Paul Kinzel is a Hydrologist with the USGS Water Resources Mission Area.
Education
M.S. in Civil Engineering, University of Colorado, Boulder, May 1998
B.S. in Environmental Science, State University of New York, Plattsburgh, May 1995
Science and Products
Clear Creek Reservoir Bathymetry
To better characterize the water supply capacity of Clear Creek Reservoir, Chaffee County, Colorado, the U.S. Geological Survey, in cooperation with the Pueblo Board of Water Works and Colorado Mountain College, carried out a bathymetry survey of Clear Creek Reservoir. The equipment and methods used in this study allowed water-resource managers to maintain typical reservoir operations, eliminating...
Filter Total Items: 28
Topographic LiDAR surveys of rivers in Alaska, July 24-26, 2019
The U.S. Geological Survey in collaboration with the U.S. Army Corps of Engineers Cold Regions Research and Engineering Laboratory (CRREL) collected topographic LiDAR surveys of four rivers in Alaska from July 24-26, 2019 to support research related to remote sensing of river discharge. Data were acquired for the Matanuska, Chena, Salcha, and Tanana Rivers using a Riegl VQ-580 LiDAR. The LiDAR was
Aerial images, digital elevation models, channel width maps, and river metrics along the Colorado River in Canyonlands National Park, Utah (1940 - 2018)
These data consist of rectified aerial photographs, measurements of active channel width, measurements of river and floodplain bathymetry and topography, and ancillary data. These data are specific to the corridor of the Colorado River in Canyonlands National Park between Potash, Utah and the confluence of the Green and Colorado Rivers near Spanish Bottom, Utah. The time period for these data are
Helicopter-based videos and field measurements of flow depth and velocity from the Tanana River, Alaska, acquired on July 24, 2019
This data release includes videos acquired from a helicopter and field measurements of flow depth and velocity from the Tanana River near Nenana, Alaska, obtained on July 24, 2019. This parent data release includes links to child pages for two data sets produced during the study: 1. Acoustic Doppler Current Profiler (ADCP) field measurements of flow depth and velocity from the Tanana River, Alas
Data from a flume investigation using Fiber Optic Distributed Temperature Sensing (FO-DTS), U.S. Geological Survey Geomorphology and Sediment Transport Laboratory, Golden, Colorado, fall 2019
Evaluating technologies and approaches to identify the movement of fine sediment over coarser substrate has implications for monitoring the condition of habitat restoration sites. This goal motivated testing the efficacy of Fiber Optic Distributed Temperature Sensing (FO-DTS) as a technique for detecting the migration of sand bedforms over coarser bed material. Experiments were conducted in a labo
Satellite video and field measurements of flow velocity acquired from the Tanana River in Alaska and used for particle image velocimetry (PIV)
This data release includes a video acquired from a satellite and field measurements of flow velocity from the Tanana River in Alaska that were used to derive remotely sensed estimates of surface flow velocities via particle image velocimetry (PIV). The field data were collected on July 24, 2019, in cooperation with the USGS Alaska Science Center, and the satellite video was obtained on July 14, 2
Geo-referenced orthophotographs of the Snow River, Alaska, acquired September 1, 2018
This data release consists of orthophotographs of the Snow River in Alaska acquired on September 1, 2018. The orthophotographs were produced from images obtained using a Hasselblad A6D-100C 100 megapixel digital mapping camera deployed within a pod mounted on the landing gear of a Robinson R44 helicopter. Images were acquired as the helicopter transited a series of flight lines designed to provid
Field measurements of flow depth and optical image sequences acquired from the Salcha River, Alaska, on July 25, 2019
This data release includes field measurements of flow depth and optical image sequences acquired from the Salcha River in Alaska on July 25, 2019. These data were used to develop and test a spectrally based remote sensing technique for estimating water depth from passive optical image data. The purpose of this study was to assess the feasibility of inferring water depths from optical image seque
Remotely sensed bathymetry and field measurements from the Colorado River near Lees Ferry, Arizona, September 23, 2019
