Thesis (Ph. D.)--University of Missouri-Columbia, 2004. / Typescript. Vita. Includes bibliographical references (leaves 90-97). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 2004. / Typescript. Vita. Includes bibliographical references (leaves 90-97). Also available on the Internet.

Since the discovery of Viral Hemorrhagic Septicemia (VHS) in the Great Lakes in 2005, the assessment of its ability to spread amongst connected watersheds has been at the forefront of VHS management. This project was designed to determine a rate of passage of VHS-susceptible fish species between coastal Lake Michigan and its harbors and the artificial waterways in the Chicago metropolitan area. This information can be used to assess the potential for VHS to spread into the waterways, which drain into the Illinois River watershed. Although fishes (e.g. Round Goby and occasionally salmonids) are known to have moved from Lake Michigan into the Illinois River via the Chicago Area Waterway System (CAWS), the rate of fish passage from the lake into the waterway system is unclear. To directly assess fish movement, a total of 1216 fish were collected, tagged, and returned to Lake Michigan harbors (532, 43.8% of total) and Lake Calumet (684, 56.2%), an adjacent lake connected to Lake Michigan via the CAWS. Fishermen reports, Illinois Department of Natural Resources (IDNR) sampling, and subsequent electrofishing sampling trips yielded 51 recaptured fish (4.2% of tagged fish). Of these, 2 fish were recaptured below the O¡¯Brien Lock and Dam in the Calumet River (south of Lake Michigan and Lake Calumet) and 49 fish were recaptured in the location at which they were originally tagged. To further assess movement of VHS susceptible species between Lake Michigan and the CAWS, otoliths were collected from 375 small-bodied fish (<150 mm total length) captured in the CAWS and analyzed for ¥ä©ö©øC to determine the origin (Lake Michigan or CAWS) of these fish. Fifty-six percent of small-bodied fishes collected from the Calumet River were immigrants from Lake Michigan, whereas 35% of fish collected from the Chicago River and 28% of fish collected from the North Shore Channel were immigrants. Results indicate that fishes (particularly small-bodied species such as Round Goby) move between VHS-positive Lake Michigan into the VHS-negative Chicago area waterways and represent a potential vector for VHS to spread into the inland waters of Illinois. However, the lack of movement of fishes from Lake Michigan into the Des Plaines River and further downstream waters also indicates a watershed-based approach to managing VHS in Illinois waters rather than simply designating the entire state as VHS-affected due to positive samples in Lake Michigan, may be valid. VHS surveillance should be continued in the CAWS to ensure the status of these water bodies as ¡°VHS positive¡± or ¡°VHS negative¡± is accurate, as this is useful for informing the public and creating policies and regulations to attempt to slow the spread of this disease.

Thesis advisor: Martha Carlson Mazur / Rivermouths are dynamic systems characterized by hydrologic mixing, where water, energy, sediment and nutrients from both river and receiving water unite to form a unique yet variable environment. Water levels in these environments are thus defined by, and subject to, streamflow from the river and lake-level fluctuations. Long-term fluctuations in water levels affect hydrogeomorphic structure, as well as wetland structure, distribution, and composition. A better understanding of these dynamics will help us to comprehend the processes that govern changes in wetland area and, thus, the breadth of the ecosystem services that estuarine wetlands provide. To this end, this study examined how wetland plant communities have changed through time in relation to long-term changes in water levels from both river and lake systems, using historic aerial photograph interpretation in three rivermouths on Lake Michigan. Additionally, the observed patterns of historic water levels and streamflows were used to inform our predictions for the future in light of climate changes. Results showed that higher water levels and peak streamflows led to less wetland area; average streamflow did not play a statistically detectable role in rivermouths that had lake-dominated morphologies but was significant in the rivermouth system that was riverine dominated. This suggests that varying rivermouth morphologies respond differently to lake and stream dynamics. Restoration decisions that take rivermouth morphology into account will be important as these systems continue to change both naturally and due to climate or other anthropogenic disturbances. It is important to realize not only the extent to which humans are affecting rivermouth systems, but also the interplay between water levels, streamflows, hydrogeomorphology, and wetland ecology within these systems themselves, so as to better understand the necessary steps for restoration. / Thesis (BS) — Boston College, 2013. / Submitted to: Boston College. College of Arts and Sciences. / Discipline: Geology & Geophysics Honors Program. / Discipline: Earth and Environmental Science.

