Publications by authors named "Yakov Pachepsky"

44 Publications

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

J Environ Qual 2020 Nov 5;49(6):1612-1623. Epub 2020 Nov 5.

Dep. of Civil & Environmental Engineering, Michigan State Univ., East Lansing, MI, 48824, USA.

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.
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http://dx.doi.org/10.1002/jeq2.20153DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7859910PMC
November 2020

Using convolutional neural network for predicting cyanobacteria concentrations in river water.

Water Res 2020 Nov 26;186:116349. Epub 2020 Aug 26.

School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology, 50 UNIST-gil, Eonyang-eup, Ulju-gun, Ulsan 689-798, Republic of Korea. Electronic address:

Machine learning modeling techniques have emerged as a potential means for predicting algal blooms. In this study, synthetic spatio-temporal water quality data for a river section were generated with a 3D water quality model and used to investigate the capability of a convolutional neural network (CNN) for predicting harmful cyanobacterial blooms. The CNN model displayed a reasonable capacity for short-term predictions of cyanobacteria (Microcystis) biomass. In the nowcasting of Microcystis, the CNN performance had a Nash-Sutcliffe Efficiency (NSE) of 0.87. An increase in the forecast lead time resulted in a decrease in the prediction accuracy, reducing the NSE from 0.87 to 0.58. As the spatial observation density increased from 20% to 100% of the input image grids, the CNN prediction NSE had improved from 0.70 to 0.84. Adding noise to the data resulted in accuracy deterioration, but even at the noise amplitude of 10%, the accuracy was acceptable for some applications, with NSE = 0.76. Visualization of the CNN results characterized its performance variations across the studied river reach. Overall, this study successfully demonstrated the capability of the CNN model for cyanobacterial bloom prediction using high temporal frequency images.
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http://dx.doi.org/10.1016/j.watres.2020.116349DOI Listing
November 2020

Data assimilation in surface water quality modeling: A review.

Water Res 2020 Nov 16;186:116307. Epub 2020 Aug 16.

Watershed and Total Load Management Research Division, National Institute of Environmental Research, Ministry of Environment, Hwangyong-ro 42, Seogu, Incheon, Republic of Korea.

Data assimilation (DA) techniques are powerful means of dynamic natural system modeling that allow for the use of data as soon as it appears to improve model predictions and reduce prediction uncertainty by correcting state variables, model parameters, and boundary and initial conditions. The objectives of this review are to explore existing approaches and advances in DA applications for surface water quality modeling and to identify future research prospects. We first reviewed the DA methods used in water quality modeling as reported in literature. We then addressed observations and suggestions regarding various factors of DA performance, such as the mismatch between both lateral and vertical spatial detail of measurements and modeling, subgrid heterogeneity, presence of temporally stable spatial patterns in water quality parameters and related biases, evaluation of uncertainty in data and modeling results, mismatch between scales and schedules of data from multiple sources, selection of parameters to be updated along with state variables, update frequency and forecast skill. The review concludes with the outlook section that outlines current challenges and opportunities related to growing role of novel data sources, scale mismatch between model discretization and observation, structural uncertainty of models and conversion of measured to simulated vales, experimentation with DA prior to applications, using DA performance or model selection, the role of sensitivity analysis, and the expanding use of DA in water quality management.
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http://dx.doi.org/10.1016/j.watres.2020.116307DOI Listing
November 2020

Effect of the time scale on the uncertainty of geometric mean concentrations of fecal indicators in creek under baseflow conditions.

Sci Rep 2020 02 3;10(1):1720. Epub 2020 Feb 3.

USDA-ARS, Environmental Microbial and Food Safety Laboratory, Beltsville, Maryland, USA.

Geometric mean concentrations of fecal indicator bacteria E. coli and enterococci are commonly used to evaluate the microbial quality of irrigation, recreation, and other types of waters, as well in watershed-scale microbial water quality modeling. It is not known how the uncertainty of those geometric mean concentrations depends on the time period between sampling. We analyzed data collected under baseflow conditions from three years of weekly and several daily sampling campaigns at Conococheague Creek in Pennsylvania. Standard deviations of logarithms of geometric mean concentrations were computed over weeks, months, and seasons. The increase in standard deviations from weekly to seasonal time scale was on average about 0.1 and 0.2 for log(E. coli) and log(enterococci), respectively, and in most cases was statistically significant. This may need to be accounted for when evaluating the uncertainty of measurements for modeling purposes and in risk assessment of microbial water quality.
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http://dx.doi.org/10.1038/s41598-020-58603-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6997410PMC
February 2020

Assessment of a green roof practice using the coupled SWMM and HYDRUS models.

