Up to journal
for Research & Developement
Journal of Materials Science: Materials in Electronics
Impact Factor
0/000
Available
2000 - 2020
Volumes
15
Issues
54
Articles
875
Open Access
532


Iranian Water Researches Journal
Assessing the Impact of Climate Change on the Drought Status in Tabriz Station During Future Periods Using LARS-WG


 submission: 21/10/2019 | acception: 21/12/2019 | publication: 07/09/2020

DOI 

Authors
khadijeh Javan1*, mahdi Erfanian2

1-Urmia university،kh.javan@urmia.ac.ir

2-Urmia university،erfanian.ma@gmail.com



60 Downloads

Abstract

Drought is one of the most widespread and devastating natural hazards, which is compounded by climate change. Indicators are widely used to provide an overview of drought conditions. In this study, the impacts of climate change on drought status in Tabriz station during future periods were investigated using Deciles Index (DI) and the Standardized Precipitation Index (SPI). First, the daily output data of HadGEM2 model under RCP2.6, RCP4.5 and RCP8.5 scenarios were downscaled by LARS-WG version 6 and the ability of the model was confirmed to simulate the past climate (1987-2016) in Tabriz. Then, the precipitation was simulated for Future periods of 2021-2040, 2041-2060, and 2061-2080. Using simulated precipitation data, drought status in Tabriz was assessed using two drought indices on an annual scale. The results show that in most of the studied years, the number of droughts decreased in all three future periods compared with the base period and the number of wet years increased. The results of drought monitoring and its prediction for future periods can be used in natural resource management as well as water resource management planning. In recent years, weather and climate researchers have identified climate change as the most important concern due to increasing greenhouse gas emissions and global warming. Drought is one of the most important and most common disasters affected by climate change that is slowly and progressively causing environmental, agricultural and economic damage in both dry and humid climates around the world (Li et al., 2013). Since drought affects different segments of society such as water resources, agriculture, industry, economy, health, etc., monitoring and evaluation of this factor in the present and in the future is necessary in order to provide proper planning in different parts of society. Climatologists are currently simulating climate variables using general atmospheric circulation models (Barrow and Yu, 2005). The main purpose of these models is to calculate three-dimensional climate indices in specific grids. The outputs of these models have low spatial accuracy. Therefore, if their output directly enters hydrological models, it increases uncertainty. Downscaling methods are used today to increase the spatial accuracy of these data. Downscaling methods are divided into two categories: dynamic and statistical (Beecham et al., 2014). Statistical methods are commonly used in climatic studies. In this study, the output of HadGEM2 model under RCP2.6, RCP4.5 and RCP8.5 scenarios were downscaled by statistical method and LARS-WG model. The daily climatic variables such as minimum temperature, maximum temperature, precipitation and sunshine for Tabriz station were produced for the next three periods of 2021-2040, 2041-2060 and 2061-2080. Then, using simulated rainfall data, the drought status of Tabriz station was evaluated using two decile indices (DI) and Standardized precipitation index (SPI). The study area in this research is Tabriz Synoptic Station which is geographically located in northwest of Iran. The data used include observed and simulated data. The observed data were related to 1987- 2016. The simulated data included HadGEM2 model that was downscaled by LARS-WG under RCP2.6, RCP4.5 and RCP8.5 scenarios. LARS-WG as one of the most popular models for generating stochastic data was used to produce daily minimum and maximum temperatures, precipitation and radiation for present and future climatic conditions. This model is more applicable than others due to repeated computation, less data input, simplicity and performance (Kilsby et al., 2007). After primary data analysis, daily precipitation series were generated and then LARS-WG was implemented. Subsequent to analyzing the input data and the initial statistical studies, the base state scenarios were implemented for the observed data and the precipitation data were simulated. Model validation based on observed and simulated precipitation values showed high agreement of the model with the observed data. Then precipitation data were tested for normality of distribution. The results indicated that the precipitation data followed the normal distribution. After ensuring that the model was capable to simulate precipitation data series for Tabriz station, it was run for three periods of 2021-2040, 2060-2041 and 2061-2080 using HadGEM2 output under RCP2.6, RCP4.5 and RCP8.5. Then annual drought was calculated using SPI and DI indices. Investigation of drought status using SPI index revealed that in most of the years, the number of droughts decreased compared with the base period (1987-2016) and the number of wet periods increased. Evaluation of the DI index also showed that in all future periods the number of extreme, severe and mild droughts decreased, in compare with the base period, but the number of moderate droughts increased. According to this index, the percentage of normal years would increase significantly in all three future periods, but the percentage of wet years would show a significant decrease.




Keywords

Climate Change  Drought  HadGEM۲  LARS WG  Tabriz. 



Download fulltext PDF


Open Access

Download

Citation
جوان خ. و عرفانیان م. 1399. ارزیابی آثار تغییر اقلیم بر وضعیت خشک‌سالی ایستگاه تبریز طی دوره‌های آتی با استفاده از مدل ریزمقیاس نمایی LARS-WG. مجله پژوهش آب ایران. 38: 97-106




References

Barrow E. and Yu G. 2005. Climate scenarios for Alberta. A report prepared for the Prairie Adaptation Research Collaborative (PARC) in co-operation with Alberta Environment. Alberta Environment, Regina, Saskatchewan. 73 p

Beecham S. Rashid M. and Chowdhury R. K. 2014. Statistical downscaling of multi‐site daily rainfall in a South Australian catchment using a Generalized Linear Model. International Journal of Climatology. 34(14): 3654-3670

