The alternation of extreme events is a source of great stress on the territory and forces us to adopt solutions to help mitigate their consequences. In this study, an attempt is made to exploit Earth Observation from space as a means to point out the interaction of inland waters and the coastal areas during hydrological extreme events, i.e. floods and droughts. During a flood event, large volume of water from the river reaches the coast, adding a considerable volume of freshwater. Conversely, during a drought event salt water from the sea enters inland causing severe damage to agriculture and the local population. With this study we attempt to investigate how the systems of sea and river interact during particularly intense events using satellite optical (Sentinel-2 and Sentinel-3) and altimeter (Sentinel-3, Cryosat-2, Icesat-2) sensor data. The area selected is the Po River delta (up to 200 km from the mouth), which in recent years has been exposed to severe events: in November 2019, the Po River was subject to a copious flood that had not occurred since 2000, while in the summer of 2022, it experienced the worst drought in the last 70 years.

The analysis aims at evaluating three fundamental aspects: 1) the ability of satellite altimetry to identify extreme events in the river; 2) the potential of satellite altimetry to detect salt wedge intrusion in the Po River delta; and 3) the potential correlation between the altimetry observations and optical imagery of the river’s plume along the Adriatic coast.

The analysis was conducted by analysing long time series (of about 10 years) for the first objective and by focusing on the drought event of 2022 and the flood events that occurred in the last 5 years for the other two objectives.

The results of the analysis confirm that the satellite observed the significant increase and decrease in water levels in correspondence of the extreme events. In addition, the analysis of the data at the virtual stations in the downstream part of the Po River, together with the data along the tracks crossing the plume closer to the mouth of the river, showed the interaction between the sea and the river. In particular, the temporal series of the river clearly highlight the influence of the sea water several km upstream the river (more than 40 km as reported in the news), probably related to the salt wedge intrusion, which has caused significant damage to agriculture and drinking water aquifers for a long time after the event. The study qualitatively shows that extreme hydrological events can also be captured in the open sea in this region.

The analysis illustrates the great potential of satellite sensors to monitor extreme events and the interaction of inland and coastal waters.

How to cite: Tarpanelli, A., De Biasio, F., Nielsen, K., Filippucci, P., Cavalli, R. M., and Vignudelli, S.: Understanding the interaction between inland waters and the coastal zone during extreme events over the Po Delta from space, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8341, https://doi.org/10.5194/egusphere-egu24-8341, 2024.

For almost 30 years radar altimeters provide water elevations of rivers and lakes only where a target intersects the satellite’s ground track, called Virtual Stations (VS). This way, the observations have both limited temporal and spatial resolution, because on one hand such intersections occur by chance and because on the other hand the repeat cycle of the orbit ranges from 10 to 35 days, depending on the mission.

Boy et al. [1] illustrated recently that river signals may also be captured when the river is located at cross-track distances of several kilometers, when utilizing high resolution SAR altimeter products (particularly fully-focused SAR [2], FFSAR). Therefore, the concept of the altimeter river measurements can be revisited completely. Based on the idea presented in [1], we developed a novel algorithm to calculate water surface elevations (WSE) of rivers within a ground swath of approximately 14 km width, and with along-track resolutions as fine as 10 m from the Sentinel-6 altimeter signal. All that is needed additionally to the FFSAR-processed signal is an a-priori river polygon or centerline to correct for non-zero cross-track distances.

Our algorithm can provide WSE along most parts of the river that fall within the swath, thus delivering densely sampled WSE profiles instead of a few point measurements over only the nadir crossings (VS). This marks a drastic improvement in the number of available WSE observations and opens completely new research possibilities, as water surface slopes and level changes due to rapids and dams can be studied directly. Essentially, these new Sentinel-6 WSE measurements resemble the river WSE product obtained with the recently launched SWOT mission (albeit with more limited coverage). As such, they can be exploited in similar manners to provide much additional information for hydrological research, e.g. for assimilation in hydrological models and more reliable estimation of river discharge.

We demonstrate and validate the new measurement approach and our algorithm over two rivers in France, the Creuse river and the Garonne river, showing biases that are typically on the order of +-4 cm and random errors on the order of 5 cm, both on 30 m along-track resolution. In our presentation, we will concentrate our attention on the new challenges of the method, including a sophisticated signal detection algorithm, the altered error budget of off-nadir WSE measurements and the limitations due to signal folding, clutter, lacking contrast and the complexity of the scene.

[1] Francois Boy et al. “Measuring longitudinal river profiles from Sentinel-6 Fully-Focused SAR mode”. In: Ocean Surface Topography Science Team (OSTST) meeting. Nov. 2023. doi: 10.24400/527896/a03-2023.3781.

