Validation of Streamflow Measurements Made with Acoustic Doppler Current Profilers

The U.S. Geological Survey and other international agencies have collaborated to conduct laboratory and field validations of acoustic Doppler current profiler (ADCP) measurements of streamflow. Laboratory validations made in a large towing basin show that the mean differences between tow cart velocity and ADCP bottom-track and water-track velocities were ?0.51 and ?1.10%, respectively. Field validations of commercially available ADCPs were conducted by comparing streamflow measurements made with ADCPs to reference streamflow measurements obtained from concurrent mechanical current-meter measurements, stable rating curves, salt-dilution measurements, or acoustic velocity meters. Data from 1,032 transects, comprising 100 discharge measurements, were analyzed from 22 sites in the United States, Canada, Sweden, and The Netherlands. Results of these analyses show that broadband ADCP streamflow measurements are unbiased when compared to the reference discharges regardless of the water mode used for making the measurement. Measurement duration is more important than the number of transects for reducing the uncertainty of the ADCP streamflow measurement.     

Price Current-Meter Standard Rating Development by the U.S. Geological Survey

The U.S. Geological Survey has developed new standard rating tables for use with Price type AA and pygmy current meters, which are employed to measure streamflow velocity. Current-meter calibration data, consisting of the rates of rotation of meters at several different constant water velocities, have shown that the original rating tables are no longer representative of the average responsiveness of newly purchased meters or meters in the field. The new rating tables are based on linear regression equations that are weighted to reflect the population mix of current meters in the field and weighted inversely to the variability of the data at each calibration velocity. For calibration velocities of 0.3 m∕s and faster, at which most streamflow measurements are made, the new AA-rating predicts the true velocities within 1.5% and the new pygmy-meter rating within 2.0% for more than 95% of the meters. At calibration velocities, the new AA-meter rating is up to 1.4% different from the original rating, and the new pygmy-meter rating is up to 1.6% different.     

USGS Streamflow Data and Modeling Sand-Bed Rivers

United States Geological Survey streamflow data are commonly used for hydraulic model calibration and boundary conditions. The transitory nature of sand-bed rivers’ bathymetry is problematic for the traditional automated stream gauging methods used by the USGS. This note seeks to assess the limitations of streamflow measurements for use in hydraulic models. An overview of USGS rating-curve development and use is presented with a focus on the specific challenges of sand-bed rivers. Measurements from three consecutive USGS gauges for a storm event on the Rio Grande in Albuquerque, New Mexico, illustrate the outlined problems with rating curves. These gauges are utilized to study the impact of uncertainty in rating-curve discharges on hydraulic model results. A one dimensional hydraulic model of the study reach indicates up to 25% reduction in the calculated flow depth if questionable rating-curve discharges are used as model input. Recommendations for using USGS streamflow data in hydraulic models are outlined.     

Current Meter Calibration Strategy

A single, continuous equation, which takes into account the linear and nonlinear components of the Price meter rotor response, was used to examine two current meter calibration strategies. Results showed that the uncertainty of group calibrations is substantially greater than that of calibrations of individual meters. The difference may be due to meter fabrication variances for velocities greater than 0.3 m∕s. Calibration accuracies are less sensitive to calibration strategies at velocities less than 0.3 m∕s due to residual velocities in the towing tank.     

Correcting Acoustic Doppler Current Profiler Discharge Measurements Biased by Sediment Transport

A negative bias in discharge measurements made with an acoustic Doppler current profiler (ADCP) is attributed to the movement of sediment on or near the streambed, and is an issue widely acknowledged by the scientific community. The integration of a differentially corrected global positioning system (DGPS) to track the movement of the ADCP can be used to avoid the systematic bias associated with a moving bed. DGPS, however, cannot provide consistently accurate positions because of multipath errors and satellite signal reception problems on waterways with dense tree canopy along the banks, in deep valleys or canyons, and near bridges. An alternative method of correcting for the moving-bed bias, based on the closure error resulting from a two-way crossing of the river, is presented. The uncertainty in the mean moving-bed velocity measured by the loop method is shown to be approximately 0.6?cm/s. For the 13 field measurements presented, the loop method resulted in corrected discharges that were within 5% of discharges measured utilizing DGPS to compensate for moving-bed conditions.     

