A Scalable Approach for Identification of Reach-Scale Hydraulic Processes to Support Flood Prediction Models

Abstract

Simplification of channel routing models results in errors in streamflow predictions and uncertain flood forecasts. Conceptual frameworks have been proposed to prescribe a heterogeneous routing scheme that incorporates greater complexity where necessary, but their implementation is constrained by the need for hydraulic data that is not widely available. To address this limitation, we use reach-scale classifications to identify the least complex routing configuration appropriate for each reach. Focusing on seven reach types that differ in topographic characteristics hypothesized to influence routing behavior, we demonstrate that dimensionless scaling parameters, which are indicative of the appropriate flood wave approximation, are distinct among reach types. These results suggest that topographically defined reaches, more readily mapped at broad scales than hydraulic processes, can enable operationalization of heterogeneous routing schemes. We demonstrate regional proof of concept and identify the optimal routing configuration in Lake Champlain Basin, VT. Spatially variable routing across a river network strongly affects model outcomes; we observed a 108% difference in reach-scale flood peak attenuation between the simplest and most complex configurations. By improving representation of flood routing dynamics in broad scale models, this framework enables efficient modeling schemes that represent natural landscape variability, supporting more reliable flood hazard assessments.