Identifying Hydraulically Distinct Floodplain Types From High Resolution Topography With Implications for Broad-Scale Flood Routing

Floodplains can significantly impact the routing of flood waves across the landscape, however, their representation in broad-scale water resource and flood prediction models is limited. To identify hydraulically relevant floodplains at scale, we developed a workflow to automatically extract reach-averaged topographic features from high resolution (1-m) LiDAR-derived topographic data. These features were identified from departures in the relationship between hydraulic geometry and flood stage and hypothesized to define and characterize a zone within the floodplain that disproportionately dissipates energy and attenuates floodwaters, called the Energy Dissipation Zone. We applied the workflow in the topographically diverse Lake Champlain Basin in Vermont, USA, and used a K-medoids analysis to cluster reaches into distinct feature-based types that were expected to uniquely route hydrographs. In total, we identified eight clusters of reach types: two that were pre-sorted because of the presence of a waterbody or limited floodplain access and six that reflected variability in reach-averaged mesoscale floodplain features that describe the size and shape of the Energy Dissipation Zone. Reach types had distinct impacts on the attenuation of synthetically derived hydrographs, evaluated using the Muskingum-Cunge method. From these clusters, we propose a Hydraulic Floodplain Classification, which is comparable to other geomorphically defined systems but novel in its focus on the landscape potential to influence flood routing. The automated workflow is repeatable and has the potential to improve the functionality of continental floodplain mapping efforts. Identification of hydraulically effective zones has implications for improved watershed management to meet flood resiliency goals and to improve flood predictions and warnings.