Electromagnetic Wave Surface Velocimetry

Electromagnetic wave surface velocimeters (ESVs) measure the Doppler shift in electromagnetic waves reflected from the water surface. They provide nonintrusive water surface velocity measurements from bridges and river banks. Comparisons with laboratory and field tests show very good agreement over a wide range of elevation and planview angles. Laboratory testing shows comparable results between ESV and other measurement techniques when 0.4相似文献   

Errors in Acoustic Doppler Profiler Velocity Measurements Caused by Flow Disturbance

Acoustic Doppler current profilers (ADCPs) are commonly used to measure streamflow and water velocities in rivers and streams. This paper presents laboratory, field, and numerical model evidence of errors in ADCP measurements caused by flow disturbance. A state-of-the-art three-dimensional computational fluid dynamic model is validated with and used to complement field and laboratory observations of flow disturbance and its effect on measured velocities. Results show that near the instrument, flow velocities measured by the ADCP are neither the undisturbed stream velocity nor the velocity of the flow field around the ADCP. The velocities measured by the ADCP are biased low due to the downward flow near the upstream face of the ADCP and upward recovering flow in the path of downstream transducer, which violate the flow homogeneity assumption used to transform beam velocities into Cartesian velocity components. The magnitude of the bias is dependent on the deployment configuration, the diameter of the instrument, and the approach velocity, and was observed to range from more than 25% at 5?cm from the transducers to less than 1% at about 50?cm from the transducers for the scenarios simulated.     

Calibration Method of Current Meters

This paper presents a rapid method for propeller current meter calibration, enabling calibration of current meters in their actual working conditions using simpler equipment than what is currently used in traditional calibrations, and exploiting the uniform velocity profile present through submerged outflows (e.g., flow nozzles and orifices). Experiments were performed to confirm the fundamental hypothesis of uniform horizontal and vertical velocity distribution downstream of a submerged jet. Two experimental velocities were adopted to determine the calibration curve: one based on the discharge and the outflow area; the other derived from Torricelli’s formula, which relies on the head difference between two reservoir levels. Because a current meter measures local velocity, the influence on the measurements’ reliability as a function of current meter position in the submerged outflow jet was investigated. An uncertainty analysis was also performed, and a comparison of the results with the preexisting calibration lines obtained by towing tank is presented.     

Case Study: Equivalent Widths of the Middle Rio Grande, New Mexico

Successive reaches of the Rio Grande have maintained equivalent channel widths of 50 and 250?m, respectively, over long periods of time. It is hypothesized that alluvial channels adjust bed slope to match the long-term changes in channel width. Analytical relationships show that wider river reaches develop steeper slopes. A modeling approach using daily water and sediment discharges simulates the transient evolution of bed elevation changes. The analytical and numerical models are in very good agreement with the longitudinal profile measurements of the Bosque del Apache reach of the Rio Grande, NM, from 1992 to 1999. The slope of the 50?m wide reach was 50?cm/km and the slope of the 250?m wide reach of the same river increased to 80?cm/km. This unsteady daily transient model compares well with a steady transient solution at a constant discharge close to the mean annual flow. The transient slope adjustments can also be approximated with an exponential model. Accordingly, it takes about 20–25?years for the Rio Grande to achieve about 90% of its slope adjustment.     

Field and Laboratory Validation of High-Flow Air Bubbler Mechanics

Recent physical model studies have refined designs for high-flow air diffusers for managing accumulations of broken ice at navigation projects. Although these solutions are successful in the model, implementing them in the field can be difficult because of uncertainties in airflow scaling. This study uses field and laboratory data to test theoretical relationships between airflow from the diffuser and the resulting near-surface water velocity. In the experiments, water velocities were measured adjacent to bubbler plumes for depths ranging from 0.52?to?6.5?m and airflow rates ranging from 0.015?to?0.68 standard cubic meters per minute/meter. The observed vertical and horizontal water velocity data compared moderately well to theoretical curves based on the equations of Kobus and Ashton. In addition, a reasonably linear relationship was found between the average velocity of the horizontal, near-surface flow field V and unit airflow from the diffuser Qa.     

