Inland water bodies are vital freshwater sources, requiring effective monitoring to assess climate change and human impact. Advances in remote sensing technologies now enable cost-effective, long-term surface-water-level tracking. This study refines continuous water-level time series using satellite altimetry data from the Global Ecosystem Dynamics Investigation (GEDI) and Surface Water and Ocean Topography (SWOT) missions, focusing on their integration to enhance accuracy, precision, and revisit frequency.

GEDI, a spaceborne LiDAR altimeter aboard the International Space Station, provides high-resolution measurements (25m footprint) between 51.6°N and 51.6°S. Data from March 2019 to March 2023, available on Google Earth Engine (GEE), were evaluated for Italian lakes (2019–2022)]. An outlier detection workflow, incorporating GEDI metadata and a 3NMAD-based test, improved measurement precision. For Northern Italian lakes with gauge data, the intrinsic precision was 0.11m, while GEDI achieved sub-10cm precision for smaller ungauged lakes in Lazio.

SWOT, operational since April 2023, uses a Ka-band Radar Interferometer to monitor 86% of Earth's surface with a 100m pixel size and a 21-day revisit time. Over Northern Italian and Swiss lakes, SWOT achieved a 92% correlation with gauge measurements and a precision of ~0.06m. For Central Italian ungauged lakes, spatial NMAD was under 10cm, with minimal outliers. The complementary integration of GEDI and SWOT data offers a robust solution for monitoring inland water levels globally.

Acknowledgments

This research is performed in the framework of the GRAW project, funded by the Italian Space Agency (ASI), Agreement n. 2023-1-HB.0, as part of the ASI’s program “Innovation for Downstream Preparation for Science” (I4DP_SCIENCE).