267 Advances in Fluvial Processes and Sediment Transport (Posters)

We encourage submissions on fluvial geomorphology, fluvial processes, and sediment transport including field studies, numerical modeling, physical modeling, and spatial analyses.

Wednesday, 22 October 2025
8:00 AM - 5:30 PM
HBGCC, Hall 1

A Fluvial Sediment Budget for the Western Arm of Lake Superior

Paper number: 267-3
Program: Technical Sessions
Time: 8:00 AM – 8:00 AM

Authors

  • Michael Park Presenting Author
    University of Minnesota - Duluth, Duluth, Minnesota
  • Karen Gran
    University of Minnesota - Duluth, Duluth, Minnesota
  • John Swenson
    University of Minnesota - Duluth, Duluth, Minnesota
  • Nick Munoz
    University of Minnesota - Duluth, Duluth, Minnesota

Abstract

Minnesota and Wisconsin Points are baymouth bars at the St. Louis River estuary maintained by coarse sediments delivered via longshore drift from the north and south shores of Lake Superior. Minnesota Point is presently developed with hundreds of properties and two entry points to the Duluth-Superior Harbor. Prior study has found that Minnesota Point is currently starved of sediment due to harbor infrastructure impeding longshore sediment transport and is systematically drowned by lake level rise driven by post-glacial isostatic rebound. Conversely, Wisconsin Point is a zone of net deposition due to position relative to harbor infrastructure. Coastal bluff erosion in this region is an important source of sediment to this system. Due to a lack of systematic regional analysis, however, sediment delivered to Lake Superior by rivers has been considered insignificant. We hypothesize that rivers draining to Lake Superior contribute a nontrivial quantity of coarse sediment to this system and should be considered in the management of Minnesota Point. To improve understanding of sediment dynamics in this region, we seek to develop a fluvial sediment budget of the western arm of Lake Superior by compiling existing and novel datasets. We have conducted field surveys of over 50 riverbank slumps and identified several glacial deposits as primary fluvial sediment sources, with samples collected to characterize grain size distributions. Two machine learning models developed by the United States Geological Survey can yield volumetric sediment loads of study area watersheds in Minnesota in terms of suspended sediment concentration and bedload. We will use GIS-based analyses and existing stream gaging data to extend the Minnesota-based machine learning models to south shore streams in Wisconsin. We will couple results from grain size analyses of source sediments with modelling outputs and existing datasets to determine the volume of clay, silt, sand and gravel regularly delivered to the western arm of Lake Superior by rivers.

Geological Society of America Abstracts with Programs. Vol. 57, No. 6

doi: 10.1130/abs/2025AM-412578

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