Ocean Topography Mission Research Articles

Deep Learning Improves Reconstruction of Ocean Vertical Velocity

AbstractOcean vertical velocity (w) plays a key role in regulating the exchanges of mass, heat and nutrients between the surface and deep ocean. However, direct observation remains difficult due to its small magnitude and large spatiotemporal variability. Therefore, w fields are generally diagnosed using dynamic‐based methods. In this study, we developed a deep neural network (DNN) to reconstruct three‐dimensional fields of ocean vertical velocity based on sea surface height (SSH) fields. Compared to dynamic‐based methods, the DNN shows improved performance in the w reconstruction within upper 500 m in terms of higher correlation and less error. Remarkably, the DNN requires only a ∼45 × 45 km size SSH image as input to estimate w at the center. This suggests that the DNN has great potential for w reconstruction in the future combined with high‐resolution observations such as the Surface Water and Ocean Topography mission.

Assessing the potential for the Surface Water and Ocean Topography (SWOT) mission for constituent flux estimations

The recently launched Surface Water and Ocean Topography (SWOT) satellite will simultaneously measure river surface water widths, elevations, and slopes. These novel observations combined with assumptions for unobserved bathymetry and roughness enable the derivation of river discharge. Derived discharge data will not be available until the fall of 2023, despite the satellite having completed approximately 6 months of observations for validation and calibration and transitioning into the nominal orbit phase. SWOT has an irregular flyover frequency, ranging from roughly 1 to 10 times per 21 days. Here, we present how best to use SWOT data when it becomes live, including consideration of how best to accommodate or utilize the irregular flyover frequency of SWOT as it intersects with river reaches. We investigate the predicted capabilities of SWOT for several major rivers using synthetic/theoretical SWOT time series data and evaluate how the characteristics of river discharge dynamics and SWOT sampling frequency impact discharge estimates. This analysis indicates the irregular frequency of SWOT best captures the hydrology of larger, more stable, rivers but presents challenges in smaller, flashier rivers, particularly when sampling frequency decreases (i.e., falls to once per 21 days). Further, the use of SWOT discharge for quantifying constituent fluxes is considered. We provide recommendations concerning how to best use SWOT data for applications related to hydrology and biogeochemistry, including how to design studies to accommodate its irregular orbit cycle.

SWOT re-entry: Maneuver strategy and risk computation

The Surface Water & Ocean Topography (SWOT) mission is a joint NASA/CNES mission launched on December 16th, 2022 dedicated to oceanography and continental hydrology. Once the scientific mission is over, SWOT will have to perform a controlled re-entry to comply with the French Space Operation Act (FSOA). Indeed, the launch authorization is subject to the respect of the FSOA, fully applicable since 2020. The main requirement applying to the end-of-life of the satellite consists in limiting the casualty area and then the probability of having a victim on ground under the threshold of 10−4 in case of a natural re-entry. With a mass over two tons and a casualty area of about 47 m2, SWOT cannot comply with this requirement. Thus, the platform has been designed with a specific propulsion system to carry out end-of-life maneuvers leading to an atmospheric re-entry and impact in the South Pacific Ocean Uninhabited Area (SPOUA). CNES is in charge of defining the re-entry maneuvers strategy, performing end-of-life operations and evaluating the risk of casualties in case of failure during nominal strategy. This paper addresses these topics. The computation of the ten maneuvers used to decrease the perigee altitude and finally target the SPOUA is performed using the DOORS tool. Before describing the maneuvers strategy, this paper presents an overview of the current functionalities of this tool, which has been already used during the five ATV missions and ASTRA-1K de-orbit twenty years ago. DOORS is mainly used for mission analysis purposes, but for end-of-life operations it can be activated by the operational Flight Dynamics System (FDS). Finally, the casualty risk estimation relies on the use of two other CNES tools, DEBRISK and ELECTRA, whose methods are presented. The list of surviving fragments has been computed using the new DEBRISK-V3 methodology in case of controlled and uncontrolled re-entry. The risk of human casualty is evaluated using ELECTRA and its Monte Carlo simulations. This tool generates numerous trajectories of the satellite and its fragments with various dispersed variables. The impact locations compared to an up-to-date grid of the World population lead to the probability of victims. The complete risk of SWOT controlled re-entry encompasses both the risk related to a failure during the last re-entry maneuver and the risk associated with the natural re-entry in case a failure occurs before this last burn (during the mission or during the first re-entry maneuvers). Both of them are weighted by their probability of occurrence.

