Climate change impact assessment on extreme daily rainfalls in Kermanshah

Subject Areas : Farm water management with the aim of improving irrigation management indicators

Mojtaba Heidari ¹ , Mohammad Reza Khazaei ²

1 - Department of Civil Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran.
2 - Department of Civil Engineering, Payame Noor University, I.R of Iran

Received: 2016-08-26 Accepted : 2017-06-07 Published : 2017-12-22

Keywords: daily rainfall, Climate Change, stochastic, Downscaling, extreme rainfall,

Abstract :

One of the potential impacts of climate change is the change on extreme rainfalls frequency and magnitude. For active adaptation strategy, it is required to assess the impacts of climate change on heavy rainfalls. Many downscaling methods have been developed, however most of them are not adequate for assessing climate change impact on extreme rainfalls. Among them, the NSRP rainfall model, which is generally ignored in previous studies, have considerable capabilities for climate change impact assessment on extreme rainfalls. In this paper, capability of the NSRP for daily rainfall series generation and climate change impact assessment on extreme rainfalls in Kermanshah is evaluated. The results indicated that NSRP can realistically simulate daily rainfall series containing extreme rainfalls; and can be used for climate change impact assessment on extreme rainfalls. Using the model, 100 series of daily rainfall of length 30 years were generated under each of the future A2, B1 and A1B scenarios from the CGCM3 model. Based on the results, magnitude of annual maximum rainfall of durations of one to five days will increase in future. Seasonal cycles of monthly means and accordance of extreme rainfalls will change. Long-term average of rainfall will decrease while extreme rainfall magnitude will increase. So it can be concluded that change in rainfall averages in monthly or yearly timescales cannot provide credit information about change in rainfall extremes. Respect to the results, for the future plans which are impressible of heavy rainfalls, the climate change impacts on heavy rainfalls should be considered.

References:

حجازی زاده، ز.، فتاحی، ا.، مساح بوانی ع.، ناصرزاده، م. 1391. ارزیابی اثرات تغییر اقلیم بر هیدروگراف سیلاب در دوره های آتی مطالعه موردی: حوضه آبریز بختیاری. جغرافیا، (34): 5-24.

خزائی،م.ر. 1395. ارزیابی اثر تغییر اقلیم بر رژیم هیدرولوژیکی یک حوضه آبریز کوهستانی در ایران. نشریه علمی– پژوهشی حفاظت منابع آب و خاک، ، 5(3):43-54.

رضایی زمان، م. و افروزی، ع. 1394. ارزیابی اثرات تغییر اقلیم بر عملکرد محصولات و ارائه راهبرد تغییر الگوی کشت (مطالعه موردی: حوضه سیمینه رود). نشریه حفاظت منابع آب و خاک. 4 (4): 51-64.

عباسی ف.، اثمری م. 1390. پیش بینی و ارزیابی تغییرات دما و بارش ایران در دهه های آینده با الگوی MAGICC – SCENGEN. آب و خاک (علوم و صنایع کشاورزی)، 25(1): 70-83.

عسگری ا.، رحیم زاده، ف.، محمدیان، ن. و فتاحی ا. 1386. تحلیل روند نمایه های بارش های حدی در ایران. تحقیقات منابع آب ایران، 3(3): 55-42.

محمدی مزرعه، ح. و تقوی، ف. 1384.  روند شاخص های حدی دما و بارش در تهران. پژوهشهای جغرافیایی،37 (53): 172-151.

مهدی زاده، ص.، مفتاح هلقی، م.، سید قاسمی، س.، مساعدی، ا. 1390. بررسی تاثیر تغییر اقلیم بر میزان بارش در حوضه سد گلستان. پژوهش های حفاظت آب و خاک، 18(3): 117-132.

Burlando, P. and Rosso, R. 1993. Stochastic models of temporal rainfall: Reproducibility, estimation and prediction of extreme events. Stochastic Hydrology in its Use in Water Resources Systems Simulation and Optimization, Kluwer Academic Publishers: Dordrecht, 137–173.

Burton, A., Kilsby, C.G, Fowler, H.J., Cowpertwait P.S.P. and O’Connell, P.E. 2008. RainSim: A spatial-temporal stochastic rainfall modelling system. Environmental Modelling & Software, 23: 1356-1369.

Dubrovsky, M., Buchtele, J. and Zalud, Z. 2004. High-frequency and low-frequency variability in stochastic daily weather generator and its effect on agricultural and hydrologic modeling. Climatic Change, 63: 145-179.

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

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.

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.

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. Climatic Change, 92: 41-63.

Khazaei, M.R., Zahabiyoun, B. and Saghafian, B. 2012. Assessment of climate change impact on floods using weather generator and continuous rainfall-runoff model. International Journal of Climatology, 32: 1997-2006.

Khazaei M., Ahmadi S, Saghafian B, Zahabiyoun B. 2013. A new daily weather generator to preserve extremes and low-frequency variability. Climatic Change, 119:631-645

Kilsby C.G., Moaven-Hashemi A., O'Connell P.E. 2004. Simulation of rainfall extremes: fitting to observed annual maxima.  First International Conference on Flood Risk; University of Bath, UK: Institute of Mathematics and its Applications.

Kilsby C.G., Jones, P.D., Burton, A., Ford, A.C., Fowler, H.J., Harpham, C., James, P., Smith, A., Wilby, R.L. 2007. A daily weather generator for use in climate change studies. Environmental Modelling and Software, 22: 1705–1719.

Liu, Z., Xu, Z., Charles, S.P., Fu, G., Liu, L. 2011. Evaluation of two statistical downscaling models for daily precipitation over an arid basin in China. International Journal of Climatology, 31: 2006-2020

Pourtouiserkani, A., Rakhshandehroo, Gh., (2014) Investigating climate change impact on extreme rainfall events, Case study: Chenar-Rahdar basin, Fars, Iran. Scientia Iranica A, 21: 525-533.

Semenov, M.A., Brooks, R.J., Barrow, E.M. and Richardson, C.W. 1998. Comparison of the WGEN and LARS-WG stochastic weather generators for diverse climates. Climate Research, 10: 95-107.

Semenov, M.A. 2007. Development of high-resolution UKCIP02-based climate change scenarios in the UK. Agricultural and Forest Meteorology, 144: 127-138.

Srikanthan, R. and McMahon, T.A. 2001. Stochastic generation of annual, monthly and daily climate data: A review. Hydrology and Earth System Sciences, 5: 653-670.

Teegavarapu, R.S.V. 2012. Floods in Changing Climate: Extreme Precipitation. Cambridge University Press, UK, London, 285 pp.

Tryhorn, L., DeGaetano, A. 2011. A comparison of techniques for downscaling extreme precipitation over the Northeastern United States. International Journal of Climatology, 31: 1975-1989.

Yang, T., Li, H., Wang, W., Yu Xu, H., Yu, Z. 2012. Statistical downscaling of extreme daily precipitation, evaporation, and temperature and construction of future scenarios. Hydrological Processes, 26: 3510–3523.