پیش‌آگاهی مخاطره خشکسالی در ایستگاه سینوپتیک زابل براساس برونداد مدل‌های اقلیمیCMIP6

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکترا منابع آب، گروه علوم و مهندسی آب، دانشکده کشاورزی، دانشگاه بیرجند، بیرجند، ایران

2 دانشیار گروه علوم و مهندسی آب، دانشکده کشاورزی، دانشگاه بیرجند، بیرجند

3 دانشیار، گروه علوم و مهندسی آب، دانشکده کشاورزی، دانشگاه بیرجند، بیرجند.

4 دانشجوی دکترای منابع آب، گروه علوم و مهندسی آب، دانشکده کشاورزی، دانشگاه بیرجند، بیرجند.

چکیده

باتوجه به اهمیت خشکسالی و اقدام برای به حداقل رساندن خسارات ناشی از این بلیه طبیعی، در پژوهش حاضر به بررسی شاخص خشکسالی بارش استاندارد شده (SPI) در منطقه جنوب شرقی ایران در شهرستان زابل با استفاده از چهار مدل GCM، BCC-ESM2-MR، CanESM5، MIROC6 و MRI-ESM2-0 ارائه شده در CMIP6 پرداخته شده است. در این پژوهش، از دو سناریو SSP2-4.5 و SSP5-8.5 برای تخمین SPI در دو دوره 2044-2025 و 2084-2065 و برای پیش‌بینی داده‌های هواشناسی از روش ریزمقیاس‌نمایی BCSD استفاده شده است. با توجه به نتایج به‌دست آمده در هر دو سناریوی SSP2-4.5 و SSP5-8.5 و در تمامی مدل‌های مورد بررسی، میانگین 20 ساله شاخص SPI، شش ماهه نشان دهنده بیشترین مقدار منفی است. علاوه‌بر این مقایسه مدل‌ها و سناریوها در این پژوهش نشان می‌دهد که در مدل BCC-ESM2-MR ، میانگین 20 ساله‌ شاخص شش ماهه SPI و در مدل CanESM5، شاخص 12 و 48 ماهه نسبت به سایر مدل‌ها بیشتر است. همچنین شاخص SPI در مقیاس زمانی 12 و 48 ماهه شدت خشکسالی را در دوره‌های مورد مطالعه بیشتر از مقیاس زمانی شش ماهه نشان می‌دهد و در مقیاس‌های زمانی مورد مطالعه تقریباً هر دو سناریو بر هم منطبق هستند. طبق نتایج حاصل از این پژوهش، به‌طور کلی دوره‌های دارای وضعیت نرمال کاهش یافته و به تعداد دوره‌های دارای وضعیت خشک نسبت به دوره پایه افزوده شده است. همچنین نتایج نشان می‌دهد در بدبینانه‌ترین حالت، تعداد دوره‌های خشک در ایستگاه سینوپتیک زابل 14 دروه خواهد بود و می‌توان برای پیش‌بینی شاخص خشکسالی از مدل CanESM5 استفاده نمود.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Forecasting the risk of drought in Zabol synoptic station based on the output of CMIP6 climate models

نویسندگان [English]

  • Mahdieh Forouzan Mehr 1
  • Mehdi Dastourani 2
  • Mostafa Yaghoobzadeh 3
  • saeide Hoseinabadi 4
1 PhD Student, Water Resources, Department of Water Science and Engineering, Faculty of Agriculture, University of Birjand, Birjand, Iran.
2 Associate Professor, Department of Water Science and Engineering, Faculty of Agriculture, University of Birjand, Birjand, Iran.
3 Associate Professor & Research Group of Drought and Climate Change, Department of Water Science and Engineering, Faculty of Agriculture, University of Birjand, Birjand, Iran.
4 PhD Student, Water Resources, Department of Water Science and Engineering, Faculty of Agriculture, University of Birjand, Birjand, Iran.
چکیده [English]

