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Date of Award


Document Type

Campus Access Master's Report

Degree Name

Doctor of Philosophy in Atmospheric Sciences (PhD)

Administrative Home Department

Department of Civil, Environmental, and Geospatial Engineering

Advisor 1

Pengfei Xue

Committee Member 1

Martin T. Auer

Committee Member 2

Mark D. Rowe

Committee Member 3

Gangfeng Ma


Hydrodynamic and biophysical models were used to understand the mechanisms mediating algal blooms in the Great Lakes. The nuisance growths of Cladophora and cyanobacterial harmful algal blooms (CHABs) were of particular interest in this study.

Nuisance growth of Cladophora occurs in the Great Lakes nearshore. It has been hypothesized that controlling phosphorus discharges to the nearshore may not effectively address these nuisance conditions. Quagga mussels, which have access to offshore particulate phosphorus (PP) reserves, can provide the necessary soluble reactive phosphorus (SRP) for Cladophora growth. A biophysical model was used to simulate the phosphorus-mussels-Cladophora dynamics in Good Harbor Bay, Lake Michigan, a system with nuisance Cladophora growth but no local P source. The model predicted that in the absence of local P sources, SRP levels in the nearshore would remain below the threshold for nuisance growth. This indicates a promising pathway to control phosphorus loading without negatively impacting offshore fisheries.

CHAB biomass in Lake Erie has been successfully predicted by several short-term forecast models, using satellite images as initial fields and transport models to predict bloom movement. However, different models have been developed using different approaches and methods, making it difficult to evaluate their performance. Therefore, a comprehensive model skill assessment was conducted to compare the performance of three transport models: Lagrangian particle model (LPM), Eulerian tracer model (ETM), and property-carrying particle model (PCPM), during the 2017–2019 CHAB seasons. The assessment found all three models had comparable levels of accuracy, with the ETM and PCPM performing equally well or better than the LPM.

Predicting toxins (microcystins) in Lake Erie CHABs is more challenge than predicting CHAB biomass. Microcystins are only detectable in grab samples and have a weak correlation with CHAB biomass. Hence, a model was developed using weekly concentration maps generated from observed microcystin concentrations as initial fields and predicting microcystin spatial distribution and temporal variation for the 2018–2019 CHAB seasons. The model's performance was improved by incorporating the microcystin production rate, but the difference between model results and observed data highlights the importance of maintaining sufficient monitoring coverage.