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Remote sensing based evapotranspiration modeling for sugarcane in Brazil using a hybrid approach

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  • Bispo, R.C.
  • Hernandez, F.B.T.
  • Gonçalves, I.Z.
  • Neale, C.M.U.
  • Teixeira, A.H.C.

Abstract

The increasing pressure on water resources in agricultural areas requires the implementation of innovative tools and solutions to improve irrigation water management. Against that background, this research presents the application of a remote sensing-based methodology for estimating actual evapotranspiration (ETa) based on two-source energy balance model (TSEB) and remote sensing-water balance (RSWB) coupling for sugarcane crop in Brazil using the hybrid model Spatial EvapoTranspiration Modeling Interface (SETMI). Estimated results through SETMI and field data using the eddy covariance system (EC) considering two growing seasons were used to validate the energy balance components and ETa. In addition, the basal crop coefficient as a function of the spectral reflectance (Kcbrf) was developed through the soil-adjusted vegetation index (SAVI) and observed ET. Modeled energy balance components showed a strong correlation to the ground data from EC, with ET presenting R2 equal to 0.94 and a Pearson correlation coefficient (ρ) equal to 0.88. Regarding Kcbrf, the Kcb-SAVI relationship for sugarcane presented a high correlation with an R2 value of 0.85 and an "ρ" equal to 0.92. On average, considering the whole season, Kcb was equal to 0.75 and 0.73 for the 4th ratoon and 5th ratoon, respectively. Overall, the average Kc throughout the period was 0.73 and 0.70 for the 4th and 5th ratoons respectively, and the maximum Kc of about 1.23 for both growing seasons. On average, accumulated ETa presented 1025 mm resulting in ETa rates of 2.9 mm per day considering the two seasons. Crop water productivity (WP) obtained values similar between the seasons, averaging 12.6, 21.7, and 12.3 kg m−3 for WPp+i, WPi and WPET, respectively. The SETMI hybrid model produced suitable estimated daily ETa values over the two growing seasons through remote sensing based on the Kcb-SAVI relationship and good performance of TSEB model during the evaluated growing periods confirming the applicability of the model under tropical conditions in Brazil focusing on improving irrigation management in sugarcane crop.

Suggested Citation

  • Bispo, R.C. & Hernandez, F.B.T. & Gonçalves, I.Z. & Neale, C.M.U. & Teixeira, A.H.C., 2022. "Remote sensing based evapotranspiration modeling for sugarcane in Brazil using a hybrid approach," Agricultural Water Management, Elsevier, vol. 271(C).
    • Handle: RePEc:eee:agiwat:v:271:y:2022:i:c:s0378377422003109
    DOI: 10.1016/j.agwat.2022.107763
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    1. Gonçalves, I.Z. & Ruhoff, A. & Laipelt, L. & Bispo, R.C. & Hernandez, F.B.T. & Neale, C.M.U. & Teixeira, A.H.C. & Marin, F.R., 2022. "Remote sensing-based evapotranspiration modeling using geeSEBAL for sugarcane irrigation management in Brazil," Agricultural Water Management, Elsevier, vol. 274(C).
    2. M. Babaei & H. Ketabchi, 2022. "Determining Groundwater Recharge Rate with a Distributed Model and Remote Sensing Techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(14), pages 5401-5423, November.

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