Applying adaptive LS-PIV with dynamically adjusting detection region approach on the surface velocity measurement of river flow

2019 ◽  
Vol 74 ◽  
pp. 466-482 ◽  
Author(s):  
Ming-Tsung Yeh ◽  
Yi-Nung Chung ◽  
Yu-Xian Huang ◽  
Chien-Wen Lai ◽  
Deng-Jyi Juang
2013 ◽  
Vol 10 (7) ◽  
pp. 9967-9997 ◽  
Author(s):  
A. Kääb ◽  
M. Lamare ◽  
M. Abrams

Abstract. Knowledge of water-surface velocities in rivers is useful for understanding a range of river processes. In cold regions, river-ice break up and the related downstream transport of ice debris is often the most important hydrological event of the year, leading to flood levels that typically exceed those for the open-water period and to strong consequences for river infrastructure and ecology. Accurate and complete surface-velocity fields on rivers have rarely been produced. Here, we track river ice debris over a time period of about one minute, which is the typical time lag between the two or more images that form a stereo data set in spaceborne, along-track optical stereo-mapping. Using a series of 9 stereo scenes from the US/Japanese Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) onboard the NASA Terra spacecraft with 15 m image resolution, we measure the ice and water velocity field over a 620 km long reach of the lower Lena River, Siberia, just above its entry into the Lena delta. Careful analysis and correction of higher-order image and sensor errors enables an accuracy of ice-debris velocities of up to 0.04 m s−1 from the ASTER data. Maximum ice or water speeds, respectively, reach up to 2.5 m s−1 at the time of data acquisition, 27 May 2011 (03:30 UTC). Speeds show clear along-stream undulations with a wavelength of about 21 km that agree well with variations in channel width and with the location of sand bars along the river reach studied. The methodology and results of this study could be valuable to a number of disciplines requiring detailed information about river flow, such as hydraulics, hydrology, river ecology and natural-hazard management.


2013 ◽  
Vol 17 (11) ◽  
pp. 4671-4683 ◽  
Author(s):  
A. Kääb ◽  
M. Lamare ◽  
M. Abrams

Abstract. Knowledge of water-surface velocities in rivers is useful for understanding a range of river processes. In cold regions, river-ice break up and the related downstream transport of ice debris is often the most important hydrological event of the year, leading to flood levels that typically exceed those for the open-water period and to strong consequences for river infrastructure and ecology. Accurate and complete surface-velocity fields on rivers have rarely been produced. Here, we track river ice debris over a time period of about one minute, which is the typical time lag between the two or more images that form a stereo data set in spaceborne, along-track optical stereo mapping. Using a series of nine stereo scenes from the US/Japanese Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) onboard the NASA Terra spacecraft with 15 m image resolution, we measure the ice and water velocity field over a 620 km-long reach of the lower Lena River, Siberia, just above its entry into the Lena delta. Careful analysis and correction of higher-order image and sensor errors enables an accuracy of ice-debris velocities of up to 0.04 m s−1 from the ASTER data. Maximum ice or water speeds, respectively, reach up to 2.5 m s−1 at the time of data acquisition, 27 May 2011 (03:30 UTC). Speeds show clear along-stream undulations with a wavelength of about 21 km that agree well with variations in channel width and with the location of sand bars along the river reach studied. The methodology and results of this study could be valuable to a number of disciplines requiring detailed information about river flow, such as hydraulics, hydrology, river ecology and natural-hazard management.


2008 ◽  
Vol 123 (5) ◽  
pp. 3288-3288
Author(s):  
Patrick F. O'Malley ◽  
Woods J. Teresa ◽  
Joseph F. Vignola ◽  
John A. Judge ◽  
Jacek Jarzynski

2021 ◽  
Author(s):  
Guillaume Bodart ◽  
Jérôme Le Coz ◽  
Magali Jodeau ◽  
Alexandre Hauet

<p>Several studies have been carried out to evaluate image-based solutions for velocity measurement and discharge determination in river. However, these studies are limited because it is difficult to know the reference surface velocity field accurately. These data are usually extrapolated from measurement within the water column or integrated over a cross-section to determine the discharge to be compared with a reference, which is uncertain itself. Measurement uncertainties are difficult to quantify and cannot be neglected usually.</p><p>The only solution that arises to get a flow with a known surface velocity reference is synthetic imaging: we generate artificial images on which particles movements are known everywhere. However, these generators must allow a comparison between simulations and measurements for a wide range of conditions representative of the situations observed in the natural environment. Several Synthetic Image Generators have been designed for laboratory PIV but the generated images are made of white particles moving on a dark background. Such images are not representative of river applications with turbulence figures, foam, debris, sunlight effects but also some homogeneous areas with poor contrast where we can sometimes see the river bed through.</p><p>We propose a novel method to generate images from a synthetic river scene with accurate surface velocity references. It is based on the 3D computer graphics tool Blender which integrates a dedicated fluid simulation tool, Mantaflow. Blender allows many different configurations by playing on the modeling of the river, the surrounding objects, the textures and optical properties of the materials but also on the lighting and the camera settings and position. Mantaflow is then used to model and extract the characteristics (velocities, positions in time) of a flow that looks similar to real-life situations. The first synthetic videos obtained were used to study the sensitivity of the velocity results to the image-based velocimetry algorithm, its parameters and user choices.</p>


2021 ◽  
pp. 127240
Author(s):  
Kailin Huang ◽  
Hua Chen ◽  
Tianyuan Xiang ◽  
Yunfa Lin ◽  
Bingyi Liu ◽  
...  

2000 ◽  
Vol 2000.6 (0) ◽  
pp. 163-164
Author(s):  
Takahiro KONDOH ◽  
Masaki YUKAWA ◽  
Koichi NISHINO ◽  
Kahoru TORII

2020 ◽  
Author(s):  
Salvador Peña-Haro ◽  
Beat Lüthi ◽  
Robert Lukes ◽  
Maxence Carrel

<p>Image-based methods for measuring surface flow velocities in rivers have several advantages, one of them being that the sensor (camera) is not in contact with the water and its mounting position is very flexible hence there is no need of expensive structures to mount it. Additionally, it is possible to measure the whole river width. On the other hand, environmental factors, like wind, can affect the surface velocity and the have an impact on the accuracy of the measurements.</p><p><span>Herein we present an analysis of the wind effect on </span><span>the image based surface velocity at </span><span>Rhine river</span><span>, at the border between Switzerland and Austria. At this location the river width is of approximately 100 meters under low flow conditions, while the width of its floodplain is of about 200 m. </span><span>A</span><span>n</span> <span>ATMOS 22 ultrasonic anemometer </span><span>was installed </span><span>at the site to measure the wind </span><span>intensity</span><span> as well as </span><span>its</span><span> direction. </span></p><p><span>A time series of flow velocities and wind </span><span>from May to October 2019 </span><span>was analyzed. During this period, the </span><span>average disch</span><span>a</span><span>rge </span><span>was </span><span>320 m</span><sup><span>3</span></sup><span>/s and the average </span><span>flow </span><span>velocity 1.7 m/s. While the average wind velocity was of </span><span>2</span><span>.</span><span>3</span><span>m/s which roughly follows the same direction of the river flow.</span></p><p>A rating curve following a power law function was fitted to the image based surface flow measurements. It was found that for maximum wind speeds of 10 m/s, blowing in the opposite direction of the river flow, there was a deviation of 8%. For the average wind speed of 2.3m/s, the deviation was found to be 3%.</p>


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