ABSTRACT:

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.

ABSTRACT:

Graphs are an efficient data structure for representing and analyzing river network network topology. Such topology, and its associated feature-space, can provide insight into the diversity of hydrologic responses seen across catchments. This dataset contains binary tree representations of fifth-order North American rivers. The network data was extracted from the HydroRIVERS dataset of Lehner & Grill, 2013. Node metadata includes hyriv_id, latitude, longitude, and subbasin ID. Edge metadata includes length (km), drainage area (sq.km.), strahler order.

ABSTRACT:

companion dataset to "A DURATION-OVER-THRESHOLD MODEL FOR FLOOD FREQUENCY AND FLOW REGIME CHARACTERIZATION"

We investigated event-specific discharge-duration dynamics at 33 USGS stream gages within the US state of Vermont. Building on the method of Feng et al. 2017, flood events from 15-minute discharge timeseries were extracted using an automated threshold method, and a statistical model was fit at each gage for both frequency of discharge exceedance and conditional duration of discharge exceedance. This Duration-Over-Threshold model can estimate the arrival rate of a flowrate threshold, q, being exceeded for a given duration, d.

GitHub repository: https://github.com/sclaw/duration-over-threshold

ABSTRACT:

Topographic signatures are characterizations of reach-averaged hydraulic behavior that summarize the ease with which a river spills out into adjacent terrain. Using 1m DEM data for the state of Vermont and NHDPlus subcatchments, we generated topographic signatures for ~3,000 reaches within the Lake Champlain Basin of Vermont. These topographic signatures will be used in a machine-learning analysis to explore emergent properties of floodplain-channel connectivity that influence flood routing.