Skip to main content

Edward A Bulliner

thumbnail
Within large-river ecosystems, floodplains serve a variety of important ecological functions. A recent survey of 80 managers of floodplain conservation lands along the Upper and Middle Mississippi and Lower Missouri Rivers in the central United States found that the most critical information needed to improve floodplain management centered on metrics for characterizing depth, extent, frequency, duration, and timing of inundation. These metrics can be delivered to managers efficiently through cloud-based interactive maps. To calculate these metrics, we interpolated an existing one-dimensional HEC-RAS hydraulic model for the Lower Missouri River, which simulated water surface elevations at cross sections spaced (<1...
Within large-river ecosystems, floodplains serve a variety of important ecological functions. A recent survey of 80 managers of floodplain conservation lands along the Upper and Middle Mississippi and Lower Missouri Rivers in the central United States found that the most critical information needed to improve floodplain management centered on metrics for characterizing depth, extent, frequency, duration, and timing of inundation. These metrics can be delivered to managers efficiently through cloud-based interactive maps. To calculate these metrics, we interpolated an existing one-dimensional HEC-RAS hydraulic model for the Middle Mississippi River, which simulated water surface elevations at cross sections spaced...
thumbnail
Shapefile created by USGS. This is a polygon created from Landsat TM imagery. All Landsat 4-5 TM images overlapping the Missouri River downstream from Gavins Point Dam were identified and examined for lack of clouds. Usable images were classified into sand, vegetation, and water. Classified images were then merged, and the number of times a given pixel was classified as either sand, vegetation, or water were computed. The presented dataset represents pixels which were classified as sand in greater than 5% of images which were collected during a growing season defined as julian day 116-296 (to preclude vegetated islands, which classify as sand outside of foliation), translated into polygons.
thumbnail
This child data release includes hyperspectral and RGB images acquired from an Unmanned Aircraft System (UAS) during an experiment performed at the USGS Columbia Environmental Research Center, near Columbia, Missouri, on April 2, 2019. The purpose of the experiment was to assess the feasibility of inferring concentrations of a visible dye (Rhodamine WT) tracer from various types of remotely sensed data in water with varying levels of turbidity. Whereas previous research on remote sensing of tracer dye concentrations has focused on clear-flowing streams, the Missouri River is much more turbid and the reflectance signal associated with the sediment-laden water could obscure that related to the presence and amount...
Within large-river ecosystems, floodplains serve a variety of important ecological functions. A recent survey of 80 managers of floodplain conservation lands along the Upper and Middle Mississippi and Lower Missouri Rivers in the central United States found that the most critical information needed to improve floodplain management centered on metrics for characterizing depth, extent, frequency, duration, and timing of inundation. These metrics can be delivered to managers efficiently through cloud-based interactive maps. To calculate these metrics, we interpolated an existing one-dimensional HEC-RAS hydraulic model for the Middle Mississippi River, which simulated water surface elevations at cross sections spaced...
View more...
ScienceBase brings together the best information it can find about USGS researchers and offices to show connections to publications, projects, and data. We are still working to improve this process and information is by no means complete. If you don't see everything you know is associated with you, a colleague, or your office, please be patient while we work to connect the dots. Feel free to contact sciencebase@usgs.gov.