An intercomparison of remote sensing river discharge estimation algorithms from measurements of river height, width, and slope

Abstract

International audienceThe Surface Water and Ocean Topography (SWOT) satellite mission planned for launch in 2020 will map river elevations and inundated area globally for rivers >100 m wide. In advance of this launch, we here evaluated the possibility of estimating discharge in ungauged rivers using synthetic, daily ‘‘remote sensing’’ measurements derived from hydraulic models corrupted with minimal observational errors. Five discharge algorithms were evaluated, as well as the median of the five, for 19 rivers spanning a range of hydraulic and geomorphic conditions. Reliance upon a priori information, and thus applicability to truly ungauged reaches, varied among algorithms: one algorithm employed only global limits on velocity and depth, while the other algorithms relied on globally available prior estimates of discharge. We found at least one algorithm able to estimate instantaneous discharge to within 35% relative root-mean-squared error (RRMSE) on 14/16 nonbraided rivers despite out-of-bank flows, multichannel planforms, and backwater effects. Moreover, we found RRMSE was often dominated by bias; the median standard deviation of relativeresiduals across the 16 nonbraided rivers was only 12.5%. SWOT discharge algorithm progress is therefore encouraging, yet future efforts should consider incorporating ancillary data or multialgorithm synergy to improve results

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

“…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.…”

“…SWOT will irregularly sample mid-latitude locations approximately three times per its 21-day cycle rather than nearly continuously, as in a gauge estimate. Although irregular sampling is appropriate to monitor the global water cycle, it is inadequate for many local-scale questions on rivers where SWOT may not fully observe temporal dynamics [11,47].…”

“…Furthermore, Ref. [11] described the Mean Flow with Constant Roughness (MFCR) approach, which assumes a constant value for the roughness coefficient and uses the Water Balance Model (WBM) mean annual flow estimation. Recently, different methodologies were developed to reconstruct a spatially-and temporally-complete estimate of discharge from a set of observations [18][19][20][21].…”

“…The research in [17] implemented a form of Manning's equation to retrieve the river low flow bathymetry, roughness and discharge (H 0 , K, Q). The Mean-annual Flow and Geomorphology (MFG) algorithm was introduced in [11], which uses the so-called wide-channel approximation leading to a form of Manning's equation that approximates river depth as the difference between water surface elevation and the cross-sectional average river bathymetry. Furthermore, Ref.…”

Tracking Dynamic Northern Surface Water Changes with High-Frequency Planet CubeSat Imagery

“…Furthermore, the near-real time availability of Planet imagery provides large-scale observations of river ice breakup as it progresses downstream through remote areas and may therefore enable prediction of ice-jam flooding before it occurs, providing warning to communities located along northern rivers. with and without in situ measurements [5,[66][67][68][69][70]. A major limitation of current remotely-sensed discharge estimates is the lack of sufficient temporal sampling of high resolution imagery due to revisit time or cloud cover [68].…”