Author: Steven White, Anzy Lee, Belize Lane – Utah State University; Greg Pasternack – University of California, Davis
Title: Upscaling: Cross-Sectional Topographic Survey to Representative River Channels
Abstract: Representative channel and floodplain morphology, and their associated hydraulic attributes are critical for hydrological and flood inundation predictions. Current geospatial and remote sensing datasets and software tools facilitate the identification and accurate topographic representation of river channels. However, in the absence of high-resolution, bathymetric datasets (e.g., LiDAR/sonar), the question remains, how do we accurately represent areas without high-resolution data coverage?
Previous work has demonstrated the ability to reverse-engineer a representative 3D channel that exhibits comparable hydraulic functionality to the original high-resolution survey using RiverBuilder, a river channel modeling software. Additionally, the importance of sub-reach variability of hydraulic attributes cannot be overlooked, as their importance for identifying hydraulic controls in the context of flood inundation predictions is paramount; thus, the purpose of this work is to expand on existing topo-bathymetry modelling frameworks that assume simple channel geometry (e.g., rectangle, trapezoid, etc.) and/or discount sub-reach hydraulic variability. We developed river channels using RiverBuilder that contain critical hydraulic attributes and accurately represent sub-reach variability of said attributes using low-resolution datasets (e.g., cross-sectional survey data) to improve the identification of hydraulic controls.