Estimating of Actual Crops Evapotranspiration Using Energy Balance Algorithms in Qazvin Plain

Document Type : Research Article

Authors

1 MSc graduated student of Irrigation and drainage Dept. of, Imam Khomeini International University, Qazvin, Iran

2 Assistant professor of water engineering Dept., Imam Khomeini International University, Qazvin, Iran

3 Associated professor of water engineering Dept., Imam Khomeini International University, Qazvin, Iran

4 Ph.D. candidate Student of irrigation and drainage, water engineering Dept., Imam Khomeini International University, Qazvin, Iran

Abstract

The estimation of evapotranspiration is one of the most important parameters in irrigation planning. In this research, drainage lysimeter data and three single-source energy balance, SEBAL, METRIC and SSEB and a two source energy balance algorithm, TSEB have been evaluated. Satellite imageries of MODIS, ETM + sensors were used in the years 1379-1382 according to the lysimeter data loading and OLI & TIRS sensor images in 1392-1395. It should be noted that, the mismatching of the OLI & TIRS images timing with the lysimeter data timing, cause to try to evaluate the results of OLI images with Hargreaves Sarmari equation as a superior experimental method. According to the statistical indices, the results obtained from single-source algorithms showed that the SSEB algorithm with the lowest root mean square error in MODIS, ETM + and OLI & TIRS (RMSE = 0.87, 0.41 and 0.92 mm per day), and a large correlation It was introduced with lysimeter data as the best method in this area (R = 0.97, 0.99, 0.96). Among the sensors examined, ETM +, OLI & TIRS sensitivity is high on the two sensors, but the ETM + sensor also has better results.

