Du et al. (2026) Estimation of field-scale crop evapotranspiration from the mechanistic SIF-ET model using the UAV hyperspectral imagery

Identification

• Journal: European Journal of Agronomy
• Year: 2026
• Date: 2026-09-12
• Authors: Ruiqi Du, Yonghong Zhang, Youzhen Xiang, Fucang Zhang, Jian Gao, Qiliang Yang, Xianghui Lu
• DOI: 10.1016/j.eja.2026.128332

Research Groups

• College of Geomatics, Xi'an University of Science and Technology
• First Institute of Photogrammetry and Remote Sensing, MNR
• Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University
• Institute of Resource and Information, Xinjiang Academy of Forestry Science
• Faculty of Modern Agricultural Engineering, Kunming University of Science and Technology
• School of Soil and Water Conservation, Jiangxi University of Water Resources and Electric Power

Short Summary

This study presents a mechanistic SIF-ET model that estimates field-scale crop evapotranspiration using UAV hyperspectral imagery. The model was validated against in-situ measurements across multiple growth stages and water-nitrogen treatments.

Objective

• Estimate field-scale crop evapotranspiration with high spatial-temporal resolution

Study Configuration

• Spatial Scale: Field scale (canola, soybean, and wheat)
• Temporal Scale: Daily to long-term ET dynamics

Methodology and Data

• Models used: SIF-ET model integrated with SCOPE model for SIF retrieval
• Data sources: UAV hyperspectral imagery, in-situ measurements

Main Results

• High-resolution crop canopy SIF740 was retrieved from UAV hyperspectra imagery
• Daily ET estimates from SIF-ET model were validated against in-situ measurements (R²=0.72–0.94, RMSE = 0.04–0.11 mm/d, MAPE = 1.70–5.89%)
• Cumulative ET errors remained within acceptable bounds across repeated UAV observations

Contributions

• Provided support for precision irrigation and rational water-nitrogen management
• Revealed fine-scale cropland ET spatial-temporal heterogeneity under changing environmental conditions

Funding

• This research was funded by the National Natural Science Foundation of China (Grant No. 52109201)

Citation

@article{Du2026Estimation,
  author = {Du, Ruiqi and Zhang, Yonghong and Xiang, Youzhen and Zhang, Fucang and Gao, Jian and Yang, Qiliang and Lu, Xianghui},
  title = {Estimation of field-scale crop evapotranspiration from the mechanistic SIF-ET model using the UAV hyperspectral imagery},
  journal = {European Journal of Agronomy},
  year = {2026},
  doi = {10.1016/j.eja.2026.128332},
  url = {https://doi.org/10.1016/j.eja.2026.128332}
}