How Does Wind Influence Near-Nadir and Low-Incidence Ka-Band Radar Backscatter and Coherence from Small Inland Water Bodies?

While many studies have been conducted regarding wind-driven Ka-band scattering on the ocean and sea surfaces, few have identified the impacts of Ka-band scattering on small inland water bodies, and fewer have identified the influence of wind on coherence over water. These previous studies have been limited in spatial scale, covering only large water bodies >25 km2. The recently launched Surface Water and Ocean Topography (SWOT) mission is the first Ka-band InSAR satellite designed for mapping water surface elevations and open water areas for rivers as narrow as 100 m and lakes as small as 0.0625 km2. Because measurements of these types are novel, there remains some uncertainty about expected backscatter amplitudes given wind-driven water surface roughness variability. A previous study using the airborne complement to SWOT, AirSWOT, found that low backscatter and low coherence values were indicative of higher errors in the water surface elevation products, recommending minimum thresholds for backscatter and coherence for filtering the data to increase the accuracy of averaged data for lakes and rivers. We determined that the global average wind speed over lakes is 4 m/s, and after comparing AirSWOT backscatter and coherence data with ERA-5 wind speeds, we found that the minimum required speed to retrieve high backscatter and coherence is 3 m/s. We examined 11,072 lakes across Canada and Alaska, with sizes ranging from 350 m2 to 156 km2, significantly smaller than what could be measured with previous Ka-band instruments in orbit. We found that small lakes (0.0625–0.25 km2) have significantly lower backscatter (3–5 dB) and 0.20–0.25 lower coherence than larger lakes (>1 km2). These results suggest that approximately 75% of SWOT observable lake areas around the globe will have consistently high-accuracy water surface elevations, though seasonal wind variability should remain an important consideration. Despite very small lakes presenting lower average backscatter and coherence, this study asserts that SWOT will be able to accurately resolve the water surface elevations and water surface extents for significantly smaller water bodies than have been previously recorded from satellite altimeters. This study additionally lays the foundation for future high-resolution inland water wind speed studies using SWOT data, when the data become available, as the relationships between wind speed and Ka-band backscatter reflect those of traditional scatterometers designed for oceanic studies.

Characteristics of submesoscale eddy structures within mesoscale eddies in the Gulf of Mexico from 1/48° ECCO estimates

Submesoscale oceanic structures (<10-20 km) such as eddies and fronts are often difficult to describe given the influence of the mesoscale. In order to characterize the surface signatures of submesoscale structures, we utilize a custom spatial filtering function to separate the meso- and large-scale sea surface height (SSH) signal from the small scale SSH signal of 1/48° high resolution estimates provided by NASA’s Estimating the Circulation and Climate of the Oceans (ECCO) project. In this study, we use ECCO estimates from a 14-month global simulation between September 2011 and November 2012 with a 2 km horizontal grid spacing in the Gulf of Mexico. We then use an eddy detection and tracking algorithm to identify persistent circular features on both scales, giving rise to an atlas of submesoscale eddy-like variabilities (SEVs). We briefly investigate the geographic and temporal variability of SEVs as a whole before collocating SEVs inside mesoscale eddies, allowing us to evaluate the characteristics of internal SEVs and the impact of SEVs on mesoscale eddies. We find that SEVs, both anticyclonic and cyclonic, are ubiquitous inside mesoscale eddies with lifetimes longer than a week, accounting for an average of 10-20% of the spatial area and eddy kinetic energy of mesoscale eddies. We also show that internal SEVs are persistently associated with temperature and salinity anomalies in both eddy centers and edges of up to 0.1 °C and 0.05 psu, with anticyclonic internal SEVs being warmer and fresher while cyclonic internal SEVs are colder and saltier. Finally, we examine the life cycle of an anticyclonic Loop Current eddy, demonstrating that the number and intensity of internal SEVs within increases as the eddy approaches separation from the Loop Current until a maximum is obtained just after separation. In light of forthcoming submesoscale SSH observations from NASA’s Surface Water and Ocean Topography (SWOT) mission, our results showcase the variability of submesoscale eddy structures and their possible implications for biogeochemical cycling, the inverse energy cascade, and Loop Current prediction techniques.