J Environ Manage 2020 May 27;261:109920. Epub 2020 Jan 27.

School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology, Ulsan, 44919, South Korea. Electronic address:

Green roof can mitigate urban stormwater and improve environmental, economic, and social conditions. Various modeling approaches have been effectively employed to implement a green roof, but previous models employed simplifications to simulate water movement in green roof systems. To address this issue, we developed a new modeling tool (SWMM-H) by coupling the stormwater management and HYDRUS-1D models to improve simulations of hydrological processes. We selected green roof systems to evaluate the coupled model. Rainfall-runoff experiments were conducted for a pilot-scale green roof and urban subbasin. Soil moisture in the green roof and runoff volume in the subbasin were simulated more accurately by using SWMM-H instead of SWMM. The scenario analysis showed that SWMM-H selected sandy loam for controlling runoff whereas SWMM recommended sand. In conclusion, SWMM-H could be a useful tool for accurately understanding hydrological processes in green roofs.
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http://dx.doi.org/10.1016/j.jenvman.2019.109920DOI Listing
May 2020

Temporal stability of E. coli and Enterococci concentrations in a Pennsylvania creek.

Environ Sci Pollut Res Int 2020 Feb 10;27(4):4021-4031. Epub 2019 Dec 10.

Wilson College, Division of Integrated Sciences, Chambersburg, PA, USA.

Microbial quality of irrigation waters is a substantial food safety factor. Escherichia coli (E. coli) and Enterococci are used as the fecal indicator bacteria (FIB) to assess microbial water quality. Analysis of temporally stable patterns of FIB can facilitate effective monitoring of microbial water quality. The objectives of this study were (1) to investigate the spatiotemporal variation of E. coli and Enterococci concentrations in a large creek traversing diverse land use areas and (2) to explore the presence of temporally stable FIB concentration patterns along the creek. Concentrations of both FIB were measured weekly at five water monitoring locations along the 20-km long creek reach in Pennsylvania at baseflow for three years. The temporal stability was assessed using mean relative deviations of logarithms of FIB concentration from the average across the reach measured at the same time. The Spearman rank correlation coefficients between logarithms of FIB concentrations on consecutive sampling times was another metric used to assess the temporal stability of FIB concentration patterns. Logarithms of FIB concentrations had sinusoidal dependence on time and significantly correlated with temperature at all locations Both FIB exhibited temporal stability of concentrations. The two most downstream locations in urbanized areas tended to have logarithms of concentrations higher than the average along the observation reach. The location in the upstream forested area had mostly lower concentrations (log E. coli 1.59, log Enterococci 1.69) than average (log E. coli 2.07, log Enterococci 2.20). concentrations in colony-forming units (CFU) (100 mL). Two locations in the agricultural and sparsely urbanized area had these logarithm values close to the average. The temporal stability was more pronounced in cold seasons than in warm seasons. No significant difference was found between pattern determined for each of three observation years and for the entire three-year observation period. The Spearman rank correlations between observations on consecutive dates showed moderate to very strong relationships in most cases. Existence of the temporal stability of FIB concentrations in the creek indicates locations that inform about the average logarithm of concentrations or the geometric mean concentrations along the entire observation reach.
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http://dx.doi.org/10.1007/s11356-019-07030-9DOI Listing
February 2020

Depth-Dependent Response of Fecal Indicator Bacteria in Sediments to Changes in Water Column Nutrient Levels.

