A., 2020. Assessing the impact of climate change on drought and forecasting Neka River basin runoff in future periods. Iran. J. Ecohydrol. 7(2), 291-302 (in Persian). Dascalu, S.I., Gothard, M., Bojariu, R., Birsan, M.V., Cica, R., Vintila, R., Adler, M.J., Chendes, V., Mic, R.P., 2016. Droughtrelated variables over the Bârlad basin (Eastern Romania) under climate change scenarios. Catena 141, 92-99. Dastourani, M., Hoseinabadi, S., Yaghoobzadeh, M., Forouzan Mehr, M., 2024. The effect of climate change on meteorological drought using the data of the Sixth Climate Change Report, case study: Shiraz city. Water Resour. Engin. 17(61), 13-27 (in Persian). Davoudi, S.M., Dokhani, S., Ghazavi, R., 2022. Evaluation of the effects of watershed structures in the dry and semi-dry regions of Isfahan Province from economic, social, and natural indicators. Amphibious Sci Technol 3(2), 27-43 (in Persian). Delghandi, M., Joorablou, S., Ganji Nowroozi, Z., 2023. The impact of climate change on severity, duration and magnitude of drought using SPI and RDI in Semnan Region. J. Drought Climate Change Res. 1(1), 1-18 (in Persian). Dukat, P., Bednorz, E., Ziemblińska, K., Urbaniak, M., 2022. Trends in drought occurrence and severity at mid-latitude European stations (1951–2015) estimated using standardized precipitation (SPI) and precipitation and evapotranspiration (SPEI) indices. Meteorol Atmos. Phys. 134(1), 1-20. Ebrahimi, N., Zarrin, A., Mofidi, A., Dadashi-Roudbari, A., 2023. Projected precipitation extremes in Lake Urmia Basin under climate change. Water Soil 37(5), 769-785. Ershadfath, F., Raeini Sarjaz, M., Shahnazari, A., Eivind Olesen, J., 2022. Application of linear scaling post-processing method for bias correction of climate models retrieved from CMIP6. Iran-Water Resour. Res. 18(3), 131-144 (in Persian). Esmaeilzadeh, Z., Salahi, B., Saber, M., 2023. Revealing the relationship between the changes of some relative humidity indices of the southern coasts of Iran with Indian Ocean teleconnection patterns. Amphibious Sci. Technol. 4(3), 59-78 (in Persian). Eyring, V., Bony, S., Meehl, G.A., Senior, C.A., Stevens, B., Stouffer, R.J., Taylor, K.E., 2015. Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization, Geosci. Model Dev. 9, 1937-1958. Farmanara, S., Bakhtiari, B., Sayari, N., 2020. Meteorological drought characteristics analysis under climate change effect using copula in Fars Province. Water Soil 34(5), 1157-1173 (in Persian). Fatai, A., Azizi, A., Seyed Safaviyan, T., Imani, A., Ojaghi, A., Farhadi, H., 2016. Prediction of the changes in some climate variables in Darehrood River of Aras Basin over next decades using of GCM Models. Sci. Quart. Environ. Geol. Res. 11(29), 1-12 (in Persian). Forouzan Mehr, M., Dastourani, M., Yaghoobzadeh, M., Hoseinabadi, S., 2023. Forecasting the risk of drought in Zabol synoptic station based on the output of CMIP6 climate models. Irriga. Sci. Engineer. 46(3), 69-84 (in Persian). Ghaemi, A., Hashemi Monfared, S.A., Bahrpeyma, A., Mahmoudi, P., Zounemat-Kermani, M., 2022. Spatiotemporal variation of projected drought characteristics of Iran under the climate change scenarios. J. Meteorol. Atmosph. Sci. 5(1), 68-80 (in Persian). Hajiabadi, F., Hassanpour, F., Yaghoobzadeh, M., Hammami, H., 2020. Projection of agricultural drought using fifth IPCC assessment report data, case study: Birjand Region. J. Agricul. Meteorol. 8(1), 51-61 (in Persian). Hayes, M., Svoboda, M., Wall, N., Widhalm, M., 2011. The lincoln declaration on drought indices: universal meteorological drought index recommended. J. Am. Meteorol. Soc. 92(4), 485-488. Hejazizadeh, Z., Akbari, M., Sasanpour, F., Hosseini, A., Mohammadi, N., 2022. Investigating the effects of climate change on torrential rains in Tehran Province. Water Soil Manage. Model. 