Expected performance of the upcoming Surface Water and Ocean Topography (SWOT) mission measurements of river height, width, slope, cross-sectional area change, and discharge on Sacramento River
Abstract
River surface height, slope, and width are essential hydrologic parameters, and will be measured by the upcoming Surface Water and Ocean Topography (SWOT) mission. In this study, we used the JPL's SWOT instrument simulator to synthesize 6-months of SWOT observations of river surface height, width, and slope over the Sacramento River. We evaluated the accuracy of the simulated measurements, analyzed the potential error sources, and quantified the contribution of each error source to the total error of the three variables. We found that over our study area, as much as a 12cm height bias is caused by terrain layover, which is magnified by the parallel-to-river flight track as well as by the presence of levees in its downstream section. Both height and width errors depend on the cross-track distance. The height RMSE is 10cm at the near-range and increases to 70cm towards the far-range. The RMSE of river width is as high as 60m for cross-track distances >20km or <60km and reduces to 15m for cross-track distances between 20 and 60 km. We found surface slope errors to be dominated by height random errors; therefore, slopes computed with smoothed water surface heights show higher accuracy. The height, width, and slope RMSEs over the whole study area are 12.4 cm, 4.6 m, and 16.8 cm/km, respectively. We used the simulated time series of height and width measurements to compute the cross-sectional departures from the median stage, with an overall cross-section area RMSE of 81.6 m2 and bias of -9.4 m2. Finally, we used MetroMan, an algorithm that assumes mass-conservation among neighboring reaches to estimate Manning's n and the cross-sectional area, the two missing pieces that allowed us to estimate river discharge in our domain and evaluate how SWOT measurement errors may impact discharge calculations.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFM.H43N2264W
- Keywords:
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- 1855 Remote sensing;
- HYDROLOGY