Testing a handheld radar to measure water velocity at the surface of channels

Tamari, Serge; García, Florian; Arciniega-Ambrocio, J.-I.; Porter, Aaron

doi:10.1051/lhb/2014026

Cited by 9 publications

(9 citation statements)

References 13 publications

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“…Projection error can be estimated using a formulation similar to that proposed by Tamari et al . []. Deployment from very high bridges and/or a low tilt angle result in large distances between the antenna and the target, which, in turn, produce large illuminated areas and a weaker return signal.…”

Section: Discussionmentioning

confidence: 99%

“…In the present study we report on a large set of tests of application of the Surface Velocity Radar for velocity gauging in a wide range of riverine contexts. To the authors’ knowledge, only few field‐scale tests of hand‐held radar velocimeters have been published [ Tamari et al ., ], but no attempt has been made to systematically evaluate the uncertainty of SVR‐based discharge estimates. Discharge was often derived from a single surface velocity measurement [Corato et al, ; Fulton and Ostrowski, ] using a probability distribution function [ Chen and Chiu , ].…”

Section: Introductionmentioning

confidence: 99%

“…Tamari et al . [] used an SVR to reconstruct the transverse distribution of surface velocity at laboratory and field scale, but no discharge estimation was derived from these gaugings. In addition, the present study provides examples of SVR use in small channels, where high roughness conditions can affect the accuracy of discharge values computed with velocity‐area methods.…”

Section: Introductionmentioning

confidence: 99%

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Field assessment of noncontact stream gauging using portable surface velocity radars (SVR)

Welber

Coz²,

Laronne

et al. 2016

Water Resources Research

105

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The applicability of a portable, commercially available surface velocity radar (SVR) for noncontact stream gauging was evaluated through a series of field-scale experiments carried out in a variety of sites and deployment conditions. Comparisons with various concurrent techniques showed acceptable agreement with velocity profiles, with larger uncertainties close to the banks. In addition to discharge error sources shared with intrusive velocity-area techniques, SVR discharge estimates are affected by floodinduced changes in the bed profile and by the selection of a depth-averaged to surface velocity ratio, or velocity coefficient (a). Cross-sectional averaged velocity coefficients showed smaller fluctuations and closer agreement with theoretical values than those computed on individual verticals, especially in channels with high relative roughness. Our findings confirm that a 5 0.85 is a valid default value, with a preferred sitespecific calibration to avoid underestimation of discharge in very smooth channels (relative roughness $ 0.001) and overestimation in very rough channels (relative roughness > 0.05). Theoretically derived and site-calibrated values of a also give accurate SVR-based discharge estimates (within 10%) for low and intermediate roughness flows (relative roughness 0.001 to 0.05). Moreover, discharge uncertainty does not exceed 10% even for a limited number of SVR positions along the cross section (particularly advantageous to gauge unsteady flood flows and very large floods), thereby extending the range of validity of rating curves.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Field assessment of noncontact stream gauging using portable surface velocity radars (SVR)

Welber

Coz²,

Laronne

et al. 2016

Water Resources Research

105

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“…Melcher et al [4] indicated that the United States Geological Survey and the University of Washington collaborated in a series of initial experiments on the Lewis, Toutle, and Cowlitz Rivers during September 2000 and in a detailed experiment on the Cowlitz River during May 2001 for determining the feasibility of using helicopter-mounted radars for measuring the river discharge (surface velocities were measured using a pulsed Doppler radar). Tamari et al [10] tested a handheld radar to measure the water velocity at the surface of the channels, while Kim et al [11] analyzed the error in the electromagnetic surface velocity and discharge measurement in a rapid mountain stream flow. Therefore, rapid and effective processing, and the method used for analyzing the surface current meter signals, are key issues.…”

Section: Literature Reviewmentioning

confidence: 99%

Micro Radar Surface Velocimetry for Hydrologic Signal Processing Using a Bandpass Filtering Approach

Huang

Hsu

2016

Water

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Abstract:The collection of hydrological data is particularly important for the utilization and management of water resources, water conservation, and flood control. Most of the hydrological observation operations should be conducted manually and are time-consuming, strenuous, dangerous, and have low precision. In this study, the shortcomings of the manual observations are overcome and the uncertainties related to the radar-based flow velocity estimations by a sensor in the radar surface current meter are explored. This includes an automatic observation feature and analyses are conducted using the radar signals that are received by the instruments for the real-time observation of the signals. In this study, experiments were conducted at the Water Resources Planning Institute (WRPI) of the Water Resources Agency, Ministry of Economic Affairs, Taiwan and the surface velocity was estimated using the conventional fast Fourier transform (FFT), wavelet transform (WT), and a bandpass filter. The experimental results after signal processing using the bandpass filter were precise, when the tilt angle ranged between 20 and 40 degrees. The 10.525 GHz radar surface current meter adopted in this study is suitable for a tilt angle of 20-40 degrees; the measurement error will be relatively large if the tilt angle is less than 20 degrees or more than 40 degrees.

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“…Another is microwave Radar (active remote sensing), which detects roughness at the water surface (due to the "Bragg resonance" phenomenon, which will certainly occur during a flood) [13,14]. Nevertheless, there is still a need to better understand how a Radar responds to the roughness produced by the underlying current (something different than the roughness produced by the wind, which is well known) [15]. As an alternative, this study focuses on the "inclined Lidar" technique [16], which works only when water is very turbid: a situation likely to happen during flash floods (e.g., [2]), as discussed more in detail at the end of the study.…”

Section: Introductionmentioning

confidence: 99%

Flash Flood Monitoring with an Inclined Lidar Installed at a River Bank: Proof of Concept

Tamari

Guerrero-Meza²

2016

Remote Sensing

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Flash floods need to be monitored from a safe place, ideally with noncontact instruments installed at a riverbank and oriented so that they look obliquely at the water surface. The “inclined Lidar” technique could be useful for this purpose. It works based on the fact that a near-infrared Lidar mounted with a large incidence angle can detect suspended particles slightly below the surface, provided that the water is very turbid, something which is likely during flash floods. To check this hypothesis, an inexpensive “time of flight” (TOF) Lidar was installed during a rainy season at the Amacuzac River (Mexico), which was usually found to be extremely turbid (Secchi depth < 0.5 m). Under these circumstances, the Lidar had no difficulty detecting the water (sub) surface. Converting the measured distances into stage estimates through a simple (one point) calibration resulted in reasonable agreement with reference data (within ±0.08 m (p = 0.95) and always <0.5 m), especially during the passing of a flash flood. This is the first evidence that an inclined (TOF) Lidar can be used to monitor the stage during a flash flood. Indirectly, it also shows that a (Doppler) Lidar could be used to monitor water velocity during this type of event.

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Testing a handheld radar to measure water velocity at the surface of channels

Cited by 9 publications

References 13 publications

Field assessment of noncontact stream gauging using portable surface velocity radars (SVR)

Field assessment of noncontact stream gauging using portable surface velocity radars (SVR)

Micro Radar Surface Velocimetry for Hydrologic Signal Processing Using a Bandpass Filtering Approach

Flash Flood Monitoring with an Inclined Lidar Installed at a River Bank: Proof of Concept

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