2(2), 87-105 (in Persian). Hosseini, M., Azizian, A., 2023. Studying the effect of climate change on drought conditions and climate regions of Iran using aridity index. J. Water Soil Resour. Conserv. 13(49), 111-129 (in Persian). Javan, K., 2021. Investigation of meteorological drought in Urmia using SPI under climate change scenarios (RCP). Climate Change Res. 2(5), 81-94 (in Persian). Javan, K., Erfanian, M., 2020. Assessing the impact of climate change on the drought status in Tabriz station during future periods using LARS-WG. Iran. Water Res. J. 14(3), 97-106 (in Persian). Kim, B.S., Chang, I.G., Sung, J.H., Han, H.J., 2016. Projection in future drought hazard of South Korea based on RCP climate change scenario 8.5 using SPEI. Adv. Meteorol. 4148710. Koohi, S., Azizian, A., Mazandarani Zadeh, H., 2022. The effects of climate change on drought conditions using fuzzy logic under SSP3 and SSP5 scenarios. Iran-Water Resour. Res. 18(3), 1-17 (in Persian). Kouhi, M., 2021. Projection of future drought characteristics under RCPs scenarios in the four climate zones of Iran. J. Climatol. Res. 12(47), 55-33 (in Persian). Lee, S., Yoo, S., Choi, J., Bae, S., 2017. Assessment of the impact of climate change on drought characteristics in the Hwanghae Plain, North Korea using time series SPI and SPEI: 1981-2100. Water, 9(8), 579. Maleki Meresht, R., Salahi, B., Saber, M., 2024. Analyzing the changes in precipitation in northwest Iran during the coming decades based on the GCM Models. J. Geograph. Plan (in Persian). Masoompour Samakosh, J., Miri, M., Rezaei, S., 2024. Analysis of drought characteristics (severity, duration, magnitude) in Iran based on multivariate standardized drought index. Advanc. Technol. Water Efficie. 4(1), 82-98 (in Persian). McKee, TB., Doesken Kleist, N.J., 1993. The relationship of drought frequency and duration to time scales. Preprints 8th Conference on Applied Climatology, Anaheim, CA. 170-184. Moafi Madani, S.F., Mousavi Baygi, M., Ansari, H., 2012. Prediction of drought in the Khorasan Razavi Province during 2011-2030 by using statistical downscaling of HADCM3 model output. J. Geograph. Environ. Hazards 1(3), 21-38 (in Persian). Mohammadi, N., Hedjazizadeh, Z., 2024. The effects of climate change on increasing the risk of drought in Tehran using CMIP6 scenarios. Water Soil Manage. Model. 4(2), 133-148 (in Persian). Mohammadi, P., Malekian, A., Salajegheh, A., Nouri, M., Rafiei, H., 2024. Simulation of climate change scenarios using the CMIP6 models, case study: Taleqan Watershed. Integrat. Watershed Manage. (in Persian). Mozaffari, E., Moradi, N., Bazrafshan, O., 2021. Spatio-temporal variability of characteristics of meteorological drought in Iran under climate change scenarios. Desert Manage. 8(16), 153-163 (in Persian). Oguntunde, P.G., Abiodun, B.J., Lischeid, G., 2017. Impacts of climate change on hydro meteorological drought over the Volta Basin, West Africa. Global Planet Change 155, 121-132. Pedersen, J.T.S., Vuuren, D., Gupta, J., Santos, F.D., Jae Edmonds, J., Swart, R., 2022. IPCC emission scenarios: How did critiques affect their quality and relevance 1990–2022?. Global Environ. Chang. 75(102538). Rahvareh, M., Motamedvaziri, B., Moghaddamnia, A., Moridi, A., 2023. Investigating meteorological and hydrological drought in Zarrineh River basin. Desert Ecosys. Engineer. 