| تعداد نشریات | 282 |
| تعداد نشریات سازمان | 80 |
| تعداد شمارهها | 3,208 |
| تعداد مقالات | 35,560 |
| تعداد مشاهده مقاله | 53,006,022 |
| تعداد دریافت فایل اصل مقاله | 92,289,726 |
واکاوی تغییرات زمانی- مکانی شاخصهای حدی بارش تحت تأثیر تغییر اقلیم در ایران | ||
| پژوهش های آبخیزداری | ||
| مقاله 4، دوره 37، شماره 4 - شماره پیاپی 145، دی 1403، صفحه 34-53 اصل مقاله (2.82 M) | ||
| نوع مقاله: پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22092/wmrj.2024.364521.1565 | ||
| نویسندگان | ||
| سپیده چوبه1؛ بهنوش فرخ زاده* 2؛ ام البنین بذرافشان3؛ هانیه حسنوند4 | ||
| 1دانشآموختة دکتری، آبخیزداری- آب، گروه مرتع و آبخیزداری، دانشکدة منابعطبیعی، دانشگاه ارومیه، ارومیه، ایران | ||
| 2استادیار گروه مهندسی طبیعت، دانشکدة منابعطبیعی و محیط زیست، دانشگاه ملایر، ملایر، ایران | ||
| 3استاد گروه مهندسی منابع طبیعی، دانشکدة کشاورزی و منابعطبیعی، دانشگاه هرمزگان، بندرعباس، ایران | ||
| 4دانشآموختة کارشناسی ارشد آبخیزداری، گروه مهندسی طبیعت، دانشکدة منابعطبیعی و محیط زیست، دانشگاه ملایر، ملایر، ایران | ||
| چکیده | ||
| مقدمه و هدف تغییر اقلیم موجب تغییر نمایههای حدی و افزایش شدت و فراوانی رخداد رویدادهای حدی اقلیمی میشود. بارشهای سنگین در هنگام رخداد موجب آسیب گسترده به اقتصاد، محیط زیست و زندگی بشر میشود. براساس گزارش خطر جهانی سال 2019 که بهوسیلة انجمن اقتصاد جهانی (WEF) منتشرشده است، حوادث اقلیمی حدی (مانند بارشهای حدی) و سازگار نبودن با تغییرات اقلیمی بهعنوان خطرات برجسته در ارتباط با تأثیر بر محیط زیست و انسان شناخته شدهاند. از اینرو، در این پژوهش اثر تغییر اقلیم بر بارشهای سنگین در ایران بررسی شد. مواد و روشها در این پژوهش، از دادههای بارش 47 ایستگاه استفاده شد. در ابتدا، عملکرد مدل بررسی شد. سپس، دادههای بارش با استفاده از نرمافزار LARS-WG و با سناریوهای مختلف و برای دورة آینده، پیشبینی شد. برای ارزیابی شبیهسازی بارشهای حدی بهوسیلة مدل نامبرده، افزون بر مقایسة گرافیکی دادههای مشاهدهشده و تولیدشدة هر ایستگاه در فرآیند صحتسنجی، شاخصهای RB، MD و WS میان دادههای شاخصهای حدی مشاهده شده و شبیهسازی شده محاسبه شد. سرانجام روند بارشهای سنگین با آزمون من-کندال بررسی شد. نتایج و بحث نتایج شبیهسازی بارش در دورة 2050-2030 نشان داد که تغییرات سالانة ایستگاههای همدید، غیریکنواخت بود. بیشترین افزایش بارش سالانه در ایستگاه بم و با سناریوی SSP5-8.5 به اندازة 59/81% (32/32 میلیمتر) بود و بیشترین کاهش بارش سالانه در ایستگاه کیش و با سناریوی SSP5-8.5 به اندازة 11/63% (17/23 میلیمتر) بود. بر اساس نتایج پراکنش مکانی PRCPTOT بیشترین افزایش بارش سالانه در ایستگاه یاسوج و تحت سناریوی SSP1-2.6 بود. بهطوریکه در این ایستگاه بارش سالانه برای دورة آینده با سناریوهای SSP1-2.6 و SSP5-8.5 بهترتیب 933/49 و 889/3 میلیمتر برآورد شد. همچنین، اندازة این شاخص در دورة پایه در این ایستگاه 832/19 میلیمتر پیشبینی شد. از سوی دیگر، بیشترین کاهش بارش سالانه در ایستگاه تبریز با سناریوی SSP5-8.5 به اندازة 165/11 میلیمتر (68%) بود. نتایج بررسی تغییرات شاخصهای حدی بارش در دورة 2050-2030 در مقایسه با 2022-1985 نشان داد بیشترین تغییرات در مناطق شمال و غرب ایران بود که شدت این تغییرات بهویژه با سناریوی SSP5-8.5 بیشتر بود. بیشترین کاهش شاخص Rx1day، مربوط به ایستگاه مشهد با سناریوی SSP5-5.5 و 37% بود. بیشترین روند افزایشی مربوط به ایستگاه زنجان با سناریوی RCP8.5 بود. نتیجهگیری و پیشنهادها پژوهشهای پرشماری در سراسر جهان نشان دادهاند که تغییرات اقلیم منجر به تغییرات شاخصهای حدی بارش میشود. این تغییرات شامل کاهش دامنة بارش و تغییر الگوی بارش است. در این راستا، نتایج این پژوهش نشان داد که روند شاخصهای حدی، الگوی یکسانی نداشت و این روند در برخی ایستگاههای همدید افزایشی و در برخی دیگر کاهشی بود. بهطور کلی میتوان گفت که شدت بارش در دورة آینده و با سناریوهای اقلیمی در بیشتر ایستگاههای مطالعهشده افزایش خواهد یافت. بررسی دقیق رویدادهای حدی بارش و تأثیرات آنها بر برنامهریزی و سیاستگذاری آینده در بخشهای گوناگون ضروری است. ازاینرو، پیشنهاد میشود شبیه این پژوهشها در آبخیزهای اصلی کشور در مقیاس کوچکتر و در تعداد بیشتری از ایستگاهها با دیگر آزمونهای تشخیص روند انجام شود و نتایج آن با آزمون آماری من-کندال مقایسه شود. | ||
