Browsing by Subject "Rivers"

Now showing 1 - 5 of 5
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    Defining stream integrity using biological indicators
    (2012-09) Dolph, Christine Laurie
    Biological indicators may offer the most comprehensive and accurate means to assess the integrity of streams and rivers, as changes in a biological community represent an integrated response to all environmental stressors present in an ecosystem. Biological indicators are typically designed to quantify and=or summarize important aspects of either ecosystem structure – the types and abundance of organisms found in a given habitat – or ecosystem function – rates and patterns of ecological processes such as primary and secondary production, nutrient cycling, and decomposition of organic matter. Increasingly, resource managers use such indicators to assess whether surface waters fulfill the requirements of their designated uses under the Clean Water Act. Despite the recognition that biological indicators can aid management decisions, critical questions remain regarding the best way to design, apply, and interpret them. In this dissertation, I used a suite of statistical and empirical approaches to evaluate the design and application of several different biological indicators of stream condition in various contexts and scales across Minnesota. Specifically, I used a bootstrap approach, together with a database of fish, macroinvertebrate, and environmental data collected by the Minnesota Pollution Control Agency (MPCA) between 1996 and 2006 from approximately 1500 stream sites across Minnesota, to quantify variability associated with an Index of Biological Integrity (IBI) developed by MPCA for fish communities in streams of two Minnesota river basins. I placed this variability into a management context by comparing it to impairment thresholds used in water quality determinations for Minnesota streams. I used the same MPCA dataset to develop predictive taxa richness models for fish and macroinvertebrates as additional indicators of the biological integrity of Minnesota streams, and evaluated these models for sensitivity and precision. I further determined whether fish and macroinvertebrate assemblages exhibited significant community concordance, and whether significantly concordant communities yielded equivalent indications of stream integrity at three nested spatial scales (statewide, ecoregion and catchment) in Minnesota. Finally, I used data from the MPCA database to evaluate relationships between selected environmental variables and the composition of fish and macroinvertebrate assemblages at all three spatial scales. I collected a second dataset of macroinvertebrate samples over the course of one year (2010) from three agricultural streams in southern Minnesota to evaluate relationships between structural and functional indicators of stream condition in response to a common stream conservation practice (i.e., reach-scale restoration). Specifically, I examined whether reach-scale restoration in disturbed agricultural streams in southern Minnesota was associated with changes in (1) macroinvertebrate taxa richness, (2) seasonal variability in macroinvertebrate community composition, and (3) secondary production (i.e., macroinvertebrate biomass over time). SUMMARY OF FINDINGS: 1. I found that 95% confidence intervals for IBIs scored on a 0-100 point scale ranged as high as 40 points. However, on average, 90% of IBI scores calculated from bootstrap replicate samples for a given stream site yielded the same impairment status as the original IBI score. I suggest that sampling variability in IBI scores is related to both the number of fish and the number of rare taxa in a field collection. A comparison of the effects of different scoring methods on IBI variability indicates that a continuous scoring method may reduce the amount of bias in IBI scores. 2. Predictive taxa-loss models for fish and macroinvertebrates both distinguished reference from non-reference sites. Predictive models for fish assemblages were less sensitive and precise than models for invertebrate assemblages, likely because of a relatively low number of common fish taxa. Significant concordance between fish and invertebrate communities occurred at the statewide scale as well as in six of seven ecoregions and 17 of 21 major catchments examined. However, concordance was not consistently indicative of significant relationships between rates of fish and invertebrate taxa loss at those same scales. Fish and invertebrate communities were largely associated with different environmental variables, although the composition of both communities was strongly correlated with stream size across all three scales. 3. I found no difference in macroinvertebrate taxa richness between restored and unrestored reaches of agricultural streams in southern Minnesota. However, both compositional similarity and secondary production were higher in restored reaches relative to unrestored reaches, suggesting that reach-scale restoration may have ecological effects beyond influences on diversity. These findings highlight the added complexity conveyed by a consideration of functional, as well as structural, indicators of stream condition. Higher productivity in the restored reaches was due largely to the disproportionate success of a small number of dominant taxa. Secondary production estimates were considerably lower than those reported for other similar-sized prairie streams; these low values may be indicative of stressful conditions for biotic life in the study streams.
