Predicting microcystin concentration action-level exceedances resulting from cyanobacterial blooms in selected lake sites in Ohio.

Cyanobacterial harmful algal blooms and the toxins they produce are a global water-quality problem. Monitoring and prediction tools are needed to quickly predict cyanotoxin action-level exceedances in recreational and drinking waters used by the public. To address this need, data were collected at eight locations in Ohio, USA, to identify factors significantly related to observed concentrations of microcystins (a freshwater cyanotoxin) that could be used in two types of site-specific regression models.

Estimating microcystin levels at recreational sites in western Lake Erie and Ohio.

Cyanobacterial harmful algal blooms (cyanoHABs) and associated toxins, such as microcystin, are a major global water-quality issue. Water-resource managers need tools to quickly predict when and where toxin-producing cyanoHABs will occur. This could be done by using site-specific models that estimate the potential for elevated toxin concentrations that cause public health concerns.

Predictive models for Escherichia coli concentrations at inland lake beaches and relationship of model variables to pathogen detection.

Predictive models, based on environmental and water quality variables, have been used to improve the timeliness and accuracy of recreational water quality assessments, but their effectiveness has not been studied in inland waters. Sampling at eight inland recreational lakes in Ohio was done in order to investigate using predictive models for Escherichia coli and to understand the links between E. coli concentrations, predictive variables, and pathogens.