Response and Recovery of Streams From an Extreme Flood

Abstract:

In temperate regions, channels are expected to recover from intense floods in a matter of months to years, but quantitative empirical support for this idea remains limited. Moreover, existing literature fails to address the spatial variability of the recovery process. Using an emerging technology, we investigate the immediate response to and progressive recovery of channels in the Northeastern United States from an extreme flood. We seek to determine what factors, including the nature and extent of the immediate response of the channel to the flood and post-flood availability of sediment, contribute to the spatial variability of the rate of recovery. Taking advantage of the 2011 flooding from Tropical Storm Irene, for which pre- and post-flood aerial lidar exist, along with a third set of terrestrial lidar collected in 2015, we assess channel response and recovery with multi-temporal lidar comparison. This method, with kilometers of continuous data, allows for analysis beyond traditional cross-section and reach-scale studies. Results indicate that landscape-scale factors, such as valley morphology and gradients in unit stream power, are controls on channel response to the flood, producing spatially variable impacts. Along a 16.4-km section (drainage area = 82 km²) of the Deerfield River in Vermont, over 148,000 m³ or erosion occurred during the flood. The spatial variation of impacts was correlated (R²= 0.476) with the ratio of channel width to valley width. We expect the recovery process will similarly exhibit spatial variation in rate and magnitude, possibly being governed by gradients in unit stream power and sediment availability. We test the idea that channel widening during the flood reduces post-flood unit stream power, creating a pathway for deposition and recovery to pre-flood width. Flood-widened reaches downstream of point-sources of sediment, such as landslides, will recover more quickly than those without consistent sediment supply. Results of this study will improve our ability to predict the nature and location of flood impacts and determine what factors contribute to the spatial variability of channel recovery.