Surface Water And Ocean Topography Measurements Research Articles

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.

A Framework for Estimating Global‐Scale River Discharge by Assimilating Satellite Altimetry

AbstractUnderstanding spatial and temporal variations in terrestrial waters is key to assessing the global hydrological cycle. The future Surface Water and Ocean Topography (SWOT) satellite mission will observe the elevation and slope of surface waters at <100 m resolution. Methods for incorporating SWOT measurements into river hydrodynamic models have been developed to generate spatially and temporally continuous discharge estimates. However, most SWOT data assimilation studies have been conducted at the local scale. We developed a novel framework for estimating river discharge at the global scale by incorporating SWOT observations into the CaMa‐Flood hydrodynamic model. The local ensemble transform Kalman filter with adaptive local patches was used to assimilate SWOT observations. We tested the framework using multimodel runoff forcing and inaccurate model parameters represented by corrupted Manning's coefficient values. Assimilation of virtual SWOT observations considerably improved river discharge estimates for continental‐scale rivers at high latitudes (>50°) and also downstream river reaches at low latitudes. High assimilation efficiency in downstream river reaches was related to both local state correction and the propagation of corrected hydrodynamic states from upstream river reaches. Accurate global river discharge estimates were obtained (Kling‐Gupta efficiency [KGE] > 0.90) in river reaches with >270 accumulated overpasses per SWOT cycle when no model error was assumed. Introducing model errors decreased this accuracy (KGE ≈ 0.85). Therefore, improved hydrodynamic models are essential for maximizing SWOT information. These synthetic experiments showed where discharge estimates could be improved using SWOT observations. Further advances are needed for global‐scale data assimilation.

Nadir altimetry Vis-à-Vis swath altimetry: A study in the context of SWOT mission for the Bay of Bengal

Conventional nadir looking altimeters make along track measurements on a line and mapped sea level anomaly (SLA) information is obtained using a combination of several such altimeters (Jason, SARAL, Cryosat etc.). Mapping techniques, in general, introduce a lot of uncertainties in sea level representation and sub-mesoscale variability. Surface Water and Ocean Topography (SWOT) mission, based on radar interferometry, will measure SLA along wide swath thus providing detailed ocean information. This study aims to evaluate the advantages of SWOT measurements over nadir looking altimeters by making use of SWOT-simulator tool in the Bay of Bengal (BoB) region. Although, BoB is a small basin but interestingly it is full of mesoscale and sub-mesoscale features. The study performs several sensitivity experiments to allow a comparison of gridded SLA product from SWOT with the product from a constellation of nadir altimeters. Space-time scales for mapping the SLA from SWOT were obtained by performing a series of sensitivity experiments involving different spatial resolutions and temporal sampling. Sensitivity to different type of errors on the quality of mapped SLA fields from nadir-altimeters and SWOT is also carried out. In case of SWOT, mapped SLA fields generated using correlated noise were better as compared to the maps that were generated by making an assumption that the noise is uncorrelated. It is found that gridded SLA from SWOT have less error in the eddy dominant (high variability) regions as compared to the mapped SLA field from nadir altimeters, which perform better in the regions of low SLA variability. Apart from this, the position and strength of mesoscale eddies is well resolved by SWOT-mapped SLA fields as compared to nadir-altimeter mapped fields.

How will radar layover impact SWOT measurements of water surface elevation and slope, and estimates of river discharge?

Water surface elevation (WSE), slope and width measurements from the forthcoming Surface Water and Ocean Topography (SWOT) mission will enable spaceborne estimates of global river discharge. WSE will be measured by interferometric synthetic aperture radar (InSAR). InSAR measurements are vulnerable to contamination from layover, a phenomenon wherein radar returns from multiple locations arrive at the sensor simultaneously, rendering them indistinguishable. This study assesses whether layover will significantly impact the precision of SWOT estimates of global river discharge. We present a theoretical river layover uncertainty model at the scale of nodes and reaches, which constitute nominal 200 m and 10 km averages, respectively, along river centerlines. The model is calibrated using high-resolution simulations of SWOT radar interaction with topography covering a total of 41,233 node observations, across a wide range of near-river topographic features. We find that height uncertainty increases to a maximum value at relatively low values of topographic standard deviation and varies strongly with position in the swath. When applied at global scale, the calibrated model shows that layover causes expected height uncertainty to increase by only a modest amount (from 9.4 to 10.4 cm at the 68th percentile). The 68th percentile of the slope uncertainty increases more significantly, from 10 to 17 mm/km. Nonetheless, the 68th percentile discharge uncertainty increases only marginally. We find that the impact of layover on SWOT river discharge is expected to be small in most environments.