Methods for the determination of pH value and redox potential in the rumen fluid of adult cattle

pH sticks and pH meters were tested to determine ruminal pH and mV meters in order to measure the redox potential in rumen contents. Rumen pH can be determined by reading pH sticks left in rumen liquor or immediately after removal. Differences between pH sticks and a reference method accounted for 0.01-0.48 pH units, depending on the pH stick used and the pH range of the ruminal contents (pH < 6, 6-7, > 7). Ruminal pH is accurately measured by the pH meters pHep and GPHR (y = -0.22 + 1.03x, or y = 0.15 + 0.97 x). By using a mV meter the redox potential in rumen liquor can be determined 10 min after start of measurement. Results determined with the mV meter GPHR showed a mean difference of 10-23 mV, those determined with ORP a mean difference of 131-202 mV in comparison with a reference method. There is no linear correlation between the data of the mV measurements and the data of the methylene blue reduction test in ruminal contents (y = -328.5 - 0.003 x; p = 0.652). Therefore these data may not be in used in the same manner for rumen liquor diagnosis.     

Pitot-Static Tube System to Measure Discharges from Wells

Pumps are widely used to lift water into canals, and usually spill directly into the canal. Upstream pipe fittings frequently produce a distorted flow profile that is detrimental to the proper installation and operation of common pipe meters. Thus, meter calibration may be necessary when the pipe length upstream of the meter is less than recommended. Meter calibrations under field conditions can be difficult and expensive. A simple pitot tube system that can be clamped to the outlet of the pump discharge pipe was built and tested for measuring and calibrating pump discharges under field conditions. It is used to detect the velocity at several points across the pipe diameter; distorted profiles can be measured. Using this information, the meter technician can determine whether a correction in the meter coefficient will suffice and if flow conditioning equipment is working effectively. The system can be constructed using common shop techniques and standard small pipe fittings. Most previous pitot systems required special ports in the pipe or used special concentric tube constructions that are difficult to build.     

Convection Velocity of Vortex Structures in the Near Wake of a Circular Cylinder

The convection velocity of vortex structures in the near wake of a circular cylinder was experimentally investigated over the region 1.6–2.5 ? x/D ? 12.0 for R = 160–12,000. Dye injection technique of flow visualization and two completely noninvasive laser Doppler velocimeters were employed for R ? 320 and ?400, respectively. The convection velocity, Uc, is defined as the mean traveling velocity of vortex cores passing a streamwise separation during a mean elapsed time. For R ? 320, Uc was determined directly from the motion of dye-marked vortex cores filmed by a video camera. In the cases of R ≥ 400, the positions of peak vorticity and half of the half-velocity-defect width at each downstream section were first used to identify the mean path of vortex cores (i.e., the most probable trajectory of the vortex structures), along which spatial correlation measurements were then performed to determine the mean elapsed time corresponding to the maximum cross correlation. The present results show that, in laminar and transitional wakes, the ratio Uc/Uo increases from 0.53 to 0.84 over a region of 1.6 ? x/D ? 6.0 and then tends to be a constant of 0.84 for x/D ≥ 6.0. In a turbulent wake, Uc/Uo also increases from a certain value at a point downstream from the position of vortex formation to a mean value of about 0.86 at x/D ≥ 5.0–6.0, and then changes little with the increase of x/D. In addition, it is found that the dependence of Uc/Uo on R almost disappears for x/D ≥ 5.0.     

方坯结晶器铜管锥度的测量与分析

铜管锥度有两种表示方法,一是每米长度上的锥度,二是铜管上下口两相对面的尺寸偏差。采用电子锥度测量仪和百分表对实际铜管锥度的测量表明,因制作精度差,铜管长度方向存在负锥度和锥度不变以及弯月面处的锥度变化不合理问题。分析认为,生产螺纹钢时,弯月面处的锥度应不低于0．7％／m;生产低碳包晶钢时,弯月面锥度应不低于0．9％／m。     

Evaluation of an Experimental LiDAR for Surveying a Shallow, Braided, Sand-Bedded River

Reaches of a shallow (<1.0?m), braided, sand-bedded river were surveyed in 2002 and 2005 with the National Aeronautics and Space Administration’s Experimental Advanced Airborne Research LiDAR (EAARL) and concurrently with conventional survey-grade, real-time kinematic, global positioning system technology. The laser pulses transmitted by the EAARL instrument and the return backscatter waveforms from exposed sand and submerged sand targets in the river were completely digitized and stored for postflight processing. The vertical mapping accuracy of the EAARL was evaluated by comparing the ellipsoidal heights computed from ranging measurements made using an EAARL terrestrial algorithm to nearby (<0.5?m apart) ground-truth ellipsoidal heights. After correcting for apparent systematic bias in the surveys, the root mean square error of these heights with the terrestrial algorithm in the 2002 survey was 0.11?m for the 26 measurements taken on exposed sand and 0.18?m for the 59 measurements taken on submerged sand. In the 2005 survey, the root mean square error was 0.18?m for 92 measurements taken on exposed sand and 0.24?m for 434 measurements on submerged sand. In submerged areas the waveforms were complicated by reflections from the surface, water column entrained turbidity, and potentially the riverbed. When applied to these waveforms, especially in depths greater than 0.4?m, the terrestrial algorithm calculated the range above the riverbed. A bathymetric algorithm has been developed to approximate the position of the riverbed in these convolved waveforms and preliminary results are encouraging.     

