Abstract

The United States Environmental Protection Agency (USEPA) has listed much of the Upper Mississippi River (UMR) basin as impaired waters due to excessive turbidity, sedimentation, and nutrient loading. Of particular importance are the associated environmental problems (e.g. eutrophication, habitat and wetland loss, loss of biodiversity, and changes in water quality) that have developed within Lake Pepin, a popular recreational riverine lake of the UMR. Three major drainages contribute to these issues and empty in to the UMR near Lake Pepin - the Minnesota River Basin (MRB), St. Croix River, and UMR. The MRB makes up approximately one-third of the drainage area above Lake Pepin, but has been found to contribute approximately 85-90% of all sediment entering the lake – both in the past and present. A major tributary system of the MRB, the Blue Earth River Basin (BERB) and its subbasins, contribute as much as half of the sediment exiting the Minnesota River, despite accounting for only one-fifth of the MRB drainage area. The tremendous sediment yields from this basin are a result of both post-glacial landscape evolution and contemporary land-use practices. Recent radioisotopic fingerprinting of these sediments has helped narrow the focus of mitigations strategies as they indicate that the majority of the sediment originates from near-channel sources in the MRB, specifically ravines and bluffs. Significantly, it was also found that the rate of sedimentation has increased ten-fold over the past 150 years. Thus, mitigations strategies to curtail the sediment yields arriving downstream should focus on the near-channel sources of the BERB and its subbasins. Unfortunately, the resolution of radioisotopic methods is inadequate in locating of specific near-channel sources on which to implement mitigation strategies. Therefore, a crucial first step of an effective mitigation strategy to reduce erosion is to develop a methodology that aids in identifying the precise geographic position of ravines and bluffs with high erosion potential. This study uses Geographic Information Systems (GIS) to compile county Light Detection and Ranging (LiDar) and elevation, watershed and stream network, county infrastructure (private and public buildings and roads), county and watershed soil, county and watershed land use data in the BERB and its subbasins, to attempt to locate precise locations of ravines and bluffs with high erosion potential. Using two LiDar data sets taken in 2005 and 2012, and incorporating net sediment loss, slope grade, soil material, soil texture, connectivity to river, distance to river, surrounding adjacent land use, proximity and threat to roads, proximity and threat to public and private buildings, accessibility from roads, visibility from stream, and visibility from roads; 14 ravines and 10 bluffs were identified in the BERB, and 18 ravines and 29 bluffs were identified in the BERB, the Le Sueur River Basin (LSRB). These ravine and bluff sites exhibited an abundant amount of erosion between 2005 and 2012. As a baseline study, a comprehensive review of hydrologic and sediment transport models and stabilization techniques were completed to provide natural resource managers tools to stabilize and effectively manage these erosive sites. Preliminarily, this thesis study provides an effective protocol for identifying potential mitigation/stabilization sites that are not readily accessible with conventional surveying equipment. The models and stabilization techniques reviewed are effective strategies for watershed management in highly geomorphically active regions. Moving forward, a future LiDar dataset is recommended for further temporal and spatial analysis of the identified sites. Moreover, long-term monitoring of selected sites are recommended in order to isolate parameters to model erosion events, determine rates of change, and further understand the evolution of the landscape for effective watershed management.

Advisor

Shannon J. Fisher

Committee Member

Phillip H. Larson

Committee Member

Christopher T. Ruhland

Date of Degree

2015

Language

english

Document Type

Thesis

Degree

Master of Science (MS)

Department

Biological Sciences

College

Science, Engineering and Technology

Creative Commons License

Creative Commons Attribution-NonCommercial 4.0 International License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License

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