The Congo River Basin (CRB), located in the central region of Africa, is of particular importance for regional and global climate and carbon studies. Being the second largest river basin after the Amazon, it is also the one with the most free-flowing rivers. However, despite these important characteristics, it has not attracted as much attention among the scientific communities as the Amazon Basin or other large tropical rivers in the world. Because of the lack of comprehensive and maintained in situ data networks over time, large-scale monitoring of hydroclimatic variables has not been properly conducted. In this context, near real-time observations of the CRB, such as water surface elevation (WSE) and river discharge, as well as understanding the impacts of climate change in a spatiotemporally distributed manner across the basin present a major challenge. In the last few years, however, the scientific community, supported by the leading operational organism in the CRB (the CICOS), has worked on applying innovative tools, from hydrological and hydrodynamic modeling to the use of space data, to improve this monitoring and understanding of hydrological processes.

Our work illustrates how space Earth Observation (EO) datasets used jointly with a hydrological model improve both near-real-time monitoring and past-period revisiting (from 1980). First, we built and validated an extensive database on long-term time series of water levels (WL) from satellite altimetry using a comprehensive unprecedented in situ database (root mean square error varying between 10 cm to 75 cm). Crossing this database with the Global Inundation Extent from Multi-Satellites (GIEMS) database, we analyzed the normal behavior of surface water in the CRB, and worked  towards understanding the genesis of recent extreme events. The observations permitted to highlight the different travel time of waters from one to three months depending on its origin, and to discriminate the relative contribution of southern and northern sub-basins to the first and second peaks at the outlet of the basin Kinshasa/Brazzaville station. These datasets are then used to calibrate/validate the setting of a large-scale hydrologic and hydrodynamic model, the MGB model, in which lakes representation parameters are tuned using all the aforementioned databases and the long term CHIRPS precipitation product. In terms of discharge estimates, the model run resulted in an average KGE efficiency index value of 0.84 and 0.71 for the calibration (2001-2020) and validation (1981-2000) periods respectively.

When included within a scheduler, this model run validated by space EO datasets now permits the inference of discharge and depths all over the basin in real-time. In addition, data assimilation techniques applied to ingest remote sensing datasets, into the MGB model, improves such real-time estimates. Long term modeling also provides a new look and understanding on recent hydrological extreme events that occurred in the CRB, and permits analyzing the impact of recent global and regional climate change on freshwater in one of the most free-flowing watersheds.

How to cite: Kitambo, B., Wongchuig, S., Papa, F., Paris, A., Tshimanga, R., Gal, L., Juca-Oliveira, R., Calmant, S., Fleischmann, A., Tondo, B., and Brachet, C.: From real-time monitoring to climate studies in the Congo basin: role of spatial hydrology and remote sensing datasets, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16581, https://doi.org/10.5194/egusphere-egu23-16581, 2023.

Floodplains are essential elements of terrestrial water storage and perform various hydrogeomorphic, ecological, and socio-economic services. Ganga Plains are one of the world's largest and most populous plains. The East Ganga Plain (EGP), other than being densely populated, is also a fluvially highly dynamic region. This region hosts ‘hyperavulsive’ rivers and numerous wetlands, some of which are the largest wetlands of the Ganga Plains. Due to frequent flood hazards, all rivers of the region are embanked on both banks. We are investigating the surface dynamics of the region by calculating the surface displacement using InSAR (Interferometric Synthetic Aperture Radar) time series in ISCE-2 and Mintpy environments. We calculated the InSAR stack for the period Oct 2016 to May 2022 and built the connected network for the next three neighbours. We iteratively chose the multilooking value of azimuth 11 and range 78 to mitigate the low coherence issues due to the vegetation. We used ascending and descending tracks of Sentinel-1 to calculate the horizontal and vertical components of the velocity. Our results show that the entire area is tectonically subsiding. However, the spatial pattern of subsidence rate is varying – surfaces with seasonal water cover, such as active channel belts and wetlands, are exhibiting the highest subsidence rates with up to 7 cm/y and twice the subsidence rates of non-water surfaces. In many regions, the subsidence is accelerating.

We are using satellite-based multispectral indices (MNDWI, NDVI) and in-situ measurements such as groundwater depth and rainfall and land use data to investigate the disparity in the subsidence rates in the region. The preliminary results suggest that the waterbodies are drying, vegetation cover and irrigation are increasing, and rivers are disconnected from their floodplains due to embankments. We emphasise the anthropogenic role in the acceleration of the subsidence due to river embankment, augmented by a high drawdown of groundwater for irrigation purposes.