To support an investigation of the feasibility of measuring river bathymetry using a polarizing lidar sensor, lidar and field measurements were collected on the Colorado River near Lees Ferry, Arizona on September 23, 2019. This parent data release includes links to child pages for the following data sets: 1) Lidar data used for mapping channel bathymetry (depth), acquired with a novel instrument
UAS-based remotely sensed bathymetry and field measurements from the Colorado River, near Parshall Colorado, June 13, 2019
To support an investigation of the feasibility of measuring river bathymetry using remotely sensed data acquired from a small unmanned aircraft system (sUAS), remotely sensed bathymetry and field measurements were collected from two cross-sections on the Colorado River near Parshall, CO on June 13, 2019. This parent data release includes links to child pages for the following data sets: 1) Lidar
UAS-based remotely sensed data and field measurements from the Blue River and Colorado River, near Kremmling, Colorado, October 17-18, 2018
To support an investigation of the feasibility of measuring river bathymetry using remotely sensed data acquired from an unmanned aircraft system (UAS), several types of remotely sensed data and field measurements were collected from two cross-sections on the Blue River and two cross-sections on the Colorado River near Kremmling, Colorado, on October 17-18, 2018. This parent data release includes
Field measurements of flow velocity and optical image sequences acquired from the Salcha and Tanana Rivers in Alaska in 2018 and 2019 and used for particle image velocimetry (PIV)
This data release includes field measurements of flow velocity and optical image sequences used to derive remotely sensed estimates of surface flow velocities via particle image velocimetry (PIV) from two rivers in Alaska. These data were acquired from the Salcha River on August 31, 2018, and the Tanana River on July 24, 2019. The purpose of this study was to assess the feasibility of inferring
Hydrographic surveys collected to monitor fish spawning reef placements, Detroit and St. Clair Rivers, Michigan, July 23-25, 2018
The U.S Geological Survey conducted hydrographic surveys from July 23-25, 2018 to monitor fish spawning substrate placements (reefs) in the Detroit and St. Clair Rivers, Michigan. A multibeam echosounder was used from the Great Lakes Science Center research vessel Cisco to collect hydrographic data. These data were used to generate maps of river bottom topography in locations where spawning substr
Bathymetry of Clear Creek Reservoir, Chaffee County, Colorado, 2016
To better characterize the water supply capacity of Clear Creek Reservoir, Chaffee County, Colorado, the U.S. Geological Survey, in cooperation with the Pueblo Board of Water Works and Colorado Mountain College, carried out a bathymetry survey of Clear Creek Reservoir. A bathymetry map of the reservoir is presented here with the elevation-surface area and the elevation-volume relations. The bathym
Bathymetry of the Hong and Luoc River Junction, Red River Delta, Vietnam, 2010
The U.S. Geological Survey, in collaboration with the Water Resources University in Hanoi, Vietnam, conducted a bathymetric survey of the junction of the Hong and Luoc Rivers. The survey was done to characterize the channel morphology of this delta distributary network and provide input for hydrodynamic and sediment transport models. The survey was carried out in December 2010 using a boat-mounted
Filter Total Items: 50
Depths inferred from velocities estimated by remote sensing: A flow resistance equation-based approach to mapping multiple river attributes at the reach scale
Remote sensing of flow conditions in stream channels could facilitate hydrologic data collection, particularly in large, inaccessible rivers. Previous research has demonstrated the potential to estimate flow velocities in sediment-laden rivers via particle image velocimetry (PIV). In this study, we introduce a new framework for also obtaining bathymetric information: Depths Inferred from Velocitie
Surface flow velocities from space: Particle image velocimetry of satellite video of a large, sediment-laden river
Conventional, field-based streamflow monitoring in remote, inaccessible locations such as Alaska poses logistical challenges. Safety concerns, financial considerations, and a desire to expand water-observing networks make remote sensing an appealing alternative means of collecting hydrologic data. In an ongoing effort to develop non-contact methods for measuring river discharge, we evaluated the p
Improving remotely sensed river bathymetry by image-averaging
