Institute: New York
USGS Grant Number: G12AP20155
Year Established: 2012 Start Date: 2012-09-01 End Date: 2014-08-21
Total Federal Funds: $91,894 Total Non-Federal Funds: $91,935
Principal Investigators: Edwin Cowen
Abstract: It is proposed to use remotely imaged water surface patterns to deliver non-contact near-real-time measurements of surface velocity, bathymetry (depth), and discharge to address a national need for non-contact discharge monitoring in river systems with both relatively stable and highly dynamic channel cross-sections. Traditional methods of measuring discharge are relatively expensive and often require field technicians to work in hazardous conditions. Additionally, for high flow conditions, during which the bathymetry changes widely, the use of extrapolated rating curves can result in errors of up to 70%. The proposed non-contact discharge monitoring approach will reduce stream-gaging costs at the same, or potentially better accuracy as current methods, while reducing hazards associated with traditional methods. There have been several previous attempts, including those of the Hydro-21 task committee commissioned by the USGS, to utilize remote sensing technologies, such as radar and quantitative imaging (QI) techniques, for stream gaging. These techniques are sufficient to accurately characterize the surface velocity field, however, each of these previous remote sensing efforts have relied on alternative technologies, such as acoustic Doppler current profilers or ground-penetrating radars, to determine bathymetry. It is proposed to leverage QI measured metrics of the surface turbulence to determine bathymetry, which coupled with the mean surface velocity field, will yield a truly non-contact method for the determination of discharge. It is hypothesized, based on previous research, that a strong correlation exists between the surface integral length scale, the length scale that represents the energy containing eddy size of the surface turbulence, and the flow depth. This correlation is demonstrated in a preliminary experiment using surface particle image velocimetry (PIV) in a fully developed flow in a wide-open channel flume. Preliminary measurements demonstrate that the local streamwise averaged surface velocity, , is related to the depth-averaged velocity, , by the simple relation . Instantaneous 2-D PIV velocity fields are used to calculate the autocorrelation function of the surface turbulence, which is integrated to determine the surface integral length scale. Preliminary measurements reveal that for a flow depth of 15.7 cm the surface eddy length scale is approximately 5 cm, or about 30% of the flow depth. Accurate determination of flow depth and depth-averaged velocity yields an estimate of the discharge. The correlation between the surface fluid velocity and depth-averaged velocity and the surface integral length scale and the flow depth will be systematically studied over a wide range of flow conditions to fully understand the hypothesis and develop appropriate parameterizations. Laboratory experiments using surface PIV will be carried out varying the flow depth, bed roughness, bed shape, and flow speed, providing data across a wide range of Reynolds and Froude numbers, aspect ratios, and bed roughnesses. These experiments will be the focus of the first year. To demonstrate the feasibility of the proposed approach, field experiments will be conducted in collaboration with the USGS New York Water Science Center Ithaca Office at two local gauged river sites throughout year two over a broad range of flow conditions. The proposed project will lead to a Ph.D. for a talented young woman. Working with the PI they will recruit one or more undergraduate researchers, with an emphasis on URM candidates, to help with the research, as well as host a project for the CURIE Academy, a one-week Cornell summer residential program for high school girls who excel in math and science. The current state of the economy has resulted in several stream-gaging stations being closed across the country. However, as urban areas continue to grow and as the climate continues to change, demand for stream-gaging services will increase. It is therefore imperative that a method be developed for stream-gaging that is safe, efficient, accurate and less costly then currently available technology.