| کلیدواژهها | ||
| ایران؛ بارش سنگین؛ ریزمقیاسنمایی؛ سناریوی اقلیمی؛ مدلهای گردش عمومی جو؛ CMIP6 | ||
| عنوان مقاله [English] | ||
| Impact of Climate Change on Precipitation Extremes Indices over Iran | ||
| نویسندگان [English] | ||
| Sepideh Choobeh1؛ Behnoush Farrokhzadeh2؛ Ommolbanin Bazrafshan3؛ Haniyeh Hasanvand4 | ||
| 1Ph.D. Graduated in Watershed Management, Faculty of Natural Resources, Urmia University, Urmia, Iran | ||
| 2Assistant Professor, Department of Range and Watershed Management, Faculty of Natural Resources, Malayer University, Malayer, Iran | ||
| 3Professor, Department of Natural Resources Engineering, Faculty of Agricultural and Natural Resources, University of Hormozgan, Bandar Abbas, Iran | ||
| 4M.Sc. Graduated in Watershed Management, Department of Nature Engineering, Faculty of Natural Resources and Environment, Malayer University, Malayer, Iran | ||
| چکیده [English] | ||
| Introduction and Goal Climate change leads to changes in extreme climate indices, such as an increased intensity and frequency of extreme weather events. Heavy precipitation during these events can cause widespread damage to the economy, the environment and human life. According to the World Economic Forum's (WEF) Global Risks Report 2019, extreme climate events (such as heavy precipitation) and climate inadaptability are the greatest risks in terms of their impact on the environment and people. The purpose of this study was to examine the impact of climate change on heavy precipitations in the Iran. Materials and Methods Precipitation data from 47 stations was utilized in this study. First, the performance of the model was evaluated. LARS-WG software was employed to predict precipitation data with various scenarios for the future period. To evaluate the simulation of extreme precipitation using the aforementioned model, in addition to graphically comparing the observed and generated data of each station in the validation process, the RB, MD, and WS indices were calculated between the observed and simulated extreme index data. Finally, the Mann-Kendall test was utilized to examine the pattern of heavy precipitation events. Results and Discussion The simulation results for precipitation in the period 2030-2050 show that the synoptic stations will experience uneven annual fluctuations. The largest increase in annual precipitation was 59.81% (32.32 mm) at the Bam station and SSP5-8.5 scenario, and the largest decrease in annual precipitation was 11.63% (17.23 mm) at the Kish station and SSP5-8.5 scenario. According to the spatial distribution of PRCPTOT, the Yasouj station experienced the highest increase in annual precipitation under the SSP1-2.6 scenario. At this station, the annual precipitation for the future period was estimated to be 933.49 and 889.3 mm with the SSP1-2.6 and SSP5-8.5 scenarios respectively. Also, the magnitude of this indicator during the base period at this station was predicted to be 832.19 mm. Furthermore, it was predicted that this indicator will be 832.19 mm during the base period at this station. The results