J Environ Qual 2019 Jul;48(4):1074-1081

Concentrations of in bottom sediments can influence the assessment of microbial stream water quality. Runoff events bring nutrients to streams that can support the growth of in sediments. The objective of this work was to evaluate depth-dependent changes in populations after nutrients are introduced to the water column. Bovine feces were collected fresh and mixed into sediment. Studies were performed in a microcosm system with continuous flow of synthetic stream water over inoculated sediment. Dilutions of autoclaved bovine manure were added to water on Day 16 at two concentrations, and KBr tracer was introduced into the water column to evaluate ion diffusion. Concentrations of , total coliforms, and total aerobic heterotrophic bacteria, along with orthophosphate-P and ammonium N, were monitored in water and sediment for 32 d. Sediment samples were analyzed in 0- to 1-cm and 1- to 3-cm sectioned depths. Concentrations of and total coliforms in top sediments were approximately one order of magnitude greater than in bottom sediments throughout the experiment. Introduction of nutrients to the water column triggered an increase of nutrient levels in both top and bottom sediments and increased concentrations of bacteria in the water. However, the added nutrients had a limited effect on in sediment where bacterial inactivation continued. Vertical gradients of concentrations in sediments persisted during the inactivation periods both before and after nutrient addition to the water column.
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http://dx.doi.org/10.2134/jeq2018.12.0450DOI Listing
July 2019

On the Information Content of Coarse Data with Respect to the Particle Size Distribution of Complex Granular Media: Rationale Approach and Testing.

Entropy (Basel) 2019 Jun 17;21(6). Epub 2019 Jun 17.

USDA-ARS Environmental Microbial and Food Safety Laboratory, Beltsville, MD 20705, USA.

The particle size distribution (PSD) of complex granular media is seen as a mathematical measure supported in the interval of grain sizes. A physical property characterizing granular products used in the Andreasen and Andersen model of 1930 is re-interpreted in Information Entropy terms leading to a differential information equation as a conceptual approach for the PSD. Under this approach, measured data which give a coarse description of the distribution may be seen as initial conditions for the proposed equation. A solution of the equation agrees with a selfsimilar measure directly postulated as a PSD model by Martín and Taguas almost 80 years later, thus both models appear to be linked. A variant of this last model, together with detailed soil PSD data of 70 soils are used to study the information content of limited experimental data formed by triplets and its ability in the PSD reconstruction. Results indicate that the information contained in certain soil triplets is sufficient to rebuild the whole PSD: for each soil sample tested there is always at least a triplet that contains enough information to simulate the whole distribution.
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http://dx.doi.org/10.3390/e21060601DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7515085PMC
June 2019

Evaluating the influence of climate change on the fate and transport of fecal coliform bacteria using the modified SWAT model.

Sci Total Environ 2019 Mar 14;658:753-762. Epub 2018 Dec 14.

School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea. Electronic address:

Fecal coliform bacteria (FCB) contamination of natural waters is a serious public health issue. Therefore, understanding and anticipating the fate and transport of FCB are important for reducing the risk of contracting diseases. The objective of this study was to analyze the impacts of climate change on the fate and transport of FCB. We modified both the soil and the in-stream bacteria modules in the soil and water assessment tool (SWAT) model and verified the prediction accuracy of seasonal variability of FCB loads using observations. Forty bias-correcting GCM-RCM projections were applied in the modified SWAT model to examine various future climate conditions at the end of this century (2076-2100). Lastly, we also compared the variability of FCB loads under current and future weather conditions using multi-model ensemble simulations (MMES). The modified SWAT model yielded a satisfactory performance with regard to the seasonal variability of FCB amounts in the soil and FCB loading to water bodies. The modified SWAT model presented substantial proliferation of FCB in the soil (30.1%-147.5%) due to an increase in temperature (25.1%). Also, increase in precipitation (53.3%) led to an increase in FCB loads (96.0%-115.5%) from the soil to water body. In the in-stream environment, resuspension from the stream bed was the dominant process affecting the amount of FCB in stream. Therefore, the final FCB loads increased by 71.2% because of the growing peak channel velocity and volume of water used due to an increase in precipitation. Based on the results of MMES, we concluded that the level of FCB would increase simultaneously in the soil as well as in stream by the end of this century. This study will aid in understanding the future variability of FCB loads as well as in preparing an effective management plan for FCB levels in natural waters.
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http://dx.doi.org/10.1016/j.scitotenv.2018.12.213DOI Listing
March 2019

Export from Manured Fields Depends on the Time between the Start of Rainfall and Runoff Initiation.