How to cite: Singh, M. and Bookhagen, B.: Assessing floodplain dynamics using radar interferometry in the East Ganga Plains, India, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11349, https://doi.org/10.5194/egusphere-egu23-11349, 2023.

In this study, we aim to shed light on the feasibility of assimilating synthetic aperture radar (SAR) data into a partial differential equation-based model of a poroelastic homogeneous aquifer with anisotropic hydraulic conductivity (AHC).

Although other authors [1] have considered the problem of assimilating SAR data into a poroelastic model that uses an inhomogeneous random field model for the hydraulic conductivity, to the best of our knowledge this is the first study to consider assimilating SAR data into a poroelastic model with AHC.

Our study is inspired by the work of [2] where an aquifer test is performed on the Anderson Junction aquifer in southwestern Utah. Due to the inherent preferential direction of the fractured sandstone at the Anderson Junction site, the ratio of hydraulic conductivity along the principal axes can be on the order of 24 to 1.

We build an anisotropically conductive poroelastic finite element model of the Anderson Junction site that can predict the coupled fluid flow and mechanical displacements. Our results show that the effective elastic response of the aquifer on the Earth’s surface has an anisotropic nature driven by the underlying anisotropy in the fluid problem, even when the elasticity problem is assumed to be isotropic. We interpret these results in the context of using SAR data to improve the characterization of aquifer systems, like the Anderson Junction site, with strongly anisotropic behavior.

[1]      A. Alghamdi, “Bayesian inverse problems for quasi-static poroelasticity with application to ground water aquifer characterization from geodetic data,” Thesis, 2020. doi: 10.26153/tsw/13182.

[2]      V. M. Heilweil and P. A. Hsieh, “Determining Anisotropic Transmissivity Using a Simplified Papadopulos Method,” Groundwater, vol. 44, no. 5, pp. 749–753, 2006, doi: 10.1111/j.1745-6584.2006.00210.x.

How to cite: Salehian Ghamsari, S., Van Dam, T., and S. Hale, J.: Towards assimilating SAR data into an anisotropic model of an underground aquifer, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14634, https://doi.org/10.5194/egusphere-egu23-14634, 2023.

Water resources are under immense stress due to the continuous increase of anthropogenic and natural pressures. Therefore, effective water management backed by advanced tools and methods is essential for the sustainability of water resources. One of these tools is groundwater flow modeling, which can be used to estimate changes in groundwater storage. In this study, we propose an approach to improve groundwater flow modeling by supporting model calibration with remote sensing data. The approach is demonstrated on the Alaşehir-Sarıgöl sub-basin in the east of the Gediz River Basin, a water-stressed basin in western Turkiye. A MODFLOW-2005 based flow model is constructed to determine time series hydraulic head changes and aquifer storage. The model simulation period is from 2013 to 2021. The groundwater recharge input of the model is obtained by a remote sensing-supported water balance method (Batkan et al., 2022). Except for precipitation data measured at meteorological stations, other model parameters are remote sensing products. Evapotranspiration is obtained from the MODIS Global Evapotranspiration product (MOD16A2), and soil water content and runoff are obtained from the ERA-5 Land Model reanalysis dataset. Hydraulic parameters such as hydraulic conductivity and storage coefficient are determined as a result of the calibration of the groundwater flow model. Model performance is improved by using terrestrial water storage (TWS) data from NASA's GRACE mission in the calibration of the storage coefficient. TWS represents the total water content above and below ground in the unconfined aquifer, therefore data needs to be adjusted to obtain an estimate of groundwater storage. Streams in the region can be ignored as a contributor to the TWS as they are intermittent and have typically low discharges. The soil water content in the unconfined aquifer is determined using ERA-5 data. The calibrated model RMSE value is 7.4 m, which was subsequently improved to lower values after the conjunctive use of the GRACE-derived TWS data.

Keywords: groundwater flow modeling, model calibration, remote sensing, GRACE, ERA-5

Acknowledgment: This study is funded by the PRIMA program supported by the European Union under grant agreement No: 1924, project RESERVOIR (sustainable groundwater RESources managEment by integrating eaRth observation deriVed monitoring and flOw modelIng Results).

How to cite: Batkan, E. A., Çaylak, B., Bayırtepe, M. B., Ören, A. H., and Elçi, A.: Using GRACE Terrestrial Water Storage Data for Groundwater Flow Model Calibration of Alaşehir-Sarıgöl Sub-Basin, Turkiye, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15091, https://doi.org/10.5194/egusphere-egu23-15091, 2023.