of the study of changes in precipitation extreme indices in the period 2030-2050 compared to 1985-2022 showed that the greatest changes were in the northern and western regions of the Iran, and the severity of these changes was especially greater with the SSP5-8.5 scenario. The largest decrease in the Rx1day index was related to the Mashhad station with the SSP5-5.5 scenario, which was 37%. The highest increasing trend was related to the Zanjan station in the RCP8.5 scenarios. Conclusion and Suggestions Numerous studies around the world have shown that climate change leads to changes in extreme precipitation. A decrease in precipitation intensity and a change in precipitation patterns are among these changes. According to the results of this study, the trend of extreme indices was not uniform, and it was increasing in some synoptic stations and decreasing in others. In general, precipitation intensity is expected to increase in the future and with climate scenarios in most of the studied stations. The impact of extreme precipitation events on future planning and policymaking in various sectors should be carefully examined. Therefore, it is suggested that similar studies be conducted in the country's main watersheds on a smaller scale and in a larger number of stations with other trend detection tests, and the results be compared with the Mann-Kendall statistical test. | ||
| کلیدواژهها [English] | ||
| Atmospheric General Circulation Models, Climate Scenarios, CMIP6, Downscaling, Heavy Precipitation, Iran | ||
| مراجع | ||
|
Abbas A, Bhatti AS, Ullah S, Ullah W, Waseem M, Zhao C, Ali G. 2023. Projection of precipitation extremes over South Asia from CMIP6 GCMs. Journal of Arid Land, 15(3): 274-296. https://doi.org/10.1007/s40333-023-0050-3 Alaei Taleghani M. 2003. Geomorphology of Iran. Ghoomes Publications. 416 p. Alavinia SH, Zarei M. 2021. Analysis of spatial changes of extreme precipitation and temperature in Iran over a 50‐year period. International Journal of Climatology, 41(s1): 2269-2289. https://doi.org/10.1002/joc.6845 Alavinia SH, Zarei M. 2022. Climate change trends analysis using extreme indices of long-term precipitation and temperature in Southeast Iran. Regional Planning, 11(44): 119-134. (In Persian). https://doi.org/10.30495/jzpm.2022.4059 Askarizadeh SM, Mozaffari G, Kohi M, Rezahipoor A. 2018. Variations in precipitation and temperature extreme values in Torbat-e-Hidariyh using the LARS-WG downscaling model during 2011-2030. Geographic Thought, 10(19): 60-80. Bazrafshan Moghaddam M. 2016. Evaluation of climate change's effect on precipitation and temperature in different parts of Iran. M.Sc. Thesis, Civil Engineering. Faculty of Civil Engineering, Shahrood University of Technology, 122 p. (In Persian). Binesh N, Niksokhan MH, Sarang A. 2016. Precipitation trend analysis and determination of dry/wet years in Kan Watershed during recent years. Extension and Development of Watershed Management, 4(14): 9-16. (In Persian). Chen L, Ford TW. 2023. Future changes in the transitions of monthly-to-seasonal precipitation extremes over the Midwest in Coupled Model Intercomparison Project Phase 6 models. International Journal of Climatology, 43(1): 255-274. https://doi.org/10.1002/joc.7756 Costa AA, Guimarães SO, Sales DC, das Chagas Vasconcelos Junior F, Marinho MWS, Pereira JMR, da Silva EM. 2023. Precipitation extremes over the tropical Americas under RCP4.5 and RCP8.5 climate change