[2] Alejandro Egido and Walter H. F. Smith. “Fully Focused SAR Altimetry: Theory and Applications”. In: IEEE Transactions on Geoscience and Remote Sensing 55.1 (Jan. 2017), pp. 392–406. doi: 10.1109/TGRS.2016.2607122.

How to cite: Ehlers, F., Slobbe, C., Verlaan, M., and Kleinherenbrink, M.: Looking beyond nadir: Measuring densely sampled river elevation profiles with the Sentinel-6 altimeter, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8949, https://doi.org/10.5194/egusphere-egu24-8949, 2024.

Satellite altimetry has emerged as a key alternative for inland water level measurement in addition to ground observations. Water surface slope (WSS) is one of the basic parameters of river morphology for discharge calculation. Estimation of WSS can also avoid systematic bias in satellite water levels relative to gauged data. A range of satellite data products are available to provide accurate river water level measurements and estimates of river WSS on a worldwide scale. Nonetheless, satellite-based observation of river water surface remains challenging in small rivers, such as the mountainous river reaches with narrow water surfaces. In this study, we examined the accuracy of the ICESat-2 ATL03 photon height data in estimating WSS over the mountainous river reach of Yongding River flowing across Hebei Province and Beijing City in northern China. With minimum along-track sampling interval of 0.7m, the ICESat-2 ATL03 data provided reliable estimation of WSS over narrow river reaches which are 50 to 100m wide. Satellite virtual stations were located mainly with a histogram-based statistical method, seeking for photon height that corresponds to the peak frequency. The twelve groups of satellite virtual stations chosen for river WSS estimation finally show an overall correlation coefficient of 0.96 in validation. Relative error of WSS estimation ranges from 0.13% to 14.51%. Findings of this study provide further implications for satellite-based river water surface measurement in small mountain river basins that lack of ground observation conditions, bringing in reliable estimation of key hydrological parameters based on satellite observation.

How to cite: Lyu, H. and Tian, F.: Satellite-based water surface slope in small mountain river, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2399, https://doi.org/10.5194/egusphere-egu24-2399, 2024.

The measurement of surface water bodies plays a vital role in assessing the magnitude of floods and droughts despite their relatively little contribution to the overall hydrosphere on Earth's surface. The distribution and accessibility of water resources have been greatly impacted by global climate change and unsustainable human activities. These factors have resulted in heightened strain on surface water supplies, causing shortages that hinder both human consumption and socioeconomic progress. Therefore, the mapping and identification of surface water reserves are essential for achieving optimal utilization and sustainable management. Madhya Pradesh, henceforth referred to as MP, possesses a highly diverse range of geographical features within the Central Indian area. According to prior research, a total of thirty-six out of fifty-one districts within the state of Madhya Pradesh have seen significant hydrological drought conditions in recent years, mostly attributed to the scarcity of surface water resources. Despite the challenges faced in the MP area, there remains a lack of sufficient understanding of the long-term and seasonal variations in surface water dynamics within districts, as well as the overall availability and accessibility of surface water resources. Field-based observations of surface water bodies in regions with vast expanses, such as Madhya Pradesh (MP), pose considerable obstacles. However, the comprehension of spatiotemporal fluctuations in surface water can be enhanced with the utilization of remote sensing datasets for observations. Hence, to gain an understanding of the long-term fluctuations in surface water patterns in different regions of Madhya Pradesh, India, over a span of 38 years, we employed a publicly accessible global surface water dataset provided by the Joint Research Centre (JRC) of the European Commission. This dataset covers the time period from 1984 to 2021. Based on the results of our investigation, it is apparent that a disparity exists in the per capita accessibility of permanent water resources in the majority of MP districts, notably during periods of low precipitation, as well as in the per capita availability of seasonal water resources, particularly during months characterized by high levels of rainfall. While the monsoon period generally results in increased surface water availability, the Bundelkhand and Malwa Plateau regions experience severe shortages of surface water during dry periods, which, therefore, leads to the over-exploitation of groundwater resources. The implications of these findings are significant for the management of freshwater bodies in the Madhya Pradesh area, particularly in light of their depletion caused by climate change and human activities. Furthermore, these findings have broader implications for promoting sustainable development in the region.

How to cite: Swarnkar, S., Surjibhai, A. S., Nath, R., Singh, S., and Patra, B.: Assessment of Surface Water Dynamics between 1984-2021 in Madhya Pradesh, Central India, using Remotely Sensed Dataset, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-242, https://doi.org/10.5194/egusphere-egu24-242, 2024.

River discharge monitoring is critical for many activities ranging from water resource management to flood risk reduction. Due to limitations of in situ stations (e.g. low station density, incomplete temporal coverage and delays in data access), river discharge is not always continuously monitored in time and space. This has led researchers and space agencies, among others, to develop new methods based on satellite observations for estimating river discharge.

