Biological Weighting Functions for Evaluating the Role of Sunlight-Induced Inactivation of Coliphages at Selected Beaches and Nearby Tributaries.

Coliphages can indicate contamination of recreational waters and previous studies show that sunlight is important in altering densities of coliphages, other indicator microorganisms, and pathogens in aquatic environments. Here, we report on laboratory studies of light-induced inactivation of two coliphage groups-male-specific (F+) and somatic coliphage-under various conditions in phosphate-buffered water (PBW). Strains isolated from wastewater treatment facilities and laboratory strains (MS2 and phiX174 coliphages) were evaluated. Inactivation rates were determined in a series of irradiations using simulated solar radiation passed through light filters that blocked different parts of the ultraviolet spectral region. Inactivation rates and spectral irradiance from these experiments were then analyzed to develop biological weighting functions (BWFs) for the light-induced inactivation. BWFs were used to model the inactivation of coliphages over a range of conditions in aquatic environments that included two beach sites in Lake Michigan and one in Lake Erie. For example, modeled effects of sunlight attenuation, using UV absorption data from the three Great Lakes beach sites, inferred that direct photoinactivation rate constants, averaged over a one-meter water column in swimmable areas, were reduced 2- to 5-fold, compared to near-surface rate constants.

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

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.

Capturing Microbial Sources Distributed in a Mixed-use Watershed within an Integrated Environmental Modeling Workflow.

Many watershed models simulate overland and instream microbial fate and transport, but few provide loading rates on land surfaces and point sources to the waterbody network. This paper describes the underlying equations for microbial loading rates associated with 1) land-applied manure on undeveloped areas from domestic animals; 2) direct shedding (excretion) on undeveloped lands by domestic animals and wildlife; 3) urban or engineered areas; and 4) point sources that directly discharge to streams from septic systems and shedding by domestic animals. A microbial source module, which houses these formulations, is part of a workflow containing multiple models and databases that form a loosely configured modeling infrastructure which supports watershed-scale microbial source-to-receptor modeling by focusing on animal- and human-impacted catchments. A hypothetical application - accessing, retrieving, and using real-world data - demonstrates how the infrastructure can automate many of the manual steps associated with a standard watershed assessment, culminating in calibrated flow and microbial densities at the watershed's pour point.

Can E. coli or thermotolerant coliform concentrations predict pathogen presence or prevalence in irrigation waters?

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.

Rainfall-induced release of microbes from manure: model development, parameter estimation, and uncertainty evaluation on small plots.

A series of simulated rainfall-runoff experiments with applications of different manure types (cattle solid pats, poultry dry litter, swine slurry) was conducted across four seasons on a field containing 36 plots (0.75 × 2 m each), resulting in 144 rainfall-runoff events. Simulating time-varying release of Escherichia coli, enterococci, and fecal coliforms from manures applied at typical agronomic rates evaluated the efficacy of the Bradford-Schijven model modified by adding terms for release efficiency and transportation loss. Two complementary, parallel approaches were used to calibrate the model and estimate microbial release parameters. The first was a four-step sequential procedure using the inverse model PEST, which provides appropriate initial parameter values. The second utilized a PEST/bootstrap procedure to estimate average parameters across plots, manure age, and microbe, and to provide parameter distributions. The experiment determined that manure age, microbe, and season had no clear relationship to the release curve. Cattle solid pats released microbes at a different, slower rate than did poultry dry litter or swine slurry, which had very similar release patterns. These findings were consistent with other published results for both bench- and field-scale, suggesting the modified Bradford-Schijven model can be applied to microbial release from manure.

Survival of Manure-borne and Fecal Coliforms in Soil: Temperature Dependence as Affected by Site-Specific Factors.

Understanding pathogenic and indicator bacteria survival in soils is essential for assessing the potential of microbial contamination of water and produce. The objective of this work was to evaluate the effects of soil properties, animal source, experimental conditions, and the application method on temperature dependencies of manure-borne generic , O157:H7, and fecal coliforms survival in soils. A literature search yielded 151 survival datasets from 70 publications. Either one-stage or two-stage kinetics was observed in the survival datasets. We used duration and rate of the logarithm of concentration change as parameters of the first stage in the two-stage kinetics data. The second stage of the two-stage kinetics and the one-stage kinetics were simulated with the model to find the dependence of the inactivation rate on temperature. Classification and regression trees and linear regressions were applied to parameterize the kinetics. Presence or absence of two-stage kinetics was controlled by temperature, soil texture, soil water content, and for fine-textured soils by setting experiments in the field or in the laboratory. The duration of the first stage was predominantly affected by soil water content and temperature. In the model dependencies of inactivation rates on temperature, parameter estimates were significantly affected by the laboratory versus field conditions and by the application method, whereas inactivation rates at 20°C were significantly affected by all survival and management factors. Results of this work can provide estimates of coliform survival parameters for models of microbial water quality.

