Abstract's details
Validation of SWOT Lake water level using in situ measurements: results from a student project at Lake Guerledan (France)
Event: 2025 SWOT Science Team Meeting
Session: Hydrology: HR SWOT Data (Data Validation & Enhancement)
Presentation type: Poster
With a wide swath of 120 km, the SWOT mission's KaRin interferometric radar can track rivers and lake dynamics anywhere on Earth with unprecedented resolution [1]. The first “Pixel Cloud” datasets [2] provide information on reservoirs too small to be tracked by traditional space altimetry [3,4], but key to understand local hydrological processes.
As part of an engineering student project, we test KaRin's abilities on one of Brittany's largest freshwater bodies: the Guerlédan dam lake. Since 2015, this lake is the playground for hydrography and robotics students at the École Nationale Supérieure des Techniques Avancées (ENSTA) [5]. This year, six students were responsible for the lake’s instrumentation to monitor water levels, with the aim of comparing the collected data with SWOT observations in the area. The project took place over five months in partnership with Shom (French naval hydrographic and oceanographic service),and included two weeks of field acquisition in October 2024 and February 2025.
The project focused on two main aspects:
1. Lake in-situ instrumentation: design of a measuring scheme to monitor changes in lake level and enable sensors inter-comparison. Several sensors were deployed :
-> Pressure gauges were moored in various locations on the lake over a 5-month period for long-term water level monitoring. GNSS buoys were deployed at the lake's surface to ensure the sensors' absolute position.
-> Low-cost GNSS & acoustic altimeter system was developed and deployed for spatial water level monitoring.
-> A fixed GNSS antenna was installed for water level measurement using GNSS interferometric reflectometry (GNSS-IR).
-> An EPONIM autonomous radar tide gauge [6] was installed on the top of the dam to allow inter-comparison of all systems.
2. SWOT data analysis: processing and analysis of SWOT HR Raster 100m data [7] in the area (flag, correction parameters, etc.), and spatial and temporal comparison with in-situ data.
All instrumental deployments were successful, and the coupled GNSS & acoustic altimeter system enabled space-based acquisitions on the lake. In-situ sensors provide consistent water levels evolutions, despite inter-sensor biases in the range 4-10 cm which are still under investigation. SWOT observations could be retrieved on the lake, but an in-depth analysis of the corrections is required to explain the absolute biases observed with in-situ measurements. For future students' surveys, attention will be paid to the air draft of each sensor and their positioning to avoid any possible shifts. Satellite data analysis will be completed by adding Sentinel-3a observations over the lake.
Bibliography
[1] L. Fu et al., “The Surface Water and Ocean Topography Mission: A Breakthrough in Radar Remote Sensing of the Ocean and Land Surface Water,” Geophys. Res. Lett., vol. 51, no. 4, 2024. doi: 10.1029/2023GL107652.
[2] SWOT, “SWOT Level 2 Water Mask Pixel Cloud Data Product.” NASA Physical Oceanography Distributed Active Archive Center, 2024. doi: 10.5067/SWOT-PIXC-2.0.
[3] L. Maubant, L. Dodd, and P. Tregoning, “Assessing the Accuracy of SWOT Measurements of Water Bodies in Australia,” Geophys. Res. Lett., vol. 52, no. 6, 2025. doi: 10.1029/2024GL114084.
[4] S. Wu et al., “SWOT mission enables high-precision and wide-coverage lake water levels monitoring on the Tibetan Plateau,” J. Hydrol. Reg. Stud., vol. 59, 2025. doi: 10.1016/j.ejrh.2025.102357.
[5] S. Rohou, “Hydrographes et Roboticiens explorent le lac de Guerlédan”. Accessed: May 26, 2025. [Online]. Available: https://guerledan.ensta-bretagne.fr/
[6] Shom, “EPONIM - Equipement Ponctuel pour l’Observation du Niveau de la Mer,” 2017. Accessed: May 26, 2025. [Online]. Available: https://refmar.shom.fr/sites/default/files/2024-02/FT-maregraphe-deployable-EPONIM-2017.pdf
[7] SWOT, “SWOT Level 2 Water Mask Raster Image Data Product.” NASA Physical Oceanography Distributed Active Archive Center, 2024. doi: 10.5067/SWOT-RASTER-2.0.
