The Synthetic Aperture Radar (SAR) frequency on the Surface Water and Ocean Topography (SWOT) Mission is Ka-band: 35.75 GHz, which equates to an approximately 8mm wavelength. This is a relatively high-frequency system compared with the C-band on the now-ubiquitous Sentinel-1 or the L-band from UAVSAR and soon-to-launch NISAR Mission. Lower frequencies are the preferred method for most land surface studies because they have all-weather capabilities, and they can penetrate vegetation to reveal sub-canopy ground deformations, they make water detection easy as water surfaces are uniform; lower frequencies make these observations easier, higher frequencies make these observations harder. As a high-frequency system, SWOT was never designed to penetrate canopies or examine ground deformations. Rather, the high frequency from SWOT was selected for its potential to produce very high-resolution observations and have strong sensitivities to surface water, with the primary goals of measuring water surface elevations and water surface extents with high accuracy. Knowing that the high-frequency system would be sensitive to noise from vegetative land components, the mission requirements firmly asserted that the aim was to observe purely open water environments with high accuracy; vegetated water surfaces were to be assessed independently from the official SWOT open water algorithm goals. Recent studies being published have demonstrated that, as promised, SWOT can produce high-accuracy water surface elevations and water surface extents for the majority of cases, including in some sparsely vegetated wetlands. While there are still many studies to be conducted on SWOT open water, this presentation examines other phenomenological attributes of SWOT observations. As a swath mapper, SWOT's observations are acquired for 64km x 64km tiles covering both land and water. As a high-frequency system, with sensitivities to <1cm features, SWOT is not expected to penetrate the canopy-- it should observe it; SWOT is not expected to make water surfaces appear uniform-- it should highlight water surface roughness. Prior studies have demonstrated SWOT sensitivities related to 1) wind-driven water surface roughness, 2) vegetation structure, and 3) sub-canopy ponding and soil moisture. This presentation highlights progress in examining SWOT observations for More Than Just Surface Water Topography in support of improving SWOT discharge algorithms and other critical water cycle algorithms, such as for evaporation, transpiration, and canopy interception, for further reaching improvements to water resources research.

How to cite: Fayne, J.: More Than Just Surface Water Topography: Phenomenology Studies for the Surface Water and Ocean Topography (SWOT) Mission, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14496, https://doi.org/10.5194/egusphere-egu25-14496, 2025.

It is well known that the geoid signals over large lakes in mountainous regions are not well modeled. This introduces errors in the satellite altimetry-based water level estimates. The Surface Water and Ocean Topography mission (SWOT) launched in December 2022 provides almost complete spatial coverage, which makes it possible to detect spatial signals over lakes, for example.

Here we apply a state-space model to separate the assumed static signal from a potentially unmodeled geoid signal and the temporal variation in the water level. As data input, we use the SWOT 250m raster product. To evaluate how well the spatial and temporal signals are separated we compare the SWOT-based water level time series with time series based on other altimetry data sets.

The procedure is tested for a set of different lakes, including the African rift lakes and Lake Titicaca. Here, we based the solution on available data at the current time; however, the solutions are expected to improve as more data becomes available. The R code will be available to the user.

How to cite: Nielsen, K., Köhn, S., Andersen, O., and Liguang, J.: Lake geoid correction grids based on the SWOT Raster product, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9331, https://doi.org/10.5194/egusphere-egu25-9331, 2025.

Global warming accelerates climate change, increasing the frequency of floods and droughts, thereby emphasizing the importance of developing monitoring technologies. Therefore, the importance of continuous water resources monitoring is essential. Satellite remote sensing data is an effective tool for water resources monitoring. Monitoring water resources using conventional satellite imagery requires complex calculations and data preprocessing. The recently launched Surface Water and Ocean Topography (SWOT) satellite provides information on the height and distribution of inland water bodies without extra computational effort. In this study, validation of SWOT water surface data using Sentinel-1 imagery-based water mask and in-situ water level. For validation, a confusion matrix-based metric was used (accuracy, precision, recall, IoU). As a result, SWOT satellite data demonstrated high performance, achieving an accuracy of over 0.90 in monitoring reservoir surface areas and detecting water level changes. These findings indicate that strengths of SWOT data have potential to efficiently monitoring water resources. Furthermore, the results provide valuable insights into advancing hydrological research.