Dascălu S. I. Gothard M. Bojariu R. Birsan M. V. Cică R. Vintilă R. Adler M. J. Chendeș V. and Mic R. P. 2016. Drought-related variables over the Bârlad basin (Eastern Romania) under climate change scenarios. Catena. 141: 92-99

Farzaneh M. R. Eslamian S. Samadi S. Z. and Akbarpour A. 2012. An appropriate general circulation model (GCM) to investigate climate change impact. International Journal of Hydrology Science and Technology. 2(1): 34-47

Hayes M. J. Svoboda M. D. Wiihite D. A. and Vanyarkho O. V. 1999. Monitoring the 1996 drought using the standardized precipitation index. Bulletin of the American meteorological society. 80(3): 429-438

Hewitson B. C. and Crane R. G. 2006. Consensus between GCM climate change projections with empirical downscaling: precipitation downscaling over South Africa. International Journal of Climatology: A Journal of the Royal Meteorological Society. 26(10): 1315-1337

IPCC 2007. Climate change 2007: the physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University, Cambridge, UK. 996 p

Kilsby C. G. Jones P. D. Burton A. Ford A. C. Fowler H. J. Harpham C. James P. Smith A. and Wilby R. L. 2007. A daily weather generator for use in climate change studies. Environmental Modelling & Software. 22(12): 1705-1719

Li B. Su H. Chen F. Wu J. and Qi J. 2013. The changing characteristics of drought in China from 1982 to 2005. Natural hazards. 68(2): 723-743

Loukas A. Vasiliades L. and Tzabiras J. 2008. Climate change effects on drought severity. Advances in Geosciences. 17: 23-29

McKee Thomas B. Drought monitoring with multiple time scales." In Proceedings of 9th Conference on Applied Climatology, Boston, 1995

Oguntunde P. G. Abiodun B. J. and Lischeid G. 2017. Impacts of climate change on hydro-meteorological drought over the Volta Basin, West Africa. Global and Planetary Change. 155: 121-132

Samadi S. Z. Sagareswar G. and Tajiki M. 2010. Comparison of general circulation models: methodology for selecting the best GCM in Kermanshah Synoptic Station, Iran. International Journal of Global Warming. 2(4): 347-365

Semenov M. A. and Stratonovitch P. 2010. Use of multi-model ensembles from global climate models for assessment of climate change impacts. Climate research. 41(1): 1-14

Vrochidou A. E. Tsanis I. K. Grillakis M. G. and Koutroulis A. 2013. The impact of climate change on hydrometeorological droughts at a basin scale. Journal of Hydrology. 476: 290-301


احمدی ح. فلاح قالهری غ. و باعقیده م. 1398. پیش­ نگری اثرات تغییر اقلیم بر بارش فصلی مناطق سردسیر ایران بر اساس سناریوهای واداشت تابشی (RCP). فیزیک زمین و فضا. 45(1): 177-196.

انصافی مقدم ط. 1386. ارزیابی چند شاخص خشک‌سالی اقلیمی و تعیین مناسب­ترین شاخص در حوضه دریاچه نمک. فصلنامه تحقیقات مرتع و بیابان. 14(2): 271-288.

بحری م. دستورانی م. و گودرزی م. 1393. بررسی خشک‌سالی­ های دهه 2030-2011 تحت اثر تغییر اقلیم حوضه آبریز اسکندری اصفهان. نشریه مهندسی و مدیریت آبخیز. 7(2): 157-171.

پروانه ب. شیراوند ه. و درگاهیان ف. 1394. تحلیل وضعیت خشک‌سالی استان لرستان طی دوره 2030-2011 با استفاده از ریزمقیاس نمایی خروجی 4 مدل گردش عمومی جو. فصلنامه جغرافیایی سرزمین. 45: 1-13.

پیرنیا ع. گلشن م. بیگنه س. و سلیمانی ک. 1397. ارزیابی وضعیت خشک‌سالی در حوضه آبخیز تمر (بالادست سد گلستان) با استفاده از شاخص­های SPI و SPEI تحت شرایط اقلیمی حال و آینده. اکوهیدرولوژی. 5(1): 215-228.

جوان خ. عزیززاده م. بشیری ه. و شهریار سرنقی ف. 1394. پهنه­بندی شاخص­های خشک‌سالی SPI و DI با استفاده از داده­های شبکه­ای بارش در شمال غرب ایران. فصل­نامه جغرافیای طبیعی. 29: 117-130.

خزانه ­داری ل. زابل عباسی ف. قندهاری ش. کوهی م. و ملبوسی ش. 1388. دورنمایی از وضعیت خشک‌سالی ایران طی سی سال آینده. جغرافیا و توسعه ناحیه­ای. 12: 83-98.

صالح‌نیا ن. موسوی بایگی م. و انصاری ح. 1392. پیش­بینی خشک‌سالی با استفاده از نمایه PDSI به کمک مدل­های LARS-WG و HadCM3 (مطالعه موردی: حوضه نیشابور). مجله آبیاری و زهکشی ایران. 7(7): 93-103.

گل­ محمدی م. و مساح بوانی ع. 1390. بررسی تغییرات شدت و دوره بازگشت خشک‌سالی حوضه قره­سو در دوره‌های آتی تحت تأثیر تغییر اقلیم. نشریه آب و خاک. 25: 315-326.

نصیری ب. و یارمرادی ز. 1396. پیش­بینی تغییرات پارامترهای اقلیمی استان لرستان در 50 سال آتی با استفاده از مدل HADCM3. اطلاعات جغرافیایی (سپهر). 101: 143-154





Announcements  

  •  No announces available
Indexes  

 


ISC
magiran
Civilica
SID
nali