IDENTIFYING EROSIONAL HOTSPOTS IN DULUTH-AREA STREAMS AFTER THE 2012 FLOOD USING HIGH-RESOLUTION REPEAT AERIAL LIDAR DATA

During June 19^th-20^th 2012, northeastern Minnesota experienced a record rainfall event, causing soil saturation and inundation, slope failures, flash flooding, and damage to public infrastructure. Geomorphic effects of the flood included severe stream bank and bluff erosion and landsliding. The purposes of this study are to investigate which reaches in Duluth-area streams experienced significant geomorphic change as a result of the 2012 flood and to determine the role of human modifications to the channel network on erosional hotspots at the reach scale. Aerial lidar data collected before and after the flood were used to map out locations of significant geomorphic change. Lidar images were filtered in GeoNet to remove noise in low-gradient areas and enhance geomorphic features. We then used the Geomorphic Change Detection (GCD) program to subtract subsequent images creating DEMs (digital elevation models) of difference (DoDs). DoDs were used to identify locations with significant erosion and deposition, and quantify the volume of eroded and deposited sediment. To predict places that were highly susceptible to erosion in the flood due to natural topographic features, we used a predictive erosional model based on stream power, angle of impingement, bluff proximity, and substrate erodibility. We predict places with high stream power and angle of impingement values near erodible bluffs are natural erosional hotspots and likely had significant geomorphic change in the flood. However, infrastructure like bridges and culverts also caused significant geomorphic change. We compare DoD results with locations of predicted natural hotspots and infrastructure maps to determine what fraction of geomorphic change was likely the result of human modifications vs. natural topographic forcings. We are verifying GIS-based erosional maps with field observations. This thesis hopes to offer the City of Duluth useful data on causes of channel change in specific reaches, helping with future stream restoration efforts.