In recent years, ESA has funded the SaTellite-based Runoff Evaluation And Mapping (STREAM) and STREAM-NEXT projects, which propose to use satellite observations of precipitation, soil moisture and terrestrial water storage within a simple and conceptually parsimonious model, STREAM, to estimate runoff.

The model, applied to five large basins in the world (Mississippi-Missouri basin, Amazon basin, Danube basin, Murray-Darling basin and Niger basin)  has demonstrated a high ability to estimate runoff and river discharge in both natural and non-natural basins with a high anthropogenic impact (i.e. in basins where flow is regulated by the presence of dams, reservoirs or floodplains along the river; or in heavily irrigated areas). In particular, the good results obtained paved the way for the application of the STREAM approach on a global scale. For this purpose, the STREAM-NEXT project will generalise the STREAM model to make it applicable to more than forty basins worldwide. Depending on the availability of in situ discharge data, the selected basins shall be grouped into calibration and validation clusters. The purpose is to use the basins into the calibration cluster to tune the parameters of the regionalized STREAM model and apply the regionalised model parameters to the validation cluster basins to estimate the accuracy of the STREAM model.  Additional satellite observations, such as altimetric water levels, will be used to estimate the water stored in the reservoirs; gravimetric data with different spatial/temporal resolutions will be explored to investigate the impact of these data on the model results.

Finally, a calibration procedure and a regionalisation approach will be developed to make the STREAM model applicable to non-calibrated basins.

Here we present the STREAM-NEXT project and some preliminary results related to the generalization of the STREAM model framework. Different basins with different climate, topography and level of anthropisation will be selected to demonstrate the suitability of the approach for a global scale application. 

How to cite: Leopardi, F., Brocca, L., Saltalippi, C., Dari, J., Nielsen, K., Sneeuw, N., Tourian, M. J., Restano, M., Benveniste, J., and Camici, S.: Toward a global scale runoff estimation through satellite observations: the STREAM model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10856, https://doi.org/10.5194/egusphere-egu24-10856, 2024.

The Gravity Recovery and Climate Experiment (GRACE) and its Follow-On (GRACE-FO) missions have provided near continuous and unique measurement of total water storage  (TWS) since 2002. These international partnership missions have provided valuable insights in the fields of Hydrology, Oceanography, Ocean dynamics, Cryosphere Sciences, Solid Earth etc. These data from GRACE/GRACE-FO have improved our understanding of the Earth’s water cycle since launch and have become indispensable for climate related studies.

The spatial resolution of the data products from GRACE/GRACE-FO are roughly 300km and they typically have a temporal resolution of a month. These products provide the unique measurement of the total water storage of the entire water column and can provide a constraint for hydrological and ocean models. Several studies have used GRACE products for assimilation into the hydrological models for improved assessment of the reality on the ground and for downscaling the information to a higher spatial resolution using data assimilation. This paper will introduce the techniques that improve of temporal resolution of GRACE/GRACE-FO products from month to shorter than 5 days. That includes production of global 5-day TWS solution and the daily TWS product from GRACE that is estimated as a “swath” over the daily satellite ground-track.  The paper will discuss the analysis results over hydrological and ocean basins and validate the higher frequency signals captured by this product.  The goal for the production of this higher temporal resolution GRACE/GRACE-FO product is to be able to use these signals with a latency of a few days for ingestion into machine learning algorithms for early flood detection applications and for daily assimilation into hydrological models at short latency.

How to cite: Save, H., Tamisiea, M., Pie, N., and Bettadpur, S.: Higher Temporal Resolution Global GRACE/GRACE-FO Total Water Storage Products for Assimilation in Hydrology Models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13107, https://doi.org/10.5194/egusphere-egu24-13107, 2024.

Flooding has major economic, social, and environmental implications. Its modeling provides insights into potential risks and contributes to the protection of lives, natural resources, and infrastructure. In flood hazard assessment, the topography representation is a key factor as it dictates the water extent resulting from the simulations. In particular, for small and medium flood scenarios, it is imperative to have good knowledge of the modeled in-channel water height, especially for the river's bank full discharge. As these constitute the majority of flood events, the risk assessment is severely impacted by the quality of their estimates. However, the determination of the water profile can be a challenging task in data-sparse areas, as the bathymetry of the river channels is not well described in open-access digital elevation models (DEMs). Using the global coverage of remote sensing derived water levels and extents, this study builds towards a global estimation of river bathymetry. 
The methodology to achieve this can be divided into two parts, the correction of the river topography that can be directly observed by the sensors, above a minimum water level (the dry bathymetry), and the estimate of the part under the minimum observed water line (wet bathymetry). For the improvement of the dry bathymetry, the contours from water masks derived by optical sensors are projected in DEMs and a smooth profile is built from upstream to downstream. The wet bathymetry is calculated using hydraulic simulation and inverse problem methodologies. It requires as inputs the corrected dry bathymetry, observed water surface elevation and slope, and a prior discharge. The algorithm computes the flow using an integrated version of a modified Manning–Strickler’s equation and probability from beta distribution. It computes the roughness and the bottom depth of the section assuming a rectangular shape. 
Preliminary results are promising; a good agreement with in-situ discharge was achieved for the Po River (NSE > 0.8). It shows the potential and importance of accurate estimates of the river bathymetry for future flood monitoring and forecast.

