Estimation of Real Evapotranspiration of Wheat and Rapeseed Using SEBAL Algorithm (Case Study: Esmaeil Abad Agricultural Research Station in Qazvin Province)

Younesi, Mahdi; Mashal, Mahmoud; Yousef Gomrokchi, Afshin

doi:10.22059/ije.2022.339191.1609

Estimation of Real Evapotranspiration of Wheat and Rapeseed Using SEBAL Algorithm (Case Study: Esmaeil Abad Agricultural Research Station in Qazvin Province)

Document Type : Research Article

Authors

¹ .Sc. Student of Irrigation and Drainage, Department of Irrigation and Drainage Engineering, College of Aburaihan, University of Tehran, Tehran, Iran

² Department of Irrigation and Drainage Engineering, College of Aburaihan, University of Tehran, Tehran, Iran

³ Agricultural Engineering Research Department, Qazvin Agricultural and Natural Resources Research and Education Center, AREEO, Qazvin, Iran

10.22059/ije.2022.339191.1609

Abstract

Evapotranspiration is a complex phenomenon that depends on many factors and data, so determining it is very difficult and costly. In most methods mainly aimed at estimating evapotranspiration, point measurements have been used to estimate this variable. Therefore, it is only suitable on a local scale and cannot be extended to large basins due to the dynamics and regional changes of evapotranspiration (ET). One of the remote sensing algorithms for estimating real evapotranspiration is the Surface Energy Balance Algorithms for Land (SEBAL). In this algorithm, by estimating all energy components on the land surface such as pure radiation flux, soil heat flux, and tangible heat flux, using the energy balance equation, evapotranspiration is used. The aim of this study is to compare the estimation of real evapotranspiration using SEBAL algorithm in wheat and rapeseed crops with the results of estimating evapotranspiration by Penman-Monteith-FAO method in the field of Esmaeil Abad Agricultural Research Station in 2019-2020. Single-sample T-test of ground surface temperature reflection index showed that the spectral reflection of wheat and rapeseed crops during phenological growth period had a significant difference. The results showed that the computational values of the two models are relatively good and the mean value of square root of error (RMSE) in estimating real evapotranspiration for wheat and rapeseed plants was 3.04 and 2.09 mm/day, respectively, and the coefficient of explanation (R2) was 0.78 and 0.81, respectively. The results showed that SEBAL algorithm model in comparison with Penman-Monteith-FAO model (based on up-to-date meteorological data) The amount of evapotranspiration for wheat and rapeseed plants is lower.

Keywords

References

Niroumand HA. Applied multivariate statistical analysis. Mashhad: Ferdowsi University of Mashhad; 1999 [Persian].
Karimi AR. Evaluation of remote sensing algorithms (SEBAL and SEBS) for calculation of evapotranspiration using satellite images. MSc. Thesis, Razi University, Kermanshah, 105 pages. 2011. [Persian].
Bastiaanssen W, Ahmad MD, Chemin Y. Satellite surveillance of evaporative depletion across the Indus Basin. Water Resources Research. 2002: 38(12): 1273–1281.
Ramos JG, Cratchley CR, Kay J, Casterad M A, Martínez -Cob A, Dominguez R. Evaluation of satellite evapotranspiration estimates using ground -meteorological data available for the Flumen District into the Ebro Valley of NE Spain. Agricultural water management. 2009; 96(4): 638 -652.
Awada H, Di Prima S, Sirca C, Giadrossich F, Marras S, Spano D, et al. Daily Actual Evapotranspiration Estimation in a Mediterranean Ecosystem from Landsat Observations Using SEBAL Approach. Forests. 2021; 12(189): 1-20.
Li X, Xu X, Wang X, Xu S, Tian W, Tian J, et al. Assessing the Effects of Spatial Scales on Regional Evapotranspiration Estimation by the SEBAL Model and Multiple Satellite Datasets: A Case Study in the Agro-Pastoral Ecotone, Northwestern China. Remote Sensing. 2021; 13(1524): 1-22.
Karimi A, Farhadi Bansouleh B, Hesadi H. Estimation of Regional Evapotranspiration Using LANDSAT TM Images and SEBAL Algorithm. Iranian Journal of lrrigation and Drainage. 2013; 4(6): 353-364 [Persian].
Khoshnavaz F, Honar T, Daneshkar Arasteh P. Estimation of Agricultural Water Productivity Using Remote Sensing Technology (Case Study: Qazvin Plain Irrigation Network). Water and Soil Science. 2015: 25(1-4): 57-68 [Persian].
Karbasi M, Moghadam M, Nikbakht J, Kaviani A. Estimation of Crop Actual Evapotranspiration Using SEBAL Algorithm (Case study: Khoramdareh Region at Zanjan province). Iranian Journal of Ecohydrology. 2017; 3(3): 427-437 [Persian].
Malekpour M, Babazadeh H, Kaveh F, EbrahimiPak NA. Estimation of Actual Evapotranspiration and Water Productivity of Wheat Using SEBAL Algorithm and Landsat 5TM Images. Journal of Water Research in Agriculture. 2017; 30(4): 569-582 [Persian].
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). 2018; 49(4): 667-681 [Persian].
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(36): 1-14.
Mahmodzadeh E, Anvari S. Verification of Estimated Evapotranspiration by Surface Energy Balance Algorithm for Land and the Information of OLI and TIRS Sensors. Watershed Engineering and Management. 2021; 13(1): 150-159 [Persian].

