Estimation of Actual Evapotranspiration of Wheat Using SEBAL Algorithm Compared to Lysimetric Results under Standard Conditions in Tabriz and Karaj Research Stations

Document Type : Research Paper

Authors

1 Assistant Professor, Soil and Water Research Department, Chaharmahal and Bakhtiari Agricultural and Natural Resources Research Center, AREEO, Shahrekord, Iran.

2 Assistant Professor, Department of Irrigation and Soil Physics Research, Soil and Water Research Institute, Agricultural Research, Education and Extension Organization, Karaj, Iran

3 Assistant Professor (Retired), Department of Soil and Water Research, Eastern Azerbaijan Agriculture and Natural Resources Research Center, AREEO, Tabriz, Iran.

Abstract

The aim of this study was to estimate the actual evapotranspiration of wheat using Surface Energy Balance Algorithm for Land (SEBAL) and compare with data measured by lysimeters in two study sites in Tabriz and Karaj during three growing seasons (1396-1399). Values of actual evapotranspiration of wheat during the growing seasons were calculated by two methods: a) using Landsat 8 satellite data through SEBAL, and b) using drained lysimeter data. Considering that evapotranspiration in SEBAL is in actual conditions and lysimeters provide evapotranspiration in potential conditions (standard situation without any limitation), to reduce errors, remote sensing data were used for pixels that had moisture conditions similar to standard lysimeters conditions. Comparison of actual evapotranspiration obtained from SEBAL and lysimeter in both sites showed relatively good correlation. The coefficients of determination (R2) were 0.73 and 0.65 in, respectively, Karaj and Tabriz sites. In addition, using statistical parameters such as NRMSE, RMSE, MAE, and MBE showed that SEBAL actual evapotranspiration data and lysimeteric data were, relatively, in agreement in the two study sites. However, in most cases, evapotranspiration values by SEBAL were greater than values measured by the lysimeter. In general, considering the advantages of the SEBAL, it is suggested this technology be used to estimate the actual evapotranspiration of wheat in large-scale areas. 

