Uncertainty of annual maximum daily rainfall under greenhouse gases emission scenarios in 2040: Khorasan-Razavi province

Document Type : Research Article

Author

Department of civil engineering, Jundishapur University of Technology, Ahvaz, Iran

Abstract

Nowadays, increasing of greenhouse gases emissionscussed by human activities is the main factor of climate change. Global warming has also changed the frequency of extreme rainfall events in many areas. This research presents an analysis of how the change in the frequency of maximum daily rainfall under three emission scenarios in 2021-2040 periods in the Khorasan-Razavi province. The maximum daily rainfall series areprojected for the future periods in the 23 weather stations by developing a nonparametric downscaling model for arid and semi-arid regions. The uncertainty of climate change scenarios is quantified using a simple parametric uncertainty estimator in the three risk levels (25%, 50% and 75%) for each of emission scenarios. The frequency analysis of maximum series showsthat the daily rainfall intensitiesin therisk level 2 will be changed between -22.9% to +20.3% than baseline (1993-2012), that a wider range of these changes is related to thelonger return periods. Generally, central and southern regions will be received slight increase than northern regions. The rainfall intensities in more areas decrease with theincreasein greenhouse gases emissions that this decreasewill be more for the rainfalls with lower return periods. Flooding in the high rainfall regions will be also occurred withseverity while the low rainfall regions get a more decrease. Maximum daily rainfall will be increased in the future periods by reducing the level of risk; it can be warning to design hydraulic infrastructures with high emphasis.
 
 