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    Identifying Erosional Hotspots in Streams along the North Shore of Lake Superior, Minnesota using High-Resolution Elevation and Soils Data
    (2013) Wick, Molly Jane
    This is a University of Minnesota Water Resources Science master’s thesis describing original research to determine fluvial erosion in three coastal streams (Amity, Talmadge and French) of Minnesota’s Lake Superior shoreline. All three streams have elevated levels of turbidity, with potential for damage to fisheries. The goal of this project was to develop a GIS-based model using new, openly-available, high-resolution LiDAR datasets to predict erosional hotspots at a reach scale. The abstract summarizing the study’s key findings is extracted and reproduced below. Abstract: “Many streams on the North Shore of Lake Superior, Minnesota, USA, are impaired for turbidity driven by excess fine sediment loading. The goal of this project was to develop a GIS-based model using new, openly-available, high-resolution remote datasets to predict erosional hotspots at a reach scale, based on three study watersheds: Amity Creek, the Talmadge River, and the French River. The ability to identify erosional hotspots, or locations that are highly susceptible to erosion, using remote data would be helpful for watershed managers in implementing practices to reduce turbidity in these streams. “Erosion in streams is a balance between driving forces, largely controlled by topography; and resisting forces, controlled by the materials that make up a channel’s bed and banks. New high-resolution topography and soils datasets for the North Shore provide the opportunity to extract these driving and resisting forces from remote datasets and possibly predict erosion potential and identify erosional hotspots. We used 3-meter LiDAR-derived DEMs to calculate a stream power-based erosion index, to identify stream reaches with high radius of curvature, and to identify stream reaches proximal to high bluffs. We used the Soil Survey Geographic (SSURGO) Database to investigate changes in erodibility along the channel. Because bedrock exposure significantly limits erodibility, we investigated bedrock exposure using bedrock outcrop maps made available by the Minnesota Geological Survey (MGS, Hobbs, 2002; Hobbs, 2009), and by using a feature extraction tool to remotely map bedrock exposure using high-resolution air photos and LiDAR data. “Predictions based on remote data were compared with two datasets. Bank Erosion Hazard Index surveys, which are surveys designed to evaluate erosion susceptibility of banks, were collected along the three streams. In addition, a 500-year flood event during our field season gave us the opportunity to collect erosion data after a major event and validate our erosion hotspot predictions. Regressions between predictors and field datasets indicate that the most significant variables are bedrock exposure, the stream power-based erosion index, and bluff proximity. A logistic model developed using the three successful predictors for Amity Creek watershed was largely unsuccessful. A threshold-based model including the three successful predictors (stream power-based erosion index, bluff proximity, and bedrock exposure) was 70% accurate for predicting erosion hotspots along Amity Creek. The limited predictive power of the models stemmed in part from differences in locations of erosion hotspots in a single large-scale flood event and long-term erosion hotspots. The inability to predict site-specific characteristics like large woody debris or vegetation patterns makes predicting erosion hotspots in a given event very difficult. A field dataset including long-term erosion data may improve the model significantly. This model also requires high resolution bedrock exposure data which may limit its application to other North Shore streams.”
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    Source, Winter 2007
    (University of Minnesota Extension, 2007) University of Minnesota Extension
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    Three-Dimensional Simulation of Bridge Foundation Scour on Mississippi River Bridges 9321 & 27801
    (Center for Transportation Studies, University of Minnesota, 2016-02) Sotiropoulos, Fotis; Khosronejad, Ali
    We present data-driven numerical simulations of 100- and 500-year floods events in the Mississippi River at its intersection with the Highway I-694 by coupling coherent-structure resolving hydrodynamics with bed morphodynamics under live-bed conditions. The study area is about 1.7 miles long and 220 yard wide reach of the Upper Mississippi River, near Minneapolis MN, which contains several natural islands and man-made hydraulic structures. We employ the large-eddy simulation (LES) and bed-morphodynamic modules of the Virtual Flow Simulator (VFS-Rivers) model, a recently developed in-house code, to investigate the flow and bed evolution of the river along the reach and near the bridge piers BR 27801 and BR 932. We integrate data from airborne Light Detection and Ranging (LiDAR), sub-aqueous sonar apparatus on-board a boat and total station survey to construct a digital elevation model of the river bathymetry and surrounding flood plain, including islands and bridge piers. A field campaign under base-flow condition is also carried out to collect mean flow measurements via Acoustic Doppler Current Profiler (ADCP) to validate the hydrodynamic module of the VFS-Rivers model. Our simulation results for the bed evolution of the river under the 100- and 500-year flood reveal complex sediment transport dynamics near the bridge piers consisting of both scour and refilling events due to the continuous passage of sand dunes. A brief description of the findings in terms of maximum scour depth around individual bridge piers can be found in the executive summary of the report.
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    Topography, image, and flow model data for experimental density currents, St. Anthony Falls Laboratory, 2015-2017
    (2018-01-08) Limaye, A. B.; Grimaud, J.-L.; Lai, S. Y. J.; Foreman, B. Z.; Komatsu, Y.; Paola, C.; aslimaye@umn.edu; Limaye, A. B.
    Submarine channels convey turbidity currents, the primary means for distributing sand and coarser sediments to the deep ocean. In some cases, submarine channels have been shown to braid, similarly to rivers. Yet the strength of the analogy between the subaerial and submarine braided channels is incompletely understood. This data set includes topography, image, and flow model data for six experiments with subaqueous density currents and two experiments with subaerial rivers. The experiments were conducted to quantify (1) submarine channel kinematics, and (2) the responses of channel and bar geometry to subaerial versus submarine basin conditions, inlet conditions, and the ratio of flow-to-sediment discharge (Qw/Qs).The data set accompanies a 2018 publication in the journal Sedimentology.