Modeling the photoinactivation and transport of somatic and F-specific coliphages at a Great Lakes beach.

Fecal indicator organisms (FIOs), such as Escherichia coli and enterococci, are often used as surrogates of contamination in the context of beach management; however, bacteriophages may be more reliable indicators than FIO due to their similarity to viral pathogens in terms of size and persistence in the environment. In the past, mechanistic modeling of environmental contamination has focused on FIOs, with virus and bacteriophage modeling efforts remaining limited. In this paper, we describe the development and application of a fate and transport model of somatic and F-specific coliphages for the Washington Park beach in Lake Michigan, which is affected by riverine outputs from the nearby Trail Creek. A three-dimensional model of coliphage transport and photoinactivation was tested and compared with a previously reported E. coli fate and transport model. The light-based inactivation of the phages was modeled using organism-specific action spectra. Results indicate that the coliphage models outperformed the E. coli model in terms of reliably predicting observed E. coli/coliphage concentrations at the beach. This is possibly due to the presence of additional E. coli sources that were not accounted for in the modeling. The coliphage models can be used to test hypotheses about potential sources and their behavior and for predictive modeling.

Rainfall-induced fecal indicator organisms transport from manured fields: model sensitivity analysis.

Microbial quality of surface waters attracts attention due to food- and waterborne disease outbreaks. Fecal indicator organisms (FIOs) are commonly used for the microbial pollution level evaluation. Models predicting the fate and transport of FIOs are required to design and evaluate best management practices that reduce the microbial pollution in ecosystems and water sources and thus help to predict the risk of food and waterborne diseases. In this study we performed a sensitivity analysis for the KINEROS/STWIR model developed to predict the FIOs transport out of manured fields to other fields and water bodies in order to identify input variables that control the transport uncertainty. The distributions of model input parameters were set to encompass values found from three-year experiments at the USDA-ARS OPE3 experimental site in Beltsville and publicly available information. Sobol' indices and complementary regression trees were used to perform the global sensitivity analysis of the model and to explore the interactions between model input parameters on the proportion of FIO removed from fields. Regression trees provided a useful visualization of the differences in sensitivity of the model output in different parts of the input variable domain. Environmental controls such as soil saturation, rainfall duration and rainfall intensity had the largest influence in the model behavior, whereas soil and manure properties ranked lower. The field length had only moderate effect on the model output sensitivity to the model inputs. Among the manure-related properties the parameter determining the shape of the FIO release kinetic curve had the largest influence on the removal of FIOs from the fields. That underscored the need to better characterize the FIO release kinetics. Since the most sensitive model inputs are available in soil and weather databases or can be obtained using soil water models, results indicate the opportunity of obtaining large-scale estimates of FIO transport from fields based on publicly available rather than site-specific information.

Using the Q10 model to simulate E. coli survival in cowpats on grazing lands.

Microbiological quality of surface waters can be affected by microbial load in runoff from grazing lands. This effect, with other factors, depends on the survival of microorganisms in animal waste deposited on pastures. Since temperature is a leading environmental parameter affecting survival, it indirectly impacts water microbial quality. The Q10 model is widely used to predict the effect of temperature on rates of biological processes, including survival. Objectives of this work were to (i) evaluate the applicability of the Q10 model to Escherichia coli inactivation in bovine manure deposited on grazing land (i.e., cowpats) and (ii) identify explanatory variables for the previously reported E. coli survival dynamics in cowpats. Data utilized in this study include published results on E. coli concentrations in natural and repacked cowpats from research conducted the U.S. (Virginia and Maryland), New Zealand, and the United Kingdom. Inspection of the datasets led to conceptualizing E. coli survival (in cowpats) as a two-stage process, in which the initial stage was due to growth, inactivation or stationary state of the population and the second stage was the approximately first-order inactivation. Applying the Q10 model to these datasets showed a remarkable similarity in inactivation rates, using the thermal time. The reference inactivation rate constant of 0.042 (thermal days)(-1) at 20 °C gave a good approximation (R(2)=0.88) of all inactivation stage data with Q10=1.48. The reference inactivation rate constants in individual studies were no different from the one obtained by pooling all data (P<0.05). The rate of logarithm of the E. coli concentration change during the first stage depended on temperature. Duration of the first stage, prior to the first-order inactivation stage and the initial concentration of E. coli in cowpats, could not be predicted from available data. Diet and age are probable factors affecting these two parameters however, until their environmental and management predictors are known, microbial water quality modeling must treat them as a stochastic source of uncertainty in simulation results.