How to cite: Rezende de Oliveira Silva, I., Malaterre, P.-O., Fatras, C., Oubanas, H., Gejadze, I., and Peña-Luque, S.: Global 1D river bathymetry estimation from remotely sensed observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17133, https://doi.org/10.5194/egusphere-egu24-17133, 2024.

The implementation of action plans for sustainable water resources management requires daily river discharge time series at gauging stations, which are already decreasing in number worldwide. Although the development of remote sensing-based methods for river discharge estimation has proven its effectiveness worldwide, the temporal frequency especially at the daily scale for river discharge estimation is the most important research question to be explored. In this context, the study proposed a methodological framework to establish a virtual station (VS) where the information retrieved from the multi-mission satellites was merged using the non-parametric copula function for river discharge estimation. Here, in the first step, both passive (C/M) and active (altimeter) remote sensing signals can be integrated by deriving the joint probability distribution using the copula functions of the Archimedean family. Subsequently, the Frank copula was evaluated as the best-fit copula function as measured by the goodness-of-fit-test and subsequently selected for establishing the VS by merging the information. The proposed framework was tested on more than 10 rivers around the world. Here, MODIS from Aqua and Terra, Landsat series, and MSI from Sentinel-2 images were used for the C/M approach, whereas SARAL AltiKa, Sentinel-3 A and B, and Cryosat-2 mission altimeters were considered for water level retrieval. The established VSs along the river can be able to derive long near daily discharge time series while evaluating against the in situ discharge with reasonable accuracy measured by Nash-Sutcliffe efficiency, Root Mean Square Error, and Kling-Gupta efficiency. Conclusively, the establishment of this kind of VSs along the river can be able to derive missing discharge data records and long near-daily discharge time series along any world river which is one of the key variables for hydro climatological studies.  

Keywords: Remote Sensing, Virtual Station, Copula, Satellite merging, River Discharge, Altimeters

How to cite: Sahoo, D. P., Filippucci, P., Barbetta, S., Biancamaria, S., Andral, A., Gal, L., and Tarpanelli, A.: Establishment of Virtual Station based on Multi-mission Satellites for Near-daily River Discharge Observation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19761, https://doi.org/10.5194/egusphere-egu24-19761, 2024.

The SWOT mission (NASA, CNES, UK-SA, CSA) launched in December 2022 provides observations of surface of inland water bodies at unprecedented resolution and accuracy. Here we focus on the Level 2 river products (heights and widths at 200m scale) and we assess their usability in creating coupled hydrological-hydrodynamic simulations of large scale basin where in-situ data are sparse. First we use an automated toolchain that generates (i) the mesh and processed input data for the hydrological models SMASH [1] or MGB [2], (ii) the coupling points between the hydrological and the hydrodynamic models, (iii) the mesh for the hydrodynamic 1D model (DassFlow-1D [3]) using either SWOT Level2 river observations of water heights and widths or other EO missions (ICESat-2, Copernicus Sentinels).

Then we conduct experiments of data-assimilation of conventionnal altimetry missions (ICESat-2, Sentinel 3), in-situ level heights and SWOT Level 2 river heights in order to correct the unobserved quantities (channel bathymetry and friction coefficient) and the inflow discharges using advanced techniques taking into account correlated effects of control variables and simulated water surface properties. The accuracy obtained using this method is assessed by comparing with the sparse existing in-situ data and in terms of physical consistency of simulated flow signatures with some EO data selected for validation.

This methodology and the inference capabilities are illustrated on the Maroni basin (French Guyana) which is the first application of variational data assimilation over a multi-branch river network at basin scale. A large parameter vector composed of spatially distributed friction coefficient and channel bathymetry plus inflow/lateral hydrographs are successfully estimated at various spatio-temporal resolution given data cocktails of varying spatio-temporal densities and informative content.

[1] SMASH (Spatially distributed Modelling and ASsimilation for Hydrology) -

https://smash.recover.inrae.fr/

[2] https://www.ufrgs.br/lsh/mgb/what-is-mgb-iph/

[3] https://mathhydronum.insa-toulouse.fr/codes_presentation/pres_dassflow/

How to cite: Larnier, K., Garambois, P.-A., Emery, C., Gal, L., and Paris, A.: Coupled hydrological-hydrodynamic and data assimilation of the entire river network of the Maroni basin using SWOT river products and other EO missions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20523, https://doi.org/10.5194/egusphere-egu24-20523, 2024.

