The effects of climate change on the drought trend of Varamin plain using De-Martonne index

Document Type : Original Article

Authors

1 Phd, Department of Civil engineering, Shahr-e-Qods Branch, Islamic Azad University, Tehran, Iran.

2 M.Sc, Department of Civil engineering, University of Tehran, Tehran, Iran.

3 M.Sc, Department of Civil engineering, University of Shahid Beheshti, Tehran, Iran.

4 Phd, Civil-Water Recourses management, Ab Sanat energy co Managing Director, Tehran, Iran,

10.30467/nivar.2021.266357.1177

Abstract

Increasing greenhouse gas concentrations can lead to global warming and climate change. In this study, the trend of changes in precipitation and temperature of Varamin synoptic station during the period from 2021 to 2050 AD was investigated using the CMIP5 data of the Fifth IPCC Assessment (AR5). One of the major limitations of using these models is their low spatial resolution, which does not match the accuracy required by hydrological models in terms of space and time. Therefore, downscaling method by LARS-WG model was used to overcome this limitation. Finally, temperature and precipitation data were simulated under two scenarios of RCP2.6 and RCP8.5 for the Future period and compared with the base period. Due to the effect of temperature and precipitation on the future drought status of the plain, De-Martonne drought index was determined under two scenarios of climate change and compared with the base period. The results of the study showed the significant effects of climate change on the aggravation of conditions in the region and consequently a -1/3 degree of centigrade increase in temperature and change in precipitation pattern and changes in drought index. According to the obtained results, it can be stated that although the drought trend is affected by several factors, but in the shadow of possible climate change in the future there is a possibility of increasing the drought trend in Varamin plain, due to changes in rainfall and rising temperatures, so that both climate scenarios also predicted a drought condition for the study area.

