EGU25-17647, updated on 15 Mar 2025
https://doi.org/10.5194/egusphere-egu25-17647
EGU General Assembly 2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Performance of Raspberry Pi Reflectors and multiple in-situ sensors for surface water monitoring and sentinel-3 validation over two years
Makan Karegar, Jiaming Chen, Luciana Fenoglio-Marc, and Jürgen Kusche
Makan Karegar et al.
  • University of Bonn, Institute of Geodesy and Geoinformation, Bonn, Germany.

As part of the Collaborative Research Center (SFB 1502) funded by the German Research Foundation (DFG), a project is being carried out to analyze surface water levels and discharge using data from the latest generation of satellite altimetry. Within this project, a network of eight Raspberry Pi Reflectors (RPR) (Karegar et al. 2022, WRR) was strategically installed in the middle Rhine valley and upper Rhine along a stretch of about 110 km during the spring and summer of 2023. While the primary goal of this deployment was to validate SWOT (Surface Water and Ocean Topography) surface water level observations, four RPRs were also placed under Sentinel-3 tracks A156 and B156. Sentinel-3 L1A data were acquired and processed using the Fully Focused SAR (FFSAR) processor and automatic off-nadir processing method (Chen et al. 2025, J. Hydrology). At Worms, multiple in-situ sensors are being used. The river gauge maintained by the German Federal Waterways and Shipping Administration (WSV) records water levels at 15-minute intervals. It is a classic float and stilling well gauge located on the riverbank and connected to the water via an underground pipe. A commercial radar sensor from Vortex-io was mounted on a bridge overlooking the river. Also, an RPR was installed in Worms to evaluate its performance. Having these three sensors based on different techniques allows us assess their consistency together with Sentinel-3 observations. This presentation particularly reports on the RPR’s behavior and long-term performance in off-grid regions where there is no grid coverage or local power supply. We will also discuss their application in validating Sentinel-3 data, especially in the steep and narrow Middle Rhine Valley where the surrounding terrain significantly influences the accuracy of both GNSS-IR and Sentinel-3 measurements.

How to cite: Karegar, M., Chen, J., Fenoglio-Marc, L., and Kusche, J.: Performance of Raspberry Pi Reflectors and multiple in-situ sensors for surface water monitoring and sentinel-3 validation over two years, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17647, https://doi.org/10.5194/egusphere-egu25-17647, 2025.