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 dual bridge structure A5585 on Missouri State Highway 364 near St. Louis, Missouri, in 2010, 2011, and 2016. 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 highway bridge structures on U.S. Highway 40 near St. Louis, Missouri, in 2010, 2011, and 2016. 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 dual bridge structure A3665 on U.S. Highway 36 at St. Joseph, Missouri, in 2011, 2014, and 2018. 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 others, 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 A3047 on U.S. Highway 67 near St. Louis, Missouri, in 2010, 2011, and 2016. 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 near highway bridge structures on U.S. Highway 69 in Kansas City, Missouri, in 2010, 2011, and 2017. 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 structures A3292/L0561 on Interstate 70 near St. Louis, Missouri, in 2010, 2011 and 2016. 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 structures A3292/L0561 on Interstate 70 near St. Louis, Missouri, in 2010, 2011 and 2016. 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 A5664 on Missouri State Highway 13 at Lexington, Missouri, in 2011, 2013, and 2017. 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 others, 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 Structures A4757/L0568 on Missouri State Highway 291 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 Structures A4757/L0568 on Missouri State Highway 291 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.