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[1] سیدکابلی، حسام؛ آخوندعلی، محمدعلی؛ مساح بوانی،علیرضا و رادمنش، فریدون، 1391. «ارائۀ مدل ریز‌مقیاس نمایی داده‌های اقلیمی براساس روش ناپارامتریک نزدیک‌ترین همسایگی (KNN)». نشریۀ آب و خاک، 26(4): 1063-799.
[2] Abbaspour, K.C., Faramarzi, M., Ghasemi, S.S. and Yang, H., 2009. Assessing the impact ofclimate change on water resources in Iran. Water Resources Research 45, W10434.
[3] Beniston M., Stephenson, D. B., Christensen, O. B., Ferro, C. A. T., Frei, C., Goyette, S., Halsnaes, K., Holt, T., Jylhä, K., Koffi, B., Palutikof, J., Schöll, R., Semmler, T. and Woth, K., 2007. Future extreme events in European climate: an exploration of regional climate model projections. Climatic Change 81(s.1): 71-95.
[4] Brissette, F., Leconte, R. and Khalili, M., 2007. Efficient stochastic generation of multi-site synthetic precipitation data. Journal of Hydrology, 345,121-133.
[5] Buytaert, W., Ce´lleri, R. and Timbe, L., 2009. Predicting climate change impacts on water resources in the tropical Andes: Effects of GCM uncertainty, Geophysical Research Letters, 36, L07406, doi:10.1029/2008GL037048.
[6] Emori, S., and Brown, S. J., 2005. Dynamic and thermodynamic changes in mean and extreme precipitation under changed climate. Geophys. Res. Lett., 32, L17706.
[7] Fowler, H. J., Ekström, M., Blenkinsop, S. and Smith, A. P., 2007. Estimating change in extreme European precipitation using a multimodel ensemble. J. Geophys. Res., 112, D18104.
[8] Frich, P., Alexander, L.V., Della-Marta, P., Gleason, B., Haylock, M., Klein Tank, A. M.G. and Peterson, T., 2002. Observed coherent changes in climatic extremes during the second half of the twentieth century. Climate Research 19, 193–212.
[9] Goyal M. K., Burn, D. H. and C.S.P.Ojha, 2012. Precipitation Simulation based on k-Nearest Neighbour Approach using Gamma Kernel. ASCE Journal of Hydrologic Engineering, doi:10.1061/(ASCE)HE.1943-5584.0000615.
[10] Helfer F., Lemckert C., and Zhang H., 2012. Impacts of climate change on temperature and evaporation from a large reservoir in Australia. Journal of Hydrology, 475: 365–378.
[11] Intergovernmental Panel on Climate Change (IPCC) 2007. Climate change 2007: The physical science basis—Summary for policy makers.Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Intergovernmental Panel on Climate Change, Geneva.
[12] Kharin, V. V., Zwiers, F. W., Zhang, X. and Hegerl, G. C., 2007.Changes in temperature and precipitation extremes in the IPCCensemble of global coupled model simulations. J. Clim., 20, 1419–1444.
[13] Krishnamurthy, S.K.B., Lall, U. and Kwon, H., 2009. Changing Frequency and Intensity of Rainfall Extremes over India from 1951 to 2003. Journal of Climate (22), 4737-4746, DOI: 10.1175/2009JCLI2896.1.
[14] Mailhot, A., Duchesne, S., Caya, D. and Talbot, G., 2007. Assessment of future change in intensity-duration-frequency (IDF) curves for southern Quebec using the Canadian Regional Climate Model (CRCM). Journal of Hydrology 347, 197-210.
[15] Minville M., Brissette F. and Leconte R. 2008. Uncertainty of the impact of climate change on the hydrology of a Nordic watershed. Journal of Hydrology, 358: 70-83
[16] Prodanovic P. 2008. Response of Water Resources Systems to Climate Change. Ph.D. dissertations, Department of Civil and Environmental Engineering, The University of Western Ontario, London, Ontario, Canada. 356pp.
[17] Prudhomme, C., Jakob, D. and Svensson C., 2003. Uncertainty and climate change impact on the flood regime of small UK catchments, Journal of Hydrology, 277, 1 – 23.
[18] Sharif, M. and Burn, D.H., 2006. Simulating climate change scenarios using an improved K-nearst neighbor model. Journal of Hydrology 325,179-196.
[19] SolaimanT.A. and Simonovic, S. P., 2011a. Quantifying Uncertainties in the Modelled Estimates of Extreme Precipitation Events at Upper Thames River Basin. Water Resources Research Report no. 067, Facility for Intelligent Decision Support, Department of Civil and Environmental Engineering, London, Ontario, Canada, 64 pages.
[20] SolaimanT.A., Simonovic, S. P., 2011b. Development of Probability Based Intensity-Duration-Frequency Curves under Climate Change. Water Resources Research Report no. 072, Facility for Intelligent Decision Support, Department of Civil and Environmental Engineering, London, Ontario, Canada, 94 pages. ISSN: (print) 1913-3200; (online) 1913-3219.
[21] Stainforth, D. A., Downing, T. E., Lopez, R. W. A. and New, M., 2007. Issues in the interpretation of climate model ensembles to inform decisions, Philos. Trans. R. Soc., Ser. A, 365, 2163–2177.
[22] Tank, A.K., Wijngaard, J. and van Engelen, A., 2002. Climate of Europe. Assessment of observed daily temperature and precipitation extremes. European Climate Assessment. De Bilt, The Netherlands. ISBN 90-396- 2208-9.
[23] ToewsM.W. and Allen D.M., 2009. Evaluating different GCMs for predicting spatial recharge in an irrigated arid region. Journal of Hydrology, 374: 265-281
[24] Tolika K., Anagnostopoulou C., Maheras P. and Vafiadis M. 2008. Simulation of future changes in extreme rainfall and temperature conditions over the Greek area: A comparison of two statistical downscaling approaches. Global and Planetary change, 63, 132-151.
[25] Yi Zheng, Y., Wanga, W., Han, F. and Ping,J., 2001. Uncertainty assessment for watershed water quality modeling: A Probabilistic Collocation Method based approach. Advances in Water Resources, 34, 887-898.
 
Volume 2, Issue 4
January 2016
Pages 455-465
  • Receive Date: 17 September 2015
  • Revise Date: 25 February 2016
  • Accept Date: 25 February 2016
  • First Publish Date: 25 February 2016
  • Publish Date: 22 December 2015