J Environ Qual 2018 09;47(5):1293-1297

After rainfall or irrigation begins, surface-applied chemicals and manure-borne microorganisms typically enter the soil with infiltration until the soil saturates, after which time the chemicals and microbes are exported from the field in the overland flow. This process is viewed as a reason for the dependence of chemical export on the time between rainfall start and runoff initiation that has been documented for agricultural chemicals. The objective of this work was to observe and quantify such dependence for released from solid farmyard dairy manure in field conditions. Experiments were performed for 6 yr and consisted of manure application followed by an immediate simulated rainfall event and a second event 1 wk later. The nonlinearity of the release seen in laboratory and plot studies did not manifest itself in the field. The number of exported cells in runoff was proportional to rainfall depth after runoff initiation in each trial. The proportionality coefficient, termed export rate, demonstrated a strong dependence on the runoff delay time that could be approximated with the exponential decrease. The export rate decreased by one order of magnitude when the rainfall depth at runoff initiation increased from 18 to 42 mm. The same dependence could approximate data from the simulated rainfall event 1 wk after the manure application, assuming that the initial content in manure after 1 wk of weathering was 10% of the initial content. Overall, accounting for the dependence of manure-borne export on the runoff delay time should improve the accuracy of export predictions related to the assessment of agricultural practices on microbial water quality.
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http://dx.doi.org/10.2134/jeq2018.02.0081DOI Listing
September 2018

Development of a Nowcasting System Using Machine Learning Approaches to Predict Fecal Contamination Levels at Recreational Beaches in Korea.

J Environ Qual 2018 09;47(5):1094-1102

Microbial contamination in beach water poses a public health threat due to waterborne diseases. To reduce the risk of exposure to fecal contamination, informing beachgoers in advance about the microbial water quality is important. Currently, determining the level of fecal contamination takes 24 h. The objective of this study is to predict the current level of fecal contamination (enterococcus [ENT] and ) using readily available environmental variables. Artificial neural network (ANN) and support vector regression (SVR) models were constructed using data from the Haeundae and Gwangalli Beaches in Busan City. The input variables included the tidal level, air and water temperature, solar radiation, wind direction and velocity, precipitation, discharge from the wastewater treatment plant, and suspended solid concentration in beach water. The dependence of fecal contamination on the input variables was statistically evaluated; precipitation, discharge from the wastewater treatment plant, and wind direction at the two beaches were positively correlated to the changes in the two bacterial concentrations ( < 0.01), whereas solar radiation was negatively correlated ( < 0.01). The performance of the ANN model for predicting ENT and at Gwangalli Beach was significantly higher than that of the SVR model with the training dataset ( < 0.05). Based on the comparison of residual values between the predicted and observed fecal indicator bacteria concentrations in two models, the ANN demonstrated better performance than SVR. This study suggests an effective prediction method to determine whether a beach is safe for recreational use.
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http://dx.doi.org/10.2134/jeq2017.11.0425DOI Listing
September 2018

Spatial Patterns of Concentrations in Sediment before and after High-Flow Events in a First-Order Creek.

J Environ Qual 2018 09;47(5):958-966

Understanding spatial patterns of in freshwater sediments is necessary to characterize sediments as microbial reservoirs and to evaluate the impact of sediment resuspension on microbial water quality in watersheds. Sediment particle size distributions and streambed concentrations were measured along a 500-m-long reach of a first-order creek 1 d before and on Days 1, 3, 6, and 10 after each of two artificial high-flow events, with natural high-flow events also occurring within the sampling periods. Spatial variability of was greater in sediments than in water within any given sampling; however, variation between sampling days was greater for water than for sediment. The mean relative difference analysis revealed temporally stable patterns of concentrations in sediments. rich locations along the reach corresponded to areas with higher organic matter and fine particle contents. Although low ( < 0.5 d) or negative survival rates were observed at most locations along the reach during times where no precipitation was recorded, a small number of locations showed such large concentration increase that on average the survival rate remained positive at the reach scale. The studied creek appears to have hot spots of concentration increase, where conditions for populations to increase are much more favorable than in most other locations across the reach. The effect of this increase can be seen at the reach scale but is difficult to discern without individual sampling that is dense in space and time.
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http://dx.doi.org/10.2134/jeq2017.11.0451DOI Listing
September 2018

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

Environ Model Softw 2018 Jan;99:126-146

U.S. Department of Agriculture, Agricultural Research Service, Marshfield, WI USA.

