An integrated environmental modeling framework for performing Quantitative Microbial Risk Assessments

Whelan, G.; Kim, Keewook; Pelton, Mitch A.; Soller, Jeffrey A.; Castleton, Karl J.; Molina, Marirosa; Pachepsky, Yakov; Zepp, Richard G.

doi:10.1016/j.envsoft.2013.12.013

Cited by 35 publications

(23 citation statements)

References 73 publications

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“…Haydon & Deletic (2006) and Dorner et al (2006) reported good performance of an E. coli fate-and-transport model for catchments with areas from 10 to 100 km 2 . Whelan et al (2014) demonstrated the application of an integrated modeling system to generate various exposure scenarios in a quantitative microbial risk assessment framework. Fate and transport were simulated for Salmonella enterica, Cryptosporidium spp., and E. coli O157:H7 released from typical rural sources.…”

Section: Uses Of Coliform Indicatorsmentioning

confidence: 99%

CanE. colior thermotolerant coliform concentrations predict pathogen presence or prevalence in irrigation waters?

Pachepsky

Shelton

Dorner

et al. 2014

Critical Reviews in Microbiology

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An increase in food-borne illnesses in the United States has been associated with fresh produce consumption. Irrigation water presents recognized risks for microbial contamination of produce. Water quality criteria rely on indicator bacteria. The objective of this review was to collate and summarize experimental data on the relationships between pathogens and thermotolerant coliform (THT) and/or generic E. coli, specifically focusing on surface fresh waters used in or potentially suitable for irrigation agriculture. We analyzed peer-reviewed publications in which concentrations of E. coli or THT coliforms in surface fresh waters were measured along with concentrations of one or more of waterborne and food-borne pathogenic organisms. The proposed relationships were significant in 35% of all instances and not significant in 65% of instances. Coliform indicators alone cannot provide conclusive, non-site-specific and non-pathogen-specific information about the presence and/or concentrations of most important pathogens in surface waters suitable for irrigation. Standards of microbial water quality for irrigation can rely not only on concentrations of indicators and/or pathogens, but must include references to crop management. Critical information on microbial composition of actual irrigation waters to support criteria of microbiological quality of irrigation waters appears to be lacking and needs to be collected.

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Section: Uses Of Coliform Indicatorsmentioning

confidence: 99%

CanE. colior thermotolerant coliform concentrations predict pathogen presence or prevalence in irrigation waters?

Pachepsky

Shelton

Dorner

et al. 2014

Critical Reviews in Microbiology

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“…Application of animal manure on land is a common practice in the United States and many other countries. Modelling of runoff and stormwater contamination is a welldocumented research activity (e.g., (Bhattarai et al, 2011;Burian et al, 2001;Kara et al, 2012;Liu, 1994;L opez-Vicente et al, 2014;Luna et al, 2006;May and Sivakumar, 2009;Vezzaro and Mikkelsen, 2012;Vezzaro et al, 2014;Whelan et al, 2014)) Prior studies of pathogen and indicator mobilisation via overland flow from land applied manures have explored the influence that numerous factors have on mobilisation (Cardoso et al, 2012;Ferguson et al, 2007;Muirhead et al, 2006;Stout et al, 2005). Those factors include manure type and method of land application (e.g., Hodgson et al, 2009;Miller and Beasley, 2008;Ramirez et al, 2009;Saini et al, 2003;Thurston-Enriquez et al, 2005), slope and ground cover (e.g., Cardoso et al, 2012;Davies et al, 2004;Ferguson et al, 2007;Hodgson et al, 2009;Miller and Beasley, 2008;Stout et al, 2005;Thurston-Enriquez et al, 2005;Trask et al, 2004;Winkworth et al, 2008;Yeghiazarian et al, 2004), rainfall intensity and antecedent soil moisture (Bradford and Schijven, 2002;Davies et al, 2004;Ramirez et al, 2009;Saini et al, 2003;Schijven et al, 2004;Sistani et al, 2009;Yeghiaz...…”