A Framework for Estimating Global River Discharge From the Surface Water and Ocean Topography Satellite Mission

AbstractThe Surface Water and Ocean Topography (SWOT) mission will vastly expand measurements of global rivers, providing critical new data sets for both gaged and ungaged basins. SWOT discharge products (available approximately 1 year after launch) will provide discharge for all river that reaches wider than 100 m. In this paper, we describe how SWOT discharge produced and archived by the US and French space agencies will be computed from measurements of river water surface elevation, width, and slope and ancillary data, along with expected discharge accuracy. We present for the first time a complete estimate of the SWOT discharge uncertainty budget, with separate terms for random (standard error) and systematic (bias) uncertainty components in river discharge time series. We expect that discharge uncertainty will be less than 30% for two‐thirds of global reaches and will be dominated by bias. Separate river discharge estimates will combine both SWOT and in situ data; these “gage‐constrained” discharge estimates can be expected to have lower systematic uncertainty. Temporal variations in river discharge time series will be dominated by random error and are expected to be estimated within 15% for nearly all reaches, allowing accurate inference of event flow dynamics globally, including in ungaged basins. We believe this level of accuracy lays the groundwork for SWOT to enable breakthroughs in global hydrologic science.

Atmospheric forcing of the Hatteras coastal ocean during 2017–2018: The PEACH program

The Hatteras coastal ocean is centrally located along the east coast of the 48 contiguous United States, offshore of Cape Hatteras in a complex land/ocean/atmosphere region where major ocean currents of differing temperatures and salinities meet and interact, where the atmosphere fluctuates on a wide range of time scales, and where atmosphere-ocean interactions vary both spatially and temporally. The Gulf Stream current typically leaves its contact with the continental margin here. Continental shelf currents from the north and from the south converge here, resulting in a net shelf-to-ocean transport of shelf waters that carry important water properties and constituents. The two major drivers of these shelf currents and exchanges are the atmosphere and the oceanic Gulf Stream. Atmospheric driving of the Hatteras coastal ocean is through surface wind stress and heat flux across the air-sea interface. The complexity and importance of this region motivated the NSF-sponsored PEACH research program during 2017–2018 (PEACH: Processes driving Exchange At Cape Hatteras). In this paper, we utilize the substantial number of observations available during PEACH to describe the atmospheric forcing of the ocean then. Atmospheric conditions are described in terms of two seasons: the warm season (May to mid-September), with predominantly mild northeastward winds punctuated by occasional tropical cyclones (TCs); and the cool season (mid-September through April), with a nearly continuous, northeastward progression of energetic extratropical cyclones (ETCs) through the region. Cool season ETCs force the region with strong wind stress and ocean-to-atmosphere heat flux episodes, each with a time-scale of several days. Wind stress fluctuation magnitudes typically exceed mean stress magnitudes in each season by a factor of 3–5. These stresses account for just over 40% of the total current variability in the region, showing the wind to be a major driver of the ocean here. Atmosphere-ocean heat flux is typically into the ocean throughout the warm season (~100 W m-2); it is essentially always out of the ocean during the cool season (~500 W m-2 or more). New results herein include: southward intraseasonal oscillations of the jet stream’s position drove the strongest ETCs (including one “bomb” cyclone); and during the 41 years leading up to and including PEACH, the season-averaged number and strength of atmospheric cyclones passing over the Hatteras coastal ocean have shown little long-term change. Looking ahead, the NSF Pioneer Array is scheduled to be relocated to the northern portion of the Hatteras coastal ocean in 2024, and the NASA SWOT satellite has begun its ocean topography mission, which has a ground-track cross-over here.

Accurate Discharge Estimation Based on River Widths of SWOT and Constrained At-Many-Stations Hydraulic Geometry

River discharge monitoring is an important component of the hydrology objectives of Surface Water and Ocean Topography mission (SWOT). River discharge can be estimated Solely using river widths and At Many-stations Hydraulic Geometry (AMHG), but the accuracy is low due to the parameters of At a-station Hydraulic Geometry (AHG) given by AMHG deviate from the truth. In view of this, a Constrained At-Many-Stations Hydraulic Geometry (CAMHG) is proposed to optimize AHG parameters. The performance of CAMHG is verified in three reaches of the Yangtze River using river widths derived from SWOT. After using CAMHG, the relative root mean square error (RRMSE) of estimated discharge reduce 100.1% to 24.4%, 1137.1% to 49.9% and 48.6% to 45.5% for Hankou, Shashi and Luoshan respectively. In addition, CAMHG can also weaken the accuracy difference of estimated discharge in dry and wet seasons benefited from its more reliable AHG parameters. Thus, the proposed CAMHG can dramatically improves the accuracy of discharge estimations and it is meaningful for the discharge calculation after SWOT data release.

