Monte Carlo Approach for Uncertainty Analysis of Acoustic Doppler Current Profiler Discharge Measurement by Moving Boat
Publication: Journal of Hydraulic Engineering
Volume 143, Issue 3
Abstract
This paper presents a method using Monte Carlo simulations for assessing uncertainty of moving-boat acoustic Doppler current profiler (ADCP) discharge measurements using a software tool known as QUant, which was developed for this purpose. Analysis was performed on 10 data sets from four Water Survey of Canada gauging stations in order to evaluate the relative contribution of a range of error sources to the total estimated uncertainty. The factors that differed among data sets included the fraction of unmeasured discharge relative to the total discharge, flow nonuniformity, and operator decisions about instrument programming and measurement cross section. As anticipated, it was found that the estimated uncertainty is dominated by uncertainty of the discharge in the unmeasured areas, highlighting the importance of appropriate selection of the site, the instrument, and the user inputs required to estimate the unmeasured discharge. The main contributor to uncertainty was invalid data, but spatial inhomogeneity in water velocity and bottom-track velocity also contributed, as did variation in the edge velocity, uncertainty in the edge distances, edge coefficients, and the top and bottom extrapolation methods. To a lesser extent, spatial inhomogeneity in the bottom depth also contributed to the total uncertainty, as did uncertainty in the ADCP draft at shallow sites. The estimated uncertainties from QUant can be used to assess the adequacy of standard operating procedures. They also provide quantitative feedback to the ADCP operators about the quality of their measurements, indicating which parameters are contributing most to uncertainty, and perhaps even highlighting ways in which uncertainty can be reduced. Additionally, QUant can be used to account for self-dependent error sources such as heading errors, which are a function of heading. The results demonstrate the importance of a Monte Carlo method tool such as QUant for quantifying random and bias errors when evaluating the uncertainty of moving-boat ADCP measurements.
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Acknowledgments
This study was financed in part by Environment and Climate Change Canada. The work was performed while the first author was a postdoctoral fellow in the Department of Civil Engineering at the University of Ottawa. The authors would like to thank the Water Survey of Canada’s hydrometric technologists Colin Angus, Karen Hardy, Donald Hood, and Daniel Selinger who acquired the data that were analyzed in this study. The authors would also like to thank our collaborators at the United States Geological Survey—Office of Surface Water and at the Argentinian Centro de Estudios y Tecnología del Agua for ongoing discussions and collaborations. Lastly, the authors would like to thank the anonymous reviewers of this manuscript for their constructive feedback.
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Information & Authors
Information
Published In
Journal of Hydraulic Engineering
Volume 143 • Issue 3 • March 2017
Copyright
©2016 American Society of Civil Engineers.
History
Received: Nov 17, 2014
Accepted: Jul 29, 2016
Published online: Oct 19, 2016
Published in print: Mar 1, 2017
Discussion open until: Mar 19, 2017
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