HS6.8

River discharge is an essential component in the hydrological cycle. It is used to monitor rivers, the atmosphere, and the ocean through in-situ measurements, acquired on the surface, or from remote sensing to characterize natural disasters such as floods.

Estimating discharge in ungauged rivers with remote sensing data such as the Surface Water and Ocean Topography (SWOT) mission but without any prior in-situ information is difficult to solve, especially in the case of unknown bathymetry, friction, and lateral river flows. However, the current literature suggests that a better knowledge of bathymetry could considerably facilitate roughness and discharge inferring. SWOT observes water surface elevations, slopes, river widths for several overpasses. We propose an inverse method to estimate discharge in a non-uniform steady-state, maintaining longitudinal (alternating pool-riffle) and lateral (meanders) morphological variability of the river. The idea is to build a rating curve (water level - discharge relationship) at the reach scale using hydraulic signatures (quantities not related to a particular section of the reach, which characterize an aspect of the overall hydraulic behavior: e.g., flooded area as a function of Q, mean water level as a function of Q). The inverse approach requires building a model that produces rating curves that optimally correspond to the hydraulic signatures. It requires a direct hydraulic model and a geometric simplification to facilitate the resolution of the inverse problem.

The approach is based on the geomorphology of rivers. Indeed, the geometry of natural rivers presents high-frequency variability, characterized by alternating flow units: fast-flowing flow units in rectilinear and shallow areas (riffles), slow-flowing flow units in deeper areas (pools at alternating banks or inner side of meandering bends). This variability generates a variability of the hydraulic variables that covary at the reach scale. However, a simplification into a uniform geometry without spatial variability reappears as a bias in the frictional parameters, thus reducing the inversion's accuracy. For this, we propose a periodic approach that consists of representing the reach equivalent geometry by sinusoidal functions.

This direct periodic model is used to create a whole periodic geometry (curved based asymmetry sections, Kinoshita curves to model the meander planform) and then solve the Saint-Venant equations in the 2D Basilisk hydraulic model (http://basilisk.fr), which is based on finite volume methods with adaptive grid refinement.

This model does not require boundary conditions (use of periodic boundary conditions) and provides the ability to model floodplains and thus flood mapping. In the end, there are few parameters to adjust in the model (use of parameters covariances).

How to cite: Mahdade, M., Le Moine, N., and Ribstein, P.: How to build reach-averaged rating curves for remote sensing discharge estimation? The potential of periodic geometry hypotheses, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12476, https://doi.org/10.5194/egusphere-egu21-12476, 2021.

Historical and current information regarding river discharge is essential, not only from a water management, energy, or global change perspective but also to better analyze, control and forecast flooding. However, globally the number of ground-based gauging stations declines, and data that is measured by ground-based gauging stations is often not, or shared with a considerable delay.

It has been demonstrated that existing satellite sensors can be utilized for useful discharge measurements without requiring ground-based information. The DFO – Flood Observatory uses the Advanced Microwave Scanning Radiometer band at 36.5 GHz (e.g. TRMM, AMSR‐E, AMSR2, GMP), pre-processed by the Joint Research Center (JRC) to estimate discharges. With a nearly-daily repeat interval, this microwave signal has been successfully applied to measure water discharge at a global scale, where the calibration of the microwave discharge signal to discharge units is accomplished by comparison to results from a global hydrological numerical model, the Water Balance Model (WBM), for a calibration period. Once calibrated, daily discharge can be back-calculated to January 1998, providing a daily discharge record for more than 20 years.

Here we present the methods used to utilize remote sensing to measure discharge. We indicate the challenges and how to overcome these when using a multiple sensor approach to capture daily discharges for over a 20-year period. And we show an example for the Amazon river, comparing the remote sensed discharge data with ground observations for multiple locations. Additionally, applications are shown on how this discharge can be combined with flood extent maps to analyze flood frequency.

How to cite: Kettner, A., Brakenridge, R., and Cohen, S.: Remote sensed water discharge to analyze flood frequency, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-979, https://doi.org/10.5194/egusphere-egu21-979, 2021.

