تحلیل مشخصه‌های خشکسالی‌های تبریز (2015-1951)

نویسندگان

1 دانشیار گروه مهندسی منابع آب، دانشگاه تبریز

2 دانشجوی کارشناسی ارشد مهندسی منابع آب، دانشگاه تبریز

چکیده

در این مطالعه، جهت بررسی خشکسالی­های تبریز، از آمار بارش­های ماهانه (2015-1951) استفاده شد. سه مشخصه خشکسالی، شامل دوره تداوم، شدت و بزرگی خشکسالی از مشاهدات تخمین زده شدند. مناسب­ترین توزیع آماری بر هر کدام از مشخصه­های خشکسالی برازش داده شد. آنگاه 500 سری مصنوعی با طول مشابه با مشاهدات برای هر مشخصه تولید شد. دو حد­آستانه­ای، شامل میانگین بارش سالانه ( ) و میانگین منهای انحراف­معیار بارش سالانه ( )، برای تحلیل در نظر گرفته شد. نتایج حد­آستانه اول نشان داد که برای سری مشاهدات، بیشینه مقدار مشخصه­های Ld، Sd و Md به­ترتیب، برابر 7 سال، 500 میلی­متر و 71 میلی­متر در سال بود. توزیع­های پوواسون، پیرسون نوع 5 و ویکبای به­ترتیب، برای برازش مشخصه­های Ld، Sd و Md مناسب تشخیص داده شدند. چندک 90 درصد برای مشخصه­های Ld، Sd و Md به­ترتیب 5 سال، 443 میلی­متر و 103 میلی­متر در سال به­دست آمد. بزرگی خشکسالی، در دوره­های خشکی روی داده در تبریز حداقل 14 و بیشینه 71 میلی­متر در سال بود. نتایج حد­آستانه دوم نشان داد که برای سری مشاهدات، بیشینه مقدار مشخصه­های Ld، Sd و Md به­ترتیب معادل 2 سال، 76 میلی­متر و 38 میلی­متر در سال بود. هم­چنین توزیع­های یکنواخت، بور و مقادیر کرانه­ای به­ترتیب برای Ld، Sd و Md مناسب بود. چندک90 درصد برای Ld، Sd و Md به­ترتیب 2 سال، 51 میلی­متر و 38 میلی­متر در سال به­دست آمد.

کلیدواژه‌ها


عنوان مقاله [English]

Analysis of Drought Characteristics of Tabriz (1951-2015)

نویسندگان [English]

  • Y Dinpashoh 1
  • S Shafaei 2
1 Associate Professor of Water Resource Engineering, University of Tabriz, Iran
2 M.Sc. Student of Water Resource Engineering, University of Tabriz, Iran
چکیده [English]

In this study, for investigation of Tabriz droughts, monthly precipitation data (1951-2015) were used. Three drought characteristics, including drought duration (Ld), severity (Sd) and magnitude (Md) were extracted from observations. Data of every characteristic fitted with the most suitable statistical distribution. Then five hundred artificial series with the same length of the observed precipitation were generated for each of the characteristics. Two thresholds were considered for drought analysis, including average of annual precipitation and average of annual precipitation minus its standard deviation. The results of first threshold showed that the maximum of Ld, Sd and Md were 7 years, 500 mm and 71 mm/yr, respectively. Poisson, Pearson type 5 and Wakeby distributions were recognized as the most suitable fitted distributions for to the Ld, Sd and Md, respectively. Quantile 90% for Ld, Sd and Md were obtained as 5 years, 443 mm, 103 mm per year, respectively. The maximum and minimum of Ld in Tabriz were between 14 and 71 mm/yr. The second threshold results were showed that the maximum for Ld, Sd and Md were 2 years, 76 mm and 38 mm/yr, respectively. Uniform, Burr, and Generalized Extreme value distributions were recognized as the suitable distributions, for duration, severity and drought magnitudes, respectively. In this case, quintile 90% for drought duration, severity, magnitudes were obtained as 2 years, 51 mm and 38 mm/yr, respectively.
 