Keywords: SWOT, Water Body Detection, Water Level, Confusion Matrix

Acknowledgment

This research was supported by the BK21 FOUR (Fostering Outstanding Universities for Research) funded by the Ministry of Education (MOE, Korea) and National Research Foundation of Korea (NRF). This work is financially supported by Korea Ministry of Land, Infrastructure and Transport (MOLIT) as 「Innovative Talent Education Program for Smart City」. This work was supported by Korea Environment Industry & Technology Institute (KEITI) through Research and Development on the Technology for Securing the Water Resources Stability in Response to Future Change Project, funded by Korea Ministry of Environment (MOE)(RS-2024-00332300). This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (RS-2024-00416443). This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (NRF-2022R1A2C2010266). This work was supported by Korea Environment Industry & Technology Institute (KEITI) through Water Management Program for Drought Project, funded by Korea Ministry of Environment (MOE) (RS-2023-00230286).

How to cite: Lee, S., Cho, S., and Choi, M.: Evaluating the Applicability of SWOT Satellite Data for Reservoir Surface Area and Water Level Monitoring, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16054, https://doi.org/10.5194/egusphere-egu25-16054, 2025.

Over the last few decades flood risk management has become increasingly reliant on simulation of flood inundation from physical models of river-floodplain systems. Information from these models takes the form of flood extent and depth maps, and can directly influence decisions in sectors such as humanitarian response, insurance and urban planning. However,  it is expensive to create accurate models, due to input data requirements, resulting in relatively low-quality simulations along most rivers. One of the major issues is river bathymetry (the land below the water surface) because this cannot be measured remotely and at a large scale.

One way to overcome this issue would be to develop ‘inverse’ models that estimate bathymetry from water surfaces, which are much more observable. In the past, suitable water height measurements have been a limiting factor, however, the Surface Water and Ocean Topography mission will for the first time measure all global river water surfaces wider than ~50 m. This paper develops methods to estimate river bathymetry from SWOT data, evaluating the SWOT height observations and river bathymetry estimates for a small (40-70m wide) UK river. SWOT data is sufficiently accurate to estimate bathymetry that when used for flood modelling could simulate flood extents and depths with similar accuracy to a traditional model based on local river survey data.  

How to cite: Neal, J., Chuter, S., Probyn, I., and Bates, P.: Flood inundation modelling using the Surface Water Ocean Topography Mission, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13360, https://doi.org/10.5194/egusphere-egu25-13360, 2025.

The SWOT satellite mission is the first to conduct a global survey of the Earth’s surface waters, measuring water surface height, river width, and water surface slope, based on which river discharge is estimated. At mid-latitudes, the repeat orbit design of SWOT only allows a sampling of twice per repeat cycle, which is considered too low for most hydrological applications. We develop a linear dynamic system that ingests SWOT observations for daily discharge estimation over continuous reaches in a single-branch river network to overcome this limitation. The linear dynamic system includes a process model based on a physically-based spatiotemporal discharge correlation model and observation equations utilizing SWOT products. We solve this dynamic system through a Kalman filter, which is executed in the time domain to obtain daily discharge. Building on the strong performance of the method with synthetic data, we apply this algorithm using SWOT measurements in the Rhine River, where we validate its performance by comparing the estimates against gauge discharge data. These efforts aim to unlock the potential of SWOT data for daily discharge estimation in diverse river networks globally.

How to cite: Ke, S., J. Tourian, M., Sneeuw, N., Prata de Moraes Frasson, R., C. D. Paiva, R., Durand, M., Gleason, C., Elmi, O., Malaterre, P.-O., and David, C.: Daily river discharge estimation using SWOT data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11293, https://doi.org/10.5194/egusphere-egu25-11293, 2025.

Spatiotemporally consistent quantification of river discharge is a persistent problem in the field of hydrology. The current generation of technologically advanced satellite sensors provide reliable alternatives to the conventional gauge monitoring system. In this study, we utilize the Water Surface Elevation (WSE) measurements from the recently released river products from the Surface Water and Ocean Topography (SWOT) mission. We integrate the reach WSE measurements into a distributed hydrodynamic model through an assimilation system to study its contribution towards enhancing the modelled hydrodynamic variables over an entire river basin. Assimilation is implemented using both synthetic and real SWOT reach WSE measurements, where the former is generated using a new method involving the CNES Large Scale SWOT Hydrology Simulator and the NASA Jet Propulsion Laboratory’s (JPL) RiverObs toolkit. The study using synthetic data is conducted for a 3-year period, whereas that using real measurements are implemented based on the availability during the science phase of the mission. Real measurements from the SWOT mission are affected by the presence of outliers that are filtered prior to assimilation to ensure consistent improvements in the output variables corresponding to each satellite overpass date over the study region. SWOT reaches are accurately connected to the river network grid before initiating the assimilated model run. Results reveal notable improvement in modelled discharge after assimilation, with the NSE values exceeding 0.6 and 0.4 for the synthetic and real SWOT data-based experiments, respectively. The improvements, though pronounced towards the downstream reaches, are evident at all validation stations across the basin.