Reconstructing Upper-Ocean Vertical Velocity Field from Sea Surface Height in the Presence of Unbalanced Motion

AbstractReconstructability of upper-ocean vertical velocity w and vorticity ζ fields from high-resolution sea surface height (SSH) data is explored using the global 1/48° horizontal-resolution MITgcm output in the context of the forthcoming Surface Water and Ocean Topography (SWOT) mission. By decomposing w with an omega equation of the primitive equation system and by taking into account the measurement design of the SWOT mission, this study seeks to reconstruct the subinertial, balanced w and ζ signals. By adopting the effective surface quasigeostrophic (eSQG) framework and applying to the Kuroshio Extension region of the North Pacific, we find that the target and reconstructed fields have a spatial correlation of ~0.7 below the mixed layer for w and 0.7–0.9 throughout the 1000-m upper ocean for ζ in the error-free scenario. By taking the SWOT sampling and measurement errors into account, the spatial correlation is found to decrease to 0.4–0.6 below the mixed layer for w and 0.6–0.7 for ζ, respectively. For both w and ζ reconstruction, the degradation due to the SWOT errors is more significant in the surface layer and for smaller-scale signals. The impact of errors lessens with the increasing depth and lengthening horizontal scales.

Will the Surface Water and Ocean Topography (SWOT) Satellite Mission Observe Floods?

AbstractThe Surface Water and Ocean Topography (SWOT) mission will measure water surface elevations and inundation extents of rivers of the world but with limited temporal sampling. By comparing flood location and duration of 4,664 past flood events recorded by the Dartmouth Flood Observatory to SWOT's orbit ephemeris, we estimate that SWOT would have seen 55% of these, with higher probabilities associated with more extreme events and with those that displaced more than 10,000 people. However, SWOT measurements will exhibit uneven temporal sampling and may require a combination of data obtained at different times to accurately characterize large events. This is illustrated using recent flooding in the United States, in eastern Iowa and in Houston and surrounding areas from Hurricane Harvey. SWOT data have significant potential to improve flood forecasting models by offering data needed to enhance flow routing modeling, provided that users can overcome the potential hurdles associated with its temporal and spatial sampling characteristics.

Global Observations of Fine-Scale Ocean Surface Topography With the Surface Water and Ocean Topography (SWOT) Mission

The future international Surface Water and Ocean Topography (SWOT) Mission, planned for launch in 2021, will make high-resolution 2D observations of sea-surface height using SAR radar interferometric techniques. SWOT will map the global and coastal oceans up to 77.6° latitude every 21 days over a swath of 120 km (20 km nadir gap). Today’s 2D mapped altimeter data can resolve ocean scales of 150 km wavelength whereas the SWOT measurement will extend our 2D observations down to 15-30 km, depending on sea state. SWOT will offer new opportunities to observe the oceanic dynamic processes at these scales, that are important in the generation and dissipation of kinetic energy in the ocean, and act as one of the main gateways connecting the interior of the ocean to the upper layer. The active vertical exchanges linked to these scales have impacts on the local and global budgets of heat and carbon, and on nutrients for biogeochemical cycles. This review paper highlights the issues being addressed by the SWOT science community to understand SWOT’s very precise SSH / surface pressure observations, and it explores how SWOT data will be combined with other satellite and in-situ data and models to better understand the upper ocean 4D circulation (x,y,z,t) over the next decade. SWOT’s new SAR-interferometry technology aims to observe ocean SSH scales down to 15-30 km in wavelength. At these scales, SSH includes “balanced” geostrophic eddy motions and high-frequency internal tides and internal waves. This presents both a challenge in reconstructing the 4D upper ocean circulation, or in the assimilation of SSH in models, but also an opportunity to have global observations of the 2D structure of these phenomena, and to learn more about their interactions. At these small scales, the ocean dynamics evolve rapidly, and combining SWOT 2D SSH data with other satellite or in-situ data with different space-time coverage is also a challenge. SWOT’s new technology will be a forerunner for the future altimetric observing system, and so advancing on these issues today will pave the way for our future.