Flooding is one of the most financially devastating natural hazards in the world. Studying storage-discharge relations can have the potential to improve existing flood forecasting systems, which are based on rainfall-runoff models. This presentation will assess the non-linear relation between daily water storage (ΔS) and discharge (Q) simulated by physical-based hydrological models at the Rum River Watershed, a HUC8 watershed in Minnesota, between 1995-2015, by training Long Short-Term Memory (LSTM) networks and other machine learning (ML) algorithms. Currently, linear regression models do not adequately represent the relationship between the simulated total ΔS and total Q at the HUC-8 watershed (R² = 0.3667). Since ML algorithms have been used for predicting the outputs that represent arbitrary non-linear functions between predictors and predictands, they will be used for improving the accuracy of the non-linear relation of the storage-discharge dynamics. This research will mainly use LSTM networks, the time-series deep learning neural network that has already been used for predicting rainfall-runoff relations. The LSTM network will be trained to evaluate the storage-discharge relationship by comparing two sets of non-linear hydrological variables simulated by the semi-distributed Hydrological Simulated Program-Fortran (HSPF): the relationship between the simulated discharges and input hydrological variables at selected HUC-8 watersheds, including air temperatures, cloud covers, dew points, potential evapotranspiration, precipitations, solar radiations, wind speeds, and total water storage, and the dynamics between simulated discharge and input variables that do not include the total water storage. The result of this research will lay the foundation for assessing the accuracy of downscaled storage-discharge dynamics by applying similar methods to evaluate the storage-discharge dynamics at small-scaled, HUC-12 watersheds. Furthermore, its results have the potentials for us to evaluate whether downscaling of storage-discharge dynamics at the HUC-12 watershed can improve the accuracy of predicting discharge by comparing the result from the HUC-8 and the HUC-12 watersheds.

How to cite: Teng, P.-F. and Nieber, J.: Toward Downscaling Storage-Discharge Dynamics: Training Long Short-Term Memory (LSTM) model for Simulating Nonlinear Storage-Discharge Relations at The Rum River Watershed, MN, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3809, https://doi.org/10.5194/egusphere-egu21-3809, 2021.

The data from NASA’s Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) mission offer a unique opportunity to map rivers and lakes with an unprecedented number of observations in areas where previous missions have failed to provide valuable water level estimates. ICESat-2 carries just one instrument, the Advanced Topographic Laser Altimeter System (ATLAS), which is a green wavelength, photon-counting lidar, and several data products are available, such as the ATL03 product, which holds the photon data, and the ATL13 product which contains estimated inland water surface heights and statistics for water bodies across the world. The along-track resolution of the ATL03 product is less than 1 m, and with the three pairs of beams, i.e. six beams in total, the mission provides exceptional opportunities for inland water studies in areas with mountainous topography.

In general, inland water altimetry in mountainous areas has proven to be a challenge for both conventional Low Resolution Mode (LRM) and Synthetic Aperture Radar (SAR) altimetry, causing issues not only with waveforms, but also the position of the range window. In this study, we present the ability of ICESat-2 to obtain water levels in several mountainous rivers in China, where even SAR missions such as CryoSat-2 and Sentinel-3 have been unsuccessful. Results are shown for both the ATL03 and the ATL13 version 4 products to evaluate their performances.

How to cite: Ranndal, H., Nielsen, K., and Andersen, O. B.: Evaluation of ICESat-2 ATL03 and ATL13 River Levels in Mountainous Areas of China, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13378, https://doi.org/10.5194/egusphere-egu21-13378, 2021.

River discharge is a key variable to quantify the water cycle and its flux.  This study focuses on the river Rhine, of width between 200 and 500 meters. River discharge is evaluated in this paper from the Sentinel-3 altimeter water level using various approches, which are the empirical rating curve method, the semi-empirical Bjerklie method and the physically-based method based on hydraulic equations.

The Sentinel-3 GPOD ESA products from the SAMOSA+ retracker perform better than the standard Copernicus products that use the OCOG and ocean retrackers. Root-mean-square errors (RMSEs) between altimetry and in-situ stations are between 0.10 m and 0.30 m at 10 of the 17 virtual tide gauge locations. The empirical rating curve method applied to the altimetric water level and in-situ discharge provides estimates of the water discharge with accuracy of 3-7% (expressed as RMSE normalized with the mean of the discharge).

