The USGS Ohio Water Microbiology Laboratory addresses water-related public-health concerns and is involved in investigations of processes that affect microorganisms in the environment and testing of new methods to improve detection and interpretation of microbiological presence in water.
Amie M Brady
Amie is the supervisor of the Public Health Science and Laboratory Sevices section for the Ohio-Kentucky-Indiana Water Science Center and is the Laboratory Manager for the Ohio Water Microbiology Laboratory and the Kentucky Sediment Laboratory.
Amie received her Bachelor of Science (1999) and Masters of Science (2002) degrees in Environmental Science from the Ohio State University. She started her career at the USGS in 2000 at the Ohio Water Science Center working on a variety of water-quality projects. She became the Laboratory Manager for the Ohio Water Microbiology Laboratory and the Kentucky Sediment Laboratory in 2019. In 2020, Amie became the supervisor of the Public Health Science and Laboratory Sevices section for the Ohio-Kentucky-Indiana Water Science Center.
Science and Products
Using models to estimate microcystin concentrations in Ohio recreational and source waters
Harmful Algae Blooms (HABs)
Ohio Microbiology Program - NAWQA - Cycle 3
Ohio Microbiology Program - Home
Biodegradation Of Microcystins In Lake Erie Source Waters And Filters From Drinking-Water Plants
Testing Of A Model For Predicting Recreational Water Quality Of The Cuyahoga River in the Cuyahoga Valley National Park Based On Real-time Turbidity And Streamflow Data
Nowcast - Water-Quality Conditions At Beaches And A Recreational River
Data for multiple linear regression models for estimating Escherichia coli (E. coli) concentrations or the probability of exceeding the bathing-water standard at recreational sites in Ohio and Pennsylvania as part of the Great Lakes NowCast, 2019
Laboratory quality-control data associated with samples analyzed for microbiological constituents at the USGS Ohio Water Microbiology Laboratory
Data for multiple linear regression models for predicting microcystin concentration action-level exceedances in selected lakes in Ohio
Laboratory quality-control data associated with samples analyzed for microbiological constituents at the Ohio Water Microbiology Laboratory, 2012-2017
The USGS Ohio Water Microbiology Laboratory addresses water-related public-health concerns and is involved in investigations of processes that affect microorganisms in the environment and testing of new methods to improve detection and interpretation of microbiological presence in water.
The USGS Ohio Water Microbiology Laboratory addresses water-related public-health concerns and is involved in investigations of processes that affect microorganisms in the environment and testing of new methods to improve detection and interpretation of microbiological presence in water.
The USGS Ohio Water Microbiology Laboratory addresses water-related public-health concerns and is involved in investigations of processes that affect microorganisms in the environment and testing of new methods to improve detection and interpretation of microbiological presence in water.
The U.S. Geological Survey Ohio Water Microbiology Laboratory
Evaluation of a modified rapid viability-polymerase chain reaction method for Bacillus atrophaeus spores in water matrices
Predicting microcystin concentration action-level exceedances resulting from cyanobacterial blooms in selected lake sites in Ohio
Nowcasting methods for determining microbiological water quality at recreational beaches and drinking-water source waters
Pilot-scale testing of dairy manure treatments to reduce nutrient transport from land application, northwest Ohio, 2015–17
Real-time assessments of water quality—A nowcast for Escherichia coli and cyanobacterial toxins
Escherichia coli and microbial source tracking marker concentrations in and near a constructed wetland in Maumee Bay State Park, Oregon, Ohio, 2015–16
Multi-year microbial source tracking study characterizing fecal contamination in an urban watershed
Microbiological and hydrological data were used to rank tributary stream contributions of bacteria to the Little Blue River in Independence, Missouri. Concentrations, loadings and yields of E. coli and microbial source tracking (MST) markers, were characterized during base flow and storm events in five subbasins within Independence, as well as sources entering and leaving the city through the rive
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. With this study
Water Quality, Cyanobacteria, and Environmental Factors and Their Relations to Microcystin Concentrations for Use in Predictive Models at Ohio Lake Erie and Inland Lake Recreational Sites, 2013-14
Harmful cyanobacterial “algal” blooms (cyanoHABs) and associated toxins, such as microcystin, are a major water-quality issue for Lake Erie and inland lakes in Ohio. Predicting when and where a bloom may occur is important to protect the public that uses and consumes a water resource; however, predictions are complicated and likely site specific because of the many factors affecting toxin producti
Towards automating measurements and predictions of Escherichia coli concentrations in the Cuyahoga River, Cuyahoga Valley National Park, Ohio, 2012–14
Nowcasts are systems that can provide estimates of the current bacterial water-quality conditions based on predictive models using easily-measured, explanatory variables; nowcasts can provide the public with the information to make informed decisions on the risk associated with recreational activities in natural water bodies. Previous studies on the Cuyahoga River within Cuyahoga Valley National P
Developing and implementing the use of predictive models for estimating water quality at Great Lakes beaches