Basic data on river bathymetry is critical for numerous applications in river research and management and is increasingly obtained via remote sensing, but the noisy, pixelated appearance of image‐derived depth maps can compromise subsequent analyses. We hypothesized that this noise originates from reflectance from an irregular water surface and introduced a framework for mitigating these effects b
Field evaluation of a compact, polarizing topo‐bathymetric lidar across a range of river conditions
This paper summarizes field trials to evaluate the performance of a prototype compact topo‐bathymetric lidar sensor for surveying rivers. The sensor uses a novel polarization technique to distinguish between laser returns from the water surface and streambed and its size and weight permit deployment from a small unmanned aerial system (sUAS) or a boat. Field testing was designed to identify the ra
Inferring surface flow velocities in sediment-laden Alaskan rivers from optical image sequences acquired from a helicopter
The remote, inaccessible location of many rivers in Alaska creates a compelling need for remote sensing approaches to streamflow monitoring. Motivated by this objective, we evaluated the potential to infer flow velocities from optical image sequences acquired from a helicopter deployed above two large, sediment-laden rivers. Rather than artificial seeding, we used an ensemble correlation particle
Remote sensing of tracer dye concentrations to support dispersion studies in river channels
In river channels the flow field influences the dispersion of biota, contaminants, and other suspended or dissolved materials. Insight on patterns and rates of dispersion can be gained by injecting a pulse of visible dye and observing spatial and temporal variations in dye concentration as the pulse moves downstream. We evaluated the potential of passive optical remote sensing to enhance such trac
sUAS-based remote sensing of river discharge using thermal particle image velocimetry and bathymetric lidar
This paper describes a non-contact methodology for computing river discharge based on data collected from small Unmanned Aerial Systems (sUAS). The approach is complete in that both surface velocity and channel geometry are measured directly under field conditions. The technique does not require introducing artificial tracer particles for computing surface velocity, nor does it rely upon the pres
Near-field remote sensing of Alaskan Rivers
The U.S. Geological Survey (USGS) Geomorphology and Sediment Transport Laboratory (GSTL), in collaboration with the U.S. Army Corps of Engineers Cold Regions Research and Engineering Laboratory (CRREL), acquired remotely sensed data from several Alaskan rivers in 2017 and 2018 with the goal of developing a methodology for measuring streamflow from a helicopter. CRREL operates a custom airborne lid
Remote sensing of river flow in Alaska—New technology to improve safety and expand coverage of USGS streamgaging
The U.S. Geological Survey monitors water level (water surface elevation relative to an arbitrary datum) and measures streamflow in Alaska rivers to compute and compile river flow records for use by water resource planners, engineers, and land managers to design infrastructure, manage floodplains, and protect life, property, and aquatic resources. Alaska has over 800,000 miles of rivers including
New methods for predicting and measuring dispersion in rivers
To develop a better predictive tool for dispersion in rivers over a range of temporal and spatial scales, our group has developed a simple Lagrangian model that is applicable for a wide range of coordinate systems and flow modeling methodologies. The approach allows dispersion computations for a large suite of discretizations, model dimensions (1-, 2-, or 3-dimensional), spatial and temporal discr
Sampling strategies to improve passive optical remote sensing of river bathymetry
Passive optical remote sensing of river bathymetry involves establishing a relation between depth and reflectance that can be applied throughout an image to produce a depth map. Building upon the Optimal Band Ratio Analysis (OBRA) framework, we introduce sampling strategies for constructing calibration data sets that lead to strong relationships between an image-derived quantity and depth across
Remote measurement of river discharge using thermal particle image velocimetry (PIV) and various sources of bathymetric information
Although river discharge is a fundamental hydrologic quantity, conventional methods of streamgaging are impractical, expensive, and potentially dangerous in remote locations. This study evaluated the potential for measuring discharge via various forms of remote sensing, primarily thermal imaging of flow velocities but also spectrally-based depth retrieval from passive optical image data. We acquir