scenarios: Results from dynamical downscaling simulations. International Journal of Climatology, 43(2): 787-803. https://doi.org/10.1002/joc.7828 Doolabian Sh. 2017. Evaluating the effects of climate change on precipitation and temperature over different parts of Iran using RCP scenarios. M.Sc. Thesis, Civil Engineering, Shahrood University of Technology, 115 p. (In Persian). Esgandari R, Esmali Ouri A, Mostafazadeh R, Choobeh S. 2024. Assessment of temporal and spatial variations of precipitation climate extreme indices in the central part of Ardabil Province. Journal of Environmental Science Studies, 9(1): 8119-8133. (In Persian). https://doi.org/10.22034/jess.2023.382713.1963 Ezaz GT, Zhang K, Li X, Shalehy MH, Hossain MA, Liu L. 2022. Spatiotemporal changes of precipitation extremes in Bangladesh during 1987–2017 and their connections with climate changes, climate oscillations, and monsoon dynamics. Global and Planetary Change. 208, 103712. https://doi.org/10.1016/j.gloplacha.2021.103712 Farrokhzadeh B, Choobeh S, Nouri H, Goodarzi M. 2018. Study of climate change and land use changes impacts on surface runoff: Balighlo Chai Watershed in Ardebil. Watershed Engineering and Management, 10(3): 318-331. https://doi.org/10.22092/ijwmse.2017.107110.1165 Fathian F, Ghadami M, Haghighi P, Amini M, Naderi S, Ghaedi Z. 2020. Assessment of changes in climate extremes of temperature and precipitation over Iran. Theoretical and Applied Climatology, 141:1119-1133. https://doi.org/10.1007/s00704-020-03269-2 Ge F, Zhu S, Luo H, Zhi X, Wang H. 2021. Future changes in precipitation extremes over Southeast Asia: insights from CMIP6 multi-model ensemble. Environmental Research Letters 16(2): 024013. https://doi.org/10.1088/1748-9326/abd7ad. Khorshiddoost AM, Ghavidel Rahimi Y. 2004. Study of precipitation fluctuations, forecasting, and determination of wet and dry winter seasons in East Azerbaijan Province. Geographical Research Journal, 19(1): 25-36. (In Persian). Goodarzi M, Choobeh S. 2019. Assessment of downscaling methods in predicting climatic parameters under climate change status: A case study in Ardabil Synoptic Station. Iranian Journal of Watershed Management Science and Engineering, 13(45): 63-69 Goyal MK, Gupta AK, Jha S, Rakkasagi S, Jain V. 2022. Climate change impact on precipitation extremes over Indian cities: Non-stationary analysis. Technological Forecasting and Social Change, pp. 1-7. https://doi.org/10.1016/j.techfore.2022.121685 Gupta S, Gupta A, Himanshu SK, Singh R. 2019. Analysis of the extreme precipitation events over upper catchment of Sabarmati River Basin in Western India using extreme precipitation indices. In Advances in Water Resources Engineering and Management: Select Proceedings of TRACE. Singapore: Springer Singapore, pp.103-111. https://doi.org/10.1007/978-981-13-8181-2_8 Harrison PA, Dunford RW, Holman IP, Cojocaru G, Madsen MS, Chen, PY, Sandars D. 2019. Differences between low-end and high-end climate change impacts in Europe across multiple sectors. Regional Environmental Change, (19):695- Hejazizadeh Z, Zarei S. 2023. Investigation of changes in temperature and precipitation indicators in Kurdistan Province based on radiation injection scenarios (RCP). Journal of Applied Researches in Geographical Sciences, 23(69): 1-14. (In Persian). https://doi.org/10.61186/jgs.23.69.1 Hong YIN, Ying SUN. 2019. Characteristics of extreme temperature and precipitation in China in 