Bathymetric and velocimetric surveys at highway bridges crossing the Missouri River near Kansas City, Missouri, June 2–4, 2015

Huizinga, Richard J.

doi:10.3133/sir20165061

Cited by 11 publications

(7 citation statements)

References 5 publications

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“…Sediment and water discharge conditions vary continuously in natural rivers causing bed morphology to be out of equilibrium with prevailing flow conditions. Numerous field studies suggest that bedform disequilibrium is likely a standard phenomenon in natural river systems (e.g., Frings and Kleinhans, 2008;Julien et al, 2002;Wilbers and Ten Brinke, 2003;Ten Brinke et al, 1999). Even with these complications, bed-load flux estimated from translating dunes remains one of the most accurate bed-load estimate techniques for sand-bedded rivers (Nittrouer et al, 2008;Wilbers and Ten Brinke, 2003;Holmes and Holmes, 2010) and as such bed elevation measurements are of great importance.…”

Section: Introductionmentioning

confidence: 99%

“…Lastly, multiple single-beam surveys measure a spatially limited three-dimensional bed, η(x, y, t), at a few (x, y) locations using stationary sonar. All three sampling methodologies have been and are currently employed to collect bed elevation data in experimental (Blom et al, 2003;van der Mark et al, 2008;Guala et al, 2014;Curran et al, 2015), natural fluvial (Simons et al, 1965;Ten Brinke et al, 1999;Ashworth et al, 2000;Julien et al, 2002;Parsons et al, 2005;Gaeuman and Jacobson, 2007;Nittrouer et al, 2008;Claude et al, 2012;Shugar et al, 2010;Rodrigues et al, 2015;Wintenberger et al, 2015;Huizinga, 2016;Kaplinski et al, 2017;Buscombe et al, 2017;Hackney et al, 2018), and estuarine/coastal environments (Villard and Church, 2003;Hoekstra et al, 2004;Schmitt and Mitchell, 2014).…”

Section: Introductionmentioning

confidence: 99%

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Estimating sand bed load in rivers by tracking dunes: a comparison of methods based on bed elevation time series

Leary

Buscombe

2020

Earth Surf. Dynam.

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Abstract. Quantifying bed-load transport is paramount to the effective management of rivers with sand or gravel-dominated bed material. However, a practical and scalable field methodology for reliably estimating bed load remains elusive. A popular approach involves calculating transport from the geometry and celerity of migrating bedforms, extracted from time series of bed elevation profiles (BEPs) acquired using echo sounders. There are various echo sounder sampling methodologies to extract bed elevation profiles. Using two sets of repeat multibeam sonar surveys with high spatiotemporal resolution and coverage, we compute bed load using three field techniques (one actual and two simulated) for acquiring BEPs: repeat multibeam, single-beam, and multiple single-beam sonar. Significant differences in flux arise between repeat multibeam and single-beam sonar. Multibeam and multiple single-beam sonar systems can potentially yield comparable results, but the latter relies on knowledge of bedform geometries and flow that collectively inform optimal beam spacing and sampling rate. These results serve as a guide for design of optimal sampling and for comparing transport estimates from different sonar configurations.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Estimating sand bed load in rivers by tracking dunes: a comparison of methods based on bed elevation time series

Leary

Buscombe

2020

Earth Surf. Dynam.

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“…Lastly, multiple single-beam measures a spatially limited three-dimensional bed, η(x, y, t), at a few (x, y) locations using stationary sonar. All three sampling methodologies have been and are currently employed to collect bed elevation data in experimental (Blom et al, 2003;Van der Mark et al, 2008;Guala et al, 2014;Curran et al, 2015), fluvial (Simons et al, 1965;Ten Brinke et al, 1999;Ashworth et al, 2000;Julien et al, 2002;Parsons et al, 2005;Gaeuman and Jacobson, 2007;Nittrouer et al, 2008;Claude et al, 2012;Shugar et al, 2010;Rodrigues et al, 2015;Wintenberger et al, 2015;Huizinga, 2016;Kaplinski et al, 2017;Buscombe et al, 2017;Hackney et al, 2018), and estuarine/coastal environments (Villard and Church, 2003;Hoekstra et al, 2004;Schmitt and Mitchell, 2014).…”

