Estimation of Probable Maximum Precipitation under Climate Change in Parsian Basin

Document Type : Research Paper

Authors

1 PhD student of Climatology, Department of Geography, Najafabad Branch, Islamic Azad University, Najafabad, Iran.

2 Associate Professor, Department of Geography, Najafabad Branch, Islamic Azad University, Najafabad, Iran

3 Associate Professor, Department of Hydrology and Water Resources, Faculty of Water and Environmental Engineering, Shahid Chamran University of Ahvaz. Iran.

4 Assistant Professor, Department of Geography, Najafabad Branch, Islamic Azad University, Najafabad, Iran.

Abstract

Climate change caused by global warming has altered temporal-spatial distribution as well as rate and form of precipitation, the magnitude of floods, annual precipitation ​​in rivers, seasonal variation of probable maximum precipitation and flood, water quality, evaporation rate, concentrations of nutrients in aquifers, etc. the Atmosphere-Ocean Coupled General Circulation Model (AOGCM) is currently the most reliable tool to study the effects of climate change on different systems. This model simulates climate parameters. Estimation of probable maximum precipitation (PMP) is an important and practical research method that not only identifies behavior of extreme rainfall in climatology, but also helps hydrologists to design various large water control structures, especially dams. Climate change affects PMP in the coming periods. Consequently, PMP estimates will be modified by hydrologists.

Keywords

Main Subjects


  • Alizadeh, A. 2002. Principles of Applied Hydrology, Fourteenth Printing, Ghods Province Publishing (In Persian).

 

  • Chen, X., Hossain, F. and Leung, L.R., 2017. Probable maximum precipitation in the US Pacific Northwest in a changing climate. Water Resources Research, 53(11), pp.9600-9622.

 

  • Daryabari, S.J. Mohammadi, H. and Rezaei, Gh., 2012. Spatial analysis of probable maximum precipitation (PMP) in Iran. Quartelry Geographical Journal Territory (Sarzamin), 9(34), pp:113-124 (In Persian).

 

  • Donner, L.J., Wyman, B.L., Hemler, R.S., Horowitz, L.W., Ming, Y., Zhao, M., 2011. The dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component AM3 of the GFDL global coupled model CM3. Journal of Climate, 24(13).

 

  • Dufresne, J.L., Foujols, M.A., Denvil, S., Caubel, A., Marti, O., Aumont, O., 2013. Climate change projections using the IPSL-CM5 Earth System Model: from CMIP3 to CMIP5. Climate Dynamics, 40(9–10).

 

  • Dunne, J.P., John, J.G., Adcroft, A.J., Griffies, S.M., Hallberg, R.W., Shevliakova, E., 2012. GFDL’s ESM2 global coupled climate-carbon Earth System Models. Part I: Physical formulation and baseline simulation characteristics. Journal of Climate, 25(19).

 

  • Errasti, I., Ezcurra, A., Sáenz, J., and Ibarra-Berastegi, G., 2011. Validation of IPCC AR4 models over the Iberian Peninsula. Theoretical and Applied Climatology, 103(1-2),pp: 61-79.

 

  • Franklin, C.N., Sun, Z., Bi, D., Dix, M., Yan, H., and Bodas‐Salcedo, A., 2013. Evaluation of clouds in ACCESS using the satellite simulator package COSP: Global, seasonal, and regional cloud properties. Journal of Geophysical Research: Atmospheres, 118(2),pp: 732–748.

 

  • Hershfield, D. M.1961. Estimating the probable maximum precipitation, Proc. ASCE, Journal Hydraulic Div., 87(HY5),pp: 99-106.

 

  • Iversen, T., Bentsen, M., Bethke, I., Debernard, J.B., Kirkevåg, A., Seland, Ø., 2013. The Norwegian earth system model, NorESM1-M—Part 2: climate response and scenario projections. Geosci. Model Dev, 6(2),pp: 389–415.

 

  • Koutroulis, A.G., Grillakis, M.G., Tsanis, I.K., and Jacob, D., 2015. Exploring the ability of current climate information to facilitate local climate services for the water sector. Earth Perspectives, 2(1),pp: 1-19.

 

  • Kunkel, K.E., Karl, T.R., Easterling, D.R., Redmond, K., Young, J., Yin, X. and Hennon, P., 2013. Probable maximum precipitation and climate change. Geophysical Research Letters40(7), pp.1402-1408.

 

  • Meehl, G.A., Washington, W.M., Arblaster, J.M., Hu, A.,Teng, H., Tebaldi, C. and White III, J.B., 2012. Climate system response to external forcings and climate change projections in CCSM4. Journal of Climate, 25(11).        
  • Noriah, A.B. and Rakhecha, P.R., 2001. Probable maximum precipitation for 24 h duration over southeast Asian monsoon region—Selangor, Malaysia. Atmospheric research58(1), pp.41-54.