On the capabilities of the SWOT satellite to monitor the lake level change over the Third Pole

The lake level dynamics of the Qinghai–Tibetan Plateau (QTP, also called the ‘Third Pole’) are a crucial indicator of climate change and human activities; however, they remain poorly measured due to extremely high elevation and cold climate. The existing satellite altimeters also suffer from relatively coarse temporal resolution or low spatial coverage, preventing effective monitoring of lake level change at such a large spatial scale. The recently launched surface water and ocean topography (SWOT) mission is expected to greatly enhance the current lake level monitoring capabilities. However, a systematic evaluation is still lacking in the region. To elucidate this potential, here, we generated SWOT-like lake products for 38 major lakes (>150 km2) over the QTP during 2000–2018 using a large-scale SWOT hydrology simulator with the input of satellite altimetry and water mask databases. The comparative assessments between the satellite altimetry data and SWOT simulations using various statistical metrics and decomposed time series components demonstrate that SWOT can successfully monitor both short-term dynamics and long-term trends. Extended experiments to derive SWOT-like data of 783 lakes (>1 km2) based on the synthetic lake level series present the spatial pattern of SWOT performance that tends to improve with the increasing lake area. Our findings provide comprehensive inferences and confidence for lake level monitoring in the Third Pole in the early period of the SWOT satellite.

Estimating the Relative Impact of Measurement, Parameter, and Flow Law Errors on Discharge from the Surface Water and Ocean Topography Mission

Abstract The Surface Water and Ocean Topography (SWOT) mission will allow the estimation of discharge in rivers wider than 100 m, filling important gaps in the network of in situ measurements. This novel source of discharge observations has the potential to enable significant progress toward closing Earth’s water budget and creating new understanding of the water cycle. Quantifying the uncertainty in the SWOT estimates of discharge, mapping the error sources, and understanding their relative importance is essential to the fulfillment of this potential. Here, we break the SWOT discharge production process into its essential parts: 1) retrieval of river width and water surface heights and slopes, 2) estimation of unobservable parameters, and 3) computation of discharge with the selected flow law, and through a Monte Carlo simulation study, we assess the sensitivity of the overall discharge error to each of these parts. We analyze the discharge error characteristics in terms of bias, error standard deviation, and the correlation between true and retrieved discharges and map the contribution of the essential discharge production elements to each of the error metrics. Our study revealed that biases in parameters are the most important source of discharge biases, yet we found that a larger than expected fraction of the discharge biases can be attributed to observation errors. Surprisingly, we found that parameter biases are also the most important contributor to discharge error standard deviation and to the deterioration of the correlation between truth and retrieved discharges, which were previously thought of as being controlled by observation errors.

Understanding Volume Estimation Uncertainty of Lakes and Wetlands Using Satellites and Citizen Science

We studied variations in the volume of water stored in small lakes and wetlands using satellite remote sensing and lake water height data contributed by citizen scientists. A total of 94 water bodies across the globe were studied using satellite data in the optical and microwave wavelengths from Landsat 8, Sentinel-1 and Sentinel-2. The uncertainty in volume estimation as a function of geography and geophysical factors such as cloud cover, precipitation and water surface temperature, was studied. The key finding that emerged from this global study is that uncertainty is highest in regions with a distinct precipitation season such as in the monsoon dominated South Asia or the Pacific Northwestern region of the US. This uncertainty is further compounded when small lakes and wetlands are seasonal with alternating land use as a water body and agricultural land, such as the wetlands of Northeastern Bangladesh. On an average, 45% of studied lakes could be estimated of their volume change with a statistical significant uncertainty that is less than the expected volume in South Asia. In North America, this statistically significant uncertainty in volume estimation was found to be around 50% in lakes eastward of the 108 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> meridian with lowest uncertainty found in lakes along the East coast of the US. The study provides a baseline for understanding the current state of the art in estimating volumetric change of lakes and wetlands using citizen science in anticipation of the recently launched Surface Water and Ocean Topography (SWOT) Mission.

