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

Durand, M. T.; Andreadis, Konstantinos M.; Alsdorf, Douglas; Lettenmaier, Dennis P.; Möller, D.; Wilson, Matthew

doi:10.1029/2008gl034150

Cited by 191 publications

(205 citation statements)

References 16 publications

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“…And in fact, many studies have been devoted to the assimilation of streamflow or water altimetry measurements (Andreadis et al, 2007;Biancamaria et al, 2011;Durand et al, 2008). We would like to call the runoff estimation with the particular setting of R t ≡ 0 as "inverse routing", in order to differentiate it from the general practice of streamflow assimilation.…”

Section: Inversion Through Fixed Interval Smoothingmentioning

confidence: 99%

Inverse streamflow routing

Pan

Wood

2013

Hydrol. Earth Syst. Sci.

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Abstract. The process whereby the spatially distributed runoff (generated through saturation/infiltration excesses, subsurface flow, etc.) travels over the hillslope and river network and becomes streamflow is generally referred to as "routing". In short, routing is a runoff-to-streamflow process, and the streamflow in rivers is the response to runoff integrated in both time and space. Here we develop a methodology to invert the routing process, i.e., to derive the spatially distributed runoff from streamflow (e.g., measured at gauge stations) by inverting an arbitrary linear routing model using fixed interval smoothing. We refer to this streamflowto-runoff process as "inverse routing". Inversion experiments are performed using both synthetically generated and real streamflow measurements over the Ohio River basin. Results show that inverse routing can effectively reproduce the spatial field of runoff and its temporal dynamics from sufficiently dense gauge measurements, and the inversion performance can also be strongly affected by low gauge density and poor data quality.The runoff field is the only component in the terrestrial water budget that cannot be directly measured, and all previous studies used streamflow measurements in its place. Consequently, such studies are limited to scales where the spatial and temporal difference between the two can be ignored. Inverse routing provides a more sophisticated tool than traditional methods to bridge this gap and infer finescale (in both time and space) details of runoff from aggregated measurements. Improved handling of this final gap in terrestrial water budget analysis may potentially help us to use space-borne altimetry-based surface water measurements for cross-validating, cross-correcting, and assimilation with other space-borne water cycle observations.

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Section: Inversion Through Fixed Interval Smoothingmentioning

confidence: 99%

Inverse streamflow routing

Pan

Wood

2013

Hydrol. Earth Syst. Sci.

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“…channel width, roughness and bed elevation, or channel depth) are the subject of other recent studies. For example, Durand et al (2008) used data assimilation of synthetic SWOT measurements in a hydraulic model to estimate river bathymetric slope and depth for the same river reach as presented in this paper, obtaining RMSE of 0.3 cm km −1 and 0.56 m, respectively. Similarly, Yoon et al (2012) estimated river bathymetry for the Ohio River, USA, obtaining an RMSE of 0.52 m and an effective reach-averaged river roughness within 1 % of the true value.…”

Section: Implications For Swotmentioning

confidence: 99%

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

Wilson

Durand

Jung

et al. 2015

Hydrol. Earth Syst. Sci.

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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, resultsshow 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).

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“…In fact, most of the active gauges are located over developed countries, and the density of stations is much sparser in the non-industrialized countries [5]. The potential of spaceborne and airborne techniques for obtaining river discharge estimates has been demonstrated by many studies [1,4,[6][7][8][9][10][11]. The work in [12] found a power law correlation between satellite-derived effective width and discharge using ERS 1 SAR images and simultaneous ground measurements of discharge.…”

Section: Introductionmentioning

confidence: 99%

Estimating River Depth from SWOT-Type Observables Obtained by Satellite Altimetry and Imagery

Tourian

Elmi

Mohammadnejad

et al. 2017

Water

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Abstract:The proposed Surface Water and Ocean Topography (SWOT) mission aims to improve spaceborne estimates of river discharge through its measurements of water surface elevation, river width and slope. SWOT, however, will not observe baseflow depth, which limits its value in estimating river discharge especially for those rivers with heterogeneous channel geometry. In this study, we aim to obtain river depths from spaceborne observations together with in situ data of river discharge. We first obtain SWOT-like observables from current satellite techniques. We obtain river water level and slope time series from multi-mission altimetry and effective river width from satellite imagery (MODIS). We then employ a Gauss-Helmert adjustment model to estimate average river depth for 16 defined reaches along the Po River in Italy, for which we use our spaceborne observations in two recognized models for discharge estimation. The average river depth estimates along the Po River are validated against surveyed cross-section information, which shows a generally good agreement in the range of ∼10% relative root mean squared error. Furthermore, we analyzed the sensitivity of error in the estimated river depth to errors of individual parameters. We show that the estimated river depth is less influenced by errors of river width and river discharge, while it is strongly influenced by errors in water level. This result gives a perspective to the SWOT mission to infer river depth by coarse estimates of river width and discharge.

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

Cited by 191 publications

References 16 publications

Inverse streamflow routing

Inverse streamflow routing

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

Estimating River Depth from SWOT-Type Observables Obtained by Satellite Altimetry and Imagery

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