Lakes are crucial sources of freshwater and significant indicators of environmental change on a global level. They are reacting quickly to climate change, and it is expected that in coming decades global warming will have an even more pronounced impact on biodiversity, nutrient cycling, and hydrology. To support the comprehension of this topic at global scale as well as for understanding the complicated behaviour of lakes in a changing environment, satellite technologies provide a unique source of data. In such a context, Lakes_cci project recently provided the most complete collection of consistent satellite observations water level, water extent, lake surface water temperature, water-leaving reflectance and related chlorophyll-a concentration and turbidity and ice cover. The products span from 1992 to 2020 and quantifies over 2000 relatively large lakes, which represent a small fraction of the number of lakes worldwide but a significant fraction of global freshwater surface. To illustrate the project's scientific contribution, two use-cases are described in this study along with the main properties of the dataset.

Satellite-based radar altimetry enables the long-term and global monitoring of inland water bodies. Recent progress of these altimeters concerning the tracking and acquisition mode allows to monitor an increasing number of water bodies, including lakes of small size or located in a complex orograhpy environment. As a consequence of these more demanding situations, the current operational radar processing techniques need to get improved in order to provide accurate water level retrievals. A numerical processing technique that simulates the satellite-observed scene was proposed in [1], taking into account all these challenges. In this work, the performance of such processing technique is assessed from Sentinel-3 mission data. It concerns 1000 lakes and reservoirs worldwide with a great variety of situations, looking for the current limits and potential future improvements, including about thirty water bodies with publicly available in-situ measurements allowing to determine the current accuracy attained.

Lakes and reservoirs are considered sentinels of climate and anthropogenic changes. Lakes and reservoirs surface water storage is an essential hydrological variable but poorly known as this information is scarce. Earth Observation data are a reliable source of information to overcome this scarcity. Among these, the combined use of satellite images, to derive water extent, and radar altimetry, which enables to estimate water levels, provides valuable information on water storage changes. Here, we used Synthetic Aperture Radar images from Sentinel-1 and radar altimetry data from Sentinel-3 to monitor the water volume changes of Lake Bracciano from 2016 to 2021. This lake was affected by a water crisis in 2017 and the water supply to the city of Rome (Italy) was interrupted September 2017 to preserve its ecosystem. Hence, we demonstrate how Sentinel-1 and Sentinel-3 data can be useful to monitor water extent and level, which can be profoundly changed by the climate crisis.

Access to fresh water is a key issue for the next decades in the context of global warming. The water level of lakes is a fundamental variable that needs to be monitored for this purpose. The radar altimetry constellation brings a worldwide means to this question. Recent advances in radar altimeter onboard tracking modes have allowed monitoring thousands of lakes and rivers. Now, measurements are widely available with better resolution: it is time to drastically improve the processing. The altimetry waveforms over lakes are difficult to analyze and very different from the ocean ones. We face a large variety of signals due to surface roughness, lake geometry, and environment. The inversion process, named retracking, shall be able to describe all these components. We propose here a retracking based on physical simulations taking as inputs the lake contour and the instrument characteristics. Fitting the simulation on the waveforms gives the water surface height. The algorithm has been tested on the Sentinel-3A and Sentinel-3B time series over Occitan reservoirs (France) and Swiss lakes and compared toin situreferences. Over small Occitan reservoirs (few ha to few km2), the unbiased root-mean-square error (ub-RMSE) is better than 14 cm. Over the medium-size Swiss lakes, the ub-RMSE is better than 10 cm for most of them.

Altimetry missions provide very valuable measurements on hydrological bodies, although they have initially been built for ocean topography. The extension of their acquisition modes provides tens of thousands of lake and river observations thanks to recent OLTC table upgrades. The inversion of the waveforms is yet tricky because of mixed soil/water response, highly variable dynamics and surface roughness variations. In this paper, a physical retracking based on a priori simulation is proposed for Water Surface Height (WSH) estimation over lakes. The method is applied on Sentinel-3 SAR data. The results are illustrated and discussed over the Constance lake which is covered by three S3 tracks. Consistent estimations are obtained between the three with an unbiased RMSE better than 6cm. Extensive validation over Swiss lakes (19 tracks) has also been made leading to a median unbiased RMSE of 6cm.