How to cite: Schwatke, C., Scherer, D., and Dettmering, D.: Estimation of water level time series for lakes and rivers using SWOT KaRIn measurements , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5830, https://doi.org/10.5194/egusphere-egu24-5830, 2024.

The current global water body maps offer an approximate resolution of 30 meters, contingent on available remote sensing data. However, to address the needs of advanced applications like global carbon cycle analysis and real-time flood predictions, a water body map with higher spatial resolution becomes imperative, especially for resolving smaller rivers. Traditional water extraction methods rely on water indexes that combine visible and infrared spectra. State-of-the-art remote sensing data, including aerial photography with spatial resolutions in the order of a few meters, often includes only the visible spectrum.

In response to this challenge, we have developed a water extraction method at an impressive 60cm resolution utilizing Bayesian inference based solely on the visible spectrum from aerial photography, without using the infrared spectrum. To enhance our methodology, we integrated references of water existence from a Landsat-based dataset called G1WBM and Open Street Map (OSM), along with a hydrography dataset (J-FlwDir) presumed to be linked to water bodies.

Our method successfully detected the main streams of the Tsurumi River and Tama River in Japan, including their previously unrecognized tributaries in the Landsat-based dataset. Notably, this study identified rivers with a width exceeding 10 meters. Furthermore, it contributed valuable area information for 37% of small rivers represented as "line" features in the OSM.

These findings underscore the effectiveness of our Bayesian water detection approach, which leverages hydrography data and existing water body maps to improve the spatial resolution of large-scale water mapping significantly. Notably, this improvement is achieved using remote sensing data that lacks infrared spectra, showcasing the potential of our method in advancing the accuracy and precision of global water mapping efforts.

How to cite: Watanabe, M. and Yamazaki, D.: A 60-cm Aerial Photography-based Water Body Mapping: Application to the Tama and Tsurumi Rivers in Japan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8805, https://doi.org/10.5194/egusphere-egu24-8805, 2024.

The Surface Water and Ocean Topography (SWOT) mission, conducted by CNES and NASA was successfully launched on 16 December 2022. It aims at providing unprecedented 2D observations of the sea-surface height and mesoscale structures as well as water surface elevation, water stocks estimates and discharge over hydrological areas. A SAR-interferometry wide-swath altimeter, namely the Ka-band Radar Interferometer (KaRIn), is designed to cover two 50-km cross-track swaths. During its Calibration (Cal/Val) phase (January to July 2023), SWOT mission provided daily measurements for each swath due to its 1-day repeat cycle. While the spatial coverage during this phase is not as large as for the nominal phase with a 21-day repeat cycle, such short revisit time is relevant for Cal/Val purposes.  

The High Rate (HR) mode of KaRIn, dedicated to hydrology surfaces, provides HR SWOT products that are calibrated during the Cal/Val phase. The performance assessment of these SWOT observations can be achieved through the comparison against reference measurements. Although specific in-situ Cal/Val sites have been purposely designed for the validation of HR SWOT products on lakes and rivers, additional in-situ networks can also be useful, particularly if their spatial coverage allows a monitoring of lakes and rivers also observed by the SWOT mission. Such conditions are met for the French network (SCHAPI), providing several hundreds of georeferenced in-situ stations over rivers, and for the Swiss network (BAFU) which measures water surface elevation of main rivers and lakes. Moreover, the combination of measurements from current nadir altimetry missions (e.g. Sentinel-3, Sentinel-6 or ICESat-2) has also the potential to generate reference measurements on a large number of lakes and rivers. 

Our analysis will essentially propose a preliminary performance assessment of the distinct high-level HR SWOT products during the Cal/Val phase, using existing in-situ networks and measurements from Sentinel-3, Sentinel-6 and ICESat-2. We will first take advantage of hydrological areas being densely monitored below SWOT swaths, which are relevant to assess the quality and current limitations of the products.

How to cite: Vayre, M., Renou, J., Fjortoft, R., and Picot, N.: Cal/Val of HR SWOT products using in-situ networks and in-flight nadir altimetry missions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16275, https://doi.org/10.5194/egusphere-egu24-16275, 2024.

