Improvements to estimate ADCP uncertainty sources for discharge measurements

Abstract

The use of moving boat ADCPs (Acoustic Doppler Current Profilers) for discharge measurements requires identification of the sources and magnitude of uncertainty to ensure accurate measurements. Recently, a tool known as QUant was developed to estimate the contribution to the uncertainty estimates for each transect of moving-boat ADCP discharge measurements, by varying different sampling configurations parameters through the use of Monte Carlo simulations. QUant is not only useful for estimating ADCP discharge measurement uncertainty, but also for identifying contributions of the various sources of uncertainty. However, the software requires long computational times, and the method to estimate the uncertainty of multiple-transect measurements does not consider the correlation of the variables between transects. Therefore, improvements in QUant are needed to optimize its application for practical purposes by hydrographers immediately after discharge measurements. This work presents four approaches for optimizing the performance of QUant to estimate the contribution to the uncertainty of different selected variables on ADCP discharge measurements and describes a new method of estimating multi-transect uncertainty with the QUant model that considers the correlation of errors in selected variables between transects. The approaches for optimization and the new multi-transect uncertainty method are evaluated using a dataset of 38 field measurements from a variety of riverine settings.