AirSWOT measurements of river water surface elevation and slope: Tanana River, AK

AbstractFluctuations in water surface elevation (WSE) along rivers have important implications for water resources, flood hazards, and biogeochemical cycling. However, current in situ and remote sensing methods exhibit key limitations in characterizing spatiotemporal hydraulics of many of the world's river systems. Here we analyze new measurements of river WSE and slope from AirSWOT, an airborne analogue to the Surface Water and Ocean Topography (SWOT) mission aimed at addressing limitations in current remotely sensed observations of surface water. To evaluate its capabilities, we compare AirSWOT WSEs and slopes to in situ measurements along the Tanana River, Alaska. Root‐mean‐square error is 9.0 cm for WSEs averaged over 1 km2 areas and 1.0 cm/km for slopes along 10 km reaches. Results indicate that AirSWOT can accurately reproduce the spatial variations in slope critical for characterizing reach‐scale hydraulics. AirSWOT's high‐precision measurements are valuable for hydrologic analysis, flood modeling studies, and for validating future SWOT measurements.

Reconstructability of Three-Dimensional Upper-Ocean Circulation from SWOT Sea Surface Height Measurements

AbstractUtilizing the framework of effective surface quasigeostrophic (eSQG) theory, this study explores the potential of reconstructing the 3D upper-ocean circulation structures, including the balanced vertical velocity w field, from high-resolution sea surface height (SSH) data of the planned Surface Water and Ocean Topography (SWOT) satellite mission. Specifically, the authors utilize the 1/30°, submesoscale-resolving, OFES model output and subject it to the SWOT simulator that generates the along-swath SSH data with expected measurement errors. Focusing on the Kuroshio Extension region in the North Pacific where regional Rossby numbers range from 0.22 to 0.32, this study finds that the eSQG dynamics constitute an effective framework for reconstructing the 3D upper-ocean circulation field. Using the modeled SSH data as input, the eSQG-reconstructed relative vorticity ζ and w fields are found to reach a correlation of 0.7–0.9 and 0.6–0.7, respectively, in the 1000-m upper ocean when compared to the original model output. Degradation due to the SWOT sampling and measurement errors in the input SSH data for the ζ and w reconstructions is found to be moderate, 5%–25% for the 3D ζ field and 15%–35% for the 3D w field. There exists a tendency for this degradation ratio to decrease in regions where the regional eddy variability (or Rossby number) increases.

The SWOT Mission and Its Capabilities for Land Hydrology

Surface water storage and fluxes in rivers, lakes, reservoirs and wetlands are currently poorly observed at the global scale, even though they represent major components of the water cycle and deeply impact human societies. In situ networks are heterogeneously distributed in space, and many river basins and most lakes—especially in the developing world and in sparsely populated regions—remain unmonitored. Satellite remote sensing has provided useful complementary observations, but no past or current satellite mission has yet been specifically designed to observe, at the global scale, surface water storage change and fluxes. This is the purpose of the planned Surface Water and Ocean Topography (SWOT) satellite mission. SWOT is a collaboration between the (US) National Aeronautics and Space Administration, Centre National d’Etudes Spatiales (the French Spatial Agency), the Canadian Space Agency and the United Kingdom Space Agency, with launch planned in late 2020. SWOT is both a continental hydrology and oceanography mission. However, only the hydrology capabilities of SWOT are discussed here. After a description of the SWOT mission requirements and measurement capabilities, we review the SWOT-related studies concerning land hydrology published to date. Beginning in 2007, studies demonstrated the benefits of SWOT data for river hydrology, both through discharge estimation directly from SWOT measurements and through assimilation of SWOT data into hydrodynamic and hydrology models. A smaller number of studies have also addressed methods for computation of lake and reservoir storage change or have quantified improvements expected from SWOT compared with current knowledge of lake water storage variability. We also briefly review other land hydrology capabilities of SWOT, including those related to transboundary river basins, human water withdrawals and wetland environments. Finally, we discuss additional studies needed before and after the launch of the mission, along with perspectives on a potential successor to SWOT.