At global scale, there is still considerable uncertainty about the spatial and temporal variability of water storage and fluxes at the surface of continents. This is even more critical in the context of global climate change and the increasing human pressure on water resources. Despite this context, the following scientific questions remain difficult to answer, due to the coarse spatio-temporal resolution of current data: what is the global distribution of the heterogeneous change undergone by continental surface waters? What is the impact of anthropogenic pressure on water flows and stocks? What is the impact of these changes on the frequency and intensity of hydrological extremes (high and low waters)? To answer these questions, the Global Climate Observing System (GCOS) has identified river levels/discharges and lake/reservoir levels/volumes as essential climate variables, and recommends daily sampling (GCOS, 2022). Besides, extreme events, such as floods or droughts, cover a wide range of spatio-temporal scales. At present, water volume variations can only be observed by satellite at the coarsest scales (and are therefore of interest only for floods on the scale of the world's largest watersheds). The lack of observation of these events in basins with little or no in situ instrumentation is a major issue to understand, simulate and forecast these events. Observing these events globally, at least on a daily scale, would make it possible to quantify local flooding, thus greatly improving our knowledge of these events.

One of the main issue to tackle these questions is the still rather coarse temporal sampling of current satellite missions, particularly altimetry missions. To overcome it, we are proposing the SMall Altimetry Satellites for Hydrology (SMASH) mission. This is a constellation of around 10 compact nadir radar altimeters optimized to provide daily observations of water levels in rivers, lakes and reservoirs along the constellation tracks. The specifications of the SMASH mission are the following: daily temporal sampling, observe water bodies larger than 100 m x 100 m and rivers as narrow as 50 m, with an accuracy on water elevation ~10 cm, and should provide products in near-real time and over the long term (10 years) in open access (open science and FAIR principles).

Combining "high temporal frequency/low spatial frequency" measurements from the SMASH mission with "high spatial frequency/low temporal frequency" measurements from swath altimetry missions (current SWOT or futur Sentinel-3 Next Generation Topography missions) would cover unprecedented time and space scales and should open new fields of research.

How to cite: Biancamaria, S., Calmant, S., Frappart, F., Garambois, P.-A., Gosset, M., Grippa, M., Kouraev, A., Malaterre, P.-O., Munier, S., Papa, F., Yesou, H., Amiot, T., Cheymol, C., and Le Gac, S.: SMASH: a constellation of small altimetry satellites to monitor daily inland surface waters, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16780, https://doi.org/10.5194/egusphere-egu24-16780, 2024.

The Surface Water and Ocean Topography (SWOT) satellite, launched on December 16th 2022, is a CNES and NASA joint project, in collaboration with the Canadian Space Agency (CSA) and the United Kingdom Space Agency (UKSA). SWOT represents a major breakthrough in space altimetry by using a new technical concept based on interferometric synthetic aperture radar (InSAR): in comparison with conventional altimetry, which provides point data along profiles at resolutions of tens or hundreds of kilometres, wide-swath altimetry provides a two-dimensional image with a horizontal resolution of the order of tens or hundreds of meters. Therefore, this mission will significantly improve both offshore and coastal ocean observation, while enabling global measurement also of the water levels (and their variations over time and space) of rivers, lakes and flood zones, with a repeat period of 21 days.

Over land, SWOT is planned to survey lakes with a surface area larger than 250 m by 250 m (objective: 100 m by 100 m). To do so, three main products are available to the user community. The pixel cloud (L2_HR_PIXC) product provides longitude, latitude, height, corrections and uncertainties for pixels classified as water and pixels in a buffer zone around these water bodies, as well as in systematically included areas (defined by an a priori water occurrence mask). The product specific to lakes (L2_HR_LakeSP) is computed from the pixel cloud for each water feature observed by SWOT and not assigned to a regular river. It consists of polygon shapefiles, delineating the lake boundary and providing the area and average height of each observed lake. A Prior Lake Database (PLD) allows to link the SWOT observations to known lakes and help monitoring them over time. The L2_HR_LakeAvg product aggregates L2_HR_LakeSP data over a 21-day cycle.

The validation of L2_HR_LakeSP water surface elevations is mainly based on existing gauge networks. It is a challenge to obtain reference height data that have an absolute accuracy well below what is required for the SWOT lake products we are validating (10 cm 1-sigma at the lake level). The validation of water surface areas relies on reference water masks obtained mainly from (Very-) High-Resolution optical or radar satellite images (Pléiades, Sentinel-2, Sentinel-1, RCM…), pre-processed so that comparisons can be made at the lake scale.

This presentation will first outline the lake processing and the Prior Lake Database. Then examples of products, preliminary accuracy assessments and associated Cal/Val activities will be presented.

How to cite: Pottier, C., Cazals, C., Battude, M., Delhoume, M., Crétaux, J.-F., and Fjørtoft, R.: SWOT lake processing and products, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10929, https://doi.org/10.5194/egusphere-egu24-10929, 2024.