Data-Driven Calibration Algorithm and Pre-Launch Performance Simulations for the SWOT Mission

The Surface Water and Ocean Topography (SWOT) mission will be affected by various sources of systematic errors, which are correlated in space and in time. Their amplitude before calibration might be as large as tens of centimeters, i.e., able to dominate the mission error budget. To reduce their magnitude, we developed so-called data-driven (or empirical) calibration algorithms. This paper provided a summary of the overall problem, and then presented the calibration framework used for SWOT, as well as the pre-launch performance simulations. We presented two complete algorithm sequences that use ocean measurements to calibrate KaRIN globally. The simple and robust Level-2 algorithm was implemented in the ground segment to control the main source of error of SWOT’s hydrology products. In contrast, the more sophisticated Level-3 (multi-mission) algorithm was developed to improve the accuracy of ocean products, as well as the one-day orbit of the SWOT mission. The Level-2 algorithm yielded a mean inland error of 3–6 cm, i.e., a margin of 25–80% (of the signal variance) with respect to the error budget requirements. The Level-3 algorithm yielded ocean residuals of 1 cm, i.e., a variance reduction of 60–80% with respect to the Level-2 algorithm.

Internal tides off the Amazon shelf during two contrasted seasons: interactions with background circulation and SSH imprints

Abstract. The Amazon shelf break is a key region for internal tide (IT) generation. It also shows a large seasonal variation in circulation and associated stratification. This study, based on a high-resolution model (1/36∘) explicitly forced by tide, aims to better characterize how the ITs vary between two contrasted seasons. During the season from March to July (MAMJJ) the currents and mesoscale eddies are weak while the pycnocline is shallower and stronger. From August to December (ASOND) mean currents and mesoscale eddies are strong, and the pycnocline is deeper and weaker than in MAMJJ. For both seasons, semi-diurnal M2 ITs are generated on the shelf break mainly between the 100 and 1000 m isobath in the model. South of 2∘ N, the conversion from barotropic to baroclinic tide is more efficient in MAMJJ than in ASOND. Local dissipation of the coherent M2 at the generation sites is higher in MAMJJ (30 %) than in ASOND (22 %), because higher modes are favourably generated (modes 2 and 3), making the internal wave packet more dispersive. The remaining fraction (70 %–80 %) propagates away from the generation sites and mainly dissipates locally every ∼ 100 km, which corresponds to the mode 1 reflection beams. About 13 %, 30 %, and 40 % of the M2 coherent IT dissipates at the first, second, and third beams. M2 coherent baroclinic flux propagates more northward during MAMJJ while it seems to be blocked at 6∘ N during ASOND. There is no intensified dissipation of the coherent M2 that could explain the disappearance of the coherent flux. In fact, the flux at this location becomes more incoherent because of strong interaction with the currents. This has been shown in the paper using 25 h mean snapshots of the baroclinic flux that shows branching and stronger eastward deviation of the IT when interacting with mesoscale eddies and stratification during ASOND. Finally, we evaluated sea surface height (SSH) frequency and wavenumber spectra for subtidal (f&lt;1/28 h−1), tidal (1/28 h−1 &lt; f&lt;1/11 h−1), and supertidal (f&gt;1/11 h−1) frequencies. Tidal frequencies explain most of the SSH variability for wavelengths between 250 and 70 km. Below 70 km, the SSH is mainly incoherent and supertidal. The length scale at which the SSH becomes dominated by unbalanced (non-geostrophic) IT was estimated to be around 250 km. Our results highlight the complexity of correctly predicting IT SSH in order to better observe mesoscale and sub-mesoscale eddies from existing and upcoming altimetric missions, notably the Surface Water Ocean Topography (SWOT) mission.

Building User‐Readiness for Satellite Earth Observing Missions: The Case of the Surface Water and Ocean Topography (SWOT) Mission

AbstractThe goal in this commentary is to share the development of the NASA Applied Science pre‐launch protocol called the Early Adopter Program (EAP) that is designed to build user‐readiness of planned satellite Earth observing missions proactively and before the launch. Here we focus in particular on the Surface Water and Ocean Topography satellite mission EAP as an illustration of benefits of such a program of proactive and sustained user community engagement. Such a commentary will be of value to other satellite Earth observation missions that are currently in service, scheduled for launch or prioritized for development in the near future.