Drought is one of the most complex natural hazards that affect natural and human systems (Wilhite et al., 2005, Wilhite et al., 2007). Greenhouse gas emission has contributed to climate change in the last century (Van Pelt and Swart, 2011). Climate change has a significant impact on the hydrological cycle and consequently on water resources, and the frequency and severity of droughts and floods. The most reliable tool available for future climate simulation is the output of coupled atmosphere-ocean patterns of atmospheric general circulation (Shakarami and Massahbavani, 2007). The reports of the Intergovernmental Panel on Climate Change show that if the current trend of greenhouse gas production due to the consumption of fossil fuels continues, the concentration of these gases can reach more than 600 ppm before the end of the 21st century (IPCC, 2007). The downscale model, which is a downscale statistical method, uses semi-empirical distributions for simulation and downscale and can generate future climate parameters at the station level. A major application of these data is to monitor and evaluate future droughts (Hosseinabadi et al, 2020). In the occurrence of drought, there are many factors such as changing the course of rivers and draining reservoirs, climate change and warming of the earth. Nowadays, the increasing occurrence of drought has caused the attention of many meteorologists and climatologists around the world. Drought indicators are used to diagnose and classify drought conditions. These indicators include the possibility of evaluating the standardized precipitation evaporation and transpiration index SPEI, the Palmer drought intensity index PDSI, the standard runoff index SRI and the identification drought index RDI. SPI and SPEI are the most common drought indicators.

کلیدواژه‌ها [English]

  • Drought
  • Sixth Climate Change Report
  • SPI Index
  • Climate Change

مراجع

  • Aadhar, S, and Mishra V. 2020. On the projected decline in droughts over South Asia in CMIP6 multimodel ensemble. Journal of Geophysical Research Atmospheres, 125(20), pp.1-29. Doi: 10.1029/2020JD033587.
  • Abbasinia, A., Morshedi, J., Zohoriyan, M. and Ghorbaniyan, J., 2021. Analysis and Comparison of SPI and GRI Indices in Assessing Meteorological Drought and Groundwater, Case Study: Mehran Plain, Ilam Province. Physical Geography Quarterly, 14(Physical Geography Quarterly), pp.95-114.dor: 20.1001.1.20085656.1400.14.51.6.3. (In Persian)

 

  • Ataei, H., Kouhi, M., Modirian, R. and Bazrafshan, B., 2021. Projected Changes in Temperature and Precipitation over Kashafrood Basin Based on Statistical and Dynamical Downscaling Methods. Journal of Natural Environmental Hazards, 10(30), pp.183-202. Doi: 10.22111/JNEH.2021.37827.1777. (In Persian)

 

  • Ayugi, B., Shilenje, Z. W., Babaousmail, H., Sian, K. T. L. K., Mumo, R., Dike, V. N, and Ongoma, V. 2021. Projected Changes in Meteorological Drought Over East Africa Inferred from Bias-Adjusted CMIP6 Models, Natural Hazards, 113(1), pp.1151-1176.

 

  • Chiang, F., Mazdiyasni, O., and AghaKouchak, A. 2021. Evidence of anthropogenic impacts on global drought frequency, duration, and intensity. Nature Communications, 12(1), pp. 1-10.‏

 

  • Edwards, D.C. and McKee, T.B., 1997. Characteristics of 20 th century drought in the United States at multiple time scales(Vol. 97, p. 155). Fort Collins: Colorado State University.

 

  • Ramezani Etedali, H., Hodabakhshi, F. and Kanani, E., 2022. Outlook for the effects of climate change on drought according to the fifth IPCC report (case study: Ilam). Journal of Water and Soil Resources Conservation, 12(1), pp.87-107. Doi: 30495/WSRCJ.2022.20455. (In Persian)

 

  • Fung, K. F., Huang, Y. F., and Koo, C. H. 2020. Assessing drought conditions through temporal pattern, spatial characteristic and operational accuracy indicated by SPI and SPEI: case analysis for Peninsular Malaysia. Natural Hazards, 10(32), pp.2071-2101.‏

 

  • Goodarzi,M, and Choobeh, S. 2019. Assessment of Downscaling Methods in Predicting Climatic Parameters under Climate Change Status: A case study in Ardabil Synoptic Station. Iran-Watershed Management Science & Engineering, 13(45), pp. 63-70. Dor: ‎1001.1.20089554.1398.13.45.2.6
    (In Persian).

 

  • Hernández Vásquez, C.C., Ibáñez Castillo, L.A., Gómez Díaz, J.D. and Arteaga Ramírez, R., 2022. Analysis of meteorological droughts in the Sonora river basin, Mexico. Atmósfera, 35(3), pp.467-482. Doi: 20937/atm.52954

 

  • Hewitson, B. C., and Crane, R. G. 1996. Climate downscaling: techniques and application. Climate Research,7(2), pp.85-95.‏ doi: 10.3354/cr007085.

