Lake water levels from 1992 to present derived from satellite observations

The Lake Water Level (LWL) v5.0 dataset, developed under the Copernicus Climate Change Service (C3S), provides measurements of lake water surface heights derived from satellite altimetry. It offers consistent and accurate water level data for many lakes worldwide, supporting climate monitoring and hydrological studies.

Key strengths

• Comprehensive temporal and geographic coverage: The dataset provides extensive temporal coverage, from 1992 to present, which is essential for long-term climate studies and trend analysis. It includes many lakes worldwide, offering a global perspective on lake water levels.
• High-resolution data: High spatial and temporal resolution data allow for detailed analysis of lake dynamics and responses to climatic changes. Frequent measurements, between 1 to 27 days, ensure that short-term variations and trends can be accurately captured.
• Reliable data sources: Data is sourced from reputable institutions and satellite observations, ensuring high reliability and accuracy. In-situ measurements are employed to support the validation processes, enhancing overall confidence in the data quality.
• Enhanced geoid height calculation: The development of a module for calculating the height of the geoid has improved the assessment of water levels by providing more accurate reference surfaces. This enhancement contributes to the overall precision of lake water level estimations.
• Standardized format and thorough documentation: Data is provided in a standardized format, facilitating ease of use and integration with other datasets. Comprehensive metadata and documentation provide necessary context and usage instructions for researchers.

Key limitations

• Historical data quality: The Lake Water Level (LWL) dataset incorporates satellite altimetry data from missions such as TOPEX/Poseidon, Jason-1, Jason-2, Envisat, SARAL, and others, covering the period from 1992 to 2015. These early missions were pivotal in establishing a long-term climate data record. However, compared to more recent missions, earlier satellites often had less precise instruments and coarser inter-track spacing, which can impact spatial resolution and measurement accuracy. For example, while TOPEX/Poseidon had a relatively frequent 10-day revisit cycle, other factors (such as less advanced correction methods and limited coverage of smaller lakes) contribute to higher uncertainties in pre-2016 data.
• Potential inconsistencies due to correction method changes: Earlier processing used enhanced geophysical corrections (e.g., wet and dry tropospheric, ionospheric) from the Center for Topography of the Oceans of LEGOS (CTOH) database. These were later replaced by standard corrections in the operational Copernicus Climate Change Service (C3S) Lakes Service, based on the HYSOPE (HYdrométrie Spatiale OPErationelle) system. While the standard corrections are regularly updated and reliable for current missions, the transition may introduce inconsistencies between historical and recent datasets, potentially affecting long-term comparisons.
• Wet tropospheric correction uncertainty: A significant source of uncertainty arises from the wet tropospheric correction, which can vary regionally between 2-3 cm. This variability affects the accuracy of satellite altimetry measurements over inland waters.
• Dependence on track length and retracking quality: The overall uncertainty in water surface height is influenced by the length of the track over the lake and the quality of retracking. This uncertainty ranges from 8-10 cm for large lakes (with longer transects) to 1m for small and narrow lakes.
• LWL-S v1.0 not yet available for download: The documentation includes information on the Lake Water Level-Single Track Lakes (LWL-S) v1.0 dataset. However, only the Lake Water Level (LWL) v5.0 dataset is available for download.

Example Applications

• Flood risk assessment: Gbetkom et al. (2024) used Hydroweb water level data as one of their inputs to analyze variations in the water balance of Lake Tanganyika under recent climatic conditions (2003-2021), assess flood risks, and explore early warning indicators. The C3S-LWL v5.0 dataset uses the same core processing algorithm as HydroWeb, the HYSOPE processor, which originates from CNES/LEGOS.
• Ecological monitoring and management: Gbetkom et al. (2023) studied variations in Lake Chad's vegetation cover and surface water levels (height and area) in response to rainfall fluctuations. Hydroweb water level data were also employed in this case. The study allowed the researchers to predict the timing of vegetation growth, which has important implications for agricultural and ecological management in the area.
• Lake volume variation trend analysis: Liu et al. (2018) analyzed long-term fluctuations in Taihu Lake, located in eastern China, using ICESat/Hydroweb and Landsat data from 1975 to 2015. Hydroweb data was used for water levels from 2000 to 2010. Their results showed a gradual increase in the lake's area, volume, and a positive water budget.