Keywords

References

[1]. Lingling Z, Jun X, Chng_yu X, Zhonggen W, Cangrui L. Evapotranspiration estimation methods in hydrological models. Geogr. Sci 2013, 23(2): 359-369
[2]. Alizade A, Irrigation System Design, 1st ed. Mashhad, Emam Reza University, 2007 [In Persian]
[3]. Allen R, Tasumi M, Morse A, Trezza R. A Landsat-based energy balance and evapotranspiration model in Western US water rights regulation and planning. (2003). Journal of Irrigation and Drainage Systems.
[4]. Akbari M, Toomanian N, Droogers P, Bastiaanssen W.G.M, Gieske A. Monitoring irrigation performance in Esfahan, Iran, using NOAA satellite imagery.. 2007. Agricultural water management, 88, 99–109.
[5]. Nishida K, Nemani R, Running S, Glassy J. An operational remote sensing algorithm of land surface evaporation, Journal of geophysical research Atmosphere, (2003),. Volume 108, Issue D9
[6]. Bastiaanssen W.G.M., Menenti M., Feddes R.A, Holtslag A.A.M, A Remote Sensing Surface Energy Balance Algorithm for Land (SEBAL), Journal of Hydrology, (1998) , 212-213, 198-212.
[7]. Tasumi M, Allen R.G, Trezza R, and Wright J. L. Satellite-based energy balance to assess within population variance of crop coefficient curves. American Society of Civil Engineers, Journal of Irrigation and Drainage Engineering, 2005, 131(1): 94–109.
[8]. Hong S, Hendricjx J, Brochers B, Up-scaling of SEBAL derived evapotranspiration maps from Landsat (30 m) to MODIS (250 m) scale. Jornal of Hydrology (2009) , Vol 370. P 122-138.
[9]. Omidvar J. Et al., "Evaluation and comparison of the SEBAL and METRIC Algorithms in the Estimation of Evapotranspiration", J. Irri. Water Eng, 2013, Yr. 3,No. 12, Pp. 12-20.. [in Persian]
[10]. Mokhtari M. Estimation of Water Requirementof Olive Trees Using Satellite Remote Sensing Data (Case Study Tarom in Zanjan), Ms.c Thesis, University of Zanjan, 2013.[In Persian]
[11]. Allen, R.G., M. Tasumi, and A. Morse. Satellite-based evapotranspiration by METRIC and Landsat for western states water management. US Bureau of Reclamation Evapotranspiration Workshop. 2005. Feb 8–10, Ft. Collins
[12]. Folhes, M.T., C.D. Renno & J.V. Soares, "Remote Sensing for Irrigation WaterManagement in the Semi-Arid Northeast of Brazil", Agri. Water Manag, 2009, Vol. 96,Pp. 1398- 1408.
[13]..Ghorbani A. Faramarzi M. Karami J. Gholami N. Sobhani B.SEBAL and METRIC evaluation in Malayer. Humanities science portal of humanities science and cultural studies institution. , (2016). P153-184 [in Persian].
[14]. Marofi S. Mosavi R, Nasiri Gheidar O. Evaluation of Spatial and temporal variations of water requirement of Qazvin plain using metric algorithm and Landsat satellite images. Quarterly journal of geographic research, (2017), year thirty-second, number two, P80-92[in Persian].
[15]. Senay G.B, Budde M., Verdin J.P. and Melesse A. A Coupled Remote Sensing and Simplified Surface Energy Balance Approach to Estimate Actual Evapotranspiration from Irrigated Fields, (2007) , Sensors, 7, 979-1000.
[16]. Allen R., Tasumi M. and Trezza R. SEBAL (Surface Energy Balance Algorithms for Land) Advanced Training and User’s Manual—Idaho Implementation, (2002),Version 1.0.
[17]. Bezerra B.G,Silva B,Santos C,Bezerra J,Actual Evapotranspiration Estimation Using Remote Sensing: Comparison of SEBAL and SSEB Approaches. Advances in Remote Sensing,.(2015). Vol.4 (3),234-247
[18]. Asare Mostaghim M. Rahimi Khob A. Asare Mostaghim L,Using SSEB Algorithm to study the process of vegetation changes in Amir Kabir Cane Field using Remote Sensing Technique.. (2016). Second National Conference on Confronting Desertification and Sustainable Development of Desert Mines. 1425-1429
[19]. Norman J.M., Kustas W.P. Humes K.S,Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature. Agricultural and Forest Meteorology, (1995). 77: 263-293
[20]. Kustas W.P Norman J.M. A two-source approach for estimating turbulent fluxes using multiple angle thermal infrared observations. Water Resources Research,. 1997, 33: 1495-1508
[21]. Tang R, Li Z. L, Sun X. Temporal upscaling of instantaneous evapotranspiration: An intercomparison of four methods using eddy covariance measurements and MODIS data. Remote Sensing of Environment, (2013). 138, 102–118.
[22]. Kustas W.P. Anderson M.C. Cammalleri C. Alfieri J.G. Utility of a Termal-base Two- source Energy Balance Model for Estimating Surface flux over Complex Landscapes. Procedia Enviromental science. (2013). Vol. 19, 2013. Pp224-230.
 [23]. Bagheri M.H. Et al., "Compression Remote Sensing Single Source and two Sources Models Energy Flux in the Real Evapotranspiration Estimate", J. Rem.Sen. GIS, 2012, Yr. 4, No. 1, Pp. 81-96,. [in Persian]
[24]. Ebrahimi pak N.A. Determination of evapotranspiration potential of reference plant (grass) by lysymeter method and comparison with experimental methods in Qazvin. Ministry of Agricultural Jihad, Agricultural Research, Education and Promotion Organization, Qazvin Agricultural and Natural Resources Research Center [In Persian]
[25]. Rahmani N,Shahedi K,Miryaghobzadeh M. Evaluation of vegetation indices in Remote Sensing, Geomatic Conference. 2011. [In Persian]
[26]. Alavi Panah K. Principles of modern remote sensing and interpretation of stellite imageries and aerial photoes. 2nd edition, Tehran University press. 2011 [In Persian]
[27]. Farid Hoseini A, Astarae A. Sanaee Nejad s.A, Mirhoseini Mosavi P. Estimation of Leaf Area Index using IRS satellite data in Neyshabur, Journal of the Agriculture of Iran. Ferdowsi University. 2012 Volume 10, Issue 3. Pages 577–582. [In Persian]
[28]. Jensen J.R. Remote sensing of the environment:An Earth Perspective. 2000
[29]. Gillespie A, Rokugawa S,Mastunaga T, Cothern J.S,Hook S., Kahle A. B, A Temperture and emissivity sepration alghorithm for advanced spaceborn termal emission and reflection radiometer(ASTER) Images, IEEE Transactions on Geoscience and Remote Sensing, 1998, Vol, 36. Pp 1113-1126.
[30]. Sabziparvar A.A, Fakhrizadeh shirazi E, Marofi S, Rezaei Y. Estimating the land surface albedo using Level1-G and CDR Landsat-7satellite images. Journal of Agricultural Meteorology. 2016.Vol. 3, No. 2, Autumn & Winter 2015, pp.45-54. [In Persian]
[31]. Bastiaanssen W.G.M., Molden D.J. Makin I.W. Remote sensing for irrigated agriculture: examples from research and possible applications. Agricultural water management, 2000, 46: 137-155
[32]. Allen R.G, Tasumi M, Morse A , Trezza R. A Landsat-based energy balance and evapotranspiration model in Western US water rights regulation and planning. Irrigation and Drainage systems, 2005.19: 251-268
[33]. Senay GB. et al, Operational Evapotranspiration Mapping Using Remote Sensing and Weather Datasets: A New Parameterization for the SSEB Approach. Journal of the American Water Resources Association. (2013). Volume 49, Issue 3. Pages 577–591
[34]. Choudhury B, Idso S, Reginato R. Analysis of an empirical model for soil heat flux under a growing wheat crop for estimating evaporation by an infrared-temperature based energy balance equation. Agricultural and Forest Meteorology,1987., 39: 283-297.
[35]. Santanello J.A, Friedl M. Diurnal covariation in soil heat flux and net radiation. Journal of Applied Meteorology. 2003 :42, 851 862.
[36]. Alavi Panah, K. The principles of remote sensing and the interpretation of satellite images and aerial photographs. Tehran University Press. 2012 [In Persian].
[37]. Nazari R and Kaviani A. Evaluation of Potential Evapotranspiration and Pan Evaporative Methods by Lysimeter Data in a Semiarid Climate (Case Study: Qazvin Plain). Journal of Eco-Hydrology,. 2016, Spring 3: 19- [In Persian]
 [38]. Alavi Panah K. Principles of modern remote sensing and interpretation of stellite imageries and aerial photoes. 2nd edition, Tehran University press. 2011 [In Persian]
[39]. https://earthexplorer.usgs.gov/
Iranian journal of Ecohydrology
Volume 5, Issue 4
January 2019
Pages 1103-1117

Files

History

  • Receive Date: 31 January 2018
  • Revise Date: 09 May 2018
  • Accept Date: 15 June 2018
  • First Publish Date: 22 December 2018
  • Publish Date: 22 December 2018

Share

How to cite

Statistics