Depth-Averaged Velocity Distribution in Straight Trapezoidal Channels

In trapezoidal channels that are not “wide,” the banks exert form drag on the fluid and thereby control the depth-averaged velocity distribution. As such, commonly used equations for predicting depth-averaged velocities in wide channels are not well suited for predicting depth-averaged velocities in trapezoidal channels. Using data from three previous studies, we developed two models for predicting depth-averaged velocity distributions in straight trapezoidal channels. The data used to develop the models had a range of discharges (8.05–4,248?L/s), velocities (0.16–1.03?m/s), bottom widths (0.305–3.62?m), flow depths (0.0518–0.805?m), and bank slopes (1.0–3.0, horizontal/vertical). The first model requires measured velocity data for calibrating the model coefficients, whereas the second model uses prescribed coefficients. The first model yielded velocity distributions with coefficients of determination (r2) from 0.84 to 0.90 and we recommend its use when possible because it yields predictions that are more accurate. The second model also yielded good results (r2 = 0.86 and 94% of the predicted velocities were within 20% of the observed values).     

Conditional Assessment of Flow Measurement Accuracy

A study conducted by the Utah Water Research Laboratory assessed the accuracies of a wide variety of flow measurement devices currently in service. During the study, a wide variety of flow measurement devices, including flumes, weirs, and rated sections in open channel systems, were evaluated; magnetic and ultrasonic meters in closed-conduit systems were also tested. The specified design accuracies for each device are presented. Actual flow measurements were determined at 70 sites and were compared with the theoretical discharges of each device. Comparison of actual and theoretical flow indicates that only 33% of the measurement devices tested currently measure flow within manufacturer-designed specifications. Field data is presented, and possible reasons for the flow measurement errors and their corrections are discussed.     

Downstream Hydraulic Geometry of Alluvial Channels

This study extends the earlier contribution of Julien and Wargadalam in 1995. A larger database for the downstream hydraulic geometry of alluvial channels is examined through a nonlinear regression analysis. The database consists of a total of 1,485 measurements, 1,125 of which describe field data used for model calibration. The remaining 360 field and laboratory measurements are used for validation. The data used for validation include sand-bed, gravel-bed, and cobble-bed streams with meandering to braided planform geometry. The five parameters describing downstream hydraulic geometry are: channel width W, average flow depth h, mean flow velocity V, Shields parameter τ*, and channel slope S. The three independent variables are discharge Q, median bed particle diameter ds, and either channel slope S or Shields parameter τ* for dominant discharge conditions. The regression equations were tested for channel width ranging from 0.2 to 1,100?m, flow depth from 0.01 to 16?m, flow velocity from 0.02 to 7?m/s, channel slope from 0.0001 to 0.08, and Shields parameter from 0.001 to 35. The exponents of the proposed equations are comparable to those of Julien and Wargadalam (1995), but based on R2 values of the validation analysis, the proposed regression equations perform slightly better.     

Dissipation of Turbulent Kinetic Energy near a Bubble Plume

Profiles of the rate of dissipation of turbulent kinetic energy were inferred from temperature microstructure measurements near a bubble plume at the center of a tank with diameter of 13.7 m and maximum depth of 8.3 m. Six sets of between 18 and 51 profiles were collected at airflow rates of 0.1–0.6 L/s, measured at atmospheric pressure, and ensemble-averaged dissipation profiles were calculated. The dissipation in all cases was between 10?8 and 10?6?m2/s3 in most of the profile, but it increased sharply near the water surface. Energy considerations are used to discuss the experimental results in terms of previous numerical models of bubble plume turbulence. Two previous numerical studies show that the turbulence dissipates between 15 and 30% of the available power. In the experiments, the fraction is less than 1% because some of the energy of the plume is used to generate waves on the water surface and the profiles used to compute the volume-averaged dissipation were relatively far from the bubble plume.