Section: Introductionmentioning

confidence: 99%

Estimated human health risks from recreational exposures to stormwater runoff containing animal faecal material

Soller¹,

Bartrand²,

Ravenscroft

et al. 2015

Environmental Modelling & Software

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“…A number of dose–response models have been published to compute the probability of infection from acute exposure to pathogens, such as inadvertent ingestion during recreational activities: exponential, β‐Poisson, hypergeometric, and Gompertz‐log (Conlan et al, 2011; Haas, 2002; Haas et al, 1999; Soller et al, 2004, 2008; USEPA, 2010). The recommended dose–response model for Cryptosporidium exposure is based on the exponential function (Soller et al, 2004, 2008; Whelan et al, 2014b):

P (d) = 1 - \exp (- r C I)

where P ( d ) is the probability of infection and subsequent illness; r is the exponential constant (cells −1 or oocysts −1 ); C is the microbial concentration (cells L −1 or oocysts L −1 ), and I is the intake volume (L). Dose ( d ; cells or oocysts) is a multiple between the concentration and intake.…”

Section: Resultsmentioning

confidence: 99%

“…Dose ( d ; cells or oocysts) is a multiple between the concentration and intake. Whelan et al (2014b) and Soller et al (2004, 2008) reported a range for r between 0.04 and 0.16. Recreational water incidental ingestion rates were highest for children, with USEPA (2016) reporting the 90th percentile at 330 mL d −1 .…”

Section: Resultsmentioning

confidence: 99%

Using Integrated Environmental Modeling to Assess Sources of Microbial Contamination in Mixed‐Use Watersheds

Kim¹,

Whelan

Molina

et al. 2018

J of Env Quality

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Microbial fate and transport in watersheds should include a microbial source apportionment analysis that estimates the importance of each source, relative to each other and in combination, by capturing their impacts spatially and temporally under various scenarios. A loosely configured software infrastructure was used in microbial source‐to‐receptor modeling by focusing on animal‐ and human‐impacted mixed‐use watersheds. Components include data collection software, a microbial source module that determines loading rates from different sources, a watershed model, an inverse model for calibrating flows and microbial densities, tabular and graphical viewers, software to convert output to different formats, and a model for calculating risk from pathogen exposure. The system automates, as much as possible, the manual process of accessing and retrieving data and completes input data files of the models. The workflow considers land‐applied manure from domestic animals on undeveloped areas; direct shedding (excretion) on undeveloped lands by domestic animals and wildlife; pastureland, cropland, forest, and urban or engineered areas; sources that directly release to streams from leaking septic systems; and shedding by domestic animals directly to streams. The infrastructure also considers point sources from regulated discharges. An application is presented on a real‐world watershed and helps answer questions such as: What are the major microbial sources? What practices contribute to contamination at the receptor location? What land‐use types influence contamination at the receptor location? and Under what conditions do these sources manifest themselves? This research aims to improve our understanding of processes related to pathogen and indicator dynamics in mixed‐use watershed systems. Core Ideas We performed a microbial source apportionment and risk assessment on a mixed‐use watershed. Our work links water safety, environmental quality, and human health using integrated modeling. The modeling workflow informs on which microbial sources and land‐use types are of importance. We discuss how microbial criteria can be interpreted by linking modeling and monitoring. Such assessment can help determine the appropriateness of waivers to water quality criteria.

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An integrated environmental modeling framework for performing Quantitative Microbial Risk Assessments

Cited by 35 publications

References 73 publications

CanE. colior thermotolerant coliform concentrations predict pathogen presence or prevalence in irrigation waters?

CanE. colior thermotolerant coliform concentrations predict pathogen presence or prevalence in irrigation waters?

Estimated human health risks from recreational exposures to stormwater runoff containing animal faecal material

Using Integrated Environmental Modeling to Assess Sources of Microbial Contamination in Mixed‐Use Watersheds

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