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Effects of bathymetric lidar errors on flow properties predicted with a multi‐dimensional hydraulic model
Author(s) -
McKean J.,
Tonina D.,
Bohn C.,
Wright C.W.
Publication year - 2014
Publication title -
journal of geophysical research: earth surface
Language(s) - English
Resource type - Journals
eISSN - 2169-9011
pISSN - 2169-9003
DOI - 10.1002/2013jf002897
Subject(s) - lidar , bathymetry , geology , flow (mathematics) , environmental science , remote sensing , oceanography , mathematics , geometry
New remote sensing technologies and improved computer performance now allow numerical flow modeling over large stream domains. However, there has been limited testing of whether channel topography can be remotely mapped with accuracy necessary for such modeling. We assessed the ability of the Experimental Advanced Airborne Research Lidar, to support a multi‐dimensional fluid dynamics model of a small mountain stream. Random point elevation errors were introduced into the lidar point cloud, and predictions of water surface elevation, velocity, bed shear stress, and bed mobility were compared to those made without the point errors. We also compared flow model predictions using the lidar bathymetry with those made using a total station channel field survey. Lidar errors caused < 1 cm changes in the modeled water surface elevations. Effects of the point errors on other flow characteristics varied with both the magnitude of error and the local spatial density of lidar data. Shear stress errors were greatest where flow was naturally shallow and fast, and lidar errors caused the greatest changes in flow cross‐sectional area. The majority of the stress errors were less than ± 5 Pa. At near bankfull flow, the predicted mobility state of the median grain size changed over ≤ 1.3% of the model domain as a result of lidar elevation errors and ≤ 3% changed mobility in the comparison of lidar and ground‐surveyed topography. In this riverscape, results suggest that an airborne bathymetric lidar can map channel topography with sufficient accuracy to support a numerical flow model.