Evaluation of Evapotranspiration Using Satellite Images and SEBAL Algorithm (Case Study: Eastern Azerbaijan Province)

Document Type : Research Article

Authors

1 Ph.D. in Agricultural Climatology, Hakim Sabzevari University, Iran

2 Assistant Professor of Climatology, Hakim Sabzevari University, Iran

Abstract

Evaluation of evapotranspiration is one way to prevent water loss and to manage water resources. Therefore, in this study, an attempt has been made to calculate the actual evapotranspiration rate in the east of East Azerbaijan province using the SEBAL algorithm. For this purpose, first, based on two Landsat 8 satellite images dated 2017/08/22 and 2017/08/09, the values of Net radiation, soil heat flux, and sensible heat flux are estimated. Then, based on the difference, the amount of instantaneous heat flux was calculated and a 24-hour evapotranspiration was obtained for each image. Finally, the amount was compared with the values obtained from the Penman-Monteith method. Also, for processing and analyzing images ENVI4.8 software was used. The results indicated that the amount of evapotranspiration in the Penman-Monteith and SEBAL method on 2017/08/22 was about 6.15 and 7 mm per day, and on 2018/08/09, respectively, about 7.38 for Penman-Monty and 7.94 mm per day for SEBAL. Overall, the amounts of SEBAL actual evapotranspiration and Penman-Monteith potential evapotranspiration have a mean absolute difference (MAD) 0.705 mm per day which indicates that the estimated values are consistent with the SEBAL algorithm and the Penman-Monteith method.

Keywords

References

[1]. Gao Y, Long D, Li Z. Estimation of daily evapotranspiration from remotely sensed data under complex terrain over the upper Chao river basin in north China. International Journal of Remote Sensing. 2008; 29(11): 3295-3315.
[2]. Omidvar J. Noori S, Davar K, Sanaei-Nejad H, Farid hosseini A. Estimation of actual evapotranspiration based on satellite images using two algorithms SEBAL and Metric, Journal irrigation engineering and water. 2013; 3(12): 11-22 [Persian].
[3]. Hejazizadeh Z, bazmi N, Rahimi A, Toulabi Nejad M, Bosak A. Modeling of spatio-temporal of albedo over Iran. Researches in Geographical Sciences. 2017; 17 (47): 1-17.
[4]. Bastiaanssen WGM, Menenti M, Feddes RA, Holtslag AAM. Remote sensing surface energy balance algorithm for land (SEBAL):1 Formulation. Journal of hydrology. 1998; 212: 198-212.
[5]. Allen RG, Tasumi M, Trezza R. Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC) model. Journal of irrigation and drainage engineering. 2007; 133(4): 380-394.
[6]. Disney M, Lewis P, Thackrah G, Quaife T, Barnsley M. Comparison of MODIS broadband albedo over an agricultural site with ground measurements and values derived from Earth observation data at a range of spatial scales. International Journal of Remote Sensing. 2004; 25(23): 5297-5317.
[7]. Chang Y, Ding Y, Zhao Q, Zhang S. Remote estimation of terrestrial evapotranspiration by Landsat 5 TM and the SEBAL model in cold and high‐altitude regions: a case study of the upper reach of the Shule River Basin, China. ydrological processes. 2017; 31(3): 514-524.
[8]. Grosso C, Manoli G, Martello M, Chemin YH, Pons DH, Teatini P, Piccoli I, Morari F. Mapping maize evapotranspiration at field scale using SEBAL: A comparison with the FAO method and soil-plant model simulations. Remote Sensing. 2018; 10(9): 1452.
[9]. Elnmer A, Khadr M, Kanae S, Tawfik A. Mapping daily and seasonally evapotranspiration using remote sensing techniques over the Nile delta. Agricultural Water Management. 2019; 213: 682-692.
[10].            Ghaderi A, Dasineh M, Shokri M, Abraham J. Estimation of Actual Evapotranspiration Using the Remote Sensing Method and SEBAL Algorithm: A Case Study in Ein Khosh Plain, Iran. Hydrology. 2020; 7(2): 36.
 