Predictive models have been used at beaches to improve the timeliness and accuracy of recreational water-quality assessments over the most common current approach to water-quality monitoring, which relies on culturing fecal-indicator bacteria such as Escherichia coli (E. coli.). Beach-specific predictive models use environmental and water-quality variables that are easily and quickly measured as s
Science and Products
Using models to estimate microcystin concentrations in Ohio recreational and source waters
Harmful Algae Blooms (HABs)
Ohio Microbiology Program - NAWQA - Cycle 3
Ohio Microbiology Program - Home
Biodegradation Of Microcystins In Lake Erie Source Waters And Filters From Drinking-Water Plants
Testing Of A Model For Predicting Recreational Water Quality Of The Cuyahoga River in the Cuyahoga Valley National Park Based On Real-time Turbidity And Streamflow Data
Nowcast - Water-Quality Conditions At Beaches And A Recreational River
Data for multiple linear regression models for estimating Escherichia coli (E. coli) concentrations or the probability of exceeding the bathing-water standard at recreational sites in Ohio and Pennsylvania as part of the Great Lakes NowCast, 2019
Laboratory quality-control data associated with samples analyzed for microbiological constituents at the USGS Ohio Water Microbiology Laboratory
Data for multiple linear regression models for predicting microcystin concentration action-level exceedances in selected lakes in Ohio
Laboratory quality-control data associated with samples analyzed for microbiological constituents at the Ohio Water Microbiology Laboratory, 2012-2017
The USGS Ohio Water Microbiology Laboratory addresses water-related public-health concerns and is involved in investigations of processes that affect microorganisms in the environment and testing of new methods to improve detection and interpretation of microbiological presence in water.
The USGS Ohio Water Microbiology Laboratory addresses water-related public-health concerns and is involved in investigations of processes that affect microorganisms in the environment and testing of new methods to improve detection and interpretation of microbiological presence in water.
The USGS Ohio Water Microbiology Laboratory addresses water-related public-health concerns and is involved in investigations of processes that affect microorganisms in the environment and testing of new methods to improve detection and interpretation of microbiological presence in water.
The USGS Ohio Water Microbiology Laboratory addresses water-related public-health concerns and is involved in investigations of processes that affect microorganisms in the environment and testing of new methods to improve detection and interpretation of microbiological presence in water.
The U.S. Geological Survey Ohio Water Microbiology Laboratory
Evaluation of a modified rapid viability-polymerase chain reaction method for Bacillus atrophaeus spores in water matrices
Predicting microcystin concentration action-level exceedances resulting from cyanobacterial blooms in selected lake sites in Ohio
Nowcasting methods for determining microbiological water quality at recreational beaches and drinking-water source waters
Pilot-scale testing of dairy manure treatments to reduce nutrient transport from land application, northwest Ohio, 2015–17
Real-time assessments of water quality—A nowcast for Escherichia coli and cyanobacterial toxins
Escherichia coli and microbial source tracking marker concentrations in and near a constructed wetland in Maumee Bay State Park, Oregon, Ohio, 2015–16
Multi-year microbial source tracking study characterizing fecal contamination in an urban watershed
Microbiological and hydrological data were used to rank tributary stream contributions of bacteria to the Little Blue River in Independence, Missouri. Concentrations, loadings and yields of E. coli and microbial source tracking (MST) markers, were characterized during base flow and storm events in five subbasins within Independence, as well as sources entering and leaving the city through the rive
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. With this study
Water Quality, Cyanobacteria, and Environmental Factors and Their Relations to Microcystin Concentrations for Use in Predictive Models at Ohio Lake Erie and Inland Lake Recreational Sites, 2013-14
Harmful cyanobacterial “algal” blooms (cyanoHABs) and associated toxins, such as microcystin, are a major water-quality issue for Lake Erie and inland lakes in Ohio. Predicting when and where a bloom may occur is important to protect the public that uses and consumes a water resource; however, predictions are complicated and likely site specific because of the many factors affecting toxin producti
Towards automating measurements and predictions of Escherichia coli concentrations in the Cuyahoga River, Cuyahoga Valley National Park, Ohio, 2012–14
Nowcasts are systems that can provide estimates of the current bacterial water-quality conditions based on predictive models using easily-measured, explanatory variables; nowcasts can provide the public with the information to make informed decisions on the risk associated with recreational activities in natural water bodies. Previous studies on the Cuyahoga River within Cuyahoga Valley National P
Developing and implementing the use of predictive models for estimating water quality at Great Lakes beaches
Predictive models have been used at beaches to improve the timeliness and accuracy of recreational water-quality assessments over the most common current approach to water-quality monitoring, which relies on culturing fecal-indicator bacteria such as Escherichia coli (E. coli.). Beach-specific predictive models use environmental and water-quality variables that are easily and quickly measured as s