Evaluation and Comparison of Estimation Methods for Actual Evapotranspiration in the Urmia Lake Basin

Document Type : Research Article

Authors

1 Researcher of Remote Sensing Research Center (RSRC), Sharif university of Technology, Tehran

2 Professor, Faculty of Civil Engineering, Sharif university of Technology, Tehran

Abstract

One of the main variables in calculating the water balance and land surface energy is Actual evapotranspiration. Different methods for calculating actual evapotranspiration have been presented so far. Investigate and compare various existing methods for estimating actual evapotranspiration in the Urmia Lake basin in order to select an optimal algorithm was The purpose of this study .Using the ETLook, SEBAL, SEBS and S-SEBI algorithms based on the energy balance equation, the results obtained by comparing the results of different algorithms showed that the ETLook method has been able to utilize the latest methods of estimation of evapotranspiration. Many The weaknesses of other algorithms are covered. This two-source method analyzes vegetation and soil separately, by using soil moisture images, has not even been able to withstand its efficiency in calculating evapotranspiration, even in cloudy days. However, the commercialization of this algorithm and the great difference in the results of the global WaPOR product (produced with ETLook) with ground observations in the Urmia Lake basin has made it less and less convenient to use. Considering all the conditions, including having a suitable physical base, ease of implementation and comparison with ground values, it can be admitted that the SEBAL algorithm is the most suitable option for estimating the actual evapotranspiration of the Urmia Lake basin.

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[1]. Tang R, Li ZL & Tang B. An application of the T s–VI triangle method with enhanced edges determination for evapotranspiration estimation from MODIS data in arid and semi-arid regions: Implementation and validation. Remote Sensing of Environment. 2010;114, 540-551
[2]. Inoue Y. Synergy of Remote Sensing and Modeling for Estimating Ecophysiological Processes in Plant Production. Plant Production Science. 2003;6:3–16.
[3]. Gowda PH, Chavez J L, Colaizzi PD, Evett S, Howell T A, Tolk JA. ET mapping for agricultural water management: present status and challenges. Irrigation Science. 2007;26:223-237.
[4]. Ayoola O, Emmanuel O, Harald K, Frank A, Joel A, Salisu T, Luitpold H, Jan B. Comparison Of Sebal Estimated Heat Fluxes And Evapotranspiration Using Field And Remote Sensing Data In The Sudanian Savanna In West Africa. International Journal of Agriculture and Environmental Research. 2018; 22:2455-6939
[5]. Zhang K, Kimball JS, and Running SW. A review of remote sensing based actual evapotranspiration estimation. WIREs Water. 2016;3: 834–853.
[6]. Kjaersgaard J H, Allen RG, Garcia M, Kramber W & Trezza, R. Automated selection of anchor pixels for landsat based evapotranspiration estimation. In World Environmental and Water Resources Congress 2009: Great Rivers (pp. 1-11).
[7]. Bastiaanssen, W, Van der Wal T, and Visser T.Diagnosis of regional evaporation by remote sensing to support irrigation performance assessment, Irrig. Drain. Syst. 1996; 10(1), 1–23
[8]. Allen R, Tasumi M, and Trezza R.Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC)—Model, J.Irrig. Drain. Eng. 2007;133(4), 380–394.
[9]. Bagheri Haroni, MH, Evaluating remote sensing to estimate water balance in regional scale harvest ground water Emphasizing the net purification of groundwater (case study: Urmia Lake basin), M.Sc. thesis, TMU university, 2011.[Persian]
[10].            DroogersPW, Immerzeel W, and Lorite IJ.Estimating actual irrigation application by remotely sensed evapotranspiration observations, Agric. Water Manage.2010; 97, 1351–1359
[11].            Hu G, Jia, L & Menenti M. Comparison of MOD16 and LSA-SAF MSG evapotranspiration products over Europe for 2011. Remote Sensing of Environment. 2015; 156, 510-526.
[12].            Zhao LL, Ronglin, T, Zhengming W, Yuyun B, Chenghu Z, Bohui T, Guangjian Y, et al. A Review of Current Methodologies for Regional Evapotranspiration Estimation from Remotely Sensed Data. Sensors, 2009; 9:3801-3853.
[13].            Remote Sensing Research Center (RSRC), Estimation of evapotranspiration, costs and the amount of water saving in agriculture (case study: Urmia Lake basin for 2010 ), EWRC in Sharif university of Technology, 2015. [Persian]
[14].            Su Z. The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes SEBS-The SurfaceEnergy Balance. Hydrology and Earth System Sciences. 2002;6(1): 85-100.
[15].            Martens B, Miralles DG, Lievens H, van der Schalie R, de Jeu RAM, Fernández-Prieto D, et al. N.E.C: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geoscientific Model Development. 2018;10, 1903–1925.
 
[16].            www.fao.org/3/i7315en/I7315EN
[17].            Hatch U, Jagtap S, Jones J, Lamb M. Potential effects of climate change on agricultural water use in the southeast U.S. Journal of the American Water Resources Association. 1999;35 (6), 1551–1561.
[18].            Allen R, Pereira LS, Raes D and Smith M. Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56. FAO, Rome. 1998; 300(9), D05109.
[20].            Wang Y, Yu P, Xiong W, Wang L.Water-Yield Reduction after Afforestation and Related Processes in the Semiarid Liupan Mountains, China. American Water Resources Association. 2008;44(5):1086-1097.
[21].            Yekom Consulting engineering, Implementation of 40 percent reduction in agricultural water consumption in the Zarrine-Rud and Simin-e Hidro rivers basin (case study: Saeen ghalee and miandoab), 2016. [Persian]
Volume 6, Issue 1
April 2019
Pages 125-136
  • Receive Date: 23 August 2018
  • Revise Date: 04 November 2018
  • Accept Date: 04 November 2018
  • First Publish Date: 21 March 2019
  • Publish Date: 21 March 2019