Water-Level and Wave Benchmark Dataset for SWOT Validation in the St. Lawrence Estuary and Saguenay Fjord, Quebec, Canada

Sep 10, 2026

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This manuscript presents a comprehensive and evolving in situ benchmark dataset of water levels and wave parameters collected from March 2023 onward in the St. Lawrence Estuary and Saguenay Fjord (Quebec, Canada), created to support validation for the Surface Water and Ocean Topography (SWOT) satellite mission. It combines measurements from 18 barometrically-compensated pressure transducers with density correction using collocated salinity/temperature data and 13 GNSS-IR sensors, all referenced to a common vertical datum via RTK GNSS. Three directional wave buoys add bulk parameters and directional spectra with quality-controlled processing. The dense spatial network enables SWOT nadir and wide-swath altimetry validation and supports hydrodynamic model calibration and spatio-temporal studies, with ongoing public updates at Zenodo.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages40

Reading Time1 h 41 min

AccessFree to download

Introduction

Study dataset for SWOT validation

Sensor network and measurement components

Processing, quality control, and referencing

Applications and data availability

[https://doi.org/10.5194/essd-2026-30](https://doi.org/10.5194/essd-2026-30) Preprint. Discussion started: 25 February 2026 􀀍c Author(s) 2026 . CC BY 4.0 License. A benchmark dataset of water levels and waves for SWOT validation in the St. Lawrence Estuary and Saguenay Fjord, Quebec, Canada Pascal Matte 1,* , Xavier Chartrand 1,2,* , David Purnell3,4,* , Marc Simard5 , Alexandra Christensen5 , Francis Fortin-Legault6 , Jonathan Morin6 , Yann Côté-Nadeau6 , Élaine Desrosiers6 , Anthony Ouellet7 , Cédric Chavanne2 , François Anctil3 , Gabriela Siles8 , Scott Bedart8 , Silvia Innocenti 1 , Mohammed Dabboor 1 , Daniel L. Peters9 , and Mélanie Trudel 10 1Meteorological Research Division, Environment and Climate Change Canada, Quebec City, QC, G1J 0C3, Canada 2Institut des Sciences de la Mer, Université du Québec à Rimouski, Rimouski, QC, G5L 3A1, Canada 3Department of Civil and Water Engineering, Université Laval, Quebec City, QC, G1V 0A6, Canada 4Precipice Sensors Inc., Montreal, QC, Canada 5Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, 91109, USA 6 Canadian Hydrographic Service, Fisheries and Oceans Canada, Mont-Joli, QC, G5H 3Z4, Canada 7 Science Advice, Information and Support Branch, Fisheries and Oceans Canada, Mont-Joli, QC, G5H 3Z4, Canada 8Department of Geomatics Sciences, Université Laval, Quebec City, QC, G1V 0A6, Canada 9Watershed Hydrology and Ecology Research Division, Environment and Climate Change Canada, Victoria, BC, V8N 1V8, Canada 10 Department of Civil Engineering and Building, University of Sherbrooke, Sherbrooke, QC, J1K 2R1, Canada *These authors contributed equally to this work. Correspondence: Pascal Matte (pascal.matte@ec.gc.ca) Abstract. This manuscript presents a comprehensive and evolving novel in situ dataset of water levels and wave parameters collected from March 2023 onward in the St. Lawrence Estuary and Saguenay Fjord (Quebec, Canada), supporting validation activities for the Surface Water and Ocean Topography (SWOT) satellite mission. The dataset integrates water level measurements from 18 barometrically-compensated pressure transducers and, where possible, corrected for water density using 5 collocated salinity and temperature data, supplemented with 13 GNSS-Interferometric Reflectometry (GNSS-IR) sensors. All water level data are referenced to a common vertical datum via real-time kinematic (RTK) GNSS corrections. Three directional wave buoys provided supplementary observations of surface wave conditions, including bulk parameters and directional spectra. Quality-controlled and rigorous processing protocols were implemented across all sensor types, with particular attention to referencing accuracy and correction for environmental influences. The observational network has the densest spatial coverage 10 of water level and wave measurements ever achieved in this region, offering unprecedented opportunities for validation of SWOT’s nadir and wide-swath altimetry products, as well as for hydrodynamic model calibration and spatio-temporal studies of tidal and wave processes in complex estuarine environments. With ongoing data collection, this evolving benchmark dataset is publicly accessible at [https://doi.org/10.5281/zenodo.18225505](https://doi.org/10.5281/zenodo.18225505) and will be periodically updated with new observations, to facilitate extended SWOT science validation and support a broad range of estuarine research applications. [https://doi.org/10.5194/essd-2026-30](https://doi.org/10.5194/essd-2026-30) Preprint. Discussion started: 25 February 2026 􀀍c Author(s) 2026 . CC BY 4.0 License. 15 Copyright statement. The works published in this journal are distributed under the Creative Commons Attribution 4.0 License. This licence does not affect the Crown copyright work, which is re-usable under the Open Government Licence (OGL) . The Creative Commons Attribution 4.0 License and the OGL are interoperable and do not con

FAQs

What observational data does the benchmark dataset provide for SWOT validation?

The dataset includes water level measurements and wave parameters collected in the St. Lawrence Estuary and Saguenay Fjord. It also provides bulk wave parameters and directional spectra from directional wave buoys.

How are the water level observations processed and referenced to ensure consistency?

All water level data are referenced to a common vertical datum using RTK GNSS corrections. Where possible, transducer measurements are corrected for water density using collocated salinity and temperature data, and rigorous quality-controlled processing is applied.

Where and how can users access and reuse the dataset?

The dataset is publicly accessible at the provided Zenodo link. It is designed for extended SWOT science validation and is periodically updated with new observations.

Sep 10, 2026

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