11(37), 15-26 (in Persian). Rajaei, F., 2022. Drought forecasting under the approach of future climate change, case study: Qarakhil. J. Environ. Sci. Studies 7(2), 4990-5001 (in Persian). Raziei, T., Daneshkar Arasteh, P., Akhtari, R., Saghafian, B., 2007. Investigation of meteorological droughts in the Sistan and Balouchestan Province, using the standardized precipitation index and markov chain model. Iran-Water Resour. Rese. 3(1), 25-35 (in Persian). Raziei, T., Shokouhi, A., Saghafian, B., 2003. Forecasting the intensity, duration and frequency of drought using probabilistic methods and time series, case study of Sistan and Baluchistan Province. Desert 8(2), 310 -292 (in Persian). Robert, L., Wilby, W., 2004. Using SDSM Version 3.1 - A decision support tool for the assessment of regional climate change impacts. A Consortium for the Application of Climate Impact Assessments (ACACIA), Canadian Climate Impacts Scenarios (CCIS) Project, Environment Agency of England and Wales. Sadeqi, A., Dinpashoh., Y., 2020. Fluctuations analysis of rainfall and runoff in aras border basin under climate change conditions. Protection Water Soil Resour. 10(2), 83-96 (in Persian). Salahi, B., Foroutan, M., 2024. Monitoring and modeling the precipitation of Ardabil Plain in the coming decades based on the output of some GCMs. Hydrogeomorphol. 11(39), 99-81 (in Persian). Salahi, B., Moradi, M., 2024. Downscaling and investigation of climate change and its effect on temperature and precipitation in some western and coastal stations of Iran (Ahvaz, Bushehr, and Bandar-Lengeh). Amphibi. Sci. Technol. 5(1), 14-27 (in Persian). Salahi, B., Saber, M., Vatanparast Ghaleh Juq, F., 2023. Simulating and predicting the effects of climate change using some new scenarios of SSP and CMIP6 models on rainfall changes in Ardabil County. J. Geograph. Environ. Studies, 51(13) (in Persian). Salehpour Jam, A., Karimpour Reihan, M., Mohseni Saravi, M., Bazrafshan, J., Khalighi Sigaroudi, S., 2017. Investigation of climate change effect on drought characteristics in the future period using the HadCM3 model, case study: Khoy Station, Northwest of Iran. Desert 22(1), 43-50 (in Persian). Sedaghat Kerdar, A., Fatahi, E., 2008. Drought early warning methods over Iran. Geograph. Develop. 6(11), 59-76 (in Persian). Seraj Ebrahimi, R., Eslamian, S., Zareian, M.J., 2023. Investigation of the effects of climate change and meteorological drought on groundwater drought in wet and semi-humid areas, case study: Talesh plain. Water Resour. Engineer. 16(56), 54-68 (in Persian). Teymouri Yeganeh, M., Teymouri Yeganeh, L., 2021. Evaluating the trend of rainfall and temperature changes and their effects on meteorological drought in Kermanshah Province. J. Environ. Res. Technol. 6(10), 123-134 (in Persian). Torabinezhad, N., Zarrin, A., Dadashi-Roudbari, A., 2023. Analysis of different types of droughts and their characteristics in Iran using the Standardized Precipitation Evapotranspiration Index (SPEI). Water Soil 37(3), 473-486 (in Persian). Yaghoobzadeh, M., Amirabadizadeh, M., khozeymehnezhad, H., Zeraatkar, Z., 2018. The evaluation of the three downscaling methods in Meteorological droughts forecastingunder the effects of climate change. Iran. Jo. Irriga. Drain. 12(2), 323-334 (in Persian). Yevjevich, V.M., 1967. Objective approach to definitions and investigations of continental hydrologic droughts. An Doctoral dissertation, Colorado State University. Zarghami, M., Babaian, I., Hassanzadeh, Y., Kanani, K., 2013. Study of climate change and its effects on drought, case study: East Azerbaijan Province. Watershed Sci. Engineer. Quart. 18, 61-76 (in Persian). Zarrin, A., Dadashi-Roudbari, A., 2021. Drought risk management in a changing climate: the role of national policies and the Drought Management Plan (DMP). J. Water Sustain. Develop 8(1), 107-112 (in Persian). Zhai, J., Mondal, S.K., Fischer, T., Wang, Y., Su, B., Huang, J., Tao, H., Wang, G., Ullah, W., Uddin, M.J., 2020. Future drought characteristics through a multi-model ensemble from CMIP6 over South Asia. J. Atmospheric Res. 246(105111). | ||
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