تحلیل همبستگی شاخص‌های پیوند ازدور بزرگ‌مقیاس با تبخیروتعرق مرجع ماهانه ایستگاه‌های همدید ایران

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مهندسی آبیاری و آبادانی، دانشکده مهندسی و فناوری کشاورزی، پردیس کشاورزی و منابع طبیعی دانشگاه تهران، کرج، ایران

2 استادیار، پژوهشگاه هواشناسی و علوم جو، تهران، ایران

10.22059/ijswr.2021.322853.668951

چکیده

تبخیروتعرق مرجع به‌عنوان مؤلفه مهم در چرخه هیدرولوژی و تعیین نیاز آبی به‌حساب می‌آید. در این مطالعه تلاش شد تأثیرگذاری شاخص‌های پیوندازدور بزرگ‌مقیاس بر تبخیروتعرق مرجع ماهانه در گستره ایران مورد واکاوی قرار گیرد. به این منظور، تبخیروتعرق مرجع روزانه و سپس ماهانه با معادله PMF-56 در 123 ایستگاه همدید ایران در دوره 2019-1990 محاسبه‌ شده و همبستگی آن با 37 شاخص پیوندازدور با تأخیرهای زمانی هم‌زمان تا 12 ماه با روش همبستگی پیرسون به دست آمد و فراوانی نوع همبستگی‌ها نیز محاسبه گردید. در نهایت ضریب همبستگی در پهنه ایران با روش کریجینگ در محیط نرم افزار ArcGIS 10.4 انجام شد. نتایج به دست آمده نشان می‌دهد بیشترین همبستگی مثبت متعلق به شاخص‌های AMO، CO2، NTA، TNA و TSA و بیشترین همبستگی منفی متعلق به شاخص‌های MEI و SST3.4 در تأخیرهای زمانی مختلف است. بیشترین فراوانی همبستگی‌های معنادار با تبخیروتعرق متعلق به شاخص‌های CO2، AMO، NTA، TNA و WHWP است که به ترتیب 58، 35، 23، 23 و 21 درصد ایستگاه‌های مورد مطالعه را شامل می‌شوند. گسترده‌ترین پراکنش مکانی همبستگی‌های معنادار متعلق به غلظت دی اکسید کربن است که در همه تأخیرهای زمانی و همه ماه‌های مورد مطالعه به جر نوامبر و دسامبر به دست آمده است. نتایج این مطالعه نشان داد شاخص‌های پیوندازدور و غلظت دی اکسیدکربن می‌توانند در تأخیرهای زمانی صفر تا 12 ماهه همبستگی مناسب داشته باشند و به شرط استفاده از مدل‌های یادگیری ماشین مناسب در جهت پیش‌بینی مقدار تبخیروتعرق مرجع ماهانه مورد استفاده قرار گیرند.

کلیدواژه‌ها


عنوان مقاله [English]

Correlation Analysis of large-scale Teleconnection Indices with Monthly Reference Evapotranspiration of Iran Synoptic Stations

نویسندگان [English]

  • Jalil Helali 1
  • Ebrahim Asadi Oskouei 2
1 Department of Irrigation and Reclamation Engineering Department, Faculty of College of Agriculture & Natural Resources, University of Tehran, Karaj, Iran.
2 Assistant professor, Atmospheric Science and Meteorological Research Center (ASMERC), Tehran, Iran
چکیده [English]

Reference evapotranspiration (ETo) is considered as an important component in the hydrological cycle and determination of water requirement. In this study, an attempt was made to investigate the effect of large-scale teleconnection indices (LSTIs) on estimation of monthly reference evapotranspiration (ETo) in Iran. For this purpose, daily and monthly ETo using Penman–Monteith FAO (PMF-56) equation was calculated in 123 synoptic stations of Iran for the period of 1990-2019 and its correlation with 37 LSTIs with lag time of 0 to 12 months was obtained using the Pearson correlation method and the Significant Correlation Frequencies (SCF) was also calculated. Finally, the correlation coefficient was performed in Iran using the Kriging method in the ArcGIS 10.4 software package. The results show that the highest positive correlation belongs to AMO, CO2, NTA, TNA, and TSA indices and the highest negative correlation belongs to MEI and SST3.4 indices in different lag times. The highest SCF with ETo belongs to AMO, CO2, NTA, TNA, and WHWP indices, which include 35, 58, 23, 23, and 21% of the studied stations, respectively. The widest spatial distribution of SCF belongs to the CO2 obtained in all lag times and all months studied until November and December. The results of this study showed that the LSTIs and CO2 could have a good correlation in lag times of 0 to 12 months and could be used for prediction of monthly ETo, if an appropriate machine learning model is used.

کلیدواژه‌ها [English]

  • Iran
  • Reference Evapotranspiration
  • Large Scale Teleconnection Indices
  • CO2
  • Pearson correlation
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