Mon Dec 15, F. Flechtner
• Sorted by Date • Sorted by Last Name of First Author •
Yoo, Sanghyun, Kim, Seokhyeon, and Paik, Kyungrock, 2024. Optimal combinations of global evapotranspiration and terrestrial water storage products for catchment water balance. International Journal of Remote Sensing, 45(9):2865–2892, doi:10.1080/01431161.2024.2339198.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2024IJRS...45.2865Y,
author = {{Yoo}, Sanghyun and {Kim}, Seokhyeon and {Paik}, Kyungrock},
title = "{Optimal combinations of global evapotranspiration and terrestrial water storage products for catchment water balance}",
journal = {International Journal of Remote Sensing},
keywords = {Water Balance, GRACE, Hydrological Modelling, Evapotranspiration},
year = 2024,
month = may,
volume = {45},
number = {9},
pages = {2865-2892},
abstract = "{During the last two decades, a great number of global products about
evapotranspiration () and terrestrial water storage () have been
released. This has led to numerous combinations for describing
catchment water balance, and hence determining an appropriate
combination has become an important issue. The main objective of
this study is to evaluate various global products of and at
the catchment scale and determine the most appropriate
combination, taking two Korean catchments as examples. For , we
evaluated global evapotranspiration (Global ET), Global Land
Evaporation Amsterdam Model (GLEAM), and
Penman{\textendash}Monteith{\textendash}Leuning (PML). For , six
individual datasets of Gravity Recovery and Climate Experiment
(GRACE) were evaluated, with Global Land Data Assimilation
System (GLDAS) products used for comparison. We found that the
performance is sensitive to the choice of product while various
products displayed minimal differences in results. Based on four
evaluation criteria, the combination of PML and GRACE-SH-GFZ is
suggested as the most suitable pair. For the period between 2003
and 2013, these data exhibit noteworthy trends of increasing ,
offset by decreasing . Warming climate is suspected to be behind
these trends. Our research presents an approach that allows for
the estimation of monthly streamflow exclusively with global
data products, which is an advancement in hydrological analysis
and particularly useful for regions that lack in-situ data
networks. This approach provides a new perspective in the
application of global datasets for the assessment of water
balance and could significantly improve predictions in ungauged
basins.}",
doi = {10.1080/01431161.2024.2339198},
adsurl = {https://ui.adsabs.harvard.edu/abs/2024IJRS...45.2865Y},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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