Impacts of climate change on rainfall indices estimation in western sub-basins of Iran

Document Type : Research Paper

Author

Assistant Professor of Watershed Department, Hamedan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Hamedan, Iran

Abstract

The purpose of this study was to document changes in indices simulated by the ensemble application of Coupled Model Inter-comparison Project CMIP5 and CMIP3 when analyzing impacts of climate change on catchment rainfall indices in sub-basins of Hamedan province, west of Iran. The analysis of the precipitation indices consisted of simple rainfall intensity, very heavy rainfall days, maximum one-day rainfall, and rainfall frequency. I investigated the relative change in three rainfall indices based on general circulation models (GCMs) under a mixture of greenhouse gas emission scenarios A1B and B1, RCP8.5 and RCP8.5 for two future periods 2020–2045 and 2045-2065. Results showed that each of the rainfall indices differed in stations under the three GCMs models (GIAOM, MIHR, MPEH5) and emission scenarios A1B, B1, RCP2.5, and RCP8.5. Relative 50y change  for future periods 2046–2065 varied from -9.93% to 25% for daily intensity index, from 20.71% to 25.9% for very heavy rainfall days and from -15.71% to 13% for annual rainfall depth in the study area. Rainfall indices projection of sum of wet days, days>1mm, and maximum one-day rainfall showed decrease under the scenarios B1 and A1B and also sum of wet days, simple daily intensity, and heavy rainfall days>10 decreased under the RCP2.6.

