Simulated Surface Water And Ocean Topography Research Articles

Seamount detection using SWOT-derived vertical gravity gradient: advancements and challenges

SUMMARY Launched on 2022 December 16, the Surface Water and Ocean Topography (SWOT) satellite, using synthetic aperture radar interferometric techniques, measures sea surface heights (SSHs) across two 50-km-wide swaths, offering high-resolution and accurate 2-D SSH observations. This study explores the efficiency of SWOT in seamount detection employing the vertical gravity gradient (VGG) derived from simulated SWOT SSH data. Simulated circular and elliptical seamounts (height: 900–1500 m) are integrated within the South China Sea's 4000 m background depths. Geoid perturbations induced by these seamounts are extracted through the residual depth model principle, subsequently merged with the DTU21MSS model for simulating SWOT SSH observations. For comparative assessment, SSH data from Jason-2 and Cryosat-2 are included. An automatic algorithm (AIFS) is presented to identify seamount centres and base polygons using VGG derived from simulated altimeter SSH data. The analysis reveals SWOT-derived VGGs precisely locate all seamount centres, base polygons and elliptical seamount azimuths. The merged Jason-2 and Cryosat-2 data face challenges with identifying small circular and elliptical seamounts. Detecting long narrow elliptical seamounts remains arduous; however, SWOT-derived VGGs successfully elucidate the approximate shapes and major axis azimuths of the elliptical seamounts. Validated against ‘true values’ of VGG, the root-mean-squared deviation (RMSD) of SWOT-derived VGG stands at 1.33 Eötvös, whereas the merged Jason-2 and Cryosat-2 data exhibit an RMSD of 1.93 Eötvös. This study shows the enhanced capability of SWOT from its high-resolution 2-D SSH observations in advancing seamount detection via satellite-derived VGG. We identify challenges and recommend improved detections using data integration and machine learning.

Enhancing discharge estimation from SWOT satellite data in a tropical tidal river environment

The Surface Water and Ocean Topography (SWOT) mission aims to provide essential data on river width, height and slope in order to estimate worldwide river discharge accurately. This mission offers a powerful tool for monitoring river discharge in dynamic coastal areas, like the Saigon-Dongnai estuary in Southern Vietnam. However, estimating discharge of tidally-influenced rivers using SWOT measurements can be challenging when hydraulic variables have the same order of magnitude as SWOT measurement errors. In this paper we present a methodology to enhance discharge estimation accuracy from SWOT measurements based on simulated SWOT products at the 200 meter node resolution and varying river reach size. We assess measurement error variability and its impact on discharge estimation by employing a Monte Carlo analysis. Our approach significantly improved discharge estimation in the Saigon tidal river, reducing RMSE from 1400 m3/s to 180 m3/s and increasing R² from 0.31 to 0.95. Notably, the percentage of Monte Carlo particles meeting the 30% rRMSE threshold rose from 0% to 79%. This study underscores the feasibility of obtaining reliable discharge estimates from SWOT data in complex coastal areas where hydraulic variables are of the same order of magnitude as SWOT errors. Additionally, the proposed methodology to improve discharge estimation from SWOT measurements is widely adaptable as it can be applied to similar regions and can be combined with any discharge estimation method.

Expected Precision of Gravity Gradient Recovered from Ka-Band Radar Interferometer Observations and Impact of Instrument Errors

Full tensor of gravity gradients contains extremely large amounts of information, which is one of the most important sources for research on recovery seafloor topography and underwater matching navigation. The calculation and accuracy of the full tensor of gravity gradients are worth studying. The Ka-band interferometric radar altimeter (KaRIn) of surface water and ocean topography (SWOT) mission enables high spatial resolution of sea surface height (SSH), which would be beneficial for the calculation of gravity gradients. However, there are no clear accuracy results for the gravity gradients (the gravity gradient tensor represents the second-order derivative of the gravity potential) recovered based on SWOT data. This study evaluated the possible precision of gravity gradients using the discretization method based on simulated SWOT wide-swath data and investigated the impact of instrument errors. The data are simulated based on the sea level anomaly data provided by the European Space Agency. The instrument errors are simulated based on the power spectrum data provided in the SWOT error budget document. Firstly, the full tensor of gravity gradients (SWOT_GGT) is calculated based on deflections of the vertical and gravity anomaly. The distinctions of instrument errors on the ascending and descending orbits are also taken into account in the calculation. The precision of the Tzz component is evaluated by the vertical gravity gradient model provided by the Scripps Institution of Oceanography. All components of SWOT_GGT are validated by the gravity gradients model, which is calculated by the open-source software GrafLab based on spherical harmonic. The Tzz component has the poorest precision among all the components. The reason for the worst accuracy of the Tzz component may be that it is derived by Txx and Tyy, Tzz would have a larger error than Txx and Tyy. The precision of all components is better than 6 E. Among the various errors, the effect of phase error and KaRIn error (random error caused by interferometric radar) on the results is greater than 2 E. The effect of the other four errors on the results is about 0.5 E. Utilizing multi-cycle data for the full tensor of gravity gradients recovery can suppress the effect of errors.

