Evaluation and assessment of surface energy balance algorithm for land by Landsat 5 satellite imageries to determine water requirement and water productivity of sugar beet by lysimetric data

Document Type : Research/Original/Regular Article

Authors

1 Assistant Professor/ Soil and Water Research Department, Agricultural and Natural Resources Research Center of Chaharmahal and Bakhtiari Province, Agricultural Research, Education and Extension Organization (AREEO), Shahrekord, Iran

2 Associate Professor/ Irrigation and Soil Physics Department, Soil and Water Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran

3 Expert/ Farokhshahr Agricultural Meteorological Research Center, Shahrekord, Iran

Abstract

Introduction
 
Materials and Methods
This experiment was carried out at the Chahar-Takhteh research station (Shahrekord, Iran) at latitude 50 ̊ 56ʹ and longitude 31̊ 11ʹ, 2066 m above sea level. In the spring of 1996, 1997, and 1998, before planting the crop, the soil inside the lysimeter was irrigated to reach the saturation level. Two days after irrigation and at field capacity, monogram seeds of sugar beet, at the rate of 120,000 crops per hectare, were cropped. The row spacing in the field around the lysimeter was similar. Irrigation was based on the discharge of about 35 to 45 % of the moisture content at field capacity. The required amount of water was calculated by the neutron probe and added to the lysimeter. simultaneously, the surrounding area was also irrigated. Remote sensing data included Landsat 5 satellite images for the years of experiment, path 164, and row 38. The temporal resolution of the satellite was 16 days. Spatial resolution for visible, near, and mid-infrared bands was 30 and 120 m for thermal infrared. The 25 cloud-free images were downloaded (6, 9, and 10 images) for research years. These images were retrieved from the website (https://earthexplorer.usgs.gov) as geometrically and radiometrically corrected and processed in ERDAS Imagine 2022 software. To estimate actual evapotranspiration, the energy balance equation is used, λET=Rn-G0-H. In this equation, Rn is the net incoming radiation flux, H is the sensible heat flux, G0 is the soil heat flux, and λET is the latent heat flux of evaporation (W/m2). The statistical indicators include mean absolute error (MAE) which is unsigned, mean bias error (MBE), root mean square error (RMSE), normalized root mean square error (NRMSE), and Coefficient of Determination (R2).
 
Results and Discussion
Evapotranspiration of sugar beet in lysimeter and in SEBAL on the days of satellite passage in 1996 to 1998 (25 over-passes without clouds) showed that the difference of evapotranspiration in the two methods was -1.20 % and -0.13 mm d-1, which showed high accuracy. The negative sign means that the SEBAL estimates were lower than the corresponding values in the lysimeter. The statistical indices values of RMSE, NRMSE, MAE, and MBE for 25 pairs of evapotranspiration values were 0.7031 mm d-1, 0.1102, 0.5552, and -0.1312, respectively. The RMSE, NRMSE, MAE and MBE statistical indices for 18 pairs of monthly evapotranspiration were 54.1155 mm month-1, 0.3225, 40.9462, and -28.7955, respectively. The total values of evapotranspiration in lysimeter were equal to 1096.6, 1022.6, and 906.3 mm during the growth period (total mean equal to 1040.6 mm) from 1996 to 1998, respectively. The total values of evapotranspiration in the SEBAL were equal to 1004.6, 831.6, and 666.4 mm during the growth period, total mean of 834.2 mm. The mean difference was around 19.8%. The results of mean water productivity were 5.02 kg m-3 in lysimeter and 6.26 kg m-3 in SEBAL. Because of lower evapotranspiration values in SEBAL compared to the lysimeter, the water productivity values were higher.
 
Conclusion
Determining the water requirement of crops is the basis of planning for the sustainable use of water resources and irrigation of crops. The sugar beet has a great amount of evapotranspiration due to its large green cover. Accurate quantification of crop evapotranspiration (ETc) at local and regional scales can help water policy and decision-making in water resources and their management. The results indicated that the SEBAL algorithm using Landsat 5 satellite images with a coefficient of determination (R2=0.9889) in the daily time period and a coefficient of determination (R2=0.9318) in the monthly time period had a good correlation with lysimetric data. In general, results showed that SEBAL has a special capability as one of the widely used remote sensing algorithms to estimate crop evapotranspiration.

Keywords

Main Subjects

References

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Water and Soil Management and Modelling
Volume 3, Issue 2
2023
Pages 251-268

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History

  • Receive Date: 28 November 2022
  • Revise Date: 16 December 2022
  • Accept Date: 16 December 2022

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