Waves are a primary factor in beach health, sediment transport, safety, internal nutrient loading, and coastal erosion, the latter of which has increased along Lake Michigan's western coastline since 2014. While high water levels are undoubtedly the primary cause of this erosion, the recent losses may also be indicative of changes in the lake's wind-driven waves. This study seeks to examine long-term trends in the magnitude and direction of Lake Michigan waves, including extreme waves and storm events using buoy measurements (National Data Buoy Center Buoys 45002 and 45007) and the United States Army Corps of Engineers Wave Information Study (USACE WIS) wave hindcast.<br><br>Tests show significant long-term decreases in annual mean wave height in the lake's southern basin (up to -1.5mm/yr). When wave-approach direction was removed by testing directional bins for trends independently, an increase in the extent of the affected coast and rate of the shrinking waves was found (up to -4mm/yr). A previously unseen increasing trend in wave size in the northern basin (up to 2mm/yr) was also revealed.<br><br>Data from the WIS model indicated that storm duration and peak wave height in the southern basin has decreased at an averaged rate of -0.085hr/yr and -5mm/yr, respectively, from 1979 to 2017. An analysis of the extreme value distribution's shape in the southern basin found a similar pattern in the WIS hindcast model, with the probability of observing a wave larger than 5 meters decreasing by about -0.0125yr^-1. In the northern basin, the probability of observing a wave of the same size increased at a rate of 0.0075yr^-1.<br><br>The results for trends in the annual means revealed the importance of removing temporal- and spatial-within-series dependencies, in wave-height data. The strong dependence of lake waves on approach direction, as compared to ocean waves, may result from the relatively large differences in fetch length in the enclosed body of water. Without removal or isolation of these dependencies trends may be lost. Additionally, removal of the seasonal component in lake water level and mean wave-height series revealed that there was no significant correlation between these series.

<p>Little work has been done to estimate turbulence characteristics in the hypolimnetic waters of large lakes, where the magnitude and vertical structure of turbulent parameters have important implications for nutrient cycling and benthic exchange. In this thesis, hypolimnetic mixing is investigated over the annual stratification cycle in a large lake using a series of experiments in Lake Michigan that utilize acoustic Doppler velocimeters, thermistors, and microstructure profilers to characterize mean flow and turbulence throughout the water column. More than 500 days of physical limnological data were collected and analyzed over the course of this study, creating the most comprehensive data set of its kind in the Laurentian Great Lakes. While we found that bottom boundary layer turbulence and mean flow follow law-of-the-wall predictions in the mean, individual estimates were shown to deviate significantly from canonical expectations, with deviations linked to weakly energetic flow conditions (i.e. low speeds) and seiche-scale flow unsteadiness. Bottom boundary layer characteristics, including the mean current speed (U₅₀=3 cm/s), drag coefficient (Cd₅₀=0.0052), and turbulent kinetic energy dissipation (ϵ₅₀ =10^-8 W/kg), showed very little seasonal variation, despite highly variable surface forcing (e.g. stratification, wind speeds). Full water column turbulence profiles measured during the stratified summer were largely buoyancy suppressed, with internal Poincaré waves driving enhanced turbulent kinetic energy dissipation (ϵ= 10^-7 W/kg) in the relatively compact thermocline and weak hypolimnetic mixing (turbulent scalar diffusivity: K_z=10^-6 m²/s) limiting benthic nutrient delivery. Although small temperature gradients drove strong mixing over the isothermal period (K_z=10^-3 m²/s), velocity shear was overwhelmed by weakly stable stratification (Richardson number:Ri≈0.2), limiting the development of the surface mixed layer and suppressing hypolimnetic turbulence (ϵ=10^-9 W/kg; K_z=10^-4 m²/s). When surface temperatures fell below the temperature of maximum density (T_MD≈ 4℃), radiative convection played a major role in driving vertical transport, with energetic full water column mixing throughout the day followed by surface cooling and restratification overnight. During this “convective winter” period, daily temperature instabilities were directly correlated with elevated turbulence levels (ϵ=10^-7 W/kg; K_z≈10^-1 m²/s), and overnight turbulence characteristics were similar to those observed over the isothermal spring. Near surface dissipation and diffusivity measurements followed similarity scaling arguments, with wind shear and surface fluxes dominating production in the surface mixed layer during all three seasons. Together, these results are used to model the influence of invasive dreissenids over each forcing period, providing insight into the annual variability of effective filtration rates in the calm, hypolimnetic waters of Lake Michigan.</p><p></p>