The Tikhonov-L-curve regularization method for determining the best geoid gradients from SWOT altimetry

The Surface Water and Ocean Topography (SWOT) mission generates dense altimetry data that, when used in geoid gradient component estimations through least-squares collocation (LSC), lead to an ill-conditioned problem. Such problems also arise in geodetic network designs. This study introduces the Tikhonov-L-curve regularization to effectively address this challenge. By pinpointing the maximum curvatures of the L-curve, we discern optimal regularization parameters, countering issues stemming from the dense data of SWOT and the resulting ill-conditioned covariance matrices. Our approach not only stabilizes LSC solutions but also achieves gradient accuracies at 1-microrad levels compared to theoretical values. Additionally, we experimented with a strategic removal process that selectively eliminates adjacent geoid gradients. This technique considerably improves geoid gradient component determinations, especially evident at a threshold distance of 0.755 km within an 8′× 8′ data selection window. While our findings are rooted in simulated SWOT data, they are pivotal for future research intending to employ real SWOT data, anticipated by late 2023. This work serves as a precursor for marine gravity field determinations, emphasizing the importance of stabilized LSC solutions to avoid misleading seafloor signatures due to data compactness.

The Effects of Uncorrelated Measurement Noise on SWOT Estimates of Sea Surface Height, Velocity, and Vorticity

Abstract The Ka-band Radar Interferometer (KaRIn) on the Surface Water and Ocean Topography (SWOT) satellite will revolutionize satellite altimetry by measuring sea surface height (SSH) with unprecedented accuracy and resolution across two 50-km swaths separated by a 20-km gap. The original plan to provide an SSH product with a footprint diameter of 1 km has changed to providing two SSH data products with footprint diameters of 0.5 and 2 km. The swath-averaged standard deviations and wavenumber spectra of the uncorrelated measurement errors for these footprints are derived from the SWOT science requirements that are expressed in terms of the wavenumber spectrum of SSH after smoothing with a filter cutoff wavelength of 15 km. The availability of two-dimensional fields of SSH within the measurement swaths will provide the first spaceborne estimates of instantaneous surface velocity and vorticity through the geostrophic equations. The swath-averaged standard deviations of the noise in estimates of velocity and vorticity derived by propagation of the uncorrelated SSH measurement noise through the finite difference approximations of the derivatives are shown to be too large for the SWOT data products to be used directly in most applications, even for the coarsest footprint diameter of 2 km. It is shown from wavenumber spectra and maps constructed from simulated SWOT data that additional smoothing will be required for most applications of SWOT estimates of velocity and vorticity. Equations are presented for the swath-averaged standard deviations and wavenumber spectra of residual noise in SSH and geostrophically computed velocity and vorticity after isotropic two-dimensional smoothing for any user-defined smoother and filter cutoff wavelength of the smoothing.

Evaluating SWOT water level information using a large scale hydrology simulator: A case study over India

An important goal of the Surface Water and Ocean Topography (SWOT) mission is to provide river width, height, slope to estimate global river discharges. To appraise the feasibility of SWOT data over India, the present study utilizes the SWOT simulator from Centre National D’Etudes Spatiales (CNES) to generate a long time-series (three years) of SWOT observations over the Mahanadi River basin in India. Two independent sources of river geometry are used in this study, namely satellite-based and hydrodynamic model-based estimates. Satellite-based river geometry is derived using a web-based User Interface (UI) developed in-house to generate time series of accurate river width shapefiles from Sentinel-1 satellite imagery. To compare these results, a 1D unsteady flow analysis is carried out over the Mahanadi River to simulate channel water depth and inundation extent using the Hydrologic Engineering Center's River Analysis System (HEC-RAS) model. The simulated observations are used in this study to assess the potential error in SWOT channel water depth measurements. Results indicate a good spatial correlation between the water surface area derived from Sentinel and HEC-RAS models with a correlation of 0.74. The simulated data shows a bias of 20 cm compared to gauge observations. This study is conducted as a proof of concept in demonstrating the ability of simulated SWOT data in capturing river water surface elevation with respect to the conventional HEC-RAS model. It also implements a new tool in google earth engine (GEE) to generate input to SWOT simulator.

