QRev—Software for computation and quality assurance of acoustic doppler current profiler moving-boat streamflow measurements—User’s manual for version 2.8

Mueller, David S.

doi:10.3133/ofr20161052

Cited by 18 publications

(35 citation statements)

References 12 publications

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“…Standards are also available for other gauging methods (e.g., ISO 9555 on tracer dilution, ISO 24578 on mobile‐boat ADCP, ISO 1070 on slope‐area discharge estimates) and they all include a clause on their uncertainty analysis. Several methods have been published recently for computing the uncertainty of mobile‐boat ADCP gaugings (González‐Castro et al, ; Moore et al, ; Mueller, ). Le Coz et al () also showed that the uncertainty of stream gauging techniques can be quantified using in‐situ repeated measures experiments.…”

Section: Discussionmentioning

confidence: 99%

Impact of Stage Measurement Errors on Streamflow Uncertainty

Horner¹,

Renard²,

Coz³

et al. 2018

Water Resources Research

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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 ±0.5 cm to ±6.8 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.

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Section: Discussionmentioning

confidence: 99%

Impact of Stage Measurement Errors on Streamflow Uncertainty

Horner¹,

Renard²,

Coz³

et al. 2018

Water Resources Research

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show abstract

“…The uncertainty estimates from repeated measures experiments could be compared with those provided by uncertainty propagation methods (González‐Castro et al, ; Mueller, ; Moore et al, ; Muste et al, ; Pierrefeu et al, ). The discrepancy between repeated measures experiments and propagation methods may help better estimate the elemental uncertainty component estimates in the latter methods (Despax et al, ).…”

Section: Discussionmentioning

confidence: 99%

“…Uncertainty computation methods were recently developed to estimate the uncertainty of ADCP measurements in stationary (Huang, 2011;Lee et al, 2014) or moving-boat deployment modes: OURSIN (Pierrefeu et al, 2017), QRev (Mueller, 2016), QUant (Moore et al, 2017), or RiverFlowUA (González-Castro et al, 2016). These propagation methods are based on the Guide to the expression of Uncertainty in Measurement (JCGM, 2008a(JCGM, , 2008b.…”

Section: Uncertainty Propagation Methodsmentioning

confidence: 99%

Decomposition of Uncertainty Sources in Acoustic Doppler Current Profiler Streamflow Measurements Using Repeated Measures Experiments

Despax

Coz

Hauet

et al. 2019

Water Resources Research

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Repeated measures experiments can be conducted to empirically estimate the uncertainty of a stream gauging method, such as the widespread moving‐boat acoustic Doppler current profilers (ADCPs) approach. Previous ADCP repeated measures experiments, also known as interlaboratory comparisons, provided a credible range of uncertainty estimates reflecting the quality of the site conditions. However, the method, which is a one‐way analysis of variance, only addresses the uncertainty of one lumped factor that combines several distinct factors: instrument, operator, procedure, and cross‐section effects. To decompose the uncertainty of ADCP streamflow measurements due to cross‐section selection and team effects, a large repeated measures experiment has been conducted in the Taurion River (France). The experiment design was crossed and balanced, with two sets of 24 teams circulated over two sets of 12 cross sections. A constant flow rate was released from a dam, located immediately upstream of the experimental site. Prior to the statistical analysis, a data quality review was performed using the U.S. Geological Survey QRev software to clean the data set from avoidable errors and to homogenize the discharge computations. A two‐way analysis of variance was applied to quantify the cross‐section effect, the team effect, and their interaction, which was found to dominate the pure cross‐section effect. It was then possible to predict the average uncertainty of multiple‐transect ADCP discharge measurements, depending on the number of teams, cross sections, and repeated transects included in the discharge average. The method opens interesting avenues for documenting difficult‐to‐estimate uncertainty sources of stream gauging techniques in other measuring conditions, especially the most adverse ones.

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“…The quantification of the uncertainty of Doppler flow measurements has developed significantly in the last year. QRev [10] is an important framework developed to this purpose. Otherwise, in extensive series of data, it is possible to lead with other kinds of error.…”

Section: Observations: Uncertainty In Individual Gaugingsmentioning

confidence: 99%

“…For example, a mechanical current meter measurement can be affected by directional bias [11]. In the other hand, Doppler based current meter measurement can be biased by moving bottom [10,11]. Sometimes, in an ensemble of measurements, there is some without information about the effective occurrence of these sources of bias.…”

Section: Observations: Uncertainty In Individual Gaugingsmentioning

confidence: 99%

The estimation of the uncertainty associated with rating curves of the river Ivinhema in the state of Paraná/Brazil

2018

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The estimation of the uncertainty associated with stage-discharge relations is a challenge to the hydrologists. Bayesian inference with likelihood estimator is a promissory approach. The choice of the likelihood function has an important impact on the capability of the model to represent the residues. This paper aims evaluate two likelihood functions with DREAM algorithm to estimate specific non-unique stage-discharge rating curves: normal likelihood function and Laplace likelihood function. The result of BaRatin is also discussed. The MCMC of the DREAM and the BaRatin algorithm have been compared and its results seem consistent for the studied case. The Laplace likelihood function presented as good results as normal likelihood function for the residues. Other gauging stations should be evaluated to attend more general conclusions.

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QRev—Software for computation and quality assurance of acoustic doppler current profiler moving-boat streamflow measurements—User’s manual for version 2.8

Cited by 18 publications

References 12 publications

Impact of Stage Measurement Errors on Streamflow Uncertainty

Impact of Stage Measurement Errors on Streamflow Uncertainty

Decomposition of Uncertainty Sources in Acoustic Doppler Current Profiler Streamflow Measurements Using Repeated Measures Experiments

The estimation of the uncertainty associated with rating curves of the river Ivinhema in the state of Paraná/Brazil

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