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Author Horner, I. ♦ Renard, B. ♦ Coz, J. Le ♦ Branger, F. ♦ McMillan, H. K. ♦ Pierrefeu, G.
Source Hyper Articles en Ligne (HAL)
Content type Text
Publisher American Geophysical Union
File Format PDF
Language English
Subject Keyword statistical uncertainty ♦ river flow ♦ INCERTITUDE ♦ DEBIT DE COURS D'EAU ♦ sde ♦ Environmental Sciences
Abstract Stage measurement errors are generally overlooked when streamflow time series are derived from uncertain rating curves. We introduce an original method for propagating stage uncertainties due to two types of stage measurement errors: (i) errors of the stage read during the gauging and (ii) systematic and nonsystematic (independent) errors of the recorded stage time series. The error models are generic and can be used for any probabilistic rating curve estimation method that provides an ensemble of rating curves. The new method is applied to a range of six contrasting hydrometric stations in France. Uncertainty budgets quantifying the contribution of various error sources to the total streamflow uncertainty are computed and compared for streamflow time series averaged at time intervals from hour to year. A sensitivity analysis is conducted on the stage time series error model to identify the most sensitive parameters. The results are site specific, which illustrates the key role played by the properties of both the hydrometric site and the gauged catchment. Across the range of sites, stage errors of the gaugings are found to have limited impact on rating curve uncertainty, at least for gaugings performed in fair conditions. Nonsystematic errors in the stage time series have a negligible effect, generally. However, systematic stage errors should not be neglected. Over the six hydrometric stations in this study, the 95% uncertainty component reflecting stage systematic errors (from 60.5 cm to 66.8 cm) alone ranged from 4% to 12% of daily average streamflow, and from 1% to 3% of yearly average streamflow as sensors were assumed to be recalibrated every 30 days. Perspectives for improving and validating the streamflow uncertainty estimation techniques are eventually discussed.
ISSN 00431397
Educational Use Research
Learning Resource Type Article
Publisher Date 2018-01-01
e-ISSN 19447973
Journal Water Resources Research
Volume Number 54
Page Count 25
Starting Page 1952
Ending Page 1976