Narrow River Extraction From SAR Images Using Exogenous Information

Monitoring of rivers is of major scientific and societal importance due to the crucial resource they provide to human activities and the threats caused by flood events. Rapid revisit synthetic aperture radar (SAR) sensors such as Sentinel-1 or the future surface water and ocean topography (SWOT) mission are indispensable tools to achieve all-weather monitoring of water bodies at the global scale. Unfortunately, at the spatial resolution of these sensors, the extraction of narrow rivers is extremely difficult without resorting to exogenous knowledge. This article introduces an innovative river segmentation method from SAR images using a priori databases such as the global river widths from Landsat (GRWL). First, a recently proposed linear structure detector is used to produce a map of likely line structures. Then, a limited number of nodes along the prior river centerline are extracted from the exogenous database and used to reconstruct the full river centerline from the detection map. Finally, an innovative conditional random field approach is used to delineate accurately the river extent around its centerline. The proposed method has been tested on several Sentinel-1 images and on simulated SWOT data. Both visual and qualitative evaluations demonstrate its efficiency.

Anticipated Improvements to River Surface Elevation Profiles From the Surface Water and Ocean Topography Mission

Existing publicly available digital elevation models (DEMs) provide global-scale data but are often not precise enough for studying processes that depend on small-scale topographic features in rivers. For example, slope breaks and knickpoints in rivers can be important in understanding tectonic processes, and riffle-pool structures are important drivers of riverine ecology. More precise data (e.g. lidar) are available in some areas, but their spatial extent limits large-scale research. The upcoming Surface Water and Ocean Topography (SWOT) satellite mission is planned to launch in 2021 and will provide measurements of elevation and inundation extent of surface waters between 78° north and south latitude on average twice every 21 days. We present a novel noise reduction method for multitemporal river water surface elevation profiles from SWOT that combines a truncated singular value decomposition and a slope-constrained least-squares estimator. We use simulated SWOT data of 85-145 km sections of the Po, Sacramento, and Tanana Rivers to show that 3-12 months of simulated SWOT data can produce elevation profiles with mean absolute errors of 5.38-12.55 cm at 100-200 m along-stream resolution. Mean absolute errors can be reduced further to 4-11 cm by averaging all observations. The average profiles have errors much lower than existing DEMs, allowing new advances in riverine research globally. We consider two case studies in geomorphology and ecology that highlight the scientific value of the more accurate in-river DEMs expected from SWOT. Simulated SWOT elevation profiles for the Po reveal convexities in the river longitudinal profile that are spatially coincident with the upward projection of blind thrust faults that are buried beneath the Po Plain at the northern termination of the Apennine Mountains. Meanwhile, simulated SWOT data for the Sacramento River reveals locally steep sections of the river profile that represent important habitat for benthic invertebrates at a spatial scale previously unrecognizable in large-scale digital elevation models presently available for this river.

High-Resolution SWOT Simulations of the Macrotidal Seine Estuary in Different Hydrodynamic Conditions

The goal of the Surface Water and Ocean Topography (SWOT) mission, a future wide-swath radar altimeter, is to measure the elevations of ocean and continental water surfaces with unprecedented precision. A simulator of SWOT high-rate (HR) interferometric SAR images has been developed to provide SWOT-like data to scientists and as a tool to develop and test HR ground processing algorithms. In this letter, we evaluate the errors of the extracted water levels in different hydrodynamic and topographic contexts in the Seine estuary based on simulated SWOT HR data. The results confirm height errors generally below 10 cm after km-scale averaging for the majority of the observations. Higher errors mostly occur in areas where the surrounding topography causes layover. This letter also reveals the interactions between tide and streamflow and their impact on the spatial variability of the water levels in the estuary.

Prospects for future satellite estimation of small-scale variability of ocean surface velocity and vorticity

Prospects for future satellite estimation of small-scale variability of ocean surface velocity and vorticity

Time variability of hydrodynamics and potential use of surface water and ocean topography mission in estuarine macrotidal system: example of Seine estuary