Science and Products
- Science
Clear Creek Reservoir Bathymetry
To better characterize the water supply capacity of Clear Creek Reservoir, Chaffee County, Colorado, the U.S. Geological Survey, in cooperation with the Pueblo Board of Water Works and Colorado Mountain College, carried out a bathymetry survey of Clear Creek Reservoir. The equipment and methods used in this study allowed water-resource managers to maintain typical reservoir operations, eliminating... - Data
Filter Total Items: 28
Topographic LiDAR surveys of rivers in Alaska, July 24-26, 2019
The U.S. Geological Survey in collaboration with the U.S. Army Corps of Engineers Cold Regions Research and Engineering Laboratory (CRREL) collected topographic LiDAR surveys of four rivers in Alaska from July 24-26, 2019 to support research related to remote sensing of river discharge. Data were acquired for the Matanuska, Chena, Salcha, and Tanana Rivers using a Riegl VQ-580 LiDAR. The LiDAR wasAerial images, digital elevation models, channel width maps, and river metrics along the Colorado River in Canyonlands National Park, Utah (1940 - 2018)
These data consist of rectified aerial photographs, measurements of active channel width, measurements of river and floodplain bathymetry and topography, and ancillary data. These data are specific to the corridor of the Colorado River in Canyonlands National Park between Potash, Utah and the confluence of the Green and Colorado Rivers near Spanish Bottom, Utah. The time period for these data areHelicopter-based videos and field measurements of flow depth and velocity from the Tanana River, Alaska, acquired on July 24, 2019
This data release includes videos acquired from a helicopter and field measurements of flow depth and velocity from the Tanana River near Nenana, Alaska, obtained on July 24, 2019. This parent data release includes links to child pages for two data sets produced during the study: 1. Acoustic Doppler Current Profiler (ADCP) field measurements of flow depth and velocity from the Tanana River, AlasData from a flume investigation using Fiber Optic Distributed Temperature Sensing (FO-DTS), U.S. Geological Survey Geomorphology and Sediment Transport Laboratory, Golden, Colorado, fall 2019
Evaluating technologies and approaches to identify the movement of fine sediment over coarser substrate has implications for monitoring the condition of habitat restoration sites. This goal motivated testing the efficacy of Fiber Optic Distributed Temperature Sensing (FO-DTS) as a technique for detecting the migration of sand bedforms over coarser bed material. Experiments were conducted in a laboSatellite video and field measurements of flow velocity acquired from the Tanana River in Alaska and used for particle image velocimetry (PIV)
This data release includes a video acquired from a satellite and field measurements of flow velocity from the Tanana River in Alaska that were used to derive remotely sensed estimates of surface flow velocities via particle image velocimetry (PIV). The field data were collected on July 24, 2019, in cooperation with the USGS Alaska Science Center, and the satellite video was obtained on July 14, 2Geo-referenced orthophotographs of the Snow River, Alaska, acquired September 1, 2018
This data release consists of orthophotographs of the Snow River in Alaska acquired on September 1, 2018. The orthophotographs were produced from images obtained using a Hasselblad A6D-100C 100 megapixel digital mapping camera deployed within a pod mounted on the landing gear of a Robinson R44 helicopter. Images were acquired as the helicopter transited a series of flight lines designed to providField measurements of flow depth and optical image sequences acquired from the Salcha River, Alaska, on July 25, 2019
This data release includes field measurements of flow depth and optical image sequences acquired from the Salcha River in Alaska on July 25, 2019. These data were used to develop and test a spectrally based remote sensing technique for estimating water depth from passive optical image data. The purpose of this study was to assess the feasibility of inferring water depths from optical image sequeRemotely sensed bathymetry and field measurements from the Colorado River near Lees Ferry, Arizona, September 23, 2019
