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Near real-time altimetry for river monitoring—a global assessment of Sentinel-3
Abstract
For applications such as weather, flood, and drought forecasting that need water level estimates as soon as possible, near real-time (NRT) products are most appropriate. Unlike in-situ sensors for water level measurements, which typically deliver NRT data, satellite altimeters deliver physically meaningful observations with substantial delays after acquisition. The new radar altimetry mission, Sentinel-3, is capable of delivering NRT water levels within a few hours of observation. Currently, it remains unexplored how accurate the NRT product is in the context of river monitoring. This study assesses Sentinel-3A/B NRT products in mapping river water level variations globally. Based on a three-year comparison, we find that the water level derived from NRT is almost as good as that from the delayed products (median root-mean-square error (RMSE): 21.5 cm and 23.5 for S3A and S3B), and both products achieve very similar RMSE values (median: 52.5 cm and 59.0 cm for NRT and non-time critical) against in-situ data at 25 locations. This study highlights the usefulness of Sentinel-3 NRT product for river monitoring and forecasting. And we recommend the NRT product if latency is a primary concern.
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“Errors typically range between a few centimeters to a few tens of centimeters for the currently flying nadir missions of the Copernicus program68,69, while they range more around several tens of centimeters to one meter for the historical missions70,71.”
From Global scale river discharge and mean depth from radar altimetry and model (2026) · cites this paper as [69]
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Cited by
Global scale river discharge and mean depth from radar altimetry and model
Paris, A., Garambois, P.-A., Gal, L., Cerbelaud, A., Larnier, K., David, C. H., Jucá Oliveira, R. A., Correa, S. W., Tourian, M. J., & Calmant, S. (2026) · Nature Communications · doi:10.1038/s41467-026-78275-5
Metadata
- Authors
- Jiang, L., Zhao, Y., Nielsen, K., Andersen, O. B., & Bauer-Gottwein, P.
- ORCID
- Jiang, Liguang
- Venue
- Environmental Research Letters
- Publisher
- IOP Publishing
- Published
- 2023-06-20
- Volume
- 18
- Issue
- 7
- Pages
- 074017
- ISSN
- 1748-9326
- Cited by
- 14
- References
- 1
- Licence
- creativecommons.org/licenses/by/4.0 (vor)
- iopscience.iop.org/info/page/text-and-data-mining (tdm)
- Funders
- Danida Fellowship Centre (18‐M01‐DTU)
- CRSRI Open Research Program (CKWV20221009/KY)
- SUSTech research startup grant (Y01296129)
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