Remote sensing techniques are crucial for sustaining a continuous and global climate monitoring of inland waters. In particular, recent progress in satellite radar altimetry has enabled the observation of an increasing number of small and medium size lakes and reservoirs, even in complex topography. The arrival of nadir radar altimeters operating in Synthetic Aperture Radar (SAR) mode has considerably improved the resolution of the observations in the along-track direction, passing from several kilometers in conventional limited-pulse altimeters, to hundreds of meters in close-burst altimeters when applying unfocused SAR (UFSAR) processing and even to the theoretical limit of half the along track antenna length in open-burst altimeters that can totally exploit the Fully-Focused SAR (FFSAR) processing technique. Sentinel-6 is the first operational mission to operate in open-burst mode allowing this enhanced performance over inland waters [1]. Complementary to nadir radar altimetry, SWOT mission provides since the beginning of 2023 radar interferometry observations over wide-swaths that could entail great advances in hydrology [2].

The inversion methods to estimate geophysical parameters, such as Lake Water Level (LWL), from the backscattered altimetry signal are commonly called retrackers. These retrackers can be empirical, such as the widely used OCOG method or physically-based, that is to say, a background waveform model is derived from the theoretical knowledge of the microwave scattering process and then fitted to the real backscattered signal received on-board. Several retrackers of the second type have been developed for processing conventional pulse-limited radar observations, like the Brown-like models, and also for UFSAR observations in the case, for example, of the SAMOSA model. Nevertheless, no specific retracker for FFSAR observations has been developed yet. One of the limitations of analytical and numerical physical-based retrackers concerns the assumption that the radar footprint is completely covered by water. This assumption, that holds for large lakes, begins to degrade the accuracy on the retrieved geophysical parameters when monitoring smaller water bodies. For this reason, a retracker based on numerical simulations was proposed in 2021 adapted to UFSAR observations [3]. This latter model has the advantage of taking into account a prior knowledge of the lake contour and, in this way, only in-water areas of the radar footprint contributes to the simulated backscattered waveform. In this work, the derivation of a similar retracker taking into account the FFSAR processing particularities is presented. This results in the first retracking model specifically developed for FFSAR observations. Preliminary performance is assessed with a variety of lakes for which in-situ observations of LWL are available. Furthermore, a comparison with the recently delivered first products of the SWOT mission over lakes will be presented.

[1] Donlon, C.J., et al, 2021. The Copernicus Sentinel-6 mission: Enhanced continuity of satellite sea level measurements from space. Remote Sensing of Environment, 258, p.112395.

[2] Biancamaria, S., et al, 2016. The SWOT mission and its capabilities for land hydrology. Remote sensing and water resources, 117-147.

[3] Boy, F., et al, 2021. Improving Sentinel-3 SAR mode processing over lake using numerical simulations. IEEE Transactions on Geoscience and Remote Sensing, 60, pp.1-18.

How to cite: Yanez, C., Boy, F., Calassou, G., Daguzé, J.-A., and Asfour, K.: Performance assessment of Lake Water Level estimation from Sentinel-6 Fully-Focused SAR observations and comparison to SWOT mission, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5773, https://doi.org/10.5194/egusphere-egu24-5773, 2024.

The aim of the study is to investigate the changes in the water level and surface area of Lake Iznik in Northwestern Anatolia, Türkiye, between 2014 and 2024. In this context, High-Resolution Satellite images provided by European Space Agency (ESA)'s Sentinel-2 are used to determine the lake surface area, and satellite altimetry data provided by Copernicus Land Service is utilized to determine the lake water level. Additionally, temperature and precipitation data from a meteorological station near the lake are obtained from the Turkish State Meteorological Service due to their significant impact on the lake's water level and surface area changes.

The estimated trend for the change in the water level from 2014 to 2024 is -23±1.9 cm/yr, and the change in the surface area trend is estimated as -1.2±0.2 km²/yr. The results indicate a decrease in both the lake's water level and surface area. Furthermore, Standardized Precipitation Index (SPI) and Standardized Precipitation-Evapotranspiration Index (SPIE) are calculated from precipitation and temperature data obtained from meteorological stations near the lake. These indices reveal a decrease in precipitation and an increase in temperatures in the Lake Iznik basin over the past 10 years.

Consequently, it is observed that the changes in the water level and surface of Lake Iznik are influenced by climate change, and hence,necessary measures need to be taken for the conservation and sustainable use of the lake.

How to cite: Erkoç, M. H., Doğan, U., Keser, B., and Bayram, B.: Effect of Climate Change on Water Level and Surface Area of Lake Iznik (NW Türkiye) , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4412, https://doi.org/10.5194/egusphere-egu24-4412, 2024.