 

  • Rana, A., Foster, K., Bosshard, T., Olsson, J., and Bengtsson, L., 2014. Impact of climate change on rainfall over mumbai using distribution-based scaling of global climate model projections. Journal of Hydrology: Regional Studies, 1,pp: 107-128.

 

  • Reichler, T., and Kim, J., 2008. Uncertainties in the climate mean state of global observations, reanalyses, and the GFDL climate model. Journal of Geophysical Research: Atmospheres, 113(D5).

 

  • Semenov M.A. and Barrow E., 2002. LARS-WG a stochastic weather generator for use in climate impact studies. User Man Herts UK.

 

  • Stevens, B., Giorgetta, M., Esch, M., Mauritsen, T., Crueger, T., Rast, S., et al. 2013. Atmospheric component of the MPI‐M Earth System Model: ECHAM6. Journal of Advances in Modeling Earth Systems, 5(2),pp: 146–172.

 

  • Thanh Thuy, L.T., Kawagoe, S. and Sarukkalige, R., 2019. Estimation of probable maximum precipitation at three provinces in Northeast Vietnam using historical data and future climate change scenarios, Journal of Hydrology: Regional Studies, Volume 23, 100599.

 

  • Thrasher, B., Xiong, J., Wang, W., Melton, F., Michaelis, A., and Nemani, R., 2013. Downscaled climate projections suitable for resource management. Eos, Transactions American Geophysical Union, 94(37),pp: 321-323.

 

  • Timbal, B., Abbs, D., Bhend, J., Chiew, F., Church, J., Ekström, M., and Moise, A., 2015. Murray basin cluster report: climate change in Australia. projections for Australia’s natural resource management regions. Ekström, Penny Whetton, Chris Gerbing, Michael Grose, Leanne Webb and James Risbey. Canberra: CSIRO and Bureau of Meteorology.

 

  • Voldoire, A., Sanchez-Gomez, E., Mélia, D.S., Decharme, B., Cassou, C., Sénési, S., 2013. The CNRM-CM5. 1 global climate model: description and basic evaluation. Climate Dynamics, 40(9–10).

 

  • Volodin, E.M., Dianskii, N.A., and Gusev, A.V., 2010. Simulating present-day climate with the INMCM4. coupled model of the atmospheric and oceanic general circulations. Izvestiya, Atmospheric and Oceanic Physics, 46(4),pp: 414–431.

 

  • Von Salzen, K., Scinocca, J. F., McFarlane, N. A., Li, J., Cole, J. N. S., Plummer, D., 2013. The Canadian fourth generation atmospheric global climate model (CanAM4). Part I: representation of physical processes. Atmosphere-Ocean, 51(1),pp: 104–125.

 

  • Vuuren, D.V., Edmonds, J., Kainuma, M., Riahi, K., Weyant, J., 2011. A special isue on the RCPs, Climate Change. 109, pp: 1-4.

 

  • Watanabe, M., Suzuki, T., O’ishi, R., Komuro, Y., Watanabe, S., Emori, S., 2010. Improved climate simulation by MIROC5: mean states, variability, and climate sensitivity. Journal of Climate, 23(23).

 

  • Wei, T., Yang, S., Moore, J. C., Shi, P., Cui, X., Duan, Q., 2012. Developed and developing world responsibilities for historical climate change and CO2 mitigation. Proceedings of the National Academy of Sciences, 109(32).

 

  • World Meteorological Organization 2009, Manual on Estimation of Probable Maximum Precipitation (PMP), Chairperson, Publications Board, p 65.

 

  • Wu, T., Li, W., Ji, J., Xin, X., Li, L., Wang, Z., 2013. Global carbon budgets simulated by the beijing climate center climate system model for the last century. Journal of Geophysical Research: Atmospheres, 118(10).
  • Yukimoto, S., Adachi, Y., Hosaka, M., Sakami, T., Yoshimura, H., Hirabara, M., 2012. A new global climate model of the Meteorological Research Institute: MRI-CGCM3 model description and basic performance. Meteorological Society of Japan, 90(0),pp: 23–64.

 

  • Zamani Ahmad Mahmodi, R., 2017. Optimum water allocation for adaptation conditions to climate change based on MCDM approach (case study: jarre'h reservoir), PhD Thesis in Water Resources Engineering, Faculty of Water Science Engineering, Shahid Chamran University of Ahvaz., Iran
Volume 45, Issue 4
February 2023
Pages 31-48
  • Receive Date: 28 May 2021
  • Revise Date: 16 July 2021
  • Accept Date: 20 July 2021
  • Publish Date: 20 February 2023