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Satellite remote sensing of river discharge: a framework for assessing the accuracy of discharge estimates made from satellite remote sensing observations
Abstract
This research presents an evaluation of the accuracy and uncertainty of estimates of river discharge made using satellite observed data sources as input to a modified form of Manning’s equation. Conventional U.S. Geological Survey (USGS) streamflow gaging station data and in-situ measurements of width, depth, height, slope, discharge, and velocity from 30 USGS gage sites were used as ground-truth to assess accuracy. This study explores accuracy in relation to the amount of ground truth information available, the number of calibration points available, and the accuracy of the input data. This research indicates that remotely sensed discharge estimates associated with the modified Manning equation may be expected to have an uncertainty in range of 10% overall given a sufficient number of calibration points. The uncertainty associated with the modified Manning algorithm increased markedly for depths <3 meters (m) and for discharges <1000 cubic meters per second (m3 / s) for many rivers after calibration. Rivers that exhibit (1) a wide range of flow conditions, (2) a significant number of dams in the watershed and along the channel, and (3) a high baseflow index are more likely to have relatively large errors overall and particularly at the low end of the streamflow range. Uncertainty in remotely sensed measurements of water-surface elevation (WSE) and width in the expected range (WSE, + / − 10 cm; Width, + / − 15 m) introduces uncertainty in the discharge estimates on the order of 10% and is greatest at the low end of discharge as rivers get shallower and narrower. As WSE and width measurement uncertainty increases, discharge uncertainty increases accordingly. In general, the observation errors are greater than the errors associated with the algorithm for a well-calibrated model (e.g., 20 calibration points).
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“Several sensors have been used in the past decades, building on pioneering work by ref. 16, and later studies that reported typical uncertainties below 20% based on large samples of in situ discharge measurements in the United States17,18.”
From Global scale river discharge and mean depth from radar altimetry and model (2026) · cites this paper as [18]
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Cited by
Global scale river discharge and mean depth from radar altimetry and model
Paris, A., Garambois, P.-A., Gal, L., Cerbelaud, A., Larnier, K., David, C. H., Jucá Oliveira, R. A., Correa, S. W., Tourian, M. J., & Calmant, S. (2026) · Nature Communications · doi:10.1038/s41467-026-78275-5
Metadata
- Authors
- Bjerklie, D. M., Durand, M., Lenoir, J., Dudley, R. W., Birkett, C. M., Jones, J. W., & Harlan, M.
- Affiliations
- U.S. Geological Survey
- The Ohio State Univ.
- NASA Goddard Space Flight Ctr.
- Venue
- Journal of Applied Remote Sensing
- Publisher
- SPIE-Intl Soc Optical Eng
- Published
- 2023-03-28
- Volume
- 17
- Issue
- 01
- Pages
- 1-47
- ISSN
- 1931-3195
- Cited by
- 18
- References
- 0
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- Bjerklie, D. M., Durand, M., Lenoir, J., Dudley, R. W., Birkett, C. M., Jones, J. W., & Harlan, M. (2023). Satellite remote sensing of river discharge: a framework for assessing the accuracy of discharge estimates made from satellite remote sensing observations. Journal of Applied Remote Sensing. https://doi.org/10.1117/1.jrs.17.014520
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