تحلیل وضعیت خشکسالی هواشناسی ایستگاه نیشابور به‌کمک داده‌های گزارش پنجم تغییر ‌اقلیم

نویسندگان

1 دانش‌آموخته کارشناسی ارشد گروه علوم و مهندسی آب، دانشکده کشاورزی، دانشگاه بیرجند

2 استادیار گروه علوم و مهندسی آب، دانشکده کشاورزی، دانشگاه بیرجند

چکیده

خشکسالی یک پدیده خزنده محیطی است که اثرات مخرب زیادی بر اقتصاد، کشاورزی و جامعه دارد. این پدیده در بخش‌های شرقی، مرکزی و جنوبی ایران به‌دلیل آب و هوای خشک و نیمه‌خشک نمود بیشتری دارد. با توجه به اینکه خشکسالی هواشناسی با کمبود بارندگی آغاز می‌شود، بدین منظور، شاخص خشکسالی بارش استاندارد‌  (SPI)با مقیاس‌های زمانی مختلف‌ (3، 6 و 12 ماهه) به‌کمک داده‌های گزارش پنجم، برای ایستگاه سینوپتیک نیشابور تعیین شد. داده‌های بارش مصنوعی به‌کمک شش مدل و دو سناریو انتشار RCP4.5 و RCP8.5 و با استفاده از مدل ریزمقیاس نمایی LARS-WG تعیین گردید. در نهایت، با استفاده از داده‌های بارش، مقادیر شاخص خشکسالی SPI برای دوره پایه (2011- 1992) و دوره آتی (2039- 2020) برای سه مقیاس زمانی محاسبه شد. نتایج نشان داد که بیشترین و کمترین مقدار متوسط بارش روزانه در مقیاس سالیانه برای دوره آتی تحت تأثیر سناریو RCP4.5 به‌ترتیب، مربوط به مدل‌های Canesm2 و MIROC بود و تحت تأثیر سناریو RCP8.5 مربوط به مدل‌های GISS-ES-R و Csiromk-3.6 می‌‌باشد. مقادیر شاخص SPI در مقیاس زمانی 12 ماهه نسبت به 3 و 6 ماهه شدت خشکسالی را بیشتر نشان می‌دهد. همچنین نتایج نشان داد تحت تأثیر سناریو RCP4.5 مدل‌های MIROC و GISS-ES-R و تحت تأثیر سناریو RCP8.5 مدل‌های Canesm2 و MIROC تعداد سال‌های خشک بیشتری را برآورد کرده‌اند.

کلیدواژه‌ها


عنوان مقاله [English]

Analysis of Meteorological Drought Situation of Neyshabour Station Using Data of the Fifth Report of Climate Change

نویسندگان [English]

  • Saeed Ghavam Saeedi 1
  • mostafa yaghoobzadeh 2
  • mohammad hosein najafi mood 2
  • Mokhtar Salehi Tabas 1
1 MSc, Dept. of Science and Water Eng., Faculty of Agric., Univ. of Birjand, Iran
2 Assist. Prof., Dept. of Science and Water Eng., Faculty of Agric., Univ. of Birjand, Iran
چکیده [English]

Drought is a crawling environmental phenomenon that has a major impact on the economy, agriculture and society. This phenomenon is more pronounced in the eastern, central and southern parts of Iran due to its dry and semi-arid climate. According to the fact that the meteorological drought starts by the rainfall shortage, so, the standard precipitation index (SPI) with different time scales (3, 6 and 12 months) are obtained for the Neyshabour synoptic station using the fifth report data. Precipitation synthetic data were determined using the 6 models and the two RCP4.5 and RCP8.5 emission scenarios of the LARS-WG downscaling model. Finally, using the rainfall data, the value of SPI drought index for the base period (1992-2011) and the future period (2020-2039) were calculated in the three-time scales. The results showed that the highest and lowest daily precipitation mean values in the yearly scale for the future period under influence of the RCP 4.5 scenario the Canesm2 and MIROC models and under influenced of the RCP8.5 scenario belonged to the GISS-ES-R and Csiromk-3.6 models, respectively. The SPI values at 12-month time scale showed more drought intensity than the 3 and 6-month periods. The results also showed that under the RCP4.5 scenario the MIROC and GISS-ES-R models and under the RCP8.5 scenario the Canesm2 and MIROC models estimated a greater number of dry years.

کلیدواژه‌ها [English]

