These data are high-resolution bathymetry (riverbed elevation) and depth-averaged velocities in ASCII format, generated from hydrographic and velocimetric surveys of the Missouri River near Structure A1800 on Interstate 635 in Kansas City, Missouri, in 2010, 2011, and 2015. Hydrographic data were collected using a high-resolution multibeam echosounder mapping system (MBMS), which consists of a multibeam echosounder (MBES) and an inertial navigation system (INS) mounted on a marine survey vessel. Data were collected as the vessel traversed the river along planned survey lines distributed throughout the reach. Data collection software integrated and stored the depth data from the MBES and the horizontal and vertical position and attitude data of the vessel from the INS in real time. Data processing required computer software to extract bathymetry data from the raw data files and to summarize and map the information. Velocity data were collected using an acoustic Doppler current profiler (ADCP) mounted on a survey vessel equipped with a differential global positioning system (DGPS). Data were collected as the vessel traversed the river along planned transect lines distributed throughout the reach. Velocity data were processed using the Velocity Mapping Toolbox (Parsons and other, 2013), and smoothed using neighboring nodes.

These data are high-resolution bathymetry (riverbed elevation) and depth-averaged velocities in ASCII format, generated from hydrographic and velocimetric surveys of the Missouri River near Structure A0767 on Interstate 435 in Kansas City, Missouri, in 2010, 2011, and 2015. Hydrographic data were collected using a high-resolution multibeam echosounder mapping system (MBMS), which consists of a multibeam echosounder (MBES) and an inertial navigation system (INS) mounted on a marine survey vessel. Data were collected as the vessel traversed the river along planned survey lines distributed throughout the reach. Data collection software integrated and stored the depth data from the MBES and the horizontal and vertical position and attitude data of the vessel from the INS in real time. Data processing required computer software to extract bathymetry data from the raw data files and to summarize and map the information. Velocity data were collected using an acoustic Doppler current profiler (ADCP) mounted on a survey vessel equipped with a differential global positioning system (DGPS). Data were collected as the vessel traversed the river along planned transect lines distributed throughout the reach. Velocity data were processed using the Velocity Mapping Toolbox (Parsons and other, 2013), and smoothed using neighboring nodes.

These data are high-resolution bathymetry (riverbed elevation) and depth-averaged velocities in ASCII format, generated from hydrographic and velocimetric surveys of the Missouri River near Structure A0767 on Interstate 435 in Kansas City, Missouri, in 2010, 2011, and 2015. Hydrographic data were collected using a high-resolution multibeam echosounder mapping system (MBMS), which consists of a multibeam echosounder (MBES) and an inertial navigation system (INS) mounted on a marine survey vessel. Data were collected as the vessel traversed the river along planned survey lines distributed throughout the reach. Data collection software integrated and stored the depth data from the MBES and the horizontal and vertical position and attitude data of the vessel from the INS in real time. Data processing required computer software to extract bathymetry data from the raw data files and to summarize and map the information. Velocity data were collected using an acoustic Doppler current profiler (ADCP) mounted on a survey vessel equipped with a differential global positioning system (DGPS). Data were collected as the vessel traversed the river along planned transect lines distributed throughout the reach. Velocity data were processed using the Velocity Mapping Toolbox (Parsons and other, 2013), and smoothed using neighboring nodes.

These data are high-resolution bathymetry (riverbed elevation) and depth-averaged velocities in ASCII format, generated from hydrographic and velocimetric surveys of the Missouri River near Structure A7650 on Interstate 35 in Kansas City, Missouri, in 2010, 2011, and 2015. Hydrographic data were collected using a high-resolution multibeam echosounder mapping system (MBMS), which consists of a multibeam echosounder (MBES) and an inertial navigation system (INS) mounted on a marine survey vessel. Data were collected as the vessel traversed the river along planned survey lines distributed throughout the reach. Data collection software integrated and stored the depth data from the MBES and the horizontal and vertical position and attitude data of the vessel from the INS in real time. Data processing required computer software to extract bathymetry data from the raw data files and to summarize and map the information. Velocity data were collected using an acoustic Doppler current profiler (ADCP) mounted on a survey vessel equipped with a differential global positioning system (DGPS). Data were collected as the vessel traversed the river along planned transect lines distributed throughout the reach. Velocity data were processed using the Velocity Mapping Toolbox (Parsons and other, 2013), and smoothed using neighboring nodes.

These data are high-resolution bathymetry (riverbed elevation) and depth-averaged velocities in ASCII format, generated from hydrographic and velocimetric surveys of the Missouri River near Structure A7650 on Interstate 35 in Kansas City, Missouri, in 2010, 2011, and 2015. Hydrographic data were collected using a high-resolution multibeam echosounder mapping system (MBMS), which consists of a multibeam echosounder (MBES) and an inertial navigation system (INS) mounted on a marine survey vessel. Data were collected as the vessel traversed the river along planned survey lines distributed throughout the reach. Data collection software integrated and stored the depth data from the MBES and the horizontal and vertical position and attitude data of the vessel from the INS in real time. Data processing required computer software to extract bathymetry data from the raw data files and to summarize and map the information. Velocity data were collected using an acoustic Doppler current profiler (ADCP) mounted on a survey vessel equipped with a differential global positioning system (DGPS). Data were collected as the vessel traversed the river along planned transect lines distributed throughout the reach. Velocity data were processed using the Velocity Mapping Toolbox (Parsons and other, 2013), and smoothed using neighboring nodes.