Flooding is represented with a 2D hydrodynamic model over a reach of the Ohio river between Cannelton and Newburgh locks and dams. The geometry of the river and floodplain was provided by the National Oceanic and Atmospheric Administration (NOAA), based on U.S. Army Corps of Engineers (USACE) survey channel data merged with United States Geological Survey (USGS) LiDAR in the overbank regions. The description of hydraulic structures from USACE and in-situ water depth measurements from USGS stations were also used. Working from the 1D HEC-RAS model from Ohio University that covers a much larger area, the friction for our 2D local model was set uniformly over the floodplain. These values were further calibrated to 45 m1/3s-1 over the river bed and 17 m1/3s-1 with in-situ water depth measurements from USGS stations at Cannelton, Owensboro, and Newburgh over high flows periods in 2022 and 2023. 

The performance of the model was first assessed for the significant flooding event in February 2018, with RMSEs of the order of a few tens of centimeters. Remote-sensing (RS) products provided by satellite missions such as Sentinel-1 SAR, Sentinel-2 optical and Landsat-8 optical imagery undoubtedly offer opportunities to improve our ability to monitor and forecast flooding. For this study, the performance of the TELEMAC-2D (www.opentelemac.org) Ohio model was improved with the joint assimilation of in-situ and remote-sensing data within an EnKF framework that accommodates 2D RS-derived observations alongside with in-situ water level time-series. The RS-derived flood extent maps are expressed in terms of wet surface ratios (WSR) in selected subdomains of the floodplain. The assimilation of in-situ data reduces the RMSE to tenths of a centimeter. Ongoing work on the assimilation of WSR aims at improving the dynamic of the floodplain.  This 2D Ohio model will serve as a demonstrative test case for the FloodDAM-DT (https://www.spaceclimateobservatory.org/flooddam-dt) prototype dedicated to flood detection, mapping, prediction and risk assessment.

How to cite: Ricci, S., Nguyen, T. H., Piacentini, A., Rodriguez-Suquet, R., Pena-Luque, S., Bonassies, Q., Fatras, C., Astifan, B., Davis, R., Durand, M., and Coss, S.: Merits of Data Assimilation on Improving Flood Forecasting - A case study of Ohio Cannelton-Newburgh, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17653, https://doi.org/10.5194/egusphere-egu24-17653, 2024.

Wetlands and inundated areas cover only a few percent of the Earth's surface. However, they play an important role in freshwater regulation, biodiversity, and climate. In particular, a significant proportion of atmospheric methane is emitted from these areas [1]. There is therefore a need for data that can reliably capture surface water interannual variability over the past decades. 

The Global Inundation Extent from Multi-Satellites (GIEMS-2) [2] is based on microwave remote sensing data (SSM/I and SSMIS). It provides a 0.25° global monthly estimate of inundated and saturated areas and has been extended to 2020 to cover three decades (1992-2020). 

First, an evaluation of GIEMS-2 together with other products is presented. Key findings include consistent spatial patterns, seasonal cycles and time series anomalies observed by GIEMS-2 with the other observational datasets studied (MODIS-derived surface water, CYGNSS-derived surface water, river discharge). This highlights the interest of such a product for the calibration of hydrological models, as has been achieved for example by Xi et al. (2022) for TOPMODEL [3]. 

In a second part, the use of GIEMS-2 for the estimation of methane emissions from wetlands and inundated areas is discussed. GIEMS-2 has been processed with other data sources to derive a dynamic map of wetlands (including peatlands), open water (lakes, rivers, reservoirs) and rice paddies. This comprehensive product allows a consistent view of the area between the different classes, limiting problems of double counting and miss counting. This new database can then be used to constrain the extent of the water surface in models estimating methane flux rates, in order to study the influence of surface water changes on interannual variations in methane emissions.

[1] Marielle Saunois et al. “The Global Methane Budget 2000–2017”. In: Earth System Science Data 12.3 (July 2020), pp. 1561–1623. doi: 10.5194/essd-
12-1561-2020. url: https://doi.org/10.5194/essd-12-1561-2020.
[2] C. Prigent, C. Jimenez, and P. Bousquet. “Satellite-Derived Global Surface Water Extent and Dynamics Over the Last 25 Years (GIEMS-2)”. In: Jour-
nal of Geophysical Research: Atmospheres 125.3 (Feb. 2020). doi: 10.1029/2019jd030711. url: https://doi.org/10.1029/2019jd030711.
[3] Yi Xi et al. “Gridded Maps of Wetlands Dynamics over Mid-Low Latitudes for 1980–2020 Based on TOPMODEL”. In: Scientific Data 9.1 (June 2022), p. 347. issn: 2052-4463. doi: 10.1038/s41597-022-01460-w

How to cite: Bernard, J., Prigent, C., Jimenez, C., Saunois, M., Frappart, F., Normandin, C., Zeiger, P., Peng, S., Xi, Y., Fluet-Chouinard, E., and Zhang, Z.: Development of a global and dynamic map of wetland and inundated areas based on microwave remote sensing product (GIEMS-2) over 1992-2020, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10126, https://doi.org/10.5194/egusphere-egu24-10126, 2024.