کاربست داده های بازتحلیل و دیده بانی جهت مقایسه شاخص های خشکسالی هواشناسی (مطالعه موردی: منطقه اسفراین – سبزوار)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری / تخصصی بیابانزدایی، دانشگاه علوم کشاورزی و منابع طبیعی گرگان.

2 استاد/ گروه مدیریت مناطق بیابانی دانشگاه علوم کشاورزی و منابع طبیعی گرگان

3 استاد / گروه آموزشی مرتع و آبخیزداری، دانشگاه فردوسی مشهد

4 استادیار/ گروه پژوهشی تغییر اقلیم، پژوهشکده اقلیم شناسی، سازمان هواشناسی کشور

5 دانشیار/ گروه محیط زیست، دانشگاه علوم کشاورزی و منابع طبیعی گرگان.

چکیده

پایش و تحلیل شرایط خشکسالی ازاصلیترین نیازهای مدیریت منابع آب به شمار میرود.در این پژوهش شاخصهای SPIو SPEIجهت ارزیابی خشکسالی منطقه اسفراین-سبزوار مقایسه شدند.از آنجایی که منطقه مطالعاتی مورد نظر فاقد آمار کافی و بلندمدت جهت ارزیابی خشکسالی است،داده-های بازتحلیلERA-Interimجهت تلفیق باداده‌های دیدبانی مورداستفاده قرارگرفت.برای این منظوربااستفاده ازرابط وب،اسکریپتPython،ECMWF WebAPIو نرم‌افزار ArcGIS؛داده‌های اقلیمی بارش ودما برای هر یک از ایستگاه‌هادردوره آماری 1979 تا 2016 استخراج شد.پس ازاصلاح اُریبی داده‌هابراساس داده‌های دیدبانی،داده‌های تلفیقی بارش و دما برای دوره آماری مورد نظر بدست آمد که مبنای محاسبه خشکسالی قرار گرفت.در نهایت ارزیابی خشکسالی و برآورد همبستگی شاخص‌های SPI و SPEI سه ایستگاه سرچشمه،قاسم‌آبادو جغتای درمقیاس زمانی3،6،12،18 و 24 ماهه صورت گرفت.پس از تهیه داده‌های تلفیقی بازتحلیل و دیدبانی،میانگین مربعات خطا و اُریبی به ترتیب از39/0 و 69/6 به 32/0و24/0 کاهش یافت؛در نتیجه می‌توان از این داده‌ها جهت ارزیابی خشکسالی در مناطقی که داده‌های دیدبانی در دسترس نیستند و یا پراکنش نامناسبی دارند،استفاده کرد.نتایج ارزیابی خشکسالی نشان داددر مقیاس‌های زمانی کوتاه‌مدت فراوانی دوره‌های خشک و مرطوب زیاد است که با افزایش مقیاس زمانی فراوانی دوره‌های خشک و مرطوب کاهش می‌یابداما تداوم آن‌ها افزایش می‌یابد.در ایستگاه‌های مورد مطالعه در اکثر موارد هماهنگی در دوره‌های خشک و مرطوب در هر دو شاخص دیده شد. بر اساس نتایج عرضه شده در خصوص همبستگی بین شاخص‌های خشکسالیSPIوSPEIمشاهده شد که در همه ایستگاه های مورد بررسی،بین شاخص‌های خشکسالی مورد استفاده همبستگی مثبت و معنی‌داری وجود دارد.که این همبستگی در مناطق مرطوب‌تر بالاتر است. در نتیجه می‌توان از شاخصSPIدر مناطق فاقد داده دما و با دقت شاخصSPEIاستفاده کرد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Application of Reanalysis and Observational Data for Comparison of Drought indices (Case Study: Esfarayen Sabzevar Region)

نویسندگان [English]

  • E. Silakhori 1
  • M. Ownegh 2
  • A. Mosaedi 3
  • I. Babaeian 4
  • A.R. Salman-mahini 5
1 PhD Student of Combating Desertification, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran.
2 Professor, Department of Watershed and Desert Area Management, Gorgan University of Agricultural Sciences and Natural Resources; Gorgan, Iran.
3 Professor, Department of Watershed and Rangeland Science, Ferdowsi University of Mashhad, Iran.
4 Assistant Professor, Climate Change Division, Climate Research Institute (CRI), Mashhad; Iran.
5 Associate Professor, Department of Environmental Sciences, Gorgan University of Agricultural Sciences and Natural Resources
چکیده [English]