2017 based on ETCCDI indices. Advances in Climate Change Research, 15(4): 363 -373. https://doi.org/10.12006/j.issn.1673-1719.2018.164 Jafarzadeh A, Khashei-Siuki A, Shahidi A. 2016. Assessment of statistical downscaling methods LARS-WG & SDSM in forecasting climate parameter variation. Journal of Water and Soil Conservation, 23(4): 309-322. (In Persian). https://doi.org/10.22069/jwfst.2016.10385.2482 Jahanbakhsh Asl S, Mohammad Khorshiddoost A, Din Pazhooh Y, Sarafroozeh F. 2015. Trend analysis and estimating return periods of extreme temperature and precipitation in Tabriz. Geography and Planning, 18(50): 107-133. (In Persian). Jowkar L, Panahi F, Sadatinejad SJ, Shakiba A. 2021. Precipitation extremes variability trend in Bakhtegan Catchment using agMERRA and station data. Irrigation and Water Engineering, 12(1): 364-381. (In Persian). https://doi.org/10.22125/iwe.2021.138351 Kamal A, Massah Bavani A. 2010. Climate change and variability impact on basin runoff with interference of two hydrology models uncertainty. Water and Soil, 24(5): 39-50. (In Persian). https://doi.org/10.22067/jsw.v0i0.5283 Katiraie-Boroujerdy PS, Akbari Asanjan A, Chavoshian A, Hsu KL, Sorooshian S. 2019. Assessment of seven CMIP5 model precipitation extremes over Iran based on a satellite‐based climate data set. International Journal of Climatology, 39(8): 3505-3522. https://doi.org/10.1002/joc.6035 Khazaei MR, Khazaee H, Saghafian B. 2020. Climate change impact on extreme precipitations in arid region of Iran. Journal of Environmental Science and Technology, 22(9): 31-42. (In Persian). https://doi.org/10.22034/jest.2021.40667.4508 Kazemi Rad L, Modaberi H. 2023. Evaluation of climatic parameters in even lake affected by climate change. Journal of Environmental Science Studies, 8(3): 6936-6942. https://doi.org/10.22034/jess.2022.332757.1890 Khoi DN, Trong Quan N, Thi Thao Nhi P, Nguyen VT. 2021. Impact of climate change on precipitation extremes over Ho Chi Minh City, Vietnam. Water, 13(2): 120-147. https://doi.org/10.3390/w13020120 Kouzegaran S. 2017. Evaluating the effects of climate change on precipitation and temperature over different parts of Iran using RCP scenarios. Ph.D. Thesis. Agrometeorology. Faculty of Agriculture. Ferdowsi University of Mashhad. 182 p. (In Persian). Kouzegaran S, Mousavi Baygi M. 2015. Investigation of meteorological extreme events in the North-East of Iran. Water and Soil, 29(3): 750-764. (In Persian). https://doi.org/10.22067/jsw.v0i0.40845 Lotfi rad M, Ahmadian S, Adib A. 2020. The effect of climate change on the trend of seasonal precipitation in Iran. National Conference on Building, Environment and Energy Management. Ahvaz. August 5. 9 p. (In Persian). Mohammadi H, Azizi G, Khoshahklagh F, Ranjbar F. 2017. Analysis of daily precipitation extreme indices trend in Iran. Physical Geography Research Quarterly, 49(1): 21-37. (In Persian). https://doi.org/10.22059/jphgr.2017.61577 Mohammadlo M, Haghizadeh A, Zeinivand H, Tahmasebi Pour N. 2017. Evaluation of climate change on temperature and precipitation trends in Barandozchay watershed, in the West Azerbaijan, using general circulation models (GCM). Journal of Geographic Space, 16(56):151-168. Moriasi DN, Gitau MW, Pai N, Daggupati P. 2015. Hydrologic and water quality models: Performance measures and evaluation criteria. Transactions of the ASABE, 58(6): 1763-1785. Neelin JD, Martinez-Villalobos C, Stechmann SF, Chen G, Norris