To support an investigation of the feasibility of measuring river bathymetry using a polarizing lidar sensor, lidar and field measurements were collected on the Colorado River near Lees Ferry, Arizona on September 23, 2019. This parent data release includes links to child pages for the following data sets: 1) Lidar data used for mapping channel bathymetry (depth), acquired with a novel instrumentUAS-based remotely sensed bathymetry and field measurements from the Colorado River, near Parshall Colorado, June 13, 2019
To support an investigation of the feasibility of measuring river bathymetry using remotely sensed data acquired from a small unmanned aircraft system (sUAS), remotely sensed bathymetry and field measurements were collected from two cross-sections on the Colorado River near Parshall, CO on June 13, 2019. This parent data release includes links to child pages for the following data sets: 1) LidarUAS-based remotely sensed data and field measurements from the Blue River and Colorado River, near Kremmling, Colorado, October 17-18, 2018
To support an investigation of the feasibility of measuring river bathymetry using remotely sensed data acquired from an unmanned aircraft system (UAS), several types of remotely sensed data and field measurements were collected from two cross-sections on the Blue River and two cross-sections on the Colorado River near Kremmling, Colorado, on October 17-18, 2018. This parent data release includesField measurements of flow velocity and optical image sequences acquired from the Salcha and Tanana Rivers in Alaska in 2018 and 2019 and used for particle image velocimetry (PIV)
This data release includes field measurements of flow velocity and optical image sequences used to derive remotely sensed estimates of surface flow velocities via particle image velocimetry (PIV) from two rivers in Alaska. These data were acquired from the Salcha River on August 31, 2018, and the Tanana River on July 24, 2019. The purpose of this study was to assess the feasibility of inferringHydrographic surveys collected to monitor fish spawning reef placements, Detroit and St. Clair Rivers, Michigan, July 23-25, 2018
The U.S Geological Survey conducted hydrographic surveys from July 23-25, 2018 to monitor fish spawning substrate placements (reefs) in the Detroit and St. Clair Rivers, Michigan. A multibeam echosounder was used from the Great Lakes Science Center research vessel Cisco to collect hydrographic data. These data were used to generate maps of river bottom topography in locations where spawning substr - Maps
Bathymetry of Clear Creek Reservoir, Chaffee County, Colorado, 2016
To better characterize the water supply capacity of Clear Creek Reservoir, Chaffee County, Colorado, the U.S. Geological Survey, in cooperation with the Pueblo Board of Water Works and Colorado Mountain College, carried out a bathymetry survey of Clear Creek Reservoir. A bathymetry map of the reservoir is presented here with the elevation-surface area and the elevation-volume relations. The bathym
Bathymetry of the Hong and Luoc River Junction, Red River Delta, Vietnam, 2010
The U.S. Geological Survey, in collaboration with the Water Resources University in Hanoi, Vietnam, conducted a bathymetric survey of the junction of the Hong and Luoc Rivers. The survey was done to characterize the channel morphology of this delta distributary network and provide input for hydrodynamic and sediment transport models. The survey was carried out in December 2010 using a boat-mounted - Publications
Filter Total Items: 50
Depths inferred from velocities estimated by remote sensing: A flow resistance equation-based approach to mapping multiple river attributes at the reach scale
Remote sensing of flow conditions in stream channels could facilitate hydrologic data collection, particularly in large, inaccessible rivers. Previous research has demonstrated the potential to estimate flow velocities in sediment-laden rivers via particle image velocimetry (PIV). In this study, we introduce a new framework for also obtaining bathymetric information: Depths Inferred from VelocitieSurface flow velocities from space: Particle image velocimetry of satellite video of a large, sediment-laden river
Conventional, field-based streamflow monitoring in remote, inaccessible locations such as Alaska poses logistical challenges. Safety concerns, financial considerations, and a desire to expand water-observing networks make remote sensing an appealing alternative means of collecting hydrologic data. In an ongoing effort to develop non-contact methods for measuring river discharge, we evaluated the pImproving remotely sensed river bathymetry by image-averaging