This work was supported by the National Center for Space Studies in the framework of the future mission surface water and ocean topography (SWOT). The estuarine zones with their complex hydrodynamics represent a great challenge for the future SWOT mission. The Seine estuary was selected by the SWOT Science Definition Team for the calibration/validation of the mission. Thus the aim of this study is to investigate the temporal hydrodynamic variability in the Seine estuary and the SWOT ability to reproduce this variability and hydrodynamic phenomena. For this, we used several statistical techniques and frequency analyses applied on the tide-gauge measurements of the Seine estuary and on SWOT simulated data. SWOT samples (SWOT simulated data) have been extracted synthetically from observations using the number of overpasses per repeat cycle [21 days (d)] in order to study the ability of SWOT to reproduce the time variability of the hydrodynamics. Results have demonstrated similar frequencies of multiyear, annual, and intraannual along the estuary from the Seine discharge to the Cherbourg sea level. The 11- to 22-d frequency has been only observed for estuarine and coastal time series suggesting the tide effect in these contexts. The distribution of levels has shown a high influence of tides and discharges at the downstream and the upstream, respectively. Low frequencies of water level are explained by the climate patterns of North Atlantic Oscillation with a mean range of 65%, whereas the high frequencies are associated to the periods of flooding and stormy events. Finally, simulated SWOT samples of water level show a better restitution of observations for high overpasses number. The results have shown a better restitution of hydrodynamic variability by SWOT in the river and upstream of estuary than in the downstream of estuary and coastal zone: in the estuary downstream and the coast, the annual mode is underexpressed while the 3-month (m) mode is overexpressed, which means the annual mode is underestimated and the 3-m mode is amplified by SWOT.

Discharge Estimation in Ungauged Basins Through Variational Data Assimilation: The Potential of the SWOT Mission

AbstractSpace‐borne instruments can measure river water surface elevation, slope, and width. Remote sensing of river discharge in ungauged basins is far more challenging, however. This work investigates the estimation of river discharge from simulated observations of the forthcoming Surface Water and Ocean Topography (SWOT) satellite mission using a variant of the classical variational data assimilation method “4D‐Var.” The variational assimilation scheme simultaneously estimates discharge, river bathymetry, and bed roughness in the context of a 1.5 D full Saint‐Venant hydraulic model. Algorithms and procedures are developed to apply the method to fully ungauged basins. The method was tested on the Po and Sacramento Rivers. The SWOT hydrology simulator was used to produce synthetic SWOT observations at each overpass time by simulating the interaction of SWOT radar measurements with the river water surface and nearby land surface topography at a scale of approximately 1 m, thus accounting for layover, thermal noise, and other effects. SWOT data products were synthesized by vectorizing the simulated radar returns, leading to height and width estimates at 200 m increments along the river centerlines. The ingestion of simulated SWOT data generally led to local improvements on prior bathymetry and roughness estimates which allowed the prediction of river discharge at the overpass times with relative root mean squared errors of 12.1% and 11.2% for the Po and Sacramento Rivers, respectively. Nevertheless, equifinality issues that arise from the simultaneous estimation of bed elevation and roughness may prevent their use for different applications, other than discharge estimation through the presented framework.

Automated River Reach Definition Strategies: Applications for the Surface Water and Ocean Topography Mission

AbstractThe upcoming Surface Water and Ocean Topography (SWOT) mission will measure water surface heights and widths for rivers wider than 100 m. At its native resolution, SWOT height errors are expected to be on the order of meters, which prevent the calculation of water surface slopes and the use of slope‐dependent discharge equations. To mitigate height and width errors, the high‐resolution measurements will be grouped into reaches (∼5 to 15 km), where slope and discharge are estimated. We describe three automated river segmentation strategies for defining optimum reaches for discharge estimation: (1) arbitrary lengths, (2) identification of hydraulic controls, and (3) sinuosity. We test our methodologies on 9 and 14 simulated SWOT overpasses over the Sacramento and the Po Rivers, respectively, which we compare against hydraulic models of each river. Our results show that generally, height, width, and slope errors decrease with increasing reach length. However, the hydraulic controls and the sinuosity methods led to better slopes and often height errors that were either smaller or comparable to those of arbitrary reaches of compatible sizes. Estimated discharge errors caused by the propagation of height, width, and slope errors through the discharge equation were often smaller for sinuosity (on average 8.5% for the Sacramento and 6.9% for the Po) and hydraulic control (Sacramento: 7.3% and Po: 5.9%) reaches than for arbitrary reaches of comparable lengths (Sacramento: 8.6% and Po: 7.8%). This analysis suggests that reach definition methods that preserve the hydraulic properties of the river network may lead to better discharge estimates.