JM, Lenderink G. 2022. Precipitation extremes and water vapor: Relationships in current climate and implications for climate change. Current Climate Change Reports, 8(1): 17-33. https://doi.org/10.1007/s40641-021-00177-z Panda DK, Mishra A, Jena SK, James BK, Kumar A. 2007. The influence of drought and anthropogenic effects on groundwater levels in Orissa, India. Journal of Hydrology, 343(3-4): 140-153. https://doi.org/10.1016/j.jhydrol.2007.06.007 Peñuelas J, Ciais P, Canadell JG, Janssens IA, Fernández-Martínez M, Carnicer J, Sardans J. 2017. Shifting from a fertilization-dominated to a warming-dominated period. Nature Ecology and Evolution, 1(10): 1438-1445. https://doi.org/10.1038/s41559-017-0274-8 Purnomo H. 2018. Aplikasi metode interpolasi inverse distance weighting dalam penaksiran sumberdaya laterit nikel. Journal Ilmiah Bidang Teknologi ANGKASA, 10(1): 49-60. Rahimzadeh F. 2006. Investigating the changes in precipitation extremes indices in Iran. Nivar, 30(58-59): 7-20. (In Persian). Rahimzadeh F, Asgari A, Fattahi E. 2009. Variability of extreme temperature and precipitation in Iran during recent decades. International Journal of Climatology: A Journal of the Royal Meteorological Society, 29(3): 329-343. Shukla PR, Skea J, Calvo Buendia E, Masson-Delmotte V, Pörtner HO, Roberts DC, Malley J. 2019. IPCC, 2019: Climate change and land: An IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems. 874 p. Soltani M, Laux P, Kunstmann H, Stan K. Sohrabi MM, Molanejad M, Martin MV. 2016. Assessment of climate variations in temperature and precipitation extreme events over Iran. Theoretical and Applied Climatology, pp. 775-795. https://doi.org/10.1007/s00704-015-1609-5 Tavangar S, Moradi H, Massah Bavani AR. 2019. Climate change effect on the precipitation amount and intensity in the southern coast of the Caspian Sea. Irrigation and Water Engineering, 10(2):190-204. (In Persian). https://doi.org/10.22125/iwe.2019.100751 Van der Wiel K, Bintanja R. 2021. Contribution of climatic changes in mean and variability to monthly temperature and precipitation extremes. Communications Earth and Environment, 2(1):1-11. https://doi.org/10.1038/s43247-020-00077-4 Zhao W, Zhong Y, Li Q, Li M, Liu J, Tang L. 2022. Comparison and correction of IDW based wind speed interpolation methods in urbanized Shenzhen. Frontiers of Earth Science, 16(3): 798-808. https://doi.org/10.1007/s11707-021-0948-z Zhang X, Aguilar E, Sensoy S, Melkonyan H, Tagiyeva U, Ahmed N, Wallis T. 2005. Trends in Middle East climate extreme indices from 1950 to 2003. Journal of Geophysical Research: Atmospheres, 110(D22): 1-12. https://doi.org/10.1029/2005JD006181 Zhang M, Chen Y, Shen Y, Li B. 2019. Tracking climate change in central Asia through temperature and precipitation extremes. Journal of Geographical Sciences, pp. 3-28. https://doi.org/10.1007/s11442-019-1581-6 Zand M, Miri M, Kousari M. 2023. Detection of climate change in Lorestan Province using climate extreme indices. Watershed Engineering and Management, 15(1): 27-41. (In Persian). https://doi.org/10.22092/ijwmse.2022.354926.1905 Zarrin A, Dadashi-Roudbari A. 2022. Technical note: assessing the effect of climate change on heavy precipitation in Iran Based on a CMIP6 Ensemble model. Journal of Water and Sustainable Development, 8(4):119-124. (In Persian). https://doi.org/10.1001.1.24235474.1400.8.4.14.9 | ||
|
آمار تعداد مشاهده مقاله: 1,520 تعداد دریافت فایل اصل مقاله: 521 |
||