Swath-altimetry measurements of the main stem Amazon River: measurement errors and hydraulic implications

Abstract. The Surface Water and Ocean Topography (SWOT) mission, scheduled for launch in 2020, will provide a step-change improvement in the measurement of terrestrial surface-water storage and dynamics. In particular, it will provide the first, routine two-dimensional measurements of water-surface elevations. In this paper, we aimed to (i) characterise and illustrate in two dimensions the errors which may be found in SWOT swath measurements of terrestrial surface water, (ii) simulate the spatio-temporal sampling scheme of SWOT for the Amazon, and (iii) assess the impact of each of these on estimates of water-surface slope and river discharge which may be obtained from SWOT imagery. We based our analysis on a virtual mission for a ~260 km reach of the central Amazon (Solimões) River, using a hydraulic model to provide water-surface elevations according to SWOT spatio-temporal sampling to which errors were added based on a two-dimensional height error spectrum derived from the SWOT design requirements. We thereby obtained water-surface elevation measurements for the Amazon main stem as may be observed by SWOT. Using these measurements, we derived estimates of river slope and discharge and compared them to those obtained directly from the hydraulic model. We found that cross-channel and along-reach averaging of SWOT measurements using reach lengths greater than 4 km for the Solimões and 7.5 km for Purus reduced the effect of systematic height errors, enabling discharge to be reproduced accurately from the water height, assuming known bathymetry and friction. Using cross-sectional averaging and 20 km reach lengths, results show Nash–Sutcliffe model efficiency values of 0.99 for the Solimões and 0.88 for the Purus, with 2.6 and 19.1 % average overall error in discharge, respectively. We extend the results to other rivers worldwide and infer that SWOT-derived discharge estimates may be more accurate for rivers with larger channel widths (permitting a greater level of cross-sectional averaging and the use of shorter reach lengths) and higher water-surface slopes (reducing the proportional impact of slope errors on discharge calculation).

On the Investigation of the Sea-Level Variability in Coastal Zones Using SWOT Satellite Mission: Example of the Eastern English Channel (Western France)

The future mission of surface water and ocean topography (SWOT), launched in 2020 over a period of 3–5 years, will be designated to address the issue of combining surface water hydrology with physical oceanography aiming to present new perspectives of applications for coastal areas. The extent to which the synthetic SWOT measurements can reproduce the temporal variability of the sea level was investigated. The eastern English Channel (NW France) was considered as a case of application. The hourly sea-level records were filtered from the aliased harmonic tides by classic harmonic analyses to obtain the nontidal residual. This residual was used to simulate synthetically the satellite samples based on the number of overpasses per repeat cycle at each geographical station. Both real and synthetic SWOT measurements were compared by the use of different approaches of inference statistics and wavelets. The statistical behavior, deduced from the functions of probability density (pdf) and cumulative distribution (cdf), shows correlations between 65% and 75% for hourly measurements, which increase to 85% for monthly average ones. The frequency of positive and negative extreme values is under-estimated with an order less than 25%. The potential use of SWOT depends on the number of measurements and the sampling interval between SWOT overpasses per repeat orbit. In the time–frequency domain, the wavelet multiresolution analysis of the nontidal sea level displays four components: 1) 1 year; 2) <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\sim$</tex-math></inline-formula> 4–7 month; 3) <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\sim$</tex-math></inline-formula> 2–3 month; and 4) <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$&lt;2$</tex-math></inline-formula> month bands. Such modes seem to be well manifested by SWOT samples with a mean explained variance more than 75%. The aliasing frequency of the altimeter generates a dispersion and an overexpression of the energy spectrum, which increases with the number of overpasses per repeat orbit and the high frequency ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\sim $</tex-math></inline-formula> 2–3 and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$&lt;2$</tex-math></inline-formula> month bands). The reconstructed wavelet components evidence the capacity of SWOT to estimate the annual and the seasonal variability of the nontidal sea level. In particular, SWOT is able to reproduce the most of extreme storm surges in the English Channel. The main finding of this research clearly shows the utility of SWOT satellite altimetry in observing and understanding the sea-level variability and storm surges, complementing tide-gauge observations for the validation and improvement of coastal models.

Using High-Resolution Altimetry to Observe Mesoscale Signals

Abstract An Ocean System Simulation Experiment is used to quantify the observing capability of the Surface Water and Ocean Topography (SWOT) mission and its contribution to higher-quality reconstructed sea level anomaly (SLA) fields using optimal interpolation. The paper focuses on the potential of SWOT for mesoscale observation (wavelengths larger than 100 km and time periods larger than 10 days) and its ability to replace or complement altimetry for classical mesoscale applications. For mesoscale variability, the wide swath from SWOT provides an unprecedented sampling capability. SWOT alone would enable the regional surface signal reconstruction as precisely as a four-altimeter constellation would, in regions where temporal sampling is optimum. For some specifics latitudes, where swath sampling is degraded, SWOT capabilities are reduced and show performances equivalent to the historical two-altimeter constellation. In this case, merging SWOT with the two-altimeter constellation stabilizes the global sampling and fully compensates the swath time sampling limitations. Benefits of SWOT measurement are more important within the swath. It would allow a precise local reconstruction of mesoscale structures. Errors of surface signal reconstruction within the swath represent less than 1% (SLA) to 5% (geostrophic velocities reconstruction) of the signal variance in a pessimistic roll error reduction. The errors are slightly reduced by merging swath measurements with the conventional nadir measurements.