Impact of Vertical Mixing Parameterizations on Internal Gravity Wave Spectra in Regional Ocean Models

AbstractWe present improvements in the modeling of the vertical wavenumber spectrum of the internal gravity wave continuum in high‐resolution regional ocean simulations. We focus on model sensitivities to mixing parameters and comparisons to McLane moored profiler observations in a Pacific region near the Hawaiian Ridge, which features strong semidiurnal tidal beams. In these simulations, the modeled continuum exhibits high sensitivity to the background mixing components of the K‐Profile Parameterization (KPP) vertical mixing scheme. Without the KPP background mixing, stronger vertical gradients in velocity are sustained in the simulations and the modeled kinetic energy and shear spectral slopes are significantly closer to the observations. The improved representation of internal wave dynamics in these simulations makes them suitable for improving ocean mixing estimates and for the interpretation of satellite missions such as the Surface Water and Ocean Topography mission.

Engaging Potential Users of the Planned Surface Water and Ocean Topography (SWOT) Mission in the Year of Launch

Engaging Potential Users of the Planned Surface Water and Ocean Topography (SWOT) Mission in the Year of Launch

Additive Manufacturing of Compliant Mechanisms for Deployable Aerospace Structures

In the past 10 years, complex deployable structures have become common on CubeSats and large-scale spacecraft. As new missions are pursued, there is an increased need for more mass and volume efficient deployments. Over the same period, metal additive manufacturing (AM) has enabled new forms of spaceflight hardware. However, AM of compliant mechanisms has not been fully leveraged for deployable aerospace structures. The Surface Water Ocean Topography and NASA-ISRO Synthetic Aperture Radar mission missions launching in 2022 both utilize large deployable masts. Each mast deployment is driven by numerous spring and damper mechanisms. Because of volume constraints, the spring mechanisms designed utilize high aspect ratio rectangular cross section torsion springs that represent the state of the art of manufacturing. This extreme spring design resulted in manufacturing difficulties and hardware failures during ground mechanism testing. Upon re-examining the mechanism design, AM enables torque performance, mass, and complexity improvements. AM allows for torsion spring cross sections not otherwise possible with traditional spring manufacturing methods. Prototype springs of various cross sections were printed in maraging steel and tested. Results confirmed design analysis, and doubling of the spring constant was achieved when compared to the traditional springs. The use of AM also allows springs to be built monolithically with surrounding structure. Design, manufacturing, and test findings will be discussed along with future implications for deployable aerospace structures.

Sparse Approximation of the Precision Matrices for the Wide-Swath Altimeters

The upcoming technology of wide-swath altimetry from space will deliver a large volume of data on the ocean surface at unprecedentedly high spatial resolution. These data are contaminated by errors caused by the uncertainties in the geometry and orientation of the on-board interferometer and environmental conditions, such as sea surface roughness and atmospheric state. Being highly correlated along and across the swath, these errors present a certain challenge for accurate processing in operational data assimilation centers. In particular, the error covariance matrix R of the Surface Water and Ocean Topography (SWOT) mission may contain trillions of elements for a transoceanic swath segment at kilometer resolution, and this makes its handling a computationally prohibitive task. Analysis presented here shows, however, that the SWOT precision matrix R−1 and its symmetric square root can be efficiently approximated by a sparse block-diagonal matrix within an accuracy of a few per cent. A series of observational system experiments with simulated data shows that such approximation comes at the expense of a relatively minor reduction in the assimilation accuracy, and, therefore, could be useful in operational systems targeted at the retrieval of submesoscale variability of the ocean surface.

Reimagining the Surface Water and Ocean Topography Mission as the “Landsat” of Surface Water [Perspective

The Surface Water Ocean Topography (SWOT) mission, jointly developed by NASA and French Space Agency (CNES) with contributions from the Canadian and U.K. space agencies, and planned for launch in 2022, is designed to provide a spatially distributed and high-frequency measurement of water elevation data for the hydrology and oceanography communities for the first time <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> , <xref ref-type="bibr" rid="ref2" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[2]</xref> . By virtue of its novel observational capability and stated scientific goals, SWOT satellite data are expected to have a profound impact on our understanding of global surface water. Although there have been many satellite missions that can either map water extent or water elevation, SWOT is the first mission that will measure extent and elevation concurrently regardless of cloud cover conditions and with a higher degree of precision.

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.