Lake Urmia, located in northwestern Iran, is the largest salt lake in the Middle East (ME) and one of the largest hypersaline lakes in the world. The lake has an important role in biodiversity preservation and the economic and cultural aspects of its surrounding region. Over the last two decades, the combined effects of climate change and anthropogenic activities have caused a significant depletion of lake water. The interaction of lake water and groundwater has motivated us to study the surrounding aquifers to determine the impact of human activities on the lake. The Shabestar plain located in the northeast of Lake Urmia is chosen as the research area for the current study. The goal is to find a Remote Sensing (RS) based method to estimate the changes in groundwater level, due to over-exploitation, both in time and space. We use a random forest algorithm to determine the contribution of different factors in the estimation of the aquifer’s hydraulic properties. Input data include the surface deformation rate produced by Interferometric Synthetic Aperture Radar (InSAR) technique between 2016 and 2022, weather-driven parameters including temperature, precipitation, soil moisture, normalized differential vegetation index, and evapotranspiration, and the hydrological factors including observed well and lake water levels. The built model is then used for estimating the spatiotemporal groundwater level changes throughout the aquifer. The groundwater level change and its relationship with the lake water surface is investigated. The model has the potential to be generalized in the estimation of groundwater depletion in similar aquifers.

How to cite: Khodaei, B., Hashemi, H., Naghibi, S. A., and Berndtsson, R.: InSAR-AI-Based Approach for Groundwater Level Prediction in Arid Regions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-754, https://doi.org/10.5194/egusphere-egu23-754, 2023.

The Sentinel-6 mission, launched in November 2020 is a satellite mission carrying an altimeter operating in open-burst, the Poseidon-4 altimeter. This altimeter has a PRF of approximately 9 kHz, able to perform focussing of whole target observation echoes in a totally coherent way. This means that not only we are obtaining measurements with very reduced contaminant contributions coming from along-track replicas, but also the along-track resolution can therefore be narrowed down to its theoretical limit (∼0.5 m) when processing the data with a Fully-Focussed SAR (FF-SAR) algorithm. The latter is what is of interest, especially when compared to the ∼300 m along-track resolution provided by other operational processors based on Unfocussed SAR algorithms, widely used in the bast majority of satellite missions with radar altimeters that operate with closed-burst (e.g. Sentinel-3).

In this study, we apply this algorithm to perform measurements of the water surface height (WSH) over a series of inland targets including relatively small reservoirs and lakes, with typical sizes between 0.1 and 10 km. To do so, a FF-SAR Ground Prototype Processor (GPP) developed by isardSAT and based on the back projection algorithm [1] has been used to process the Sentinel-6’s altimetry data and generate FF-SAR L1B records of the nadir targets being evaluated. This study will present the methodology defined to obtain the WSH measurements using the FF-SAR products alongside the validation process, based on comparison of results with in situ water height measurements.

[1] Egido, Alejandro and Walter H. F. Smith. “Fully Focused SAR Altimetry: Theory and Applications.” IEEE Transactions on Geoscience and Remote Sensing 55 (2017): 392-406.

How to cite: Molina Burgués, R., Gibert, F., Gómez, A., Garcia-Mondéjar, A., and Roca i Aparici, M.: Water Surface Height Measurements with Sentinel-6 Fully-Focussed SAR Over Inland Targets, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-449, https://doi.org/10.5194/egusphere-egu23-449, 2023.

The vast Amazon wetlands support multiple social-ecological systems basin-wide, and influence global water and carbon cycles. Recent environmental changes related to climate and infrastructure expansion have altered their rhythmicity and dynamics in many aspects, and understanding their impacts on hydrological variables such as river and floodplain water levels and discharges, inundation extent and storage, is urgent. The combination of new hydrodynamic modeling approaches with in situ and multisatellite data provides great opportunities to fostering this research agenda.

Here, we present an unprecedented analysis of the Amazon’s surface water dynamics, its status and long-term trends, as well as perspectives with in situ and satellite data. We analyze inundation extent, water levels and river-floodplain interactions based on in situ (water levels across rivers and floodplains) and satellite data (radar altimetry, optical imagery, passive microwave and L-band SAR), as well as hydrodynamic modeling (MGB and CaMa-Flood models). Firstly, we present the outcomes of a recent intercomparison project where 29 inundation datasets were compared across the basin (Fleischmann et al., 2022; WebGIS at <http://amazon-inundation.herokuapp.com/>). While a higher agreement was observed along the Amazon river floodplain, major discrepancies occurred for interfluvial wetlands, stressing the need of pursuing optimal merging techniques to improve local to large-scale inundation estimates. By looking at the dynamic inundation datasets, we were able to analyze long-term inundation trends, revealing a major increase of 26% in the maximum annual inundation across the Amazon River system since 1980, associated with longer flood duration and higher river-floodplain connectivity over multiple areas.