Section: Introductionmentioning

confidence: 99%

Estimating Sand Bedload in Rivers by Tracking Dunes: a comparison of methods based on bed elevation time-series

Leary¹,

Buscombe²

2019

Preprint

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Abstract. Quantifying bedload transport is paramount to the effective management of rivers with sand or gravel-dominated bed material. However, a practical and scalable field methodology for reliably estimating bedload remains elusive. A popular approach involves calculating transport from the geometry and celerity of migrating bedforms, extracted from time-series of bed elevation profiles acquired using echosounders. Various echosounder sampling methodologies of how to extract bed elevations profiles exist. Using two sets of repeat multibeam sonar surveys with large spatio-temporal resolution and coverage, we compute bedload using three field techniques (one actual and two simulated) for acquiring bed elevation profiles: repeat multi-, single-, and multiple single-beam sonar. Significant differences in flux arise between repeat multibeam and single beam sonar. Mulitbeam and multiple single beam sonar systems can potentially yield comparable results, but the latter relies on knowledge of bedform geometries and flow that collectively inform optimal beam spacing and sampling rate. These results serve to guide design of optimal sampling, and for comparing transport estimates from different sonar configurations.

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“…To accurately map the depth measurements in space, multibeam echosounders are used with an inertial navigation system (INS) to measure the heave, pitch, roll, heading, and position of the echosounder. Multibeam echosounders and examples of their use for surveying rivers and lakes are described in Huizinga (2016) and Huizinga and Heimann (2018). The MB2 echosounder data were displayed and recorded using Teledyne PDS software (Teledyne PDS, 2019, 2021a, b) version 4.1.5.3 in 2017and version 4.3.0.1 in 2018and 2019.…”

Section: Multibeam Echosoundermentioning

confidence: 99%

Bathymetry of New York City’s East of Hudson reservoirs and controlled lakes, 2017 to 2019

Nystrom¹,

Huston²,

Welk³

2021

Scientific Investigations Report

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New York City maintains an extensive system of reservoirs and aqueducts to provide drinking water to its residents, including 16 reservoirs and controlled lakes in Westchester and Putnam Counties in southern New York, east of the Hudson River (also called "East of Hudson reservoirs and controlled lakes"). These reservoirs were put into service from 1842 to 1915, and their capacities have likely changed since their original construction. To provide updated bathymetric surface, contour, and capacity data, the U.S. Geological Survey, in cooperation with New York City Department of Environmental Protection, surveyed the bathymetry of the 16 East of Hudson reservoirs and controlled lakes from 2017 to 2019 using a multibeam echosounder. The points measured with the multibeam echosounder were combined with light detection and ranging data to generate 3.28-foot raster grids of the bathymetric surfaces, bathymetric contours at 2-foot intervals of elevation, and elevation-area-capacity tables. The results of the bathymetric survey show that the East of Hudson reservoirs range from about 25 feet deep (Kirk Lake) to about 162 feet deep (Kensico Reservoir) and have a total capacity of 142.9 billion gallons, with a combined surface area of more than 11,600 acres.The accuracy of the mapped bathymetric data was evaluated using quality assurance datasets collected with a singlebeam echosounder; about 284,000 quality assurance points were spatially joined with the mapped raster surface to compute measurement errors. The calculated mean point elevation error for the East of Hudson reservoirs was 0.35 foot, the median error was 0.21 foot, and the 95-percent accuracy was 1.68 feet; the 95-percent accuracy of the computed capacity at spillway elevation was 1.6 percent or less. The largest errors occurred in the steepest areas of the reservoirs and in areas where the data were interpolated. Geospatial files of the bathymetry data, including mapped bathymetric surfaces, contours, and capacity tables, quality assurance points, and associated metadata are available for download as part of an accompanying U.S. Geological Survey data release.

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Bathymetric and velocimetric surveys at highway bridges crossing the Missouri River near Kansas City, Missouri, June 2–4, 2015

Cited by 11 publications

References 5 publications

Estimating sand bed load in rivers by tracking dunes: a comparison of methods based on bed elevation time series

Estimating sand bed load in rivers by tracking dunes: a comparison of methods based on bed elevation time series

Estimating Sand Bedload in Rivers by Tracking Dunes: a comparison of methods based on bed elevation time-series

Bathymetry of New York City’s East of Hudson reservoirs and controlled lakes, 2017 to 2019

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