<p dir="ltr">Recent high-water levels in Lake Michigan caused extensive shoreline changes along the Indiana coastline. To evaluate recent shoreline changes of the Indiana coastline along Lake Michigan, topographic LiDAR surveys available for the years 2008, 2012, 2013, 2018, 2020, and 2022 were analyzed. This study included LiDAR data of over 400 cross-shore transects, generated at 100 m spacing. Beach profiles were generated to detect the shoreline position and quantify beach width and nearshore volume change. The analysis revealed accretion of both shoreline and beach width from 2008 to 2013 during a low water level period. The beach was rebuilt with a median increased value of 4 m. On the contrary, the shoreline eroded during increasing and high-water periods. Both shoreline and beach width receded with median values of 41 m and 32 m respectively during the period of water level increase from 2013 to 2020. Consequently, the beach profiles lost a median sand volume of 21.6 m³/m. Overall, the Indiana shoreline moved with a median of 18 m landward from 2008 to 2022. However, there was a large amount of spatial variability in the shoreline changes. The shoreline movement varied spatially between 63 m recession to 29 m accretion. Similarly, beach profiles showed a loss of median sand volume of 10 m³/m. The volume change ranged from 918 m³/m loss to 296 m³/m accumulation varying spatially along the shoreline. The largest sand loss was experienced at the downdrift of Michigan city harbor near Mt. Baldy. In addition to the spatial variation, the recession also varied slightly with shoreline type. The natural and hardened beaches were mostly recessional. The recession along the hardened shoreline was influenced by the timing of construction and its proximity to inland areas. Buffered beaches, characterized by a swath of vegetation or dunes, experienced the least erosion.</p>

No description available.

<p dir="ltr">The recent surge in water levels within the Great Lakes has laid bare the vulnerability of the surrounding coastal areas. Over the past few years, communities along the Great Lakes coast have struggled with widespread coastal transformations, witnessing phenomena such as shoreline retreat, alterations in habitat, significant recession of bluffs and dunes, infrastructure and property damage, coastal flooding, and the failure of coastal protection structures. Unlike the ocean coasts, the Great Lakes coastal regions experience a unique confluence of large interannual water level fluctuations, coastal storms, and ice cover dynamics, which complicates the ongoing coastal management endeavors. To address this multifaceted challenge, the interplay between all these factors and their impact on coastal changes should be understood and applied to improve the resilience of Great Lakes coastal areas.</p><p><br></p><p dir="ltr">In this dissertation, several steps were taken to improve knowledge of coastal processes in the Great Lakes, spanning from the initial use of remote sensing for quantifying coastal changes to the subsequent stages of modeling and predicting shoreline changes as well as leveraging machine learning techniques to simulate and forecast influential factors like waves and ice cover. First, a fully automated shoreline detection algorithm was developed to quantify the shoreline changes in Lake Michigan, detecting the most vulnerable areas, and determining the main factors responsible for the spatial variability in the shoreline changes. Additionally, a reduced complexity model was designed to simulate the shoreline changes in Lake Michigan by considering both waves and water level fluctuations, which significantly improved the shoreline changes modeling and forecasting for Lake Michigan. Furthermore, new deep learning-based frameworks based on the Convolution Long Short-Term Memory (ConvLSTM) and Convolution Neural Network (CNN) were introduced to model and extend the current records of wave heights and ice cover datasets, adding 70% and 50% data to the existing waves and ice time series respectively. Finally, the extended waves and ice time series were used to study the long-term trends and the correlation between the interannual water level and waves changes, revealing a statically significant decreasing trend in the ice cover over Lake Michigan of 0.6 days/year, and an increasing trend in the waves interannual variability at Chicago area.</p>

No description available.