کلیدواژه‌ها [English]

  • Drought characteristics
  • Drought duration
  • Drought magnitude
  • Drought severity
  • Tabriz
Ahmadi F, Mirabbasi R and Radmanesh F, 2015. Application of joint deficit index (JDI) for analyzing droughts over the southern margins of Caspian Sea. Iranian Journal of Soil and Water Research 46(3):431-442. (In Persian)
Amirataee B, Montaseri M and Yasi M, 2014. Comparison of inherent performance of seven drought indices in drought mitigation using a Monte Carlo simulation approach. Journal of Civil and Environmental Engineering 43(1):25-39. (In Persian)
Bakhtiare Enayat B, Malekian A and Salajegheh A, 2015. Time and lag correlation analysis between climate drought and hydrological drought in Hashtgerd Plain. Iranian Journal of Soil and Water Research 46(3):431-442. (In Persian)
Barzegari F and Malekynejhad H, 2015. Linear moments application in drought prediction (Case study: Central catchment of Iran). Water and Soil Science 25(1):113-123. (In Persian)
Combs S, 2012. The Impact of the 2012 Drought and Beyond. Texas Comptroller of Public Accounts. Pp: 1–12.
Chen S-T, Kuo C-C and Yu PS, 2009. Historical trends and variability of meteorological droughts in Taiwan. Hydrological Sciences Journal 54(3), 430-441.
Dinpashoh Y, 2004. Meteorological drought analysis using pattern analysis. PhD Thesis in Irrig. Eng. and Science, Faculty of Agriculture, University of Tabriz. (In Persian)
Ekhtiari Khajeh S and Dinpashoh Y, 2018. Application of Effective Drought Index (EDI) in Characterizing Drought Periods (Case study: Tabriz, Bandar Anzali, and Zahedan). Journal of Irrigation Science and Engineering 41(1): 133-145. (In Persian)
Ghorbani-Aghdam M, Dinpashoh Y and Mostafaeipour A, 2013. Application of factor analysis in defining drought prone areas in Lake Urmia Basin. Natural Hazards 69(1):267-277.
Hisdal H and Tallaksen ML, 2003. Estimation of regional meteorological and hydrological drought characteristics: a case study for Denmark. Journal of Hydrology 281: 230-247.
Karabulut M, 2015. Drought analysis in Antakya-Kahramanmaras Graben, Turkey. J Arid Land 7(6): 741-754.
Karavatiz CA, Alexandris S, Demetrios ET and Athanasopoulos G. 2011. Application of the standardized precipitation index (SPI) in Greece. Water Resources Management 3:787-805.
Livada I and Assimakopulos VD, 2007. Spatial and temporal analysis of drought in Greec using the Standardization of Precipitation Index (SPI). Theoretical and Applied Climatology 89:143-153.
Matalas NC, 1991. Drought description. Stochastic Hydrology and Hydraulics 5: 255-260.
Mckee TB, Doesken N and Kleist J, 1993. The relationship of drought frequency and duration to time scales, Pp: 179-184. 8th Conference on Applied Climatology. 17-22 January, Anaheim, California.
Mirabbasi Najaf Abadi R, Ahmadi F, Ashuri M, Nazeri Tahroudi M, 2017. Droughts analysis in the Northeast of Iran using Joint Deficit Index (JDI). Ecohydrology 4(2): 573-585. (In Persian)
Mishra AK and Singh VP, 2011. A review of drought concept. Journal of Hydrology 203:157-175.
Rezaei Banafsheh M, Rezaei A, Faridpour M, 2015. Analyzing agricultural drought in East Azarbaijan province emphasizing remote sensing technique and vegetation condition index. Water and Soil Science 25(1):113-123. (In Persian)
Rhee J and Im J, 2017.Meteorological drought forecasting for ungauged areas based on machine learning: using long-range climate forecast and remote sensing data. Agricultural and Forest Meteorology 237: 105-122.
Santos MA, 1983. Regional droughts: A stochastic characterization. Journal of Hydrology 66: 183-211.
Seidan J and Mohammadi F, 1997. Methods of climate classification. Quarterly Journal of Geographical Researches 45: 74-108. (In Persian)
Todisco F, Mannocchi F and Vergni L, 2013. Severity-duration-frequency curves in the mitigation of drought impact: An agricultural case study. Natural Hazards 65: 1863-1881.
Vrochidou AK, 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.
     Wambua R, Mutua B and Rauda J, 2014. Performance of Standardized Precipitation Index (SPI) and Effective Drought Index (EDI) in drought forecasting using Artificial Neural Network (ANNS) for Upper Tana River basin, Kenya. International Journal of Engineering Research and Technology 3(11):547-556.
Wijayaratne LH and Golube E, 1991. Multiyear drought simulation. Water Resources Bulletin 27(3): 387-395.
Wilhite DA, 2000.Ddrought as a Natural Hazard, Concepts and Definitions. Pp:345-410. In: DA Wilhite (ed). Drought, )1(A Global Assessment Rout ledge.
Wilhite DA and Glantz MH, 1985. Understanding the drought phenomenon, the role of definitions. Water International 10(3): 111-120.
Zare Abianeh H, Bayat Varkeshi M and Dinpashoh Y. 2011. Study of aridity index trends in southern half of Iran. Water and Soil Science 21(2):81-92. (In Persian)