Keywords

References

Albert, M.G., Klein Tank, Francis, Zwiers, W., and Xuebin Zhang, 2009 nalysis of extremes in a changing climate in support of informed decisions for adaptation. Climate Data and Monitoring, World Meteorological Organization. WCDMP-No. 72.
Andreas, H., Fahad, S., and Daniela, J, 2013. Assessing the robustness of projected precipitation changes over central Africa based on a multitude of global and regional climate projections. Climatic Change, DOI 10.1007/s10584-013-0863-8.
Ahmadi, L., Moridi, A., and Kakaei, E. 2014–A case study. Journal of Earth System Science Volume 123. The Effects of Climate Change on Extreme Rainfall Events in the Upper Thames River Basin: A Comparison of Downscaling Approaches.
Babaian. A. 2009. studied climate change impact in Iran in 2010-2039 with downscaling GCM model of ECO-G data. Journal of geography, 16: 135-152.
Beijing, China Wilby RL, Harris I. 2006. A framework for assessing uncertainties       in climate change impacts: low-flow scenarios for the River Thames, UK. Water Resources Research 42, W02419.DOI:10.1029/2005WR004065.
Botao, Z., Qiuzi, H., Ying, X., and Lianchun, S., Xuebin, Z, 2014. Projected Changes in Temperature and Precipitation Extremes in China by the CMIP5 Multi-model Ensembles. American Meteorological Society, 27, 6591-6611.
Brown, P.J., Bradley, R.S., and Keimig, F.T. 2010. Changes in extreme climate indices for the northeastern United States. Journal of Climate, 23(24), 6555-6572.
Chen, H.P. 2013: Projected change in extreme rainfall events in China by the end of the 21st century using CMIP5 models, Chinies Science Bulltin, 58, 1462–1472.
Chen, J., Brissette, F.P., and Leconte, R. 2011. Uncertainty of the downscaling method in quantifying the impact of climate change on hydrology. Journal of Hydrology, 401(3–4), 192–202. DOI: 10.1016/j.jhydrol.2011.02.020.
Chen, S.T., Yu, P.S., and Tang, Y.H. 2010. Statistical downscaling of daily rainfall using support vector machines and multivariate analysis. Journal of Hydrology, 385, 13-22.
Chen, X.C., Y., Xu, C.H., Xu, et al. 2014. Assessment of precipitation simulations in China by CMIP5 multi-model, Advanced Climate Change Research, 10(3), 217–225.
Dong, S.Y., Xu, Y., and B.T. Zhou, et al. 2014: Projected risk of extreme heat in China based on CMIP5 models, Advanced Climate Change Research,10(5), 365–369.
Eemenov, M.A., and Brooks, R.J. 1999. Spatial interpolation of the LARS-WG stochastic weather generator in Great Britain. Climate Research, 11, 137–148.
Eum, H. I., and Simonovic, S.P. 2012. Assessment of variability of extreme climate events for the Upper Thames Basin in Canada. Hydrological Processes, 26, 485-499.
Fahad Saeed, Andreas Haensler, Torsten Weber, Stefan Hagemann and Daniela J. 2013. Representation of Extreme Precipitation Events Leading to Opposite Climate Change Signals over the Congo Basin. Atmosphere, 4, 254-271.
Fowler, H.J., and Kilsby, C.G. 2003. extreme rainfall. Geophysical Research Letters Vol. 30, No. 13, 1720, DOI: 10.1029 2003 GL 017327, 2003. Implications of changes in seasonal and annual.
Hashmi, M.Z., Shamseldin, A.Y., and Melville, B.W. 2011. Comparison of SDSM and LARS-WG for simulation and downscaling of extreme rainfall events in a watershed. Stochastic Environmental Research and Risk Assessment, 25, 475-484.
Hu, Y., Maskey, S., and Uhlenbrook, S. 2012. Trends in temperature and rainfall extremes in the Yellow River source region, China. Climatic Change, 110, 403-429.
IPCC, Intergovernmental Panel on Climate Change, 2007. Fourth Assessment Report, Climate Change.
Jeong, D.I., St-Hilaire, A.T., Ouarda, B.M.J., and Gachon, P. 2012. CGCM3 predictors used for daily temperature and rainfall downscaling in Southern Que ´bec, Canada. Theoretical and Applied Climatology, 107, 389-406.
Jie Chen, François P., and Brissette, 2011. Uncertainty of the downscaling method in quantifying the impact of climate change on hydrology Journal of Hydrology, 401,190–202.
Jones, P.D., and Reid, P.A. 2001. Assessing future changes in extreme rainfall over Britain using regional climate model integrations. International Journal of Climatology, 21, 1337–1356. DOI:  10.1002/ joc.677.
Kay, A. L., Davies, H.N., Bell, V.A., and Jones, R.G. 2009. Comparison of uncertainty sources for climate change impacts: flood frequency in England.
Khan, M.S., Coulibaly, P., and Dibike, Y. 2006. Uncertainty analysis of statistical downscaling methods. Journal of Hydrology, 319, 357–382.
Leanna, M.M. King, Sarah Irwin, Rubaiyaarwar. 2014.Assessment of climate change impacts on rainfall using large scale climate variables and downscaling. Canadian Water Resources Journal / Revue Canadienne des Ressource shydriques, 37, 3, 253-274.
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.
Massahbavani, A., and Sadatashofteh, P. 2010. Impact of climate change on maximum discharges: Case study: Aidoghmoosh watershed, East Azerbaijan, ran. Iranian Journal of Agricultural Science and Technology and Natural Resources, 53, 25-39.
Manville, 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.
Mary W. 2004. Simulation of the variability and extremes of daily rainfall during the Indian summer monsoon for present and future times in a global time-slice experiment. Climate Dynamics, 22, 183–204.
Nazaripouya, H., Kardavany P., and Faraji, A. 2016. Assessing Climate Change Impacts on   Hydro-Climatic Parameters in the Dam Basin of Ekbatan, Hamedan. Iranian Journal of Ecohydrology. 3, 181-194.
Pourtouiserkani, A., and Rakhshandehroo, H. 2014. Investigating climate change impact on extreme rainfall events Case study:  Chenar-R basin, Fars, Iran. Scientia Iranica, 21(3), 525-533.
Schoof, J.T. 2012. Scale issues in the development of future rainfall scenarios. Journal of Contemporary Water Research and Education, 147, 8-16.
Semenov, M.A. 2008. Simulation of extreme weather events by a stochastic weather generator. Climate Research, 35, 203–212.
Semenov, M.A., and Stratonovitch, P. 2010. Use of multi-model ensembles from global climate models for assessment of climate change impacts. Climate Research, 40(1), 1–14.
Semenov, M.A., Brooks, R.J., Barrow, E.M., and Richardson, C.W. 1998. Comparison of the WGEN and LARS-WG stochastic weather generators in diverse climates. Climate Research, 10, 95–107.
Seree, S. 2015. Studied assessment of CMIP3-CMIP5 climate model precipitation projection and implication of flood vulnerability of Bangkok. American Journal of Climate Change, 4, 140-162.
Solaiman, T., King, L., and Simonovic, S.P. 2010. Extreme rainfall vulnerability in the Upper Thames River basin: Uncertainty in climate model projections. International Journal of Climatology, 31, 2350-2364.
Tomozeiu, R., Cacciamani, C., Pavan, V., Morgillo, A., and Busuioc, A. 2007. Climate change scenarios for surface temperature in Emilia-Romagna (Italy) obtained using statistical downscaling models. Theoretical and Applied Climatology, 90, 25-47.
Von Stoch, H., Zorita, E., and Cubasch, U. 1993. Downscaling of global climate change estimates to regional scales: an application to Iberian rainfall in wintertime. Journal of Climate 6, 1161–1171.
Wetterhall, F., Halldin, S., and Xu, C.-Y. 2007. Seasonality properties off statistical-downscaling methods in central Sweden. Theoretical and Applied Climatology, 87, 123-137.
Wilks, D.S. 2010. Use of stochastic weather generators for rainfall downscaling. Wiley Interdisciplinary Reviews Climate Change, 1(6), 898–907.
Wilks, D.S. 1999. Multisite downscaling of daily rainfall with a stochastic weather generator. Climate Research, 11, 125–136.
Wilks, D.S. 2010. Use of stochastic weather generator for rainfall downscaling. Climate Change,1, 898–907.
Xu, C., Shen, X., and Xu, Y. 2007. An analysis of climate change in East Asia by using the IPCC AR4 simulations. Advances in Climate Change Research, 3(5), 287–292 (In Chinese).
Xu, Ying, Wu, Jie, Shi Ying, Zhou Bo-Tao, Li Rou-Ke and Wu, Jia 2015. Change in extreme Climate Events over China Based on CMIP5, Atmospheric and Oceanic Science Letters, 8, 4, 185-192.
Environmental Resources Research
Volume 7, Issue 2
January 2019
Pages 87-104

Files

Share

How to cite

Statistics