Liblab et al. (2026) A dynamic OPTRAM soil moisture constraint for PT-JPL evapotranspiration from Sentinel-2 validated across land covers and climates

Identification

• Journal: Agricultural and Forest Meteorology
• Year: 2026
• Date: 2026-07-21
• Authors: Abderrahman Liblab, Jamal Elfarkh, Nadia Ouaadi, Bouchra Aït Hssaine, said grich, Jamal Ezzahar, Abdelghani Chehbouni
• DOI: 10.1016/j.agrformet.2026.111375

Research Groups

• Center for Remote Sensing Applications (CRSA), University Mohammed VI Polytechnic (UM6P)
• LMFE, Faculty of Sciences Semlalia, Cadi Ayyad University

Short Summary

This study introduces a dynamic soil moisture constraint for the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) evapotranspiration model, validated across diverse land covers and climates using Sentinel-2 data.

Objective

• Investigate the impact of incorporating contextual soil moisture information on PT-JPL evapotranspiration estimates at high spatial resolution.

Study Configuration

• Spatial Scale: 10 m resolution ET mapping
• Temporal Scale: Daily to seasonal timescales

Methodology and Data

• Models used: Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model with Optical Trapezoid Model (OPTRAM) soil moisture constraint
• Data sources: Sentinel-2 satellite data, in situ measurements

Main Results

• The SpatioDynamic Aggregation and Regression (SDAR) algorithm provided a highly stable and transferable soil moisture constraint for PT-JPL, increasing R² by 7%, reducing RMSE by 6.27%, and lowering bias by 71% compared to the static STAR scheme.
• SDAR's superiority was most pronounced over sparsely vegetated surfaces.

Contributions

• This study demonstrates that contextual soil moisture information strengthens PT-JPL evapotranspiration estimates, making them more physically consistent and scale-adaptive.
• The introduction of the SpatioDynamic Aggregation and Regression (SDAR) algorithm enables an automated soil moisture constraint for PT-JPL, overcoming limitations in edge geometry, parameterization strategy, and sensitivity to surface heterogeneity.

Funding

• This research was funded by [project/program name] with reference code [reference code].

Citation

@article{Liblab2026dynamic,
  author = {Liblab, Abderrahman and Elfarkh, Jamal and Ouaadi, Nadia and Hssaine, Bouchra Aït and grich, said and Ezzahar, Jamal and Chehbouni, Abdelghani},
  title = {A dynamic OPTRAM soil moisture constraint for PT-JPL evapotranspiration from Sentinel-2 validated across land covers and climates},
  journal = {Agricultural and Forest Meteorology},
  year = {2026},
  doi = {10.1016/j.agrformet.2026.111375},
  url = {https://doi.org/10.1016/j.agrformet.2026.111375}
}