Direct measurement of turbulence properties by a BB-ADCP in bottom boundary layer
No abstract available.
California↗
Geology topics
C. #NAME? Ling
Publications and source records attributed to C. #NAME? Ling.
Estimates of bottom roughness length and bottom shear stress in South San Francisco Bay, California
A field investigation of the hydrodynamics and the resuspension and transport of particulate matter in a bottom boundary layer was carried out in South San Francisco Bay (South Bay), California, during March-April 1995. Using broadband acoustic Doppler current profilers, detailed measurements of turbulent mean velocity distribution within 1.5 m above bed have been obtained. A global method of data analysis was used for estimating bottom roughness length z o and bottom shear stress (or friction velocities u * ). Field data have been examined by dividing the time series of velocity profiles into 24-hour periods and independently analyzing the velocity profile time series by flooding and ebbing periods. The global method of solution gives consistent properties of bottom roughness length z o and bottom shear stress values (or friction velocities u * ) in South Bay. Estimated mean values of z o and u * for flooding and ebbing cycles are different. The differences in mean z o and u * are shown to be caused by tidal current flood-ebb inequality, rather than the flooding or ebbing of tidal currents. The bed shear stress correlates well with a reference velocity; the slope of the correlation defines a drag coefficient. Forty-three days of field data in South Bay show two regimes of z o (and drag coefficient) as a function of a reference velocity. When the mean velocity is >25–30 cm s −1 , the ln z o (and thus the drag coefficient) is inversely proportional to the reference velocity. The cause for the reduction of roughness length is hypothesized as sediment erosion due to intensifying tidal currents thereby reducing bed roughness. When the mean velocity is <25–30 cm s −1 , the correlation between z o and the reference velocity is less clear. A plausible explanation of scattered values of z o under this condition may be sediment deposition. Measured sediment data were inadequate to support this hypothesis, but the proposed hypothesis warrants further field investigation.
Journal of Geophysical Research C: Oceans↗
Granular-flow rheology: Role of shear-rate number in transition regime
This paper examines the rationale behind the semiempirical formulation of a generalized viscoplastic fluid (GVF) model in the light of the Reiner-Rivlin constitutive theory and the viscoplastic theory, thereby identifying the parameters that control the rheology of granular flow. The shear-rate number ( N ) proves to be among the most significant parameters identified from the GVF model. As N → 0 and N →∞, the GVF model can reduce asymptotically to the theoretical stress versus shear-rate relations in the macroviscous and grain-inertia regimes, respectively, where the grain concentration ( C ) also plays a major role in the rheology of granular flow. Using available data obtained from the rotating-cylinder experiments of neutrally buoyant solid spheres dispersing in an interstitial fluid, the shear stress for granular flow in transition between the two regimes proves dependent on N and C in addition to some material constants, such as the coefficient of restitution. The insufficiency of data on rotating-cylinder experiments cannot presently allow the GVF model to predict how a granular flow may behave in the entire range of N ; however, the analyzed data provide an insight on the interrelation among the relevant dimensionless parameters.
Journal of Engineering Mechanics↗
Mesoscale variability of the Upper Colorado River snowpack
In the mountainous regions of the Upper Colorado River Basin, snow course observations give local measurements of snow water equivalent, which can be used to estimate regional averages of snow conditions. We develop a statistical technique to estimate the mesoscale average snow accumulation, using 8 years of snow course observations. For each of three major snow accumulation regions in the Upper Colorado River Basin – the Colorado Rocky Mountains, Colorado, the Uinta Mountains, Utah, and the Wind River Range, Wyoming – the snow course observations yield a correlation length scale of 38 km, 46 km, and 116 km respectively. This is the scale for which the snow course data at different sites are correlated with 70 per cent correlation. This correlation of snow accumulation over large distances allows for the estimation of the snow water equivalent on a mesoscale basis. With the snow course data binned into 1/4° latitude by 1/4° longitude pixels, an error analysis shows the following: for no snow course data in a given pixel, the uncertainty in the water equivalent estimate reaches 50 cm; that is, the climatological variability. However, as the number of snow courses in a pixel increases the uncertainty decreases, and approaches 5-10 cm when there are five snow courses in a pixel.
Colorado, Utah, Wyoming↗