Hydrological Variability from Gauging Stations and Simulated SWOT Data, for Major French Rivers

This study was carried out under the aegis of the program Surface Water and Ocean Topography (SWOT) associated with the National Center of Space Studies (CNES). The future SWOT mission will offer new opportunities to survey the hydrodynamic in the rivers because it will provide data on the water level/ discharges with a high spatial resolution (oceans: 1 km, rivers: 100 m of width) and with a global cover. However, it is important to estimate the capacity of SWOT to reproduce the hydrodynamic phenomena in the estuaries and the temporal and the spatial variability of this dynamic. The aim of this paper is 1) to estimate the capacity of SWOT to reproduce the hydrological variability of watersheds, and 2) to validate the use of these data for other zone without hydrometric station. Based on discharge measurements and simulated Surface Water and Ocean Topography (SWOT) data, we have investigated the hydrological variability of the main French rivers (Seine, Loire, Garonne and Rh?ne) by applying a series of statistical analyses to the discharge time series. A frequency analysis has been also used using a technique of wavelet. Results have shown a similar hydrological variability of the four watersheds. Three different periods of hydrologic variability has been identified: before 1970, between 1970 and 1990, and after 1990. Using these analyses, simulated SWOT samples and discharges were compared during the three studied periods. Simulated SWOT data, obtained by a synthetic sampling of river discharges basing on the number of measurements per repeat orbit, reproduce the hydrological variability of rivers. Such reproduction seems to be independent in the number of SWOT passages (from two to four), except for the minimum and maximum annual discharges where number of overpass seems to have an influence. These results were validated by coherence wavelet which underlines coherence higher than 90% between simulated SWOT data and in-situ discharges. Nevertheless, good correlation was not observed for the minimum and the maximum annual discharge with an underestimation for SWOT maximum annual and an overestimation of the minimum annual SWOT ones. Moreover, best identification of minimum, mean and maximum annual discharge depends on SWOT overpasses.

Examining the Potential Impact of SWOT Observations in an Ocean Analysis–Forecasting System

AbstractNASA’s Surface Water and Ocean Topography (SWOT) satellite, scheduled for launch in 2020, will provide observations of sea surface height anomaly (SSHA) at a significantly higher spatial resolution than current satellite altimeters. This new observation type is expected to improve the ocean model mesoscale circulation. The potential improvement that SWOT will provide is investigated in this work by way of twin-data assimilation experiments using the Navy Coastal Ocean Model four-dimensional variational data assimilation (NCOM-4DVAR) system in its weak constraint formulation. Simulated SWOT observations are sampled from an ocean model run (referred to as the “nature” run) using an observation-simulator program provided by the SWOT science team. The SWOT simulator provides realistic spatial coverage, resolution, and noise characteristics based on the expected performance of the actual satellite. Twin-data assimilation experiments are run for a two-month period during which simulated observations are assimilated into a separate model (known as the background model) in a series of 96-h windows. The final condition of each analysis window is used to initialize a new 96-h forecast, and each forecast is compared to the nature run to determine the impact of the assimilated data. It is demonstrated here that the simulated SWOT observations help to constrain the model mesoscale to be more consistent with the nature run than the assimilation of traditional altimeter observations alone. The findings of this study suggest that data from SWOT may have a substantial impact on improving the ocean model forecast of mesoscale features and surface ocean velocity.

Inland Water Height Estimation Without Ground Control Points for Near-Nadir InSAR Data

Surface Water and Ocean Topography (SWOT) is a future wide-swath radar altimetry mission. The main instrument is the Ka-band radar interferometer (KaRIn). It provides interferometric radar images that will be processed to obtain water elevation estimates worldwide. Due to the specific geometric and radiometric characteristics of KaRIn/SWOT, the phase-to-height conversion is one of the most critical processing steps. We propose methods to estimate water heights without using classical approaches based on spatial phase unwrapping and control points. Results obtained on the simulated SWOT data are shown.

Characterization of surface water storage changes in Arctic lakes using simulated SWOT measurements

The planned Surface Water and Ocean Topography (SWOT) satellite mission will measure freshwater storage changes in global lakes. Herein, the anticipated SWOT storage change accuracy is evaluated for the lakes in the Peace-Athabasca Delta, Northern Alaska and Western Siberia. Because of the significant lack of Arctic lake measurements, we simulated realistic daily to seasonal changes in water elevations in the study region using a combination of data from lake gauges, satellite radar altimeter, and satellite imagery. This ‘truth’ dataset is sampled with several candidate SWOT orbits and then corrupted with expected instrument errors to simulate SWOT observed storage changes. The number of revisits increases with increasing or decreasing latitude for a given repeat cycle (e.g. four to eight revisits for a 22-day cycle), allowing us to investigate storage change errors at monthly sampling. SWOT storage change accuracy is primarily controlled by lake size. Lakes larger than 1 km2 have relative errors generally less than 5% whereas one-hectare size lakes are about 20%. We concluded that the storage change accuracy is insensitive to the orbital inclination or repeat periods, but is sensitive to lake shapes.