These data are high-resolution bathymetry (riverbed elevation) and depth-averaged velocities in ASCII format, generated from hydrographic and velocimetric surveys of the Missouri River near Structure A4060 on Missouri State Highway 9 in Kansas City, Missouri, in 2010, 2011, and 2015. Hydrographic data were collected using a high-resolution multibeam echosounder mapping system (MBMS), which consists of a multibeam echosounder (MBES) and an inertial navigation system (INS) mounted on a marine survey vessel. Data were collected as the vessel traversed the river along planned survey lines distributed throughout the reach. Data collection software integrated and stored the depth data from the MBES and the horizontal and vertical position and attitude data of the vessel from the INS in real time. Data processing required computer software to extract bathymetry data from the raw data files and to summarize and map the information. Velocity data were collected using an acoustic Doppler current profiler (ADCP) mounted on a survey vessel equipped with a differential global positioning system (DGPS). Data were collected as the vessel traversed the river along planned transect lines distributed throughout the reach. Velocity data were processed using the Velocity Mapping Toolbox (Parsons and other, 2013), and smoothed using neighboring nodes.

These data are high-resolution bathymetry (riverbed elevation) and depth-averaged velocities in ASCII format, generated from hydrographic and velocimetric surveys of the Missouri River near Structure A4060 on Missouri State Highway 9 in Kansas City, Missouri, in 2010, 2011, and 2015. Hydrographic data were collected using a high-resolution multibeam echosounder mapping system (MBMS), which consists of a multibeam echosounder (MBES) and an inertial navigation system (INS) mounted on a marine survey vessel. Data were collected as the vessel traversed the river along planned survey lines distributed throughout the reach. Data collection software integrated and stored the depth data from the MBES and the horizontal and vertical position and attitude data of the vessel from the INS in real time. Data processing required computer software to extract bathymetry data from the raw data files and to summarize and map the information. Velocity data were collected using an acoustic Doppler current profiler (ADCP) mounted on a survey vessel equipped with a differential global positioning system (DGPS). Data were collected as the vessel traversed the river along planned transect lines distributed throughout the reach. Velocity data were processed using the Velocity Mapping Toolbox (Parsons and other, 2013), and smoothed using neighboring nodes.

These data are high-resolution bathymetry (riverbed elevation) and depth-averaged velocities in ASCII format, generated from hydrographic and velocimetric surveys of the Missouri River near Structure A5817 on Missouri State Highway 269 in Kansas City, Missouri, in 2010, 2011, and 2015. Hydrographic data were collected using a high-resolution multibeam echosounder mapping system (MBMS), which consists of a multibeam echosounder (MBES) and an inertial navigation system (INS) mounted on a marine survey vessel. Data were collected as the vessel traversed the river along planned survey lines distributed throughout the reach. Data collection software integrated and stored the depth data from the MBES and the horizontal and vertical position and attitude data of the vessel from the INS in real time. Data processing required computer software to extract bathymetry data from the raw data files and to summarize and map the information. Velocity data were collected using an acoustic Doppler current profiler (ADCP) mounted on a survey vessel equipped with a differential global positioning system (DGPS). Data were collected as the vessel traversed the river along planned transect lines distributed throughout the reach. Velocity data were processed using the Velocity Mapping Toolbox (Parsons and other, 2013), and smoothed using neighboring nodes.

These data are high-resolution bathymetry (riverbed elevation) and depth-averaged velocities in ASCII format, generated from hydrographic and velocimetric surveys of the Missouri River near Structure A5817 on Missouri State Highway 269 in Kansas City, Missouri, in 2010, 2011, and 2015. Hydrographic data were collected using a high-resolution multibeam echosounder mapping system (MBMS), which consists of a multibeam echosounder (MBES) and an inertial navigation system (INS) mounted on a marine survey vessel. Data were collected as the vessel traversed the river along planned survey lines distributed throughout the reach. Data collection software integrated and stored the depth data from the MBES and the horizontal and vertical position and attitude data of the vessel from the INS in real time. Data processing required computer software to extract bathymetry data from the raw data files and to summarize and map the information. Velocity data were collected using an acoustic Doppler current profiler (ADCP) mounted on a survey vessel equipped with a differential global positioning system (DGPS). Data were collected as the vessel traversed the river along planned transect lines distributed throughout the reach. Velocity data were processed using the Velocity Mapping Toolbox (Parsons and other, 2013), and smoothed using neighboring nodes.

These data are high-resolution bathymetry (riverbed elevation) and depth-averaged velocities in ASCII format, generated from hydrographic and velocimetric surveys of the Missouri River near Structure A4649 on U.S. Highway 169 in Kansas City, Missouri, in 2010, 2011, and 2015. Hydrographic data were collected using a high-resolution multibeam echosounder mapping system (MBMS), which consists of a multibeam echosounder (MBES) and an inertial navigation system (INS) mounted on a marine survey vessel. Data were collected as the vessel traversed the river along planned survey lines distributed throughout the reach. Data collection software integrated and stored the depth data from the MBES and the horizontal and vertical position and attitude data of the vessel from the INS in real time. Data processing required computer software to extract bathymetry data from the raw data files and to summarize and map the information. Velocity data were collected using an acoustic Doppler current profiler (ADCP) mounted on a survey vessel equipped with a differential global positioning system (DGPS). Data were collected as the vessel traversed the river along planned transect lines distributed throughout the reach. Velocity data were processed using the Velocity Mapping Toolbox (Parsons and other, 2013), and smoothed using neighboring nodes.