Flooding is one of the most devastating natural hazards in the world, corresponding to near half of the disasters occurred the last 20 years, and presenting and important increase since the previous 20 years. At the same time, exploitation of satellite data to estimate hydro-logical parameters continues to increase due to use of better sensors, improvement in knowledge of/and utilization of satellite data, and expansion of research topics The aim of this paper is to present a state of art of the applications of remote sensing data, ie images satellites for water extent, altimetry satellites for water heigh retrieval, their limitations and finally what are the next steps with the arrival of promising news missions.

Small water bodies play a pivotal role in the Sahel since they provide a critical water resource to livestock and people and they also offer important ecosystems services. Monitoring, modelling and better understanding the hydrological behaviour of this small water bodies is therefore a key issue. The SWOT mission will bring a resolution and spatial coverage breakthrough allowing monitoring water level and volume in small water bodies worldwide. This study assesses the potential of SWOT for monitoring water volumes in Sahelian ponds and lakes. This is done by analysing synthetic data produced using the SWOT HR simulator developed by NASA-JPL. In addition, data from the Global Precipitation Mission have been also employed to investigate the backscatter coefficient variability over land and water in the Sahel. Overall, the first application of SWOT _ HR simulator over the Sahel has shown the good potential of SWOT for monitoring the seasonal variability of water levels in this region.

In this paper, we describe the ALTICORE (value added satellite ALTImetry in COastal REgions) initiative, a consortium aiming at providing high quality coastal altimetry over some European seas. Taking the Ligurian Sea in the NW Mediterranean as an example, which acts as a test zone for this work, we show the improvement in availability and quality of ENVISAT data, through our processing, when compared with the official altimetric products delivered by AVISO. We also introduce the building concepts of solutions for data search, extraction, update and delivery based on web-services. This grid-type infrastructure is being designed within ALTICORE.

The paper discusses application of active and passive microwave data for assessment of time and space variations of first-year ice cover. The Caspian and Aral seas are chosen as main study areas. The Caspian Sea evolution is primarily climate driven, while for the Aral Sea there is a mix of anthropic and climate factors. We analyze ice cover conditions using a novel method that combines active and passive satellite measurements for ice discrimination. This method uses the synergy of simultaneous data from active (radar altimeter) and passive (radiometer) microwave instruments onboard the TOPEX/Poseidon (T/P) satellite, launched in 1992. The benefits, drawbacks, and potential of ice cover studies using the proposed method are discussed. We analyze in detail how this method is influenced by the difference in footprints of the T/P sensors and by the radiometric properties of ice and snow at different stages of ice cover evolution. In order to link the T/P-derived results to historical observations that end in the mid-1980s, long time series of passive microwave data from SMMR and SSM/I sensors have also been analyzed. Satellite time series of ice cover extent and duration of ice period have been obtained for the Caspian and Aral seas since 1978. A good agreement is obtained between historical and satellite data, with significant spatial and temporal variability of ice conditions. There is a marked decrease of both duration of ice season and ice extent during the winters 1998/1999-2001/2002. These satellite-derived time series of sea ice parameters are very valuable in view of the heterogeneous and mostly unpublished data on ice conditions over the Caspian and Aral seas since the mid-1980s.

The paper discusses time and space variations of ice cover in the Caspian and Aral seas. We use the synergy of data from active (radar altimeter) and passive (radiometer) microwave instruments onboard the TOPEX/Poseidon satellite, as well as passive microwave data from SSMR and SSM/I sensors. The results indicate significant spatial and temporal variability of ice conditions, with a marked decrease of both duration of ice season and ice extent during winters 1998/99-2001/02. The satellite-derived time series of sea ice parameters are very valuable in view of the heterogeneous and mostly unpublished data on ice conditions over the Caspian and Aral seas since the mid-1980s.