How to cite: Soman, M. K. and Indu, J.: Evaluating the potential of reach water surface elevation product from the SWOT mission in assimilated hydrodynamic modelling., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12598, https://doi.org/10.5194/egusphere-egu25-12598, 2025.

The Surface Water and Ocean Topography (SWOT) mission, a collaboration between the US and the French Space agencies, aims to monitor ocean surface and inland waters continuously. The Ka-band radar interferometer onboard the satellite provides two-dimensional measurements of water surface elevations across two 50-km wide swaths. The SWOT mission is crucial for land hydrology as it offers significant improvements over past satellite altimetry missions with its high accuracy, wide spatial coverage, and high resolution. Our study comprehensively evaluates the accuracy of water level measurements from the SWOT Level 2 River Single-Pass Vector Node Data Product over five major river basins in India, namely Narmada, Godavari, Mahanadi, Cauvery, and Krishna. We assess the accuracy of SWOT data by comparing SWOT water elevation measurements with the water levels derived from the in-situ gauge datasets at corresponding dates and locations. We select 82 in-situ gauge stations, each with at least eight valid measurements, to evaluate the SWOT data by calculating the r², RMSE, and MAE parameters for each station. Across all five basins, the median r², RMSE, and MAE values at each station are 0.81, 0.43 m, and 0.33 m, respectively, showcasing the high accuracy of SWOT water elevation measurements over most observation points. Furthermore, we validate the SWOT water elevation levels against measurements from other satellite altimetry missions to observe its consistency across various observation platforms.

How to cite: Deshpande, R. S. and Syed, T. H.: Evaluation of SWOT Vector Node Products Over Indian River Basins, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15404, https://doi.org/10.5194/egusphere-egu25-15404, 2025.

River discharge is one of the important hydrological essential climate variable (ECV) that is a key for understanding the water cycle of the catchment contributing to the river behavior and prevention strategies for efficient water resources. Surface Water Ocean Topography (SWOT) mission is first of its kind to estimate river discharge exclusively from remotely sensed hydraulic data. The present study demonstrated potential of SWOT mission KaRin swath observations to estimate water surface elevations (WSE), river width and slope over Ganga River, India. A field campaign was carried out in synchronous with the SWOT satellite (track 10) overpass during the Cal-Val phase of the mission. More than 4000 kinematic observation were collected using DGPS to monitor spatial variability of the water stage within the 120 km of swath altimetry. The elevation profile over water surface were estimated and observed the variation in water level from 61 to 70 m with an average slope of 8.69 cm/km. Acoustic Doppler Current Profiler (ADCP) was also operated every 10 km along the river similar to the reach wise discharge product for calibration/validation purpose.. This study generated a reliable dataset to validate the SWOT observations along with the estimated river discharge data set of the Ganga River near Varanasi with the aim of enhancing the accuracy of swath altimeter products. SWOT pixel cloud (SWOT_L2_HR_PIXC) data from KaRIn instrument was processed during Cal-Val phase form Cycle 484 (April 8, 2023) to Cycle 502 (April 26, 2023). For delineating the water extent from the Level-2 PIXC dataset, we have made use of a high-resolution national wetland inventory and assessment database of 1:12500 scale, so that small tributaries and nearby wetlands can also be consider for accuracy assessments over smaller water bodies. The PIXC product contains only a small fraction of the pixels in the interferogram (mainly water pixels and pixels in floodplains) that was further processed to estimate the river hydraulic parameters such as river slope, water level, and other related parameters for each pixel. The generated water elevation maps were validated with GPS measured elevations and similar order of variation in the water levels was observed by SWOT mission, with root mean square error of the order of 25 cm. The SWOT derived river slope (8.89 cm/ Km) was also in good agreement with the GPS observations. We have further analyzed the science phase data close to the virtual station near Varanasi from January 2024 to November 2024. The average water stage was observed to nearly 67.53 meter with peak-to-peak variation of the order of 8 meters. The river width during this period was observed to be varying between 400-3000 meter. Initial results from swath altimetry measurements have added a new dimension in the field of land hydrology and are essential for understanding hydrological processes. 

How to cite: Chander, S., Agrawal, R., Dubey, A., Gaur, S., Ohri, A., and Gupta, P.: Hydrological experiment over Ganga River to validate hydraulic parameters within the swath of SWOT mission, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20346, https://doi.org/10.5194/egusphere-egu25-20346, 2025.