Keywords

References

1. آقاخانی افشار، ا.، ی.، حسن زاده، ع.، بسالت‌پور، م.، پوررضا بیلندی،  1395، ارزیابی سالیانه مؤلفه‌های اقلیمی حوضه آبخیز کشف‌رود در دوره‌های آتی با استفاده از گزارش پنجم هیات بین‌الدول تغییر اقلیم، مجله پژوهش‌های حفاظت آب و خاک، دوره 23، شماره 6، صفحات 233-217.
2. شهوری، ن.، ص.، خلیلیان، س.ح.، موسوی، س.ا.، مرتضوی، 1398، بررسی اثرات تغییراقلیم بر منابع آب حوضه دشت ورامین با استفاده از مدلSWAT، نشریه آبیاری و زهکشی ایران، دوره 13، شماره 2، صفحات  366-354.
3. قربانی، خ.، ا.، سهرابیان، م.، سالاری جزی، م.، عبدالحسینی، 1395، پیش‌بینی اثر تغییراقلیم بر روند دبی ماهانه رودخانه با بکار بردن مدل هیدرولوژیکی (IHACRES) (مطالعه موردی: حوضه آبریز گالیکش)، نشریه حفاظت منابع آب و خاک، دوره 5، شماره 4، صفحات 20-33.
4. عزیزی، ح.، ح.، ابراهیمی، ح.، محمد ولی سامانی، و.، خاکی، 1399، ارزیابی شدت اثر تغییراقلیم بر منابع آب زیرزمینی دشت ورامین با استفاده از شاخص NISTOR، تحقیقات منابع آب ایران، دوره 16، شماره3، صفحات 174-189.
5. فراهانی، م.، آنا.، راسخی، پ.، بهنام، ع.، کشوری، 1397، بررسی اثرات تغییراقلیم بر دما، بارش و خشکسالی‌های دوره آتی حوضه شادگان، تحقیقات منابع آب ایران، دوره 14، شماره3، صفحات 125-139.
6. Amani, Z., R. Deihimfard, and E. Makhtasi Bidgli, 2016. Evaluation of drought under increasing of temperature due to climate change in rain fed wheat-growing areas of Fars province using Aridity Index, Electronic Journal of crop production, 9(2): 151-174.
7. Binesh, N., M.H. Niksokhan, and A. Sarang, 2018. Analysis of Climate Change Impact on Extreme Rainfall Events in the West Flood-Diversion catchment of Tehran, Journal of Watershed Management Research, 9(17): 226-234.
8. De Martonne, E. 1926. A new climatological function: The Aridity Index Gauthier-Villars, Paris, France.
9. Deniz, A., H. Toros, and S. Incecik, 2011. Spatial variations of climate indices in Turkey, International Journal of Climatology, 31:394-403.
10. Hooshmand, D., and M.j. Khordadi, 2014. Uncertainty Assessment of AOGCMs and Emission Scenarios in Climatic Parameters Estimation (Case Study: Mashhad Synoptic Station), Geography and Environmental Hazards, 3(11): 77-92.
11. IPCC. Summary for Policymakers, 2013, In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change.
12. Najafi, M.R., and S. Moazami, 2015, Trends in total precipitation and magnitude–frequency of extreme precipitation in Iran, 1969-2009, Int. J. Climatol, 36(4): 1863-1877.
13. Poormohammadi, S., and H. Malekinezhad, 2013. Classification of Homogeneous Climatic Regions under the Impact of Climate Change and Greenhouse Gas Emissions Scenarios Using L-Moments Technique in Iran, Journal of Watershed Management Research, 4(8): 58-76.
14. Rasco, P., L. Szeidl, and M.A. Semenov, 1991. A serial approach to local stochastic models, J.  Ecological Modeling, 57: 27-41.
15. Semenov, M.A., and R.J. Brooks, 1999. Spatial interpolation of the LARS-WG stochastic weather generator in Great Britain, Climate Research, 11: 137-148.
16. Semenov, M.A., and E.M. Barrow, 2002. LARS-WG a stochastic weather generator for use in climate impact studies, User’s manual, Version3.0.
17. Semenov, M.A., and P. Stratonovitch, 2010. Use of multi-model ensembles from global climate models for assessment of climate change impacts. http://www.int-res. com /articles /cr_oa / c041p001.pdf
18. Stocker, T.F., D. Qin, G.K. Plattner, M. Tignor, S.K. Allen, J. Boschung, D.E. Vasconcellos, and V. Menezes, 2013. The physical science basis, working group contribution to the fifth assessment report of the intergovernmental panel on climate change-abstract for decision-makers. Groupe d'experts intergouvernemental sur l'evolution du climat/Intergovernmental Panel on Climate Change-IPCC, C/O World Meteorological Organization, 7bis Avenue de la Paix, CP 2300 CH-1211 Geneva 2 (Switzerland).
19. Wilby, R.L., and I.A. Harris, 2006. Frame work for assessing uncertainties in climate change impacts: low flow scenarios for the River Thames, UK. Water Resources Research, 42, W02419, DOI: 10.1029/2005WR004065.
20. Woldemeskel, F.M., A. Sharma, B. Sivakumar, and R.  Mehrotra, 2015. Quantification of precipitation and temperature uncertainties simulated by CMIP3 and CMIP5 models. J. Geophysic, Res. Atm, 121(1): 3-17.
21. Xu, C.H. and Y. Xu, 2012. The Projection of Temperature and Precipitation over China under RCP Scenarios using a CMIP5 Multi-Model Ensemble, Atmospheric and Oceanic Science Letters, 5(6): 527-533.
22. Zarezade Mehrizi, SH., A. Khoorani, J. Bazrafshan, and O. Bazrafshan, 2018. Assessment of future runoff trends under multiple climate change scenarios in the Gamasiab river basin, Iranian Journal of Ecohydrology, 5(3): 777-789.

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History

  • Receive Date: 07 January 2021
  • Revise Date: 17 March 2021
  • Accept Date: 03 April 2021
  • First Publish Date: 03 April 2021

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