In present paper,Standard Precipitation Index SPI and SPEI indices were compared in order to assessment of drought conditions in the Esfarayen-Sabzevar region.As the aforementioned region does not have sufficient long-term data to assess the drought, reanalysis data of ERA-Interim were used to combine with the observed data.For this purpose,climatic data of precipitation and temperature were extracted for each station in the statistical period of 1979-2016 using the web interfaces,Python script,ECMWF WebAPI and ArcGIS software. After correcting the bias of the data based on observational data,combined data of precipitation and temperature were obtained for the aforementioned period that was basis for calculating the drought.Finally,drought assessment and estimating the correlation of SPI and SPEI of three stations of Sarcheshmeh,Ghasemabad,andJoghtay in the time scales of3,6,12,18,and24months were done.After generating data combination, the Root mean square error(RMSE)and Bias were decreased from0.39and6.69to0.32and0.24 respectively;therefore,these data can be used for drought assessment in areas with not available data.Results showed that in the short time scales,the frequency of dry and wet periods is high which decreases with increasing the time scale,but their continuity increases.In the stations,in most of the cases,coordination in the dry and wet periods was observed in both indices.Based on the provided results regarding the correlation between SPIand SPEI indices, there is a positive and significant correlation between above indices and the correlation is higher in the humid regions.As a result,the SPI index can be used in the regions without temperature data and with a precession similar to the SPEI index.

کلیدواژه‌ها [English]

