Thu Aug 14, F. Flechtner
• Sorted by Date • Sorted by Last Name of First Author •
de Moura Almeida, Yellinson and Sant'Anna Marotta, Giuliano, 2025. Exploring relationships between GNSS time series, terrestrial water storage and geological features in Brazil. Journal of South American Earth Sciences, 164:105686, doi:10.1016/j.jsames.2025.105686.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2025JSAES.16405686D,
author = {{de Moura Almeida}, Yellinson and {Sant'Anna Marotta}, Giuliano},
title = "{Exploring relationships between GNSS time series, terrestrial water storage and geological features in Brazil}",
journal = {Journal of South American Earth Sciences},
year = 2025,
month = oct,
volume = {164},
eid = {105686},
pages = {105686},
abstract = "{The heterogeneous distribution of precipitation, demographic variability
and anthropogenic factors influence water storage in different
ways in Brazil. The climatic and geological complexity of Brazil
makes it difficult to monitor water reserves. Therefore, studies
in the field of hydrogeodesy have increased considerably. Among
the techniques used are positioning by GNSS (Global Navigation
Satellite Systems) and satellite gravimetry. This study aims to
evaluate how geological characteristics, throughout the
Brazilian territory, influence the correlation between GNSS time
series and total water storage, from the GRACE-FO mission.
Correlations for the seasonal and trend components were
estimated at 108 stations distributed throughout the Brazilian
territory. Trends were estimated by linear regression and
singular spectral analysis. The trend estimated by SSA presented
lower RMSE in more than 90\% of the stations studied.
Correlations were assessed in relation to the geological
characteristics of each station. It was possible to establish
good correspondence between GNSS and GRACE data, observed by
clustering nearby stations. However, differences observed at
nearby stations can be attributed, in part, to geological
characteristics of each station, as can be observed in the
Paraguay Hydrographic Region. In addition, seasonal correlations
between the data also allow identifying regions where the
behavior of the surface to the hydrological load is poroelastic
or elastic, such as part of the S{\~a}o Francisco Hydrographic
Region and the Tiet{\^e} Basin, respectively.}",
doi = {10.1016/j.jsames.2025.105686},
adsurl = {https://ui.adsabs.harvard.edu/abs/2025JSAES.16405686D},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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