While changes in regional-scale hydroclimatic processes have led to the intensification of the Amazon’s hydrological cycle, local geomorphological processes are able to largely alter river-floodplain interactions. To investigate it, we used long-term optical data from the Global Surface Water dataset to assess changes along the Amazon River channels and the associated erosion/sedimentation processes. Our results evidence major changes along the river over the last decades, and a mapping of the impacts on 238 riparian communities shows that 21% have been largely affected by bank erosion, damaging several properties, while 19% have been affected by sedimentation, impairing transportation and reducing access to the river waters.

Finally, we present the first outcomes of a new floodplain hydrology monitoring network in the Mamirauá region of Central Amazon, which includes the widest floodplain reach of the Amazon. The network under development is the first of its kind in the Amazon, and aims at improving our understanding of river-floodplain dynamics through the optimal combination of in situ (more than 25 in situ water level loggers, several weather stations, among others) and satellite data, especially from current SAR altimetry missions such as Sentinel-3A/B and Sentinel6 and the forthcoming wide-swath SWOT mission. The presented results provide an important step towards a broad understanding of the Amazon surface water dynamics, from basin to local scales, and the sustainable use of the region’s river and wetland resources.

How to cite: Fleischmann, A., Papa, F., Fassoni-Andrade, A., Hamilton, S., Wongchuig, S., Paiva, R., Espinoza, J. C., Melack, J., Fluet-Chouinard, E., Zumak, A., Alves, P., Paris, A., Moreira, D., Silva, T., Yamazaki, D., Revel, M., and Collischonn, W.: Major changes in the dynamics of Amazon surface waters revealed by hydrodynamic modeling, in situ and multisatellite data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-870, https://doi.org/10.5194/egusphere-egu23-870, 2023.

In a context of a changing climate and an increasing anthropic pressure on natural resources, it is more than ever necessary to maintain or even improve our capacity to understand and monitor inland waters. It is particularly the case in French Guyana, where, despite its relative density, the in situ monitoring network fails at providing everyday information on rivers all over the territory. The use of free and open spatial datasets and hydrological modeling have shown great skills in complementing existing monitoring networks all over the world.  

Our work illustrates the use of a hydrological model, namely the MGB, set-up for 10 major watersheds in French Guiana (including the transboundary Maroni and Oyapock River - resp. with Suriname and Brazil- and some smaller ungauged basins) fed on a daily and near-real-time basis by IMERG-RT (Integrated Multi-satellitE Retrievals for GPM - Real Time) remote sensing precipitation products within a scheduler (namely HYFAA). In ungauged basins we used model parameters regionalisation to infer model parameters. The model performed well at inferring discharges, with KGE values higher than 0.7 when compared to gages. An extended dataset of rating curve between water surface elevation from nadir altimetry and simulated discharges is extracted using a physical-based processing of radar echoes on ESA Sentinel3 A&B and Jason3/Sentinel6 missions and also the time series available on Hydroweb website (https://hydroweb.theia-land.fr/). The quality of the rating curves confirms the skill of the model even in ungauged locations and watersheds with small contributive area. 

Thanks to this set-up, discharges and water levels are estimated daily all over the territory, and routinely corrected by the use of satellite altimetry. Using statistical rainfall predictions and watersheds concentration time, the system allows short-term forecasts of the discharge. In coordination with the in situ network operator, the critical thresholds were defined and are used to trigger  flood and droughts alerts, accessible online and received by email upon registration. As the methods used in this study have largely proved to be deployable anywhere, this simple framework draws the contour of future operational early warning systems based on space observation. 

How to cite: Paris, A., Gal, L., Calmant, S., Juca Oliveira, R., Boussaroque, M., Gosset, M., Gallay, M., Gobinddass, M.-L., and Biancat, C.: Spatial Hydrology for the Operational monitoring of French Guiana rivers, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9210, https://doi.org/10.5194/egusphere-egu23-9210, 2023.