  • SPI Index
  • SPEI Index
  • Reanalysis Data
  • ERA-Interim
  • R statistical software
Abramopoulos F, Rosenzweig C and Choudhury B (1988) Improved ground hydrology calculations for global climate models (GCMs): Soil water movement and evapotranspiration. Journal of Climate 1(9):921-941
Austin RB, Cantero-Martinez C, Arrúe JL, Playán E and Cano-Marcellán P (1998) Yield-rainfall relationships in cereal cropping systems in the Ebro river valley of Spain. European Journal of Agronomy, Elsevier 8(3-4):239-248
Banimahd S and Khalili D (2014) Drought class transition analysis by Markov Chains and Log-Linear models: approach for early drought warning. Iran-Watershed Management Science & Engineering 8(24):1-5
Bordi I, Fraedrich K, Petitta M and Sutera A (2006) Large-scale assessment of drought variability based on NCEP/NCAR and ERA-40 re-analyses. Water Resources Management 20(6):899-915
DeGaetano AT (1999) A temporal comparison of drought impacts and responses in the New York city metropolitan area. Climatic Change, Springer 42(3):539-560
Dupigny-Giroux L-A (2001) Towards characterizing and planning for drought in vermont-part i: a climatological perspectwe. JAWRA Journal of the American Water Resources Association, Wiley Online Library 37(3):505-525
European center for Medium-Range Weather Forecasts (ECMWF) (2013) European centre for Medium-Range Weather Forecasts (ECMWF) 2005. User Guide
Evans J and Geerken R (2004) Discrimination between climate and human-induced dryland degradation. Journal of Arid Environments 57(4):535-554
Flannigan MD and Harrington J (1988) A study of the relation of meteorological variables to monthly provincial area burned by wildfire in Canada (1953-80). Journal of Applied Meteorology 27(4):441-452
Hayes MJ (1999) Drought indices. National Drought Mitigation Center, Available on line: http://www. civil. utah. edu/~ cv5450/swsi/indices. htm# deciles
Karl TR and Riebsame WE (1984) The identification of 10- to 20-year temperature and precipitation fluctuations in the contiguous united states. Journal of Applied Meteorology, 950-966, Available at: http://dx.doi.org/10.1175%2F1520-0450%281984% 29023%3C0950%3ATIOTYT%3E2.0.CO%3B2
Khalighi Sigaroudi S, Sadeghi sangdehi S, Awsati K and Ghavidel Rahimi Y (2009) The study of drought and wet year assessment models for stations in Mazandaran Province. Iranian journal of Range and Desert Reseach 16(1):44-54 (In Persian)
Labudova L, Schefczyk L and Heinemann G (2014) The comparison of the SPI and the SPEI using COSMO model data in two selected Slovakian river basins. EGU General Assembly Conference Abstracts
Leilah AA and Al-Khateeb SA (2005) Statistical analysis of wheat yield under drought conditions. Journal of Arid environments, Elsevier 61(3):483-496
Liu Y, Zhou Y, Ju W, Wang S, Wu X, He M and Zhu G (2014) Impacts of droughts on carbon sequestration by China’s terrestrial ecosystems from 2000 to 2011. Biogeosciences 11(10):2583-2599
Mavromatis T (2007) Drought index evaluation for assessing future wheat production in Greece. International Journal of Climatology, Wiley Online Library 27(7):911-924
Mckee TB, Doesken NJ and Kleist J (1993) The relationship of drought frequency and duration to time scales. AMS 8th Conference on Applied Climatology (January):179-184. Available at: http://ccc.atmos.colostate.edu/relationshipofdroughtfrequency.pdf
Mosaedi A, Khalili zade M and Mohammadi A (2008) Drought monitoring in Golestan Province. J. agric. sci. natur. resour 15(2) (In Persian)
Mostafazadeh R and Zabihi M (2016) Comparison of SPI and SPEI indices to meteorological drought assessment using R programming (Case study: Kurdistan Province). Journal of the Earth and Space Physics 42(3):633-643 (In Persian)
Nosrati K (2015) Assessment of Standardized Precipitation Evapotranspiration Index (SPEI) for drought identification in different climates of Iran. Environmental Sciences 12(4):63-74 (In Persian)
Pickup G (1999) Desertification and climate change-the Australian perspective. Climate Research 11(1):51-63
Potop V (2011) The application a new drought index-standardized precipitation evapotranspiration index in the Czech Republic. Mikroklima a mezoklima krajinnych struktur a antropogennnich prostredi 2(2010):4.2. Available at: http://www.cbks.cz/ SbornikSMlyn11/Potop1.pdf
Raziei T, Bordi I and Pereira LS (2011) An application of GPCC and NCEP/NCAR datasets for drought variability analysis in Iran. Water resources management. Springer 25(4):1075-1086
Raziei T, Bordi I, Pereira LS and Sutera A (2010) Space-time variability of hydrological drought and wetness in Iran using NCEP/NCAR and GPCC datasets. Hydrology and Earth System Sciences 14(10):1919-1930
Raziei T, Saghafian B, Paulo AA, Pereira LS and Bordi I (2009) Spatial patterns and temporal variability of drought in Western Iran. Water Resources Management 23(3):439-455
Rossi G (2003) Tools for drought mitigation in Mediterranean Regions. Springer Science & Business Media
Singh VP, Guo H and Yu FX (1993) Parameter estimation for 3-parameter log-logistic distribution (LLD3) by Pome. Stochastic Hydrology and Hydraulics, Springer 7(3):163-177
Stagge JH, Kohn I, Tallaksen LM and Stahl K (2015) Modeling drought impact occurrence based on meteorological drought indices in Europe. Journal of Hydrology, Elsevier, B.V. 530:37-50, Available at: http://dx.doi.org/10.1016/j.jhydrol.2015.09.039
Tajbakhsh S, Eisakhani N and Fazel Kazemi N (2015) Assessment of meteorological drought in Iran using standardized precipitation and evapotranspiration index (SPEI). Journal of the Earth and Space Physics 41:313-321 (In Persian)
Thornthwaite CW (1948) An approach toward a rational classification of climate. Geographical Review 38:55-94
Vicente-Serrano SM, Beguer’ia S and López-Moreno JI (2010) A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. Journal of climate 23(7):1696-1718
Vicente-Serrano SM and Lopez-Moreno JI (2005) Hydrological response to different time scales of climatological drought: an evaluation of the standardized precipitation index in amountainous mediterranean basin. Hydrology and Earth System Sciences 9:523-533
Xie P, Janowiak JE, Arkin PA, Adler R, Gruber A, Ferraro R, Huffman GJ and Curtis S (2003) GPCP pentad precipitation analyses: An experimental dataset based on gauge observations and satellite estimates. Journal of Climate 16(13):2197-2214
Yao N, Li Y, Lei T and Peng L (2018) Drought evolution, severity and trends in mainland China over 1961–2013. Science of the Total Environment 616–617:73–89. Available at: http://www.science direct.com/science/article/pii/S0048969717330450
Zare Abianeh H and Mahboobi A (2004) Evaluation of drought situation and its process in Hamadan region on the basis of drought statistical indexes. Pajouhesh & Sazandegi 16(64):2-7 (In Persian)
Zare Abyaneh H, Ghabaei Sough M and Mosaedi A (2015) Drought monitoring based on Standardized Precipitation Evaoptranspiration Index (SPEI) under the effect of climate change. Journal of Water and Soil 29(2):374-392
Zeynali B and Safarian Zengir V (2017) Drought monitoring in Urmia Lake by fuzzy index. Journal of Natural Environmental Hazards 6(12):37-62