Farshi AA, Shariati MR, Jarollahi R, Ghaemi MR, Shahabifar M, Tavallaei MM. An Estimate of Water Requirement of Main Field Crops and Orchards in Iran. 1 edition. Karaj: Agricultural Education and Extension Research Organization.1997 [Persian].
Moayeri M. Determination of Water Requirement and Comprehensive Irrigation Management of Rapeseed Farms. Institute of Agricultural Engineering and Technical Research, Agricultural Education and Extension Research Organization. 2019 [Persian].
Rouse J, Haas R, Schell J, Deering D. Monitoring Vegetation Systems in the Great Plains with ERTS. Third ERTS Symposium NASA. 1973; 309-317.
Boegh E, Soegaard H, Broge N, Hasager CB, Jensen NO, Schelde K, et al. Airborne multispectral data for quantifying leaf area index, nitrogen concentration, and photosynthetic efficiency in agriculture. Remote Sensing of Environment. 2002; 81: 179-193.
Faris Beg AA, Al-Sulttani AH, Ochtyra A, Jarocińska A, Marcinkowsk A. Estimation of Evapotranspiration Using SEBAL Algorithm and Landsat-8 Data-A Case Study: Tatra Mountains Region. Journal of Geological Resource and Engineering. 2016; 6: 257-270.
Ihlen V, Zanter K. Landsat 8 (L8) Data Users Handbook. Department of the Interior. U.S. Geological Survey. Version 5.0. 2019.
Alizadeh A. Soil, Water, Plant Relationship. 14^th Mashhad: Sadjad University; 2014 [Persian].
Allen R, Tasumi M, Trezza R. SEBAL (Surface Energy Balance Algorithms for Land) Advanced Training and User’s Manual. Idaho Implementation, Version 1.0. 2002.
Bastianssen WGM. 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. 1995
Papadavid G, Hadjimitsis D, Toulios L, Michaelides S. A Modified SEBAL Modeling Approach for Estimating Crop Evapotranspiration in Semi -arid Conditions. Water Resources Management. 2013; 27(9): 3493 -3506.
Kaviani A, Sohrabi T, Daneshkar Arasteh P. Evapotranspiration and Water Productivity Estimation Using SEBAL Algorithm and Comparison With Lysimeter Data. Iranian Journal of Irrigation and Drainage. 2011; 5(2): 165-175 [Persian].
Kaviani A, Sohrabi T, Daneshkar Arasteh P. Estimation of Agricultural Water Productivity in Qazvin Plain Using MODIS, AVHRR Images and Lysimeter Data. Iranian Water Researches Journal. 2013; 7(2): 1-10 [Persian].
Abdollahi Dehaki Z. Study of Irrigation Adequacy and Determination of Irrigated Area of Qazvin Network Using Satellite Imagery and SEBAL Algorithm. MSc. Thesis, Imam Khomeini International University, Qazvin, 115 pages. 2015 [Persian].
Nazari R, Kaviani A. Evaluation of the Results of Evapotranspiration Estimation of Grass Reference Plant Using METRIC and SEBAL Models in Qazvin Plain. Journal of Water Research in Agriculture. 2016; 30(2): 187-199 [Persian].
Firuzi NezamAbadi F, Kaviani A, Moghadasi M, BahmanAbadi B. Comparison Result of Evaluating Actual Evapotranspiration of Crops and Orchards by SEBS and SEBAL Algorithms (Case study: Qazvin plain). Iranian Journal of Irrigation and Drainage. 2019; 12(5): 1266-1280 [Persian].
Allen RG, Morse A, Tasumi M, Trezza R, Bastiaanssen W, Wright JL, et al. Evapotranspiration from a satellite -based surface energy balance for the Snake Plain Aquifer in Idaho. Proc. USCID Conference. 2002.
Khodarahmi Z, EbrahimiPak NA. Determining the water requirement of wheat in the Qazvin plain by using plant coefficient in real conditions and comparing the results with lysimeter data and the country's national water document. The 11^th International Seminar on Irrigation and Evaporation Reduction. Shahid Bahonar University of Kerman, Kerman, Iran. 2011 [Persian].
Zare Abyaneh H, Heidari A, Daneshkar Arasteh P. Evaluation of Water Management Performance in Irrigation Network of Qazvin Plain. Journal of Irrigation and Water Engineering. 2020, 10(2): 76-88 [Persian].