River stage (surface water level H), discharge (volumetric water flow rate Q), and seasonal ice cover (freeze-up timing F, and break-up timing B) are crucial observables for hydrology and water cycle science.  In-situ river gauging measurements of H, Q, F, and B are laborious and costly to install and maintain at a limited number of locations.  It will be a breakthrough to use satellite data for global river measurements on a nearly-daily basis with multi-decadal data records.  Passive microwave radiometer (PMR) data have been collected from space globally since the 1980s.  Nevertheless, the typical satellite PMR resolution is coarse (10s km), which is much larger than general river widths.  The key question is how PMR can possibly measure the river parameters. 

The answer is physically founded on the first principle of Maxwell equations to derive vector wave equations for all polarization combinations in heterogeneous multi-layered geophysical media.  The wave equations are solved with dyadic Green’s functions subject to boundary conditions. The renormalization method is applied to determine the effective permittivity in each layer while all multiple wave-boundary interactions are included. To circumvent the limitation of the isothermal condition in the Kirchhoff approach, the fluctuation-dissipation theorem is used to calculate the brightness temperatureTb(h) for the horizontal polarization (the first modified Stoke parameter), Tb(v) for the vertical polarization (the second parameter), the polarization cross-correlation amplitude U (the third parameter), and the phase V (the fourth parameter).

Based on this physical foundation, a protocol to derive the river observables (H, Q, F, and B) is developed due to the high sensitivity of microwave emissivity of water versus ice and soil conveyed in the brightness temperatures. This overcomes and renders the high spatial resolution requirement unnecessary for river remote sensing by wide-swath PMR for global river observations on a daily or near-daily basis. The PMR method relies on the total areal change of river water within the footprint rather than depending on the river width per se.  As such, PMR can measure a narrow river when its meandering makes a sufficient total surface area in the PMR footprint.  The PMR method is also robust against short-term river channel migration and in-stream sand bars that can be changed by river sedimentation and dynamic processes.

To demonstrate the PMR capability for river monitoring, examples of satellite results for river measurements are compared and validated with in-situ river gauging time-series data records for various rivers from the tropics to cold land regions using PMR data at Ka-band such as AMSR-E, AMSR2, TRMM, and GPM and at L-band such as SMOS and SMAP.  The capability to measure global rivers allows PMR satellite missions to address hydrology and water cycle science as a key contribution, including the future Copernicus Imaging Microwave Radiometer (CIMR) to be launched in the 2025+ time frame, further extending the existing long-term data records for river measurements. Moreover, a significant advance of water cycle science is expected with the synergy of PMR together with SWOT successfully launched by NASA in December 2023.

How to cite: Nghiem, S., Brakenridge, R., Kugler, Z., and Podkowa, A.: Passive Microwave Emission Theory and Applications to Satellite Measurements of Global Rivers, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1206, https://doi.org/10.5194/egusphere-egu23-1206, 2023.

ICESat-2 measures the ground surface elevation with 6 laser beams grouped in three pairs of two, and pairwise separated by 3.3 km across track. This measurement configuration provides an unprecedented opportunity to measure local the water surface slope. Local water surface slopes can inform hydrodynamic models and improve performance.

The slopes are estimated by a linear regression of the water surface height as a function of the distance along the river. Water surface slopes are estimated for all intersections, independent of intersection angle, between ICESat-2 crossings and the river centerline where data is available and of reliable quality. The package is applied to the Amur river basin using 3.5 years of ICESat-2 data. More than 3700 slope estimates were produced with a median relative standard error of 2.1% across 1502 SWORD reaches out of 3360 reaches that intersect ICEsat-2 tracks.

In this study, an automatic method for estimating river surface slopes is developed and implemented in an R package. The package uses ICESat-2 ATL13 data and the SWOT River Database (SWORD) as the only compulsory input data. The R package can be tuned to fit the application of interest based on the user settings. This enables slope estimates to be computed globally with minimal additional effort.

This R package provides a tool that is easy to use and systematically gives local water surface slope estimates for a specified area of interest. Studies have shown how information of river slopes from twin in-situ gauge stations can improve discharge estimates from models. The global sparseness of in-situ stations limits the usability of models informed with slope estimates from gauge stations. Water surface slope estimates on local scale from satellite data increases the usability of these models.

How to cite: Christoffersen, L., Nielsen, K., Bauer-Gottwein, P., and Sørensen, L.: Estimating river surface slopes from ICESat-2 to inform hydrodynamic models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12986, https://doi.org/10.5194/egusphere-egu23-12986, 2023.

