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کد مقاله : JEST-1812-4508 (R4) بازدید : 172 صفحه: 31 - 42

10.22034/jest.2021.40667.4508

نوع مقاله: پژوهشی

اثر تغییر اقلیم بر بارش‌های حدی مناطق خشک ایران

محورهای موضوعی : مدیریت منابع آب

محمد رضا خزائی 1 , حدیث خزائی 2 , بهرام ثقفیان 3

1 - استادیار، گروه مهندسی عمران، دانشگاه پیام نور، ایران.*(مسوول مکاتبات)
2 - دانشکده فنی مهندسی، واحد علوم و تحقیقات تهران، دانشگاه آزاد اسلامی، تهران، ایران.
3 - استاد، دانشکده فنی مهندسی، واحد علوم و تحقیقات تهران، دانشگاه آزاد اسلامی، تهران، ایران.

تاریخ دریافت : 1397/09/13 تاریخ پذیرش : 1397/12/25 تاریخ انتشار : 1399/09/01

کلید واژه: خشک, تغییر اقلیم, بارش, ریزمقیاس نمایی, بارش حدی,

چکیده مقاله :

زمینه و هدف: یکی از آثار مهم تغییر اقلیم، تغییر رژیم بارش های حدی در آینده است که پیش بینی آن برای اتخاذ تدابیر مقابله با آثار زیانبار تغییر اقلیم ضروری است. در این مقاله اثر تغییراقلیم بر بارش های روزانه حداکثر سالانه در مناطق خشک ایران ارزیابی شده است. روش بررسی: سناریوهای آینده توسط مدل NSRP ریزمقیاس شد. سری های طولانی مدت بارش روزانه برای اقلیم فعلی و سناریوهای آینده تولید شد و با مقایسه توزیع فراوانی بارش های حدی روزانه دوره تاریخی و سناریوهای آینده، اثر تغییر اقلیم بر بارش های حدی در مناطق خشک ایران ارزیابی شد. روش ریزمقیاس نمایی به گونه ای است که دامنه وسیعی از ویژگی های سناریوهای بزرگ مقیاس به سناریوهای ریزمقیاس شده منتقل شده است. ایستگاه های مورد مطالعه، ایستگاه های سینوپتیک بم، زاهدان، مهرآباد تهران و یزد به عنوان نمایندگان مناطق خشک ایران انتخاب گردید. یافته ها: نتایج اعتبارسنجی نشان داد عملکرد روش مورد استفاده برای شبیه سازی سری بارش روزانه و توزیع بارش های حدی مناسب است. در اغلب ایستگاه ها و تحت سناریوهای مختلف انتشار، شدت بارش های حدی روزانه در آینده افزایش خواهد یافت. این در حالی است که بارش سالانه در آینده کاهش می یابد. به عنوان نمونه در یزد انتظار می رود بارش های حدی 50 ساله بین 14 تا 58 درصد افزایش یابد، اما تغییر میانگین بارش سالانه بین 3% افزایش تا 20% کاهش باشد. بحث و نتیجه گیری: این نتایج بیانگر افزایش وخامت شرایط بارش در مناطق خشک ایران در آینده است. لذا انجام مطالعات وسیع تر و در نظر گرفتن اقدامات پیش گیرانه برای کاهش خسارات تغییر اقلیم آینده دراین مناطق ضروری است.

چکیده انگلیسی:

Background and Objective: One of the major impacts on climate changes is change in extreme precipitation regime in the future, which have to be predicted to counteract the harmful effects of climate change. In this paper, climate change impact is assessed on extreme rainfalls in arid regions of Iran. Method: Future scenarios are downscaled using the NSRP model. Long-term daily rainfall series are generated for current climate and future scenarios. By comparing the distribution of extreme daily rainfalls for current and future conditions, the impacts of climate change on extreme rainfalls are assessed. In downscaling method, a wide range of statistics of large-scale scenarios has been transferred to downscaled scenarios. The understudying stations are in Bam, Zahedan, Tehran and Yazd synoptic stations as representatives of the arid regions of Iran. Findings: Validation results indicate that the performance of this method in simulating daily rainfall series and distribution of extreme rainfall is acceptable. Results for most of stations and scenarios show that intensity of extreme daily rainfalls will increase in the future while average rainfall will decrease. As instance, in Yazd, extreme rainfall of 50 years return period would increase between 14 to 58 percent, while the average precipitation will change between +3 to -20 percent. Discussion and Conclusion: These results indicate that the precipitation situation in arid areas of Iran will worsen in the future. Therefore, more extensive investments and taking preventive activities to adapt to climate change is essential.

