James J. Duncker

Effect of temporal resolution on the accuracy of ADCP measurements

The application of acoustic Doppler current profilers (ADCP’s) in river flow measurements is promoting a great deal of progress in hydrometry. ADCP’s not only require shorter times to collect data than traditional current meters, but also allow streamflow measurements at sites where the use of conventional meters is either very expensive, unsafe, or simply not possible. Moreover, ADCPs seem to offer a means for collecting flow data with spatial and temporal resolutions that cannot be achieved with traditional current-meters. High-resolution data is essential to characterize the mean flow and turbulence structure of streams, which can in turn lead to a better understanding of the hydrodynamic and transport processes in rivers. However, to properly characterize the mean flow and turbulence intensities of stationary flows in natural turbulent boundary layers, velocities need to be sampled over a long-enough time span. The question then arises, how long should velocities be sampled in the flow field to achieve an adequate temporal resolution? Theoretically, since velocities cannot be sampled over an infinitely long time interval, the error due to finite integration time must be considered. This error can be estimated using the integral time scale. The integral time scale is not only a measure of the time interval over which a fluctuating function is correlated with itself but also a measure of the time span over which the function is dependent on itself. This time scale, however, is not a constant but varies spatially in the flow field. In this paper we present an analysis of the effect of the temporal resolution (sampling time span) on the accuracy of ADCP measurements based on the integral time scale. Single ping velocity profiles collected with frequencies of 1 Hz in the Chicago River at Columbus Drive using an uplooking 600 kHz ADCP are used in this analysis. The integral time scale at different depths is estimated based on the autocorrelation function of the velocity fluctuations and is used to evaluate the mean-square error as a function of the integration time. The implications of these errors in typical ADCP measurements for discharge estimates in natural streams are discussed. 1 Post-doctoral Research Associate, Illinois Water Resources Center, University of Illinois, 221 N. Broadway, Urbana, IL 61801 2 Hydrologist, U.S. Geological Survey, 221 N. Broadway, Urbana, IL 61801

Comparison of estimates of uncertainty of discharge at US geological survey index-velocity gages on the Chicago sanitary and ship canal, Illinois

Estimates of uncertainty of discharge at time scales from 5 minutes to 1 year were obtained for two index-velocity gages on the Chicago Sanitary and Ship Canal (CSSC), Ill., instrumented with acoustic velocity meters (AVMs). The velocity measurements obtained from the AVMs are corrected to a mean channel velocity by use of an index-velocity rating (IVR). The IVR is a regression-derived relation between the AVM velocity estimates and those obtained using acoustic Doppler current profilers (ADCPs). The uncertainty estimation method is based on the firstorder variance method, but the AVM velocity error is estimated from an empirical perspective, using the statistics of the IVR regression. It is not clear whether to include the standard error of the IVR regression ( ) in the discharge uncertainty. At the 5-minute time scale when is included, has the dominant contribution to the discharge uncertainty, and the discharge uncertainty (expressed as the standard deviation of the discharge estimate) is about 5 m 2 e σ 2 e σ 2 e σ

Bathymetric survey of Rock Run Rookery Lake, Will County, Illinois.

The bathymetric data set was collected in Rock Run on Dec. 10, 2015 by USGS ILWSC staff Clayton Bosch and Louis Pappas. The bathymetric data were collected with an RD Instruments 1200 kHz ADCP (S/N 8617) and Trimble Ag 162 GPS mounted on the M/V La Moine. A temporary reference point (TRP) was established on the north side of the footbridge over the connecting channel to the Des Plaines River. The mean water surface elevation (504.97 feet, WGS 84) during the survey was established from a temporary reference point whose elevation was later established by GPS survey. The measured depths were then converted to a lake bed elevation. The location and depth data were compiled into a bathymetry dataset (Rock Run Bathymetry Data.csv). The dataset was imported as a shapefile into ArcMap (ArcGIS software 10.3.1). A shape file of lake boundary elevation was developed based on imagery from September 16, 2015 (U.S. Department of Agriculture Farm Services Agency National Agriculture Imagery Program (NAIP)) (point data can be found in Rock Run Lake Boundary.csv). This shape file was merged with the elevation shape file to enforced the lake and island edges in the final bathymetry. This elevation shape file was then contoured using Geostatistical Analyst/Deterministic methods/Radial Basis Functions with Completely Regularized Spline (defaults were used except Sector type: 4 Sectors, Angle: 42, Major semiaxis: 800, Minor semiaxis: 500). The raster was then exported to a GeoTIFF file with a resulting raster cell size of 1 foot.