 

  • Hosseinabadi, S., Yaghoubzadeh, M., Amirabadizadeh, M, and Forouzanmehr, M. 2020. Assessment of meteorological drought in future periods using the data of the Fifth Climate Change Report (Case study: Zabol and Shiraz counties). Geographical Studies of Arid Areas. 10 (40), pp. 87-75. (In Persian)

 

  • Issaharou-Matchi, I., Rabiou, H., M Moussa, B., Soumana, I., Saley, K., Mahamane, A., and Saadou, M. 2021. Assessment of Drought Characteristics under Changing Climatic Conditions using SPI and SPEI Indices in Semi-Arid Environment of Southeastern Niger. International Journal of Environment and Climate Change.11(10), pp. 146-157.

 

  • 2007. The Physical Science Basis. In: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K., Tignor, M., Miller, H. (Eds.), Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge UK

 

  • 2014. The Physical Science Basis. In: Stocker, T.F., Qin, D., Plattner, G.K., Tignor, M., Allen, S.K., Boschung, J., Nauels, A., Xia, Y., Bex, V., Midgley, P.M. (Eds.), Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press Cambridge.

 

  • Javan, Kh. 2021. Investigation of hydrological drought trend in the catchment area of Lake Urmia. Hydrogeomorphology, 7(25), pp. 138-119. (In Persian)

 

  • Jafarzadeh, A., Pourreza-Bilondi, M., Akbarpour, A., Khashei-Siuki, A., and Samadi, S. 2021. Application of multi-model ensemble averaging techniques for groundwater simulation: synthetic and real-world case studies. Journal of Hydroinformatics, 23(6), pp. 1271-1289.‏

 

  • Keyantash, J., and Dracup, J. A. 2002. The quantification of drought: an evaluation of drought indices. Bulletin of the American Meteorological Society, 83(8), pp. 1167-1180.‏ doi: 10.1175/1520-0477-83.8.1167.

 

  • Liu, C., Yang, C., Yang, Q., and Wang, J. 2021. Spatiotemporal drought analysis by the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) in Sichuan Province, China. Scientific Reports, 11(1), pp. 1-14.‏ doi: 10.1038/s41598-020-80527-3.

 

  • McKee, T. B., Doesken, N. J, and Kleist, J. 1993. The relationship of drought frequency and duration to time scales. In Proceedings of the 8th Conference on Applied Climatology, 17(22), pp. 179-183.

 

  • Meresa, H., Murphy, C. and Fealy, R., 2021, April. Climate change impact on the hydrometeorological drought propagation. In EGU General Assembly Conference Abstracts(pp. EGU21-8285).

 

  • MesbahZadeh, T., Mirakbari, M., Mohseni Saravi, M., Khosravvi, H, and Mortezaie Farizhedi, Gh.2019. Study of Current and Future Meteorological Drought Conditions Using the CMIP5 Model under RCP Scenarios. Iran-Watershed Management Science & Engineering, 13(46), pp.11-22. Dor: 20.1001.1.20089554.1398.13.46.4.0 (In Persian)

 

  • Mishra, A. K., and Singh, V. P. 2010. A review of drought concepts. Journal of Hydrology, 391(1-20, pp. 202-216.‏

 

  • Nikbakht, J. and Hadeli, F., 2021. Comparison of SPI, RDI and SPEI indices for drought smonitoring under climate change conditions (Case study: Kermanshah station). Journal of Agricultural Meteorology, 9(1), pp.14-25. Doi: 10.22125/AGMJ.2021.249498.1103.

 

  • Noguera, I., Domínguez-Castro, F. and Vicente-Serrano, S.M., 2021. Flash drought response to precipitation and atmospheric evaporative demand in Spain. Atmosphere, 12(2), p.165.

 

  • Olagbaiye, A. E., Olasore, A., Ajayi, T. A., and Alabi, P. O. 2021. Drought Monitoring in Northern Nigeria Using Four (4) Indices. International Journal for Research in Applied Sciences and Biotechnology, 8(1), pp. 13-31. Doi: 10.31033/ijrasb.8.1.3.

 

  • Rahimi Bondarabadi, S., 2019. Evaluation of a dynamical downscaling climate model for assessment of climate change in Karkheh Basin. Watershed Engineering and Management, 11(3), pp.633-649. Doi: 10.22092/ijwmse.2019.118786. (In Persian)‏.

 

  • Rostamian, R., Eslamian, S. and Farzaneh, M. R., 2013, Application of standardised precipitation index for predicting meteorological drought intensity in Beheshtabad watershed, central Iran. Journal of Hydrology Science and Technology, 3(1), pp. 63-77. Doi: 10.1504/IJHST.2013.055233.