The performance of the semi-empirical Bjerklie method and of the physically-based Manning algorithm to estimate the river discharge is assessed from water surface slope, elevation and top width data for different part of the river and flow conditions. Firstly, daily synthetic water surface slopes and elevations are generated from selected in-situ gauges and mean top river widths. Secondly the input to the discharge algorithm comes from the 1D-hydrodynamic model Sobek. Various choises for reach lengths and for number of observed time-series are considered. Different time sampling are used to study the effect of the repeat cycle of nadir altimeter and SWOT missions. The effect of the priori information on the accuracy of the flow water discharge is investigated.

How to cite: Fenoglio-Marc, L., Zahkavova, E., Gärtner, M., Zohidov, B., Dinardo, S., and Duong, Q.: Discharge of the river Rhine from multi-sensor data from empirical and physical methods, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13857, https://doi.org/10.5194/egusphere-egu21-13857, 2021.

STREAM -SaTellite based Runoff Evaluation And Mapping- is a conceptual hydrological model able to derive daily river discharge and runoff estimates from satellite soil moisture, precipitation and terrestrial water storage anomalies observations. The model is very simple and versatile: It requires a limited number of parameters (only eight) to simulate river discharge.

The model simulates river discharge and gridded runoff at daily time scale with a 25 km spatial resolution. Forced by TRMM 3B42 rainfall data and ESA CCI soil moisture data and GRACE over five pilot large basins (Mississippi, Amazon, Niger, Danube and Murray Darling) the model already provided good runoff estimates especially over Amazon basin, with a Kling-Gupta efficiency (KGE) index greater than 0.92 both at the basin outlet and over several inner stations in the basin. Good results have been also obtained for Mississippi, Niger and Danube with KGE index greater than 0.75 for all the gauging stations.

By considering the good performances of the STREAM model and by the continuous availability (in space and time) of satellite observations, this work presents an attempt to regionalize the STREAM model parameters. The Mississippi river basin has been taken as case study and specific relationships between model parameters and different predictors (climate variables such as precipitation and evaporation, soil vegetation and topography characteristics) have been developed. By using these relationships, STREAM parameter values have been directly obtained from readily available climatic and physiographic basin characteristics and model performances are still satisfactory (median KGE over the basin equal to 0.60). The capability to use these relationships in other hydrologically similar catchments will be investigated for the Danube and Amazon river basins. The final target is to obtain global relationships as to provide to provide daily, 25 km, global runoff maps from the STREAM approach.

How to cite: Camici, S., Giuliani, G., Brocca, L., Massari, C., Tarpanelli, A., Restano, M., and Benveniste, J.: Global runoff estimation through a regionalized STREAM model, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14175, https://doi.org/10.5194/egusphere-egu21-14175, 2021.

In a near future, the Sahara and Sahelian regions could experience more rainfall than today as a result of climate change. Wetter conditions in the hottest and driest place of the planet today raise the question of whether the near future might hold in store environmental transformations, particularly in view of the growing human-induced climate, land-use and land-cover changes. Reflecting an enhancement of the global hydrological cycle under warmer conditions, some experiments provide support for the notion of a strengthening of the monsoon in the future and more rainfall in central Sahel and Sahara. However, some remote forcing could counterbalance the decadal trend. Modeling experiments suggest that the freshwater discharge coming from Greenland melting could significantly impact the sea surface temperature of North Atlantic and induce a decrease in Sahel rainfall for the next decades, remaining left open the question how Sahara will be in a warmer climate?

By chance, Lake Chad, located at the southern edge of the Sahara, is recognized for being the best site in Africa for deciphering hydrological and climate change. After being ranked at the world’s sixth largest inland water body with an open water area of 25,000 km² in the 1960s, it shrunk dramatically at the beginning of the 1970s and reached less than 2000 km² during the 1980s, decreasing by more 90% in area. Because it provides food and water to 50 millions of people, it becomes crucial to observe precisely its hydrological cycle during the last 20 years.

Here by using a new multi-satellite approach combined with ground-based observations, we show that Lake Chad extent has remained stable during the last two decades, slightly increasing at 14,000 km². We extend further this reconstruction by adding new data from the hydrological year 2019-2020, which is considered at an extreme in precipitation recorded over the Sahel. Moreover, since the 2000s, groundwater which contributes to 70% of Lake Chad’s annual water storage, is increasing due to water supply provide by its two main tributaries draining a catchment area 610,000 km² wide. Because the current climate change seems to be characterize by a higher interannual variability affecting from year to year the amount of precipitation during the rainy season and increasing the vulnerability of the economy of the region mainly based of agropastoral activities, we investigate the yearly cycle and see how it is impacted the hydrological cycle of Lake Chad and changed over time.