Remote sensing products provided by satellite missions, airborne and unmanned aerial vehicle (UAV) campaigns have tremendously developed over the last decade. They undoubtedly offer opportunities to improve our ability to monitor and forecast flooding. The observation of inland waters benefits from several altimetry missions that provide along-track water surface elevation observation from nadir (e.g. TOPEX/Poseidon, Jason, SARAL/AltiKa, Sentinel-6) or large-swath altimeters (e.g. SWOT launched in December 2022), as well as other radar/optical missions (Sentinel-1, Sentinel-2) that provide high-resolution water masks. The limitations of each type of sensor are potentially circumvented when data from different satellite sensors are combined; the fusion of multi-source data has thus become one of the mainstream research topics in the remote-sensing community nowadays. Such fusion can be achieved with data assimilation algorithms applied to hydrodynamics models, namely MASCARET-1D and TELEMAC-2D. 

The present work focuses on the validation of water surface height (WSH) data from Sentinel-6MF with respect to in-situ gauge data, UAV and 1D/2D-hydrodynamics model outputs as shown in Figure 1. This work participates in a global effort that aims at combining various remote sensing products to represent and forecast flooding. The study is carried out over a dry period in June 2022 and over a flood event that occurred in December 2021-January 2022 over the Garonne catchment near Marmande, in the southwest of France. The WSH of the river is retrieved from Sentinel-6MF high-resolution fully-focused SAR data with an algorithm that relies on the estimation of the river width and the positioning of the river center line. The impact of these a priori data is investigated and the Sentinel-6MF-derived WSH observations are compared to the WSH simulated with TELEMAC-2D. It should be noted that due to the defection of Sentinel-1B (one of the two satellites in the Sentinel-1 constellation) in mid-December 2021, this flood event is only partly observed by Sentinel-1A and that the additional data from Sentinel-6MF with a 10-day revisit period are of great use. This study shows that hydrodynamic simulations and satellite altimetry time-series compare particularly well during the dry period whereas flooding events are often underestimated by satellite altimetry data. We believe that the combined use of satellite altimetry, hydrodynamics model simulations and independent UAV-borne data is key to a better understanding of the processes involved in the Garonne river flow dynamics and flooding events. We also take advantage of this study to improve our Sentinel-6MF data processing techniques.

Figure 1- Representation of water level height and flood extent with remote sensing data and hydrodynamic models.

How to cite: Ricci, S., Nguyen, T. H., Le Gac, S., Boy, F., Piacentini, A., Rodriquez-Suquet, R., Peña-Luque, S., bonassies, Q., and emery, C.: Comparisons and water level analyses using Sentinel-6MF satellite altimetry data with 1D Mascaret and 2D Telemac models., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6513, https://doi.org/10.5194/egusphere-egu23-6513, 2023.

Wetlands play a crucial role in hydrological and biogeochemical cycles, and particularly in tropical and sub-tropical regions where they account for up to 3/4 of global methane emissions and act as water storage buffers in the landscape. The Congo being the world's second largest river both in terms of drainage area and annual mean discharge as well as the second largest rainforest area, contains large swaths of wetlands that have nevertheless been poorly studied. Remote sensing arguably offers the only viable strategy for mapping wetlands and their dynamics over the entire Congo River basin. Although there have been efforts that combine different type of sensors (microwave, optical etc.), they have been limited by the fact that most of the inundated areas in the Congo are under dense canopies while the bimodality of the river's hydrograph complicates the identification of the basin's hydrography. Global Navigation Satellite Systems Reflectometry (GNSS-R) is a remote sensing technique that has the potential to overcome some of those limitations. Recent work has shown that such observations from the Cyclone Global Navigation Satellite System (CYGNSS) satellite can successfully enable the mapping of inundation dynamics in wetlands on relatively short time scales. Here, we use CYGNSS satellite observations over the Congo River basin from early 2017 to present to quantify changes in wetland inundated area and the identification of hydrographic features such as floodplain channels in the basin. The mapping results are compared against in-situ hydrographic maps, while the dynamics are reconciled with additional satellite observations of precipitation and soil moisture. Furthermore, we use the derived data to inform and validate an existing hydaulic model of the middle reach of the Congo. Finally, we discuss the implications of GNSS-R observations for mapping wetland dynamics globally especially in the context of new and upcoming missions such as SWOT, NISAR, and HydroGNSS.

How to cite: Andreadis, K. and O'Loughlin, F.: Mapping wetland dynamics in the Congo River basin from GNSS-R and hydrological modeling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16105, https://doi.org/10.5194/egusphere-egu23-16105, 2023.