Distinguishing hydraulically-distinct floodplain types from high resolution topography with implications for broad-scale flood routing (data)

Floodplains can have a significant impact on the routing of flood waves across the landscape, yet their representation in broad-scale water resource and flood prediction models are limited. To identify hydraulically-relevant floodplains at scale, we develop a workflow that automates the extraction of reach-averaged morphologic features from high resolution topographic data hypothesized to define a zone within the floodplain that conveys floodwaters distinctly from the surrounding landscape. This zone is identified from departures in hydraulic geometry with stage. Working in the topographically diverse Lake Champlain Basin in Vermont, USA, we apply the workflow to 2,629 reaches and use the extracted features to cluster settings similar in their proposed ability to route floodwaters. In total we identified eight clusters of reach types, two that were pre-sorted and largely lack a floodplain, and six that reflect variability in floodplain features, which were parsed out from the K-medoids clustering analysis. Clusters of floodplain types had distinct impact on the routing of synthetically-derived hydrographs, evaluated using the Muskingum-Cunge routing model. From these clusters we propose a Hydraulic Floodplain Classification, which is comparable to other geographically-defined systems but unique in its focus on the potential of the landscape to influence flood routing. The automated workflow may be repeated in other regions with high resolution topographic datasets, offering an improvement in the functionality of continental to global 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.