  • Emotion scenario
  • GCM model
  • LARS-WG model
  • Precipitation
  • SPI Index
Ahmadebrahimpour E, Aminnejad B and Khalili K, 2019. Assessing future drought conditions under a changing climate: A case study of the Lake Urmia Basin in Iran. Water Supply 19(6):1851-1861.
Ashofteh PS and  Massah AR, 2009. Impact of climate change uncertainty on temperature and precipitation of Aidoghmoush Basin in 2040-2069 periods. Water and Soil Science University of Tabriz 19(2):85-98. (In Persian)
Braga AC, da Silva RM, Santos CA, de Oliveira Galvão C and Nobre P, 2013. Downscaling of a global climate model for estimation of runoff, sediment yield and dam storage: A case study of Pirapama Basin, Brazil. Journal of Hydrology 498:46-58.
Bong CHJ and Richard J, 2019. Drought and climate change assessment using standardized precipitation index (SPI) for Sarawak River Basin. Journal of Water and Climate Change. DOI:10.2166/wcc.2019.036
Changxing S, Yuanyuan Z, Xiaoli F and Wenwei S, 2013. A study on the annual runoff change and its relationship with water and soil conservation practices and climate change in the middle Yellow River Basin. CATENA 100:31-41.
Chunping T, Jianping Y and Man L, 2015. Temporal-spatial  variation  of  drought  indicated  by  SPI  and  SPEI  in  Ningxia  Hui  Autonomous  Region,  China.  Journal  of  Atmosphere 6:1399-1421.
Dehghan Z, Fathian F and Eslamian S, 2017. Comparative assessment   of   SDSM,   IDW   and   LARS-WG models   for   simulation   and   downscaling   of temperature  and precipitation. Journal of Water and Soil 29(5):1376-90. (In Persian)
Eghtedar Nezhad M, Bazrafshan O and Sadeghi Lari A, 2016. Adaptive evaluation of SPI, RDI and SDI indices in analyzing the meteorological and hydrological drought characteristics (case study: Bam plain). Water and Soil Science University of Tabriz 25(1):113-123. (In Persian)
Gidey E, Dikinya O, Sebego R, Segosebe E and Zenebe A, 2018. Predictions of future meteorological drought hazard (~ 2070) under the representative concentration path (RCP) 4.5 climate change scenarios in Raya, Northern Ethiopia. Modeling Earth Systems and Environment 4(2):475-488.
Golmohammadi M. and Massah Bavani A, 2011. The perusal of climate change impact on drought intensity and duration. Journal of Water and Soil 25(2):315-326. (In Persian)
Heim Jr RR, 2002. A review of twentieth-century drought indices used in the United States. Bulletin of the American Meteorological Society 83(8):1149-1165.
Anonymoos, 2007. The physical science basis, Pp.1-43, In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt K, Tignor M, Miller H, (eds.), Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge. UK.
Anonymoos, 2013. The physical science basis, Pp.741-865, In: Stocker TF, Qin D, Plattner GK, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM, (eds.), Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press Cambridge. UK.
Kobierska F, Jonas T, Zappa M, Bavay M, Magnusson J and Bernasconi SM, 2013. Future runoff from a partly glacier zed watershed in central Switzerland: A two-model approach. Advances in Water Resources 55:204-214.
McKee TB, Doesken NJ and Kleist J, 1993. The relationship of drought frequency and duration to time scales. Pp 179-184. In proceedings of the 8th conference of applied climatology. 17-22 January, Anaheim, California.
Montandon LM and Small EE, 2008. The impact of soil reflectance on the quantification of the Green vegetation fraction from NDVI. Remote Sensing of Environment 112(4):1835-1845.
Oguntunde PG, Abiodun BJ 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.
Pirnia A, Golshan M, Bigonah S and Solaimani K, 2018. Investigating the drought characteristics of Tamar Basin (Upstream of Golestan dam) using SPI and SPEI indices under current and future climate conditions. Iranian Journal of Eco hydrology 5(1):215-228. (In Persian)
Rezaei Banafsheh M, Rezaei A and Faridpour M, 2015. Analyzing Agricultural Drought in East Azarbaijan Province Emphasizing Remote Sensing Technique and Vegetation Condition Index. Water and Soil Science University of Tabriz 25(1):113-123. (In Persian)
Salehnia N, Mossavi Baygi M and Ansari H, 2013. Drought prediction with PDSI, Lars-WG5 and HadCM3 (case study: Neyshabour Basin). Iranian Journal of Irrigation and Drainage 7(1):93-103. (In Persian)
Sayari N, Bannayan M, Alizadeh A and Farid A, 2013. Using drought indices to assess climate change impacts on drought conditions in the Northeast of Iran (case study: Kashafrood Basin). Meteorological Applications 20(1):115-127.
Semenov MA, Barrow EM and Lars-Wg A, 2002. A stochastic weather generator for use in climate impact studies. User Man Herts UK.
Shahabfar A, Ghulam A and Eitzinger J, 2012. Drought monitoring in Iran using the perpendicular drought indices. International Journal of Applied Earth Observation and Geoformation 18:119-127.
Van Pelt SC and Swart RJ, 2011. Climate change risk management in transnational River Basin: The Rhine. Water Resource Management 25(14):3837-3861.
Vergni L and Todisco F, 2011. Spatio-temporal variability of precipitation, temperature and agricultural drought indices in central Italy. Agricultural and Forest Meteorology 151(3):301-313.
Vrochidou AE, Tsanis IK, Grillakis MG and Koutroulis AG, 2013. The impact of climate change on hydro meteorological droughts at a basin scale. Journal of Hydrology 476:290-301.
Yaghoobzadeh M, Amirabadizadeh M, Khozeymehnezhad H and Zeraatkar Z, 2018. The evaluation of the three downscaling methods in meteorological droughts forecasting under the effects of climate change. Iranian Journal of Irrigation and Drainage 12(2):324-334. (In Persian)
Yaghoobzadeh M, Amirabadizadeh M, Ramezani Y and Pourreza-bilondi M, 2017. The investigation of uncertainty emissions scenarios of climate change in soil moisture estimation during the growing season of wheat. Iranian Journal of Irrigation and Drainage 11(4):586-596. (In Persian)