منابع و مأخذ:


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  6. Holman, I.P., Tascone, D., Hess, T.M., 2009. A comparison of stochastic and deterministic methods for  modelling potential groundwater recharge under climate change in East Anglia, UK: implications for groundwater resource management. Hydrogeology Journal, 17, pp.1629-1641.
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_||_

  1. IPCC 2001. Climate change 2001. Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the third assessment report of the Intergovernmental Panel on Climate Change. UK: Cambridge University Press.
    2.
  2. IPCC. 2012. Summary for Policymakers. In: Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK, and New York, NY, USA, 1-19

    1. Tryhorn, L., DeGaetano, A., 2011. A comparison of techniques for downscaling extreme precipitation over the Northeastern United States. International Journal of Climatology, vol. 31, pp. 1975-1989.
      2.
    2. Asgari, A., Rahimzade, F., Mohammadian, N., Fattah, E., 2008. Terend Analysis of Extreme Precipitation Indices Over Iran. Iran-Water Resources Research, vol. 3(3), pp. 42-55 (In Persian)
      3.
    3. Arnbjerg-Nielsen, K., 2006. Significant climate change of extreme rainfall in Denmark. Water Sci. Technol. 54 (6–7), pp. 1–8.
      4.
    4. Zhai, P., Zhang, X., Wan, H., Pan, X., 2005. Trends in total precipitation and frequency of daily precipitation extremes over China. J. Climate, 18, pp. 1096–1108.
      5.
    5. Agilan, V., Umamahesh, N.V., 2016. Is the covariate based non-stationary rainfall IDF curve capable of encompassing future rainfall changes? Journal of Hydrology, 541, pp. 1441-1455.
      6.
    6. Cheng, L., AghaKouchak, A., 2014. Nonstationary Precipitation Intensity-Duration-Frequency Curves for Infrastructure Design in a Changing Climate. Scientific Reports, 4, pp. 7093 (1-6)
      7.
    7. Tfwala, C.M., Rensburg, L.D., Schall, R., Mosia, S.M., Dlamini, P., 2017. Precipitation intensity-duration-frequency curves and their uncertainties for Ghaap plateau. Climate Risk Management, 16, pp. 1–9.
      8.
    8. Khazaei, M.R., Khazaei, H., 2018. Scenarios In Climate Change Impact Assessment on Monthly Stream-flow of Karun Basin. Journal of Environmental Science and Technology, 20(1), pp. 29-40 (In Persian)
      9.
    9. Khazaei, M.R., Zahabiyoun, B., Saghafian, B., 2012. Assessment of climate change impact on floods using weather generator and continuous rainfall-runoff model. International Journal of Climatology, vol. 32(13), pp. 1997- 2006
      10.
    10. Khazaei, M.R., Ahmadi, S., Saghafian, B., Zahabiyoun, B., 2013. A new daily weather generator to preserve extremes and low-frequency variability. Climatic Change, 119, pp. 631-645
      11.

  3. Prudhomme, C., Reynard, N., Crooks, S., 2002. Downscaling of global climate models for flood frequency analysis: where are we now?. Hydrological Processes, vol. 16, pp. 1137-1150
    4.
  4. Reynard, NS., Prudhomme, C., Crooks, SM., 2001. The flood characteristics of large UK Rivers: Potential effects of changing climate and land use. Climatic Change, vol. 48, pp. 343-359

    1. Pourtouiserkani, A., Rakhshandehroo, Gh., 2014. Investigating climate change impact on extreme rainfall events, Case study: Chenar-Rahdar basin, Fars, Iran. Scientia Iranica, A, vol. 21, pp. 525-533
      2.
    2. Liu, Z., Xu, Z., Charles, SP., Fu, G., Liu, L., 2011. Evaluation of two statistical downscaling models for daily precipitation over an arid basin in China. International Journal of Climatology, vol. 31, pp. 2006-2020
      3.
    3. Yang, T., Li, H., Wang, W., YuXu, H., Yu, Z., 2012. Statistical downscaling of extreme daily precipitation, evaporation, and temperature and construction of future scenarios. Hydrological Processes, vol. 26, pp. 3510–3523
      4.
    4. Semenov, MA., 2007. Development of high-resolution UKCIP02-based climate change scenarios in the UK. Agricultural and Forest Meteorology, vol. 144, pp. 127-138
      5.
    5. Kilsby, CG., Jones, PD., Burton, A., Ford, AC., Fowler, HJ., Harpham, C., James, P., Smith, A., Wilby, RL., 2007. A daily weather generator for use in climate change studies. Environmental Modelling and Software, vol. 22, pp. 1705–1719
      6.
    6. Fowler, HJ., Blenkinsop, S., Tebaldi, C., 2007. Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling. International Journal of Climatology, vol. 27, pp. 1547-1578
      7.
    7. Kilsby, CG., Burton, A., Birkinshaw, SJ., Hashemi, AM., O’connell, PE., 2000. Extreme rainfall and flood frequency distribution modelling for present and future climates Proceedings of the British Hydrological Society. 7th National Hydrology Symposium, University of Newcastle upon Tyne, British Hydrological Society
      8.
    8. Cowpertwait, P.S.P., Kilsby, C.G., O’Connell, P.E., 2002. A space-time Neyman-Scott model of rainfall: Empirical analysis of extremes. Water Resour Res 38(8), pp. 1131 (1-14).
      9.

  5. Burton, A., Kilsby, CG., Fowler, HJ., Cowpertwait, PSP., O'connell, PE., 2008. RainSim: A spatial-temporal stochastic rainfall modelling system. Environmental Modelling & Software, 23, pp. 1356-1369
    6.
  6. Holman, I.P., Tascone, D., Hess, T.M., 2009. A comparison of stochastic and deterministic methods for  modelling potential groundwater recharge under climate change in East Anglia, UK: implications for groundwater resource management. Hydrogeology Journal, 17, pp.1629-1641.
    7.
  7. Reynard, N.S., Prudhomme, C., Crooks, S.M., 2001. The flood characteristics of large UK Rivers: Potential effects of changing climate and land use. Climatic Change, 48, pp. 343-359.
    8.



 

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