Improved estimates of GNSS-inverted TWS through a benchmarking approach: a case study for the Seine river basin

Abstract We use the vertical displacements of 331 Global Navigation Satellite System (GNSS) antennas provided by the Nevada Geodetic Laboratory (NGL) between April 2002 and May 2022 and located in the European Seine River basin. We invert these displacements using elastic loading theory for changes in Terrestrial Water Storage (TWS). We adopt a benchmarking approach to classify GNSS stations as reliable for estimating TWS changes on two pre-defined temporal-scales: seasonal and long-term. We find 302 and 183 of the 331 GNSS stations to be reliable for seasonal and long-term temporal-scales, respectively, and then use them for GNSS inversion. We compare the GNSS-inverted TWS using the benchmarking approach with initial and common approaches that use all available and pre-selected set of GNSS stations for inversion, respectively. We show that the GNSS-inverted TWS using the benchmarking approach is most consistent with ERA5-Land TWS in the western part of the basin, where the densest network of GNSS stations is available. It also detects long-lasting droughts reported earlier with great reliability, providing an alternative to hydrological models. We then recommend for future hydrogeodetic studies to benchmark the GNSS stations for the two temporal-scales, which will improve the comparison with other datasets, enhancing the interpretation of long-term and seasonal hydrological events.

Authors

Institutions

Publication Details

Journal
GPS Solutions
Published
2026-05-22
DOI
https://doi.org/10.1007/s10291-026-02090-0
Primary Topic
GNSS positioning and interference
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Improved estimates of GNSS-inverted TWS through a benchmarking approach: a case study for the Seine river basin

Donald F. Argus, Jan Mikocki, Janusz Bogusz, Artur Lenczuk et al.
GPS Solutions
GNSS positioning and interference
article

Improved estimates of GNSS-inverted TWS through a benchmarking approach: a case study for the Seine river basin

Donald F. Argus, Jan Mikocki, Janusz Bogusz, Artur Lenczuk, Anna Klos
article en

Abstract

Abstract We use the vertical displacements of 331 Global Navigation Satellite System (GNSS) antennas provided by the Nevada Geodetic Laboratory (NGL) between April 2002 and May 2022 and located in the European Seine River basin. We invert these displacements using elastic loading theory for changes in Terrestrial Water Storage (TWS). We adopt a benchmarking approach to classify GNSS stations as reliable for estimating TWS changes on two pre-defined temporal-scales: seasonal and long-term. We find 302 and 183 of the 331 GNSS stations to be reliable for seasonal and long-term temporal-scales, respectively, and then use them for GNSS inversion. We compare the GNSS-inverted TWS using the benchmarking approach with initial and common approaches that use all available and pre-selected set of GNSS stations for inversion, respectively. We show that the GNSS-inverted TWS using the benchmarking approach is most consistent with ERA5-Land TWS in the western part of the basin, where the densest network of GNSS stations is available. It also detects long-lasting droughts reported earlier with great reliability, providing an alternative to hydrological models. We then recommend for future hydrogeodetic studies to benchmark the GNSS stations for the two temporal-scales, which will improve the comparison with other datasets, enhancing the interpretation of long-term and seasonal hydrological events.

GPS SolutionsVol. 30(3)
Jet Propulsion Laboratory (US), Military University of Technology in Warsaw (PL)
Narodowe Centrum Nauki
Life below water
Openalex Percentile: Top 2%
GNSS positioning and interference
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.