[11].            Bhattarai N, Shaw SB, Quackenbush LJ, Im J, Niraula R. Evaluating five remote sensing based single-source surface energy balance models for estimating daily evapotranspiration in a humid subtropical climate. International Journal of Applied Earth Observation and Geoinformation. 2016; 49: 75-86.
[12].            Mahmoud SH, Alazba AA. 2016. A coupled remote sensing and the Surface Energy Balance based algorithms to estimate actual evapotranspiration over the western and southern regions of Saudi Arabia. Journal of Asian Earth Sciences. 2016; 124: 269-283.
[13].            Singh RK, Irmak A, Irmak S, Martin DL. Application of SEBAL model for mapping evapotranspiration and estimating surface energy fluxes in south-central Nebraska. Journal of Irrigation and Drainage Engineering. 2008; 134(3): 273-285.
[14].            Zhang SW, Lei YP, Li HJ, Wang Z. Temporal-spatial variation in crop evapotranspiration in Hebei Plain, China. Journal of Food, Agriculture and Environment. 2010; 8(2): 672-677.
[15].            Zamansani, E., khoorani, A., Sadeghi-e-lari, A., Sadidi, J. Evaluation of evapotranspiration of wheat using SEBAL algorithm (Case study: Agricultural Research Station of Haji Abad). Physical Geography Research Quarterly, 2017; 49(4): 667-681.
[16].            Badiehneshin, A., Parsinejad, M., Noory, H. Evaluation of the different levels of water supply in pistachio gardens using SEBAL algorithm (The case study of Sirjan Plain). Journal of Soil and Water Resources Conservation, 2019; 9(1): 67-86.
[17].            Asadi M, Valizadeh khamran K, Baaghdeh M, Adab H. Comparison and Estimation of Surface Albedo of Various Levels of Land use by SEBAL and METRIC Methods. Researches in Geographical Sciences. 2021; 20 (59): 157-171.
[18].            Asadi, M., Valizadeh Kamran, K., Baaghideh, M., Adab, H. Estimation of Actual Evapotranspiration by Mountain SEBAL Algorithm Based on Pea Plants (Case Study: Semi-Northern Half of Ardabil Province). 2020; 6(22): 67-85.
[19].            Choudhury FJ, Idso SB, Reginato RJ. 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(4): 283-297.
[20].            Jackson RD. Remote sensing of vegetation characteristics for farm management. International Society for Optics and Photonics. 1984; 475: 81–96.
[21].            Park AB, Colwell RN, Meyers VF. Resource survey by satellite; science fiction coming true. Yearbook of Agriculture; 1968.
[22].            Brown KW, Rosenberg NJ. A resistance model to predict evapotranspiration and its application to a sugar beet field. Agronomy Journal. 1973; 65(3): 341-347.
[23].            Brown KW. Calculations of evapotranspiration from crop surface temperature. In Developments in Agricultural and Managed Forest Ecology. 1974; 1: 199-209.
[24].            Heilman JL, Kanemasu ET, Rosenberg NJ, Blad BL. Thermal scanner measurements of canopy temperatures to estimate evapotranspiration. Remote Sensing Environ. 1976; 5: 137–145.
[25].            Idso SB, Schmugge TJ, Jackson RD, Raginato RJ. The utility of surface temperature measurements for the remote sensing of the soil water status. ournal of Geophysical Research. 1975; 80(21): 3044-3049.
[26].            Jackson RD, Reginato RJ, Idso SB. Wheat canopy temperature: a practical tool for evaluating water requirements. Water resources research. 1977; 13(3): 651-656.
[27].            Kanemasu ET, Stone LR, Powers WL. Evapotranspiration model tested for soybeans and sorghum. Agronomy Journal. 1977; 68(4): 569-572.
[28].            Verma SB, Rosenberg NJ, Blad BL, Baradas MW. Resistance‐energy Balance Method for Predicting Evapotranspiration: Determination of Boundary Layer Resistance and Evaluation of Error Effects 1. Agronomy Journal. 1976; 68(5):776-82.
[29].            Allen R, Pereira L, Raes D, Smith M. Crop evapotranspiration: guidelines for computing crop water requirements. FAO Irrigation and Drainage Paper No. 56. FAO, Rome; 1998.
[30].            Jackson RD, Pinter PJ, Reginato RJ. Net radiation calculated from remote multispectral and ground station meteorological data. Agricultural and forest Meteorology. 1985; 35(1-4): 153-164.
[31].            Bastiaanssen WGM, Pelgrum H, Wang J, Ma Y, Moreno JF, Roerink GJ, vanderwal T. A remote sensing surface energy balance algorithm for land (SEBAL): 2. Validation. Journal of Hydrology. 1998; 212: 213-229.
[32].            Duffie JA, Beckman WA, Blair N. Solar engineering of thermal processes, photovoltaics and wind. John Wiley & Sons; 2020.
[33].            Bastiaanssen WGM. SEBAL-based sensible and latent heat fluxes in the irrigated Gediz Basin, Turkey. Journal of Hydrology. 2000; 229: 87-100.
[34].            Yang Y, Shang S, Jiang L. Remote sensing temporal and spatial patterns of evapotranspiration and the responses to water management in a large irrigation district of North China. Agricultural and Forest Meteorology. 2012; 164:112-22.
[35].            Karami M, Asadi M. Estimates and Zoning of reference evapotranspiration by FAO-Penman-Monteith (Case Study: North West of Iran). International Journal of Scientific Research in Science, Engineering and Technology. 2016; 2(1): 210-216.
 
[36].            Horiguchi I. Agricultural Meteorology. Buneidou, Tokyo, Japan; 1992.
[37].            Ramos JG, Cratchley CR, Kay JA, Casterad MA, Martinez-cob A, Dominguez, R. 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. 2009; 96: 638-652.
[38].            Kiptala JK, Mohamed Y, Mul ML, Zaag P. Mapping evapotranspiration trends using MODIS and SEBAL model in a data scarce and heterogeneous landscape in Eastern Africa. Water resources research. 2013; 49(12): 8495-8510.
Iranian journal of Ecohydrology
Volume 8, Issue 1
April 2021
Pages 17-27

Files

History

  • Receive Date: 12 August 2020
  • Revise Date: 20 December 2020
  • Accept Date: 20 December 2020
  • First Publish Date: 08 March 2021
  • Publish Date: 21 March 2021

Share

How to cite

Statistics