How to cite: Sylvestre, F., Crétaux, J.-F., Berge-Nguyen, M., Pham Duc, B., Mahamat Nour, A., Bouchez, C., Frappart, F., and Papa, F.: Lake Chad hydrological cycle under current climate change, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12738, https://doi.org/10.5194/egusphere-egu21-12738, 2021.

In the recent years, southern Sweden has experienced drought conditions during the summer with potential risks of groundwater shortages. One of the main physical effects of groundwater depletion is land subsidence, a geohazard that potentially damages urban infrastructure, natural resources and can generate casualties. We here investigate land subsidence induced by groundwater depletion and/or seasonal variations in Gotland, an agricultural island in the Baltic Sea experiencing recent hydrological droughts in the summer. Taking advantage of the multiple monitoring groundwater wells active on the island, we explore the existence of a relationship between groundwater fluctuations and ground deformation, as obtained from Interferometric Synthetic Aperture Radar (InSAR). The aim in the long-term is to develop a high-accuracy map of land subsidence with an appropriate temporal and spatial resolution to understand groundwater changes in the area are recognize hydroclimatic and anthropogenic drivers of change.

We processed Sentinel-1 (S1) data, covering the time span of 2016-2019, by using the Small BAseline Subset (SBAS) to process 119 S1-A/B data (descending mode). The groundwater level of Nineteen wells distributed over the Gotland island were used to assess the relationship between groundwater depletion and the detected InSAR displacement. In addition to that, the roles of other geological key factors such as soil depth, ground capacity in bed rock, karstification, structure of bedrock and soil type in occurring land subsidence also investigated. The findings showed that the groundwater level in thirteen wells with soil depths of less than 5 meters correlated well with InSAR displacements. The closeness of bedrock to ground surface (small soil depth) was responsible for high coherence values near the wells, and enabled the detection land subsidence. The results demonstrated that InSAR could use as an effective monitoring system for groundwater management and can assist in predicting or estimating low groundwater levels during summer conditions.

How to cite: Darvishi, M. and Jaramillo, F.: Detecting land deformation due to groundwater changes with InSAR observations - the case of the island of Gotland, Sweden, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3402, https://doi.org/10.5194/egusphere-egu21-3402, 2021.

Wetlands store roughly 10% of global surface water in the terrestrial portion of the water cycle, cover roughly 9% of the Earth’s surface, and provide critical habitat for a wide variety of plant and animal species. Over the past century, many wetland areas have been lost, degraded, or stressed mainly due to anthropogenic activities, as water diversion, agricultural development, and urbanization, but also in response to natural processes, as sea level rise and climate change. Global and regional monitoring of wetland health and response to their natural and anthropogenic stressors are important and are best conducted using space-based remote sensing techniques, due to wetlands’ vast extent and often inaccessibility.

Several space-based remote sensing technologies provide high spatial resolution observations of wetland water level and its changes over time. These techniques include Synthetic Aperture Radar (SAR), optical imagery, radar and laser altimetry, and Surface Water Ocean Topography (SWOT). SAR observations include two independent observables, amplitude and phase; each observable is sensitive to different hydrological parameters. Radar and laser altimetry missions provide cm-level accuracy water level measurements along the satellite track. The SWOT mission, which is scheduled for a February 2022 launch, will use radar interferometer for repeated measurements of cm-level water level measurements over a 50-100 km wide swaths. As part of a NASA supported project, we develop a space-based multi-sensor monitoring system of surface water level changes in wetlands. The multi-sensor system will generate detailed multi-temporal maps of wetland inundation extent, water levels, and water level changes. The development of the multi-sensor monitoring system will be conducted over the south Florida Everglades, which can be considered as a natural laboratory due to its variable land cover and the availability of ground-based hydrological observations. Preliminary results based on Interferometric Synthetic Aperture Radar (InSAR) observations yielded detailed maps of water level changes of the entire Everglades wetlands with 100 m spatial resolution and 3-4 cm accuracy level. After development, the system will be tested in two other wetland areas located in Louisiana, and Peace–Athabasca Delta (Alberta, Canada).

