Authors: Andrew Vanderheiden*, Texas A&M University, Nicole Hernandez*, Texas A&M University, Haoyan Chen*, Texas A&M University, Billy Hales, Texas A&M University, Cesar Castillo , Texas A&M University
Topics: Physical Geography, Environmental Science, Water Resources and Hydrology
Keywords: river, channel, bankfull, geometry, geomorphometry, LiDAR, DEM, GIS
Session Type: Poster
Start / End Time: 8:00 AM / 9:40 AM
Room: Lincoln 2, Marriott, Exhibition Level
Presentation File: No File Uploaded
Flow monitoring along many rivers is still lacking and this complicates the identification of the flows most associated with channel adjustment. This knowledge gap has driven the use of several methods to estimate critical river stages using geomorphometric analyses of the channel bank geometry. This study aims to further understand linkages in estimated flow stages with differing channel-floodplain attributes by objectively implementing classical bankfull estimation methods and a novel method that we developed to estimate top-of-bank flow. Conducted on densely-sampled transects produced from high-resolution LiDAR digital elevation models (DEMs), our analysis of the channel geometry of the Mission River, which is a lowland meandering river on the Coastal Bend of Texas, suggests that all classical methods demonstrate a general agreement in bankfull dimensions estimated from banks whose transects are closely spaced together along the channel. LiDAR DEMs sampled at 1-2m yield results with apparent oversampling in the cross-channel dimension. In addition, a number of these methods define the top of bank erroneously in locations that are affected by terracing for portions of the reach with a larger channel. The methodology developed in this study has promise to assist researchers to assess the efficacy of geomorphometric bankfull estimation methods and to identify potential bias that may occur in the presence of complex river features and sampling schemes.