Estimating river bathymetry from data assimilation of synthetic SWOT measurements

Summary This paper focuses on estimating river bathymetry for retrieving river discharge from the upcoming Surface Water and Ocean Topography (SWOT) satellite mission using a data assimilation algorithm coupled with a hydrodynamic model. The SWOT observations will include water surface elevation (WSE), its spatial and temporal derivatives, and inundated area. We assimilated synthetic SWOT observations into the LISFLOOD-FP hydrodynamic model using a local ensemble batch smoother (LEnBS), simultaneously estimating river bathymetry and flow depth. SWOT observations were obtained by sampling a “true” LISFLOOD-FP simulation based on the SWOT instrument design; the “true” discharge boundary condition was derived from USGS gages. The first-guess discharge boundary conditions were produced by the Variable Infiltration Capacity model, with discharge uncertainty controlled via precipitation uncertainty. First-guess estimates of bathymetry were derived from SWOT observations assuming a uniform spatial depth; bathymetric variability was modeled using an exponential correlation function. Thus, discharge and bathymetry errors were modeled realistically. The LEnBS recovered the bathymetry from SWOT observations with 0.52 m reach-average root mean square error (RMSE), which was 67.8% less than the first-guess RMSE. The RMSE of bathymetry estimates decreased sequentially as more SWOT observations were used in the estimate; we illustrate sequential processing of 6 months of SWOT observations. The better estimates of bathymetry lead to improved discharge estimates. The normalized RMSE of the river discharge estimates was 10.5%, 71.2% less than the first-guess error.

Assimilation of virtual wide swath altimetry to improve Arctic river modeling

Global surface water variations are still difficult to monitor with current satellite measurements. The future Surface Water and Ocean Topography (SWOT) mission is designed to address this issue. Its main payload will be a wide swath altimeter which will provide maps of water surface elevations between 78°S and 78°N over a 120 km swath. This study aims to combine coupled hydrologic/hydraulic modeling of an Arctic river with virtual SWOT observations using a local ensemble Kalman smoother to characterize river water depth variations. We assumed that modeling errors are only due to uncertainties in atmospheric forcing fields (precipitation and air temperature) and different SWOT orbits were tested. First, we tested orbits that all have a three day repeat period but differ in terms of their spatial coverage of the study reach; these orbits correspond to the first three months of the mission, which will be dedicated to calibration and validation experiments. For these orbits, the mean spatial Root Mean Square Error (RMSE) in modeled channel water depth decreased by between 29% and 79% compared to the modeled RMSE with no assimilation, depending on the spatial coverage. The corresponding mean temporal RMSE decrease was between 54% and 91%. We then tested the nominal orbit with a twenty two day repeat period which will be used during the remaining lifetime of the mission. Unlike the three day repeat orbits, this orbit will observe all continental surfaces (except Antartica and the northern part of Greenland) during one repeat period. The assimilation of SWOT observations computed with this nominal orbit into the hydraulic model leads to a decrease of 59% and 66% in the mean spatial and temporal RMSE in modeled channel water depth, respectively. These results show the huge potential of the future SWOT mission for land surface hydrology, especially at high latitudes which will be very well sampled during one orbit repeat period. Still, further work is needed to reduce current modeling uncertainties and to better characterize SWOT measurement errors.

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.

Estimating River Depth From Remote Sensing Swath Interferometry Measurements of River Height, Slope, and Width

The Surface Water and Ocean Topography (SWOT) mission is a swath mapping radar interferometer that would provide new measurements of inland water surface elevation (WSE) for rivers, lakes, wetlands, and reservoirs. SWOT WSE estimates would provide a source of information for characterizing streamflow globally and would complement existing <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> gage networks. In this paper, we evaluate the accuracy of river discharge estimates that would be obtained from SWOT measurements over the Ohio river and eleven of its major tributaries within the context of a virtual mission (VM). SWOT VM measurements are obtained by using an instrument measurement model coupled to simulated WSE from the hydrodynamic model LISFLOOD-FP, using USGS streamflow gages as boundary conditions and validation data. Most model pixels were estimated two or three times per 22-day orbit period. These measurements are then input into an algorithm to obtain estimates of river depth and discharge. The algorithm is based on Manning's equation, in which river width and slope are obtained from SWOT, and roughness is estimated <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a priori.</i> SWOT discharge estimates are compared to the discharge simulated by LISFLOOD-FP. Instantaneous discharge estimates over the one-year evaluation period had median normalized root mean square error of 10.9%, and 86% of all instantaneous errors are less than 25%.