Back to the list of abstractAs part of an engineering student project, we test KaRin's abilities on one of Brittany's largest freshwater bodies: the Guerlédan dam lake. Since 2015, this lake is the playground for hydrography and robotics students at the École Nationale Supérieure des Techniques Avancées (ENSTA) [5]. This year, six students were responsible for the lake’s instrumentation to monitor water levels, with the aim of comparing the collected data with SWOT observations in the area. The project took place over five months in partnership with Shom (French naval hydrographic and oceanographic service),and included two weeks of field acquisition in October 2024 and February 2025.
The project focused on two main aspects:
1. Lake in-situ instrumentation: design of a measuring scheme to monitor changes in lake level and enable sensors inter-comparison. Several sensors were deployed :
-> Pressure gauges were moored in various locations on the lake over a 5-month period for long-term water level monitoring. GNSS buoys were deployed at the lake's surface to ensure the sensors' absolute position.
-> Low-cost GNSS & acoustic altimeter system was developed and deployed for spatial water level monitoring.
-> A fixed GNSS antenna was installed for water level measurement using GNSS interferometric reflectometry (GNSS-IR).
-> An EPONIM autonomous radar tide gauge [6] was installed on the top of the dam to allow inter-comparison of all systems.
2. SWOT data analysis: processing and analysis of SWOT HR Raster 100m data [7] in the area (flag, correction parameters, etc.), and spatial and temporal comparison with in-situ data.
All instrumental deployments were successful, and the coupled GNSS & acoustic altimeter system enabled space-based acquisitions on the lake. In-situ sensors provide consistent water levels evolutions, despite inter-sensor biases in the range 4-10 cm which are still under investigation. SWOT observations could be retrieved on the lake, but an in-depth analysis of the corrections is required to explain the absolute biases observed with in-situ measurements. For future students' surveys, attention will be paid to the air draft of each sensor and their positioning to avoid any possible shifts. Satellite data analysis will be completed by adding Sentinel-3a observations over the lake.
Bibliography
[1] L. Fu et al., “The Surface Water and Ocean Topography Mission: A Breakthrough in Radar Remote Sensing of the Ocean and Land Surface Water,” Geophys. Res. Lett., vol. 51, no. 4, 2024. doi: 10.1029/2023GL107652.
[2] SWOT, “SWOT Level 2 Water Mask Pixel Cloud Data Product.” NASA Physical Oceanography Distributed Active Archive Center, 2024. doi: 10.5067/SWOT-PIXC-2.0.
[3] L. Maubant, L. Dodd, and P. Tregoning, “Assessing the Accuracy of SWOT Measurements of Water Bodies in Australia,” Geophys. Res. Lett., vol. 52, no. 6, 2025. doi: 10.1029/2024GL114084.
[4] S. Wu et al., “SWOT mission enables high-precision and wide-coverage lake water levels monitoring on the Tibetan Plateau,” J. Hydrol. Reg. Stud., vol. 59, 2025. doi: 10.1016/j.ejrh.2025.102357.
[5] S. Rohou, “Hydrographes et Roboticiens explorent le lac de Guerlédan”. Accessed: May 26, 2025. [Online]. Available: https://guerledan.ensta-bretagne.fr/
[6] Shom, “EPONIM - Equipement Ponctuel pour l’Observation du Niveau de la Mer,” 2017. Accessed: May 26, 2025. [Online]. Available: https://refmar.shom.fr/sites/default/files/2024-02/FT-maregraphe-deployable-EPONIM-2017.pdf
[7] SWOT, “SWOT Level 2 Water Mask Raster Image Data Product.” NASA Physical Oceanography Distributed Active Archive Center, 2024. doi: 10.5067/SWOT-RASTER-2.0.