Continuous, High Resolution Direct Measurement of Instantaneous Velocity and Turbulence Metrics At The Surface of Rivers Used To Estimate Bathymetry and Discharge.
Abstract
We present a field scale, imagery-based method that measures mean and instantaneous velocity at the surface of rivers with high accuracy and high temporal (>1Hz) and spatial (order 1 cm) resolution. The measurements are performed simultaneously over a large spatial area (up to hundreds of m2). Instantaneous velocity measurements are used to calculate metrics of turbulence at the water surface, from which local bathymetry is estimated. This allows estimating discharge from a single non-contact measurement.
This high accuracy Infrared Quantitative Image Velocimetry (IR-QIV) technique uses mid-wavelength infrared (MWIR) imagery, which provides high thermal resolution (<20mK). Images are georeferenced to provide high spatial accuracy, and hence highly accurate instantaneous velocity measurements. This represents a significant step forward from traditional velocity measurement methods such as ADCPs, ADVs, and visible-light LSPIV since it allows measurement of instantaneous velocity over a large two-dimensional area. Experiments in a tidally forced river (Sacramento River, California, USA) showed extremely good agreement between velocity measurements using this method and acoustic velocity measurements (e.g., RMSE of approximately 0.01 m/s between velocity measured by ADCP and IR-QIV over a period of greater than 12 hours in a tidally-forced system with a wide range of hydrodynamic conditions, including flow reversal and mean velocity greater than 0.4 m/s). The images can be collected from a fixed platform such as a bridge or from an aerial platform such as an UAV. This IR-QIV method has significant advantages over other velocity measurement methods as it is capable of measuring instantaneous velocity (and hence turbulence metrics) over a large, two-dimensional area. This represents a major step forward as the additional spatial information informs better understanding of eco-hydrological processes, such as the impact of flow conditions on navigational decisions of migrating fish, and improved capability for computational model verification near complex hydrodynamic features where accurate velocity measurements with other methods are difficult.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFM.H43N2262S
- Keywords:
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- 1855 Remote sensing;
- HYDROLOGY