 

  • Saharwardi, M.S., Mahadeo, A.S. and Kumar, P., 2021. Understanding drought dynamics and variability over Bundelkhand region. Journal of Earth System Science, 130(3), p.122.

 

  • ‏ Shakarami, N, and Massahbavani, A. 2007. Uncertainty analysis of coupled ocean-atmosphere general circulation patterns on climate change scenarios of temperature and rainfall in Zainderood basin, technical workshop on the effects of climate change on water resources management. (In Persian).

 

  • Song, Y. H., Shahid, S., and Chung, E. S. 2021a. Differences in multi‐model ensembles of CMIP5 and CMIP6 projections for future droughts in South Korea. International Journal of Climatology.

 

  • Song, Z., Xia, J., She, D., Li, L., Hu, C., and Hong, S. 2021b. Assessment of meteorological drought change in the 21st century based on CMIP6 multi-model ensemble projections over mainland China. Journal of Hydrology, 601, pp. 126643.‏ doi: j.jhydrol.2021.126643.

 

  • Svoboda, M., LeComte, D., Hayes, M., Heim, R., Gleason, K., Angel, J., Rippey, B., Tinker, R., Palecki, M., Stooksbury, D., et al. 2002. The drought monitor. Bull Am Meteorol Soc. 83, pp.1181–1190. [CrossRef]

 

  • Tabatabaei, S. M., Nazeri Tahroudi, M, and Dastourani, M. 2018. Performance comparison of GP, ANN, BCSD and SVM models for temperature simulation. Journal of Meteorology and Atmospheric Sciences, 1(1), pp. 51-64. (In Persian)

 

  • Tsakiris, G., and Vangelis, H. J. E. W. 2005. Establishing a drought index incorporating evapotranspiration. European Water, 9(10), pp.3-11.‏

 

 

  • Van Pelt, S. C, and Swart, R. J. 2011. Climate change risk management in transnational river a. basins: the Rhine. Water resources management, 25(14), pp. 3837-3861.

 

  • Wang, T., Tu, X., Singh, V. P., Chen, X., and Lin, K. 2021. Global data assessment and analysis of drought characteristics based on CMIP6. Journal of Hydrology, 596, pp. 126091.‏ doi: 10.1016/j.jhydrol.2021.126091.

 

  • Wilhite, D. 2000. Drought as a natural hazard: Concepts and definitions. In Drought: A Global Assessment; Routledge: London, UK.

 

  • Wilhite, D. A., and Buchanan-Smith, M. 2005. Drought as hazard: understanding the natural and social context. Drought and Water Crises: Science, Technology, and Management Issues, 3, pp. 29.‏

 

  • Wilhite, D. A., Svoboda, M. D., and Hayes, M. J. 2007. Understanding the complex impacts of drought: A key to enhancing drought mitigation and preparedness. Water Resources Management, 21(5), pp. 763-774.

 

  • Wood, A.W., Maurer, E.P., Kumar, A. and Lettenmaier, D.P., 2002. Long‐range experimental hydrologic forecasting for the eastern United States. Journal of Geophysical Research: Atmospheres, 107(D20), pp.ACL-6.doi:10.1029/2001JD000659.

 

  • UNCCD.INT

 

  • Yaghoubzadeh, M., Ahmadi, M., Seyed Kaboli, H., Zamani,Gh, and Amirabadizadeh, M. 2017. Evaluation of the effect of climate change on agricultural drought using ETDI and SPI indicators. Journal of Soil and Water Conservation Research, 24(4), pp. 43-61. Doi: 22069/JWFST.2017.12202.2671. (In Persian)

 

  • Zareabyaneh, H., Ghabaeisoogh, M, and Mosaedi, A. 2016. Drought monitoring based on standardized precipitation-evapotranspiration index (SPEI) under the influence of climate change. Journal of Water and Soil, 29(2), pp. 392-374. Doi: 10.22067/JSW.V0I0.36472. (In Persian)

 

  • Zhang, G., Gan, T. Y., and Su, X. 2021. Twenty-First Century Drought Analysis across China using CMIP6 Under Climate Change.‏ Climate Dynamics,59(1), p. 1665-1685. Doi: 10.21203/rs.3.rs-206879/v1.

 

علوم و مهندسی آبیاری
دوره 46، شماره 3
آذر 1402
صفحه 69-84

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سابقه مقاله

  • تاریخ دریافت: 16 اسفند 1400
  • تاریخ بازنگری: 15 آذر 1401
  • تاریخ پذیرش: 19 آذر 1401
  • تاریخ انتشار: 01 آذر 1402

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