Preliminary Characterization of SWOT Hydrology Error Budget and Global Capabilities

River discharge and lake water storage are critical elements of land surface hydrology, but are poorly observed globally. The Surface Water and Ocean Topography (SWOT) satellite mission will provide high-resolution measurements of water surface elevations with global coverage. Feasibility studies have been undertaken to help define the orbit inclination and repeat period. Preliminary error budgets have been computed for estimating instantaneous and monthly river discharge from SWOT measurements (errors are assumed uncorrelated). Errors on monthly discharge due to SWOT temporal sampling were estimated using gauges and their observation times for two SWOT orbits with different inclinations (78° and 74°). These errors have then been extrapolated to rivers globally. The 78° and 74° orbital inclinations allow a good sampling frequency, avoid tidal aliasing and cover almost all the continental surface. For a 22-day repeat orbit, a single point at 72°N is sampled 11 and 16 times during one repeat period for the 78° and 74° inclination orbit, respectively. Errors in instantaneous discharge are below 25% for rivers wider than 50 m (48% of all rivers). Errors in monthly discharge are below 20% for rivers with drainage areas larger than 7000 km2 (34% of all rivers). A rough estimate of global lake storage change has been computed. Currently, available satellite nadir altimetry data can only monitor 15% of the global lake volume variation, whereas from 50% to more than 65% of this variation will be observed by SWOT, thus providing a significant increase in our knowledge of lake hydrology.

Characterization of complex fluvial systems using remote sensing of spatial and temporal water level variations in the Amazon, Congo, and Brahmaputra Rivers

AbstractThe Surface Water and Ocean Topography (SWOT) satellite mission will provide global, space‐based estimates of water elevation, its temporal change, and its spatial slope in fluvial environments, as well as across lakes, reservoirs, wetlands, and floodplains. This paper illustrates the utility of existing remote sensing measurements of water temporal changes and spatial slope to characterize two complex fluvial environments. First, repeat‐pass interferometric SAR measurements from the Japanese Earth Resources Satellite are used to compare and contrast floodplain processes in the Amazon and Congo River basins. Measurements of temporal water level changes over the two areas reveal clearly different hydraulic processes at work. The Amazon is highly interconnected by floodplain channels, resulting in complex flow patterns. In contrast, the Congo does not show similar floodplain channels and the flow patterns are not well defined and have diffuse boundaries. During inundation, the Amazon floodplain often shows sharp hydraulic changes across floodplain channels. The Congo, however, does not show similar sharp changes during either infilling or evacuation. Second, Shuttle Radar Topography Mission measurements of water elevation are used to derive water slope over the braided Brahmaputra river system. In combination with in situ bathymetry measurements, water elevation and slope allow one to calculate discharge estimates within 2.3% accuracy. These two studies illustrate the utility of satellite‐based measurements of water elevation for characterizing complex fluvial environments, and highlight the potential of SWOT measurements for fluvial hydrology. Copyright © 2010 John Wiley &amp; Sons, Ltd.

Estimation of bathymetric depth and slope from data assimilation of swath altimetry into a hydrodynamic model

The proposed Surface Water and Ocean Topography (SWOT) mission would provide measurements of water surface elevation (WSE) for characterization of storage change and discharge. River channel bathymetry is a significant source of uncertainty in estimating discharge from WSE measurements, however. In this paper, we demonstrate an ensemble‐based data assimilation (DA) methodology for estimating bathymetric depth and slope from WSE measurements and the LISFLOOD‐FP hydrodynamic model. We performed two proof‐of‐concept experiments using synthetically generated SWOT measurements. The experiments demonstrated that bathymetric depth and slope can be estimated to within 3.0 microradians or 50 cm, respectively, using SWOT WSE measurements, within the context of our DA and modeling framework. We found that channel bathymetry estimation accuracy is relatively insensitive to SWOT measurement error, because uncertainty in LISFLOOD‐FP inputs (such as channel roughness and upstream boundary conditions) is likely to be of greater magnitude than measurement error.