Mon Feb 16, F. Flechtner
• Sorted by Date • Sorted by Last Name of First Author •
Jiang, Yao, Xia, Zihao, Xiong, Lvyang, and Xu, Zongxue, 2026. Comparison and Evaluation of Multi–Source Evapotranspiration Datasets in the Yarlung Zangbo River Basin. Remote Sensing, 18(1):162, doi:10.3390/rs18010162.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2026RemS...18..162J,
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},
keywords = {evapotranspiration, terrestrial water balance, evapotranspiration products, GRACE, performance evaluation},
year = 2026,
month = jan,
volume = {18},
number = {1},
eid = {162},
pages = {162},
abstract = "{What are the main findings? By comparing ten different ET datasets with
ET estimates derived from the terrestrial water balance method
in terms of spatiotemporal variations across the Yarlung Zangbo
River basin, it was found that GLASS-ET and GLEAM-ET perform
relatively well, whereas Han-ET and Chen-ET exhibits greater
discrepancies in these aspects. By comparing ten different ET
datasets with ET estimates derived from the terrestrial water
balance method in terms of spatiotemporal variations across the
Yarlung Zangbo River basin, it was found that GLASS-ET and
GLEAM-ET perform relatively well, whereas Han-ET and Chen-ET
exhibits greater discrepancies in these aspects. What is the
implication of the main finding? Potential weaknesses are
present in all ET datasets within high-altitude regions with
complex terrain. The performance of ET datasets is highly
dependent on the regional characteristics, algorithms and
forcing data accuracy. Potential weaknesses are present in all
ET datasets within high-altitude regions with complex terrain.
The performance of ET datasets is highly dependent on the
regional characteristics, algorithms and forcing data accuracy.
Evapotranspiration (ET) data products has greatly facilitated
the hydrological research in complex basins, and various ET
datasets have been produced and applied. The applicability and
reliability of ET dataset is significant for regional studies.
Therefore, this study compared ET datasets from multisource
remote sensing (GLEAM, MOD16, GLASS, PML-V2, Han, Chen and Ma),
machine learning (Jung) and reanalysis products (ERA5-Land,
MERRA2) for the Yarlung Zangbo River basin (YZB). ET was
estimated using the terrestrial water balance (TWB) and was
taken as baseline for comparisons of different ET datasets in
terms of spatial distribution and temporal variation. Results
indicate that (1) the TWB-based ET estimates are rational with
acceptable uncertainties; (2) the multi-source ET datasets
exhibit good correlations with TWB-ET across the entire basin (r
= 0.78─0.90) in term of annual variation, with GLEAM-ET
performing the best (r = 0.88, RMSE = 14.24 mm, Rbias =
18.55\%); (3) Spatially, PML-ET and Ma-ET show higher
consistency with TWB-ET, and temporally, MOD16-ET and GLASS-ET
better capture the changing trend; (4) A comprehensive
evaluation using the linear weighted method reveals that GLASS-
ET and GLEAM-ET perform relatively well in all aspects and are
reliable datasets for ET research in the YZB. These findings
provide a scientific basis for ET estimation and data selection
in the YZB, offering important references for ET analysis and
hydrological research.}",
doi = {10.3390/rs18010162},
adsurl = {https://ui.adsabs.harvard.edu/abs/2026RemS...18..162J},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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