Jiang et al. (2026) Comparison and Evaluation of Multi-Source Evapotranspiration Datasets in the Yarlung Zangbo River Basin

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Remote Sensing
• Year: 2026
• Date: 2026-01-04
• Authors: Yao Jiang, Zihao Xia, Lvyang Xiong, ZongXue Xu
• DOI: 10.3390/rs18010162

Research Groups

The specific research group(s) of the authors are not explicitly provided in the text.

Short Summary

This study compared various multisource remote sensing, machine learning, and reanalysis evapotranspiration (ET) datasets for the Yarlung Zangbo River basin (YZB) against a terrestrial water balance (TWB)-based ET baseline to assess their applicability and reliability. It found that GLASS-ET and GLEAM-ET performed most reliably across spatial and temporal aspects for ET research in the YZB.

Objective

• To evaluate the applicability and reliability of multisource remote sensing, machine learning, and reanalysis evapotranspiration (ET) datasets in the Yarlung Zangbo River basin (YZB) by comparing them against a terrestrial water balance (TWB)-based ET estimate.

Study Configuration

• Spatial Scale: Yarlung Zangbo River basin (YZB)
• Temporal Scale: Multi-year, focusing on annual variations and temporal trends.

Methodology and Data

• Models used: Terrestrial Water Balance (TWB) was used to estimate baseline ET for comparison.
• Data sources:
  • Multisource remote sensing ET datasets: GLEAM, MOD16, GLASS, PML-V2, Han, Chen, Ma.
  • Machine learning ET dataset: Jung.
  • Reanalysis products: ERA5-Land, MERRA2.

Main Results

• Terrestrial Water Balance (TWB)-based ET estimates were deemed rational with acceptable uncertainties.
• Multi-source ET datasets showed good correlations with TWB-ET across the entire basin in terms of annual variation (correlation coefficient, r = 0.78–0.90).
• GLEAM-ET exhibited the best performance for annual variation (r = 0.88, Root Mean Square Error (RMSE) = 14.24 mm, Relative Bias (Rbias) = 18.55%).
• Spatially, PML-ET and Ma-ET demonstrated higher consistency with TWB-ET.
• Temporally, MOD16-ET and GLASS-ET better captured the changing trends.
• A comprehensive evaluation using a linear weighted method indicated that GLASS-ET and GLEAM-ET performed relatively well across all aspects, identifying them as reliable datasets for ET research in the YZB.

Contributions

• Provides a comprehensive evaluation of various ET datasets specifically for the Yarlung Zangbo River basin, a complex hydrological region.
• Offers a scientific basis for the selection of appropriate ET datasets for hydrological research and ET analysis in the YZB.
• Establishes the reliability of GLASS-ET and GLEAM-ET as suitable datasets for the region.

Funding

Funding information is not provided in the paper text.

Citation

@article{Jiang2026Comparison,
  author = {Jiang, Yao and Xia, Zihao and Xiong, Lvyang and Xu, ZongXue},
  title = {Comparison and Evaluation of Multi-Source Evapotranspiration Datasets in the Yarlung Zangbo River Basin},
  journal = {Remote Sensing},
  year = {2026},
  doi = {10.3390/rs18010162},
  url = {https://doi.org/10.3390/rs18010162}
}