Keywords


  1. ابراهیمی، ح.، گندمکار، ا.، المدرسی، س. ع.، رامشت، م. ح. 1395. برآورد دمای سطح زمین و تأثیر پوشش گیاهی بر دمای سطح با استفاده از تصاویر مودیس (مطالعه موردی: حوزه تویسرکان). فصلنامه جغرافیا و برنامه ریزی منطقه ای، 6(4)، 23-32.
  2. ارشد، ص.، مباشری، م. ر.، مرید، س.، آقاعلیخانی،م. و ارشد، س. 1387. پیش‌بینی خسارات ناشی از خشکسالی کشاورزی با استفاده از تصاویر ماهواره‌ای در اراضی دیم استان کرمانشاه. سومین کنفرانس مدیریت منابع آب ایران. دانشگاه تبریز
  3. آمارنامه کشاورزی. 1398 .جلد اول، محصولات زراعی سال 1397-1396. دفتر آمار و فنآوری اطلاعات، معاونت برنامه‌ریزی اقتصادی، وزارت جهاد کشاورزی، ایران.
  4. کریمی، ع.، ب. فرهادی بانسوله. ه. حصادی. 1391. برآورد تبخیر- تعرق واقعی در مقیاس منطقه ای با استفاده از الگوریتم سبال و تصاویر لندست. نشریه آبیاری و زهکشی ایران. شماره 4، جلد 6، ص.364-353.
  5. مشتاق، ن.، جعفری،ر. سلطانی، س. و رمضانی، ن.۱۳۹۴. کاربرد مدل توازن انرژی و داده‌های ماهواره لندسـت سـنجنده TM درتخمین تبخیر و تعرق. مجله علوم آب و خاک .۲۰۷-۲۱۸: (۷۳)۱۹
  6. یزدانی، و.، ابراهیمی، ح. 1392. مقایسه برآورد ضریب گیاهی فضای سبز به کمک روش سبال و روش لیمپ (مطالعه موردی مشهد). علوم و مهندسی آبیاری (مجله ی علمی کشاورزی)، جلد 37، شماره‌ی 4، ص 27-11.
  7. غلامی سفیدکوهی، م.، میرلطیفی، س.، محمدی، ک.، و علی محمدی، ع. 1389. برآورد ضریب گیاهی و تبخیر-تعرق واقعی گندم با استفاده از سنجش از دور مطالعه موردی: حوضه گرگانرود. مجله آبیاری و زهکشی ایران، 4(2).
  8. Allen R. G., Morse A., and Tasumi M. 2002. Application of SEBAL for western US water rights regulation and planning. Proceedings of the International Conference on Irrigation and Drainage, Workshop on Remote Sensing of ET for Large Regions; Montpellier, France.
  9. Bastiaanssen W.G.M. 1995. Regionalization of surface flux densities and moisture indicators in composite terrain: A remote sensing approach under clear skies in Mediterranean climates, Ph.D. Dissertation, CIP Data Koninklijke Bibliotheek, Den Haag, The Netherlands
  10. Bastiaanssen, W. G. M., Menenti, M., Feddes, R. A. and Holtslag, A. A. M. 1998. A remote sensing surface energy balance algorithm for land (SEBAL): Part 1.Formulation. Journal of Hydrology. 212-213, 198-212.
  11. Bastiaanssen, W. G. M., Pelgrum, H., Wang, J., Ma, Y., Moreno, J. F., Roerink, G. J. and van der,W.T. 1998. A Surface Energy Balance Algorithm for Land (SEBAL): Part 2. Validation. Journal of Hydrology. 212-213, 213-229.
  12. Bastiaanssen, W.G.M. 2000. SEBAL-based sensible and latent heat fluxes in the irrigated Gediz Basin, Turkey. Journal of Hydrology, 229: 87-100
  13. Bastiaanssen, W.G.M., M. Menenti, R.A. Feddes and A.A.M Holtslag.  “A remote sensing surface energy balance algorithm for land (SEBAL): 1. Formulation.” J. Hydrol., 212–213, 198–212.
  14. George, Paul, Prasanna, H. Gowda, P.V. Vara, Prasad, Terry A. Howell, Scott A. Staggenborg, Christopher M.U. Neale, 2013. Lysimetric evaluation of SEBAL using high resolution airborne imagery from BEAREX08, Advances in Water Resources, in press.
  15. Hair, Joseph F. (2011). Multivariate Data Analysis: An Overview. In Miodrag Lovric (Ed.), International Encyclopedia of Statistical Science (pp. 904-907). Berlin, Heidelberg: Springer Berlin Heidelberg.
  16. Mokhtari, M. H. 2005. Agricultural drought impact using remote sensing. Ms. C. Diss., ITC. The Netherlands.
  17. Morse, A., Allen, R. G., Tasumi, M., Kramber, W. J., Trezza, R., and Wright, J. L. 2000. Final Report: Application of the SEBAL meteorology for estimating evapotranspiration and consumptive use of water through remote sensing. Idaho Department of Water Resources. University of Idaho, Department of Biological and Agricultural.107p.
  18. Ramos,J.G., Cratchley,C.R., Kay,J.A., Casterad, M.A.,Martinez-cob,A and Dominguez,R. 2009. Evaluation of satellite evapotranspiration estimates using ground-meteorological data available for the Flumen District into the Ebro valley of N.E. Spain. Agricultural Water Management. 96: 638-652.
  19. Senay, G. B., Friedrichs, M., Singh, R. K., & Velpuri, N. M. (2016). Evaluating Landsat 8 evapotranspiration for water use mapping in the Colorado River Basin. Remote Sensing of Environment, 185, 171-185.
  20. Singh, R. K., & Senay, G. B. (2016). Comparison of Four Different Energy Balance Models for Estimating Evapotranspiration in the Midwestern United States. Water, 8(1), 9
  21. Teixeira, A.H., W.G.M. Bastiaanssen, M.D. Ahmad & M.G. Bos. 2009. Reviewing SEBALinput parameters for assessing evapotranspiration and water productivity for the Low-MiddleSao Francisco River basin, Brazil Part A:Calibration and validation, agricultural andforest meteorology, 149, 462-476.
  22. Waters, R., Allen, R., Tasumi, M., Trezza, M. and Bastiaanssen. W. 2002. Surface Energy Balance Algorithms for Land, Advanced Training and User’s Manual. NASA EOSDIS/Synergy grant from the Raytheon Company through The Idaho Department of Water Resources.