How to cite: Wdowinski, S., Liao, H., and Zhang, B. (.: A multi-sensor monitoring system of surface water level changes in wetlands, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6768, https://doi.org/10.5194/egusphere-egu21-6768, 2021.

Hydrological connectivity is a critical determinant of wetland functions and ecosystems by controlling the movement of biogeochemical elements within wetlands and the flow of water between their hydrological units. Hydrological barriers exist when this connectivity is impaired, either by man-made infrastructure, agriculture developments, or naturally restricted by soil and ground composition. Determining hydrological barriers in wetlands is challenging due to the costs of high-resolution and large-scale monitoring, but radar observations can become a useful tool for such task. We here use an Interferometric Synthetic Aperture Radar (InSAR) to identify hydrological barriers in several iconic wetlands worldwide, with particular focus on the Baiyangdian wetland system in Northern China. For the first, we use Sentinel 1A and 1B data covering the period 2016-2019, while for the rest we rely on ALOS PALSAR data. We calculated profiles of water level change across hydrological transects showing high coherence and visualized them in maps. For instance, in the case of the Baiyangdian wetland, we find that of the 70 transects studied, 11% of all transects are permanently disconnected by hydrological barriers across all interferograms and 58% of the transects are conditionally disconnected. The occurrence of hydrological barriers varies between wetlands, with permanent barriers more related to ditches, infrastructure and the specific wetland landscape, and conditional barriers more to low water levels during dry seasons. This study highlights the potential of the application of wetland InSAR to determine hydrological barriers for wetland management and restoration.

How to cite: Jaramillo, F., Liu, D., Aminjafari, S., and Wang, X.: Determining hydrological barriers in wetlands with InSAR methods: several iconic cases worldwide, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14620, https://doi.org/10.5194/egusphere-egu21-14620, 2021.

Fresh water is an essential resource that requires a close monitoring and a constant preservation effort. The evolution of hydrological bodies water level constitutes a key indicator on the available quantity of fresh water in a given region. The limited extent of the in situ networks currently deployed has generated a growing interest in using space borne altimetry as a complementary data source to increase the coverage of emerged fresh water stocks and ensure a more global and continuous monitoring of their water surface height.

A great effort has been carried out over the past decade to improve altimeters’ capability to acquire quality measurements over inland waters. In particular, the Open-Loop Tracking Command (OLTC), which consists in calibrating the altimeter signal acquisition window with a prior information on the overflown hydrological surface height, represents a major evolution of the tracking function. This tracking mode’s efficiency is such that it is now stated as operational mode for current Sentinel-3 and Jason-3 missions as well as the recently launched Sentinel-6A mission. The improvements brought to onboard tables contents in 2017 (Jason-3), 2018 (Sentinel-3B) and 2019 (Sentinel-3A) enhanced and confirmed the OLTC performances.

In 2020, the onboard OLTC tables of the Jason-3, Sentinel-3A and Sentinel-3B missions have benefitted from further new major upgrades. The first version of the Sentinel-6A onboard OLTC tables holds the same content as Jason-3. The tracking command defined over Jason-3 and Sentinel-6A repeat cycle now accounts for more than 30,000 hydrological targets which represents five times more targets than in the previous version. For each Sentinel-3, the number of water body surface heights coded into the OLTC has been increased by a factor of 3 to 70,000. This further major step is made possible by the analysis and merging of the most recent digital elevation models (SRTM, MERIT and ALOS/PalSAR) and water bodies databases (HydroLakes, GRaND v1.3, SWBD, GSW). This methodology ensures coherency and consistent standards between all nadir altimetry missions and types of hydrological targets.

A detailed description of the 2020 upgrades will be given as well as measurements validation results obtained since their upload. An overview of the global validation of Sentinel-6A measurements over hydrological targets will also be presented.

These 2020 OLTC upgrades constitute a great asset for building a valuable and continuous record of the water surface height of worldwide lakes, rivers, reservoirs and wetlands. In addition, for a continuous improvement of the OLTC tracking mode, the users can check the content of the onboard OLTC tables over hydrological targets for both Sentinel-3 missions on the https://www.altimetry-hydro.eu/ web portal. When relevant, they can correct existing water surface heights or submit new targets.