Basic data on river bathymetry is critical for numerous applications in river research and management and is increasingly obtained via remote sensing, but the noisy, pixelated appearance of image‐derived depth maps can compromise subsequent analyses. We hypothesized that this noise originates from reflectance from an irregular water surface and introduced a framework for mitigating these effects bField evaluation of a compact, polarizing topo‐bathymetric lidar across a range of river conditions
This paper summarizes field trials to evaluate the performance of a prototype compact topo‐bathymetric lidar sensor for surveying rivers. The sensor uses a novel polarization technique to distinguish between laser returns from the water surface and streambed and its size and weight permit deployment from a small unmanned aerial system (sUAS) or a boat. Field testing was designed to identify the raInferring surface flow velocities in sediment-laden Alaskan rivers from optical image sequences acquired from a helicopter
The remote, inaccessible location of many rivers in Alaska creates a compelling need for remote sensing approaches to streamflow monitoring. Motivated by this objective, we evaluated the potential to infer flow velocities from optical image sequences acquired from a helicopter deployed above two large, sediment-laden rivers. Rather than artificial seeding, we used an ensemble correlation particleRemote sensing of tracer dye concentrations to support dispersion studies in river channels
In river channels the flow field influences the dispersion of biota, contaminants, and other suspended or dissolved materials. Insight on patterns and rates of dispersion can be gained by injecting a pulse of visible dye and observing spatial and temporal variations in dye concentration as the pulse moves downstream. We evaluated the potential of passive optical remote sensing to enhance such tracsUAS-based remote sensing of river discharge using thermal particle image velocimetry and bathymetric lidar
This paper describes a non-contact methodology for computing river discharge based on data collected from small Unmanned Aerial Systems (sUAS). The approach is complete in that both surface velocity and channel geometry are measured directly under field conditions. The technique does not require introducing artificial tracer particles for computing surface velocity, nor does it rely upon the presNear-field remote sensing of Alaskan Rivers
The U.S. Geological Survey (USGS) Geomorphology and Sediment Transport Laboratory (GSTL), in collaboration with the U.S. Army Corps of Engineers Cold Regions Research and Engineering Laboratory (CRREL), acquired remotely sensed data from several Alaskan rivers in 2017 and 2018 with the goal of developing a methodology for measuring streamflow from a helicopter. CRREL operates a custom airborne lidRemote sensing of river flow in Alaska—New technology to improve safety and expand coverage of USGS streamgaging
The U.S. Geological Survey monitors water level (water surface elevation relative to an arbitrary datum) and measures streamflow in Alaska rivers to compute and compile river flow records for use by water resource planners, engineers, and land managers to design infrastructure, manage floodplains, and protect life, property, and aquatic resources. Alaska has over 800,000 miles of rivers includingNew methods for predicting and measuring dispersion in rivers
To develop a better predictive tool for dispersion in rivers over a range of temporal and spatial scales, our group has developed a simple Lagrangian model that is applicable for a wide range of coordinate systems and flow modeling methodologies. The approach allows dispersion computations for a large suite of discretizations, model dimensions (1-, 2-, or 3-dimensional), spatial and temporal discrSampling strategies to improve passive optical remote sensing of river bathymetry
Passive optical remote sensing of river bathymetry involves establishing a relation between depth and reflectance that can be applied throughout an image to produce a depth map. Building upon the Optimal Band Ratio Analysis (OBRA) framework, we introduce sampling strategies for constructing calibration data sets that lead to strong relationships between an image-derived quantity and depth acrossRemote measurement of river discharge using thermal particle image velocimetry (PIV) and various sources of bathymetric information
Although river discharge is a fundamental hydrologic quantity, conventional methods of streamgaging are impractical, expensive, and potentially dangerous in remote locations. This study evaluated the potential for measuring discharge via various forms of remote sensing, primarily thermal imaging of flow velocities but also spectrally-based depth retrieval from passive optical image data. We acquir