How to cite: Boitard, S., Le Gac, S., Blumstein, D., Munesa, E., Boy, F., Jeansou, E., Cancet, M., Grignon, L., Picot, N., and Féménias, P.: New upgrades of Open-Loop Tracking Command (OLTC) tables of nadir altimeters in 2020 and benefits for inland waters users, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4129, https://doi.org/10.5194/egusphere-egu21-4129, 2021.

The scope of this presentation is to feature and provide an update on the ESA G-POD/SARvatore family of altimetry services portfolio for the exploitation of CryoSat-2 and Sentinel-3 data from L1A (FBR) data products up to SAR/SARin Level-2 geophysical data products. At present, the following on-line & on-demand services compose the portfolio:

-       The SARvatore (SAR Versatile Altimetric TOolkit for Research & Exploitation) for CryoSat-2 and Sentinel-3 services developed by the Altimetry Team in the R&D division at ESA-ESRIN. These processor prototypes are versatile and allow the users to customize and adapt the processing at L1b & L2 according to their specific requirements by setting a list of configurable options. The scope is to provide users with specific processing options not available in the operational processing chains (e.g. range walk correction, stack sub-setting, extended receiving window, zero padding, high-posting rate and burst weighting at L1b & SAMOSA+, SAMOSA++ and ALES+ SAR retrackers at L2). AJoin & Share Forum (https://wiki.services.eoportal.org/tiki-custom_home.php) allows users to post questions and report issues. A data repository is also available to the Community to avoid the redundant reprocessing of already processed data (https://wiki.services.eoportal.org/tiki-index.php?page=SARvatore+Data+Repository&highlight=repository).

-       The TUDaBo SAR-RDSAR (Technical University Darmstadt – University Bonn SAR-Reduced SAR) for CryoSat-2 and Sentinel-3 service. It allows users to generate reduced SAR, unfocused SAR & LRMC data. Several configurable L1b & L2 processing options and retrackers (BMLE3, SINC2, TALES, SINCS) are available. The processor will be extended during an additional activity related to the ESA HYDROCOASTAL Project (https://www.satoc.eu/projects/hydrocoastal/) to account in the open ocean for the vertical motion of the wave particles (VMWP) in unfocused SAR and in a simplified form of the fully focused SAR called here Low Resolution Range Cell Migration Correction-Focused (LRMC-F).  

-       The ALES+ SAR for CryoSat-2 and Sentinel-3 service. It allows users to process official L1b data and produces L2 NetCDF products by applying the empirical ALES+ SAR subwaveform retracker, including a dedicated SSB solution, developed by the Technische Universität München in the frame of the ESA Sea Level CCI (http://www.esa-sealevel-cci.org/) & BALTIC+ SEAL Projects (http://balticseal.eu/).

-       The Aresys Fully Focused SAR for CryoSat-2 service. Currently under development, it will provide the capability to produce CS-2 FF-SAR L1b products thanks to the Aresys 2D transformed frequency domain AREALT-FF1 processor prototype. Output products will also include geophysical corrections and threshold peak & ALES-like subwaveform retracker estimates.

The G-POD graphical interface allows users to select, in all the services, a geographical area of interest within the time-frame related to the L1A (FBR) & L1b data products availability in the service catalogue.  

After the task submission, users can follow, in real time, the status of the processing. The output data products are generated in standard NetCDF format, therefore being compatible with the multi-mission “Broadview Radar Altimetry Toolbox” (BRAT, http://www.altimetry.info) and typical tools.

Services are open, free of charge (supported by ESA) for worldwide scientific applications and available, after registration and activation (to be requested for each chosen service to eo-gpod@esa.int), at https://gpod.eo.esa.int.

How to cite: Benveniste, J., Dinardo, S., Buchhaupt, C., Scagliola, M., Passaro, M., Fenoglio-Marc, L., Sabatino, G., Ambrózio, A., and Restano, M.: SAR, SARin, RDSAR and FF-SAR Altimetry Processing on Demand for CryoSat-2 and Sentinel-3 at ESA G-POD, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12480, https://doi.org/10.5194/egusphere-egu21-12480, 2021.