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.
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http://dx.doi.org/10.1016/j.envsoft.2017.08.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6069999PMC
January 2018

MATLAB algorithm to implement soil water data assimilation with the Ensemble Kalman Filter using HYDRUS.

MethodsX 2018 7;5:184-203. Epub 2018 Mar 7.

Department of Applied Physics, University of Córdoba, Córdoba, Spain.

Data assimilation is becoming a promising technique in hydrologic modelling to update not only model states but also to infer model parameters, specifically to infer soil hydraulic properties in Richard-equation-based soil water models. The Ensemble Kalman Filter method is one of the most widely employed method among the different data assimilation alternatives. In this study the complete Matlab© code used to study soil data assimilation efficiency under different soil and climatic conditions is shown. The code shows the method how data assimilation through EnKF was implemented. Richards equation was solved by the used of Hydrus-1D software which was run from Matlab. •MATLAB routines are released to be used/modified without restrictions for other researchers•Data assimilation Ensemble Kalman Filter method code.•Soil water Richard equation flow solved by Hydrus-1D.
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http://dx.doi.org/10.1016/j.mex.2018.02.008DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5945924PMC
March 2018

Temporal Stability of Escherichia coli Concentrations in Waters of Two Irrigation Ponds in Maryland.

Appl Environ Microbiol 2018 02 17;84(3). Epub 2018 Jan 17.

USDA-ARS Environmental Microbial and Food Safety Laboratory, Beltsville, Maryland, USA.

Fecal contamination of water sources is an important water quality issue for agricultural irrigation ponds. concentrations are commonly used to evaluate recreational and irrigation water quality. We hypothesized that there may exist temporally stable spatial patterns of concentrations across ponds, meaning that some areas mostly have higher and other areas mostly lower than average concentrations of To test this hypothesis, we sampled two irrigation ponds in Maryland at nodes of spatial grids biweekly during the summer of 2016. Environmental covariates-temperature, turbidity, conductivity, pH, dissolved oxygen, chlorophyll , and nutrients-were measured in conjunction with concentrations. Temporal stability was assessed using mean relative differences between measurements in each location and averaged measurements across ponds. Temporally stable spatial patterns of concentrations and the majority of environmental covariates were expressed for both ponds. In the pond interior, larger relative mean differences in chlorophyll corresponded to smaller mean relative differences in concentrations, with a Spearman's rank correlation coefficient of 0.819. Turbidity and ammonium concentrations were the two other environmental covariates with the largest positive correlations between their location ranks and the concentration location ranks. Tenfold differences were found between geometric mean concentrations in locations that were consistently high or consistently low. The existence of temporally stable patterns of concentrations can affect the results of microbial water quality assessment in ponds and should be accounted for in microbial water quality monitoring design. The microbial quality of water in irrigation water sources must be assessed to prevent the spread of microbes that can cause disease in humans because of produce consumption. The microbial quality of irrigation water is evaluated based on concentrations of as the indicator organism. Given the high spatial and temporal variability of concentrations in irrigation water sources, recommendations are needed on where and when samples of water have to be taken for microbial analysis. This work demonstrates the presence of a temporally stable spatial pattern in the distributions of concentrations across irrigation ponds. The ponds studied had zones where concentrations were mostly higher than average and zones where the concentrations were mostly lower than average over the entire observation period, covering the season when water was used for irrigation. Accounting for the existence of such zones will improve the design and implementation of microbial water quality monitoring.
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http://dx.doi.org/10.1128/AEM.01876-17DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5772220PMC
February 2018

Development and evaluation of the bacterial fate and transport module for the Agricultural Policy/Environmental eXtender (APEX) model.

Sci Total Environ 2018 Feb 17;615:47-58. Epub 2017 Oct 17.

USDA-ARS, Environmental Microbial and Food Safety Lab, 10300 Baltimore Avenue, BARC-East Bldg. 173, Beltsville, MD 20705, USA. Electronic address:

The Agricultural Policy/Environmental eXtender (APEX) is a watershed-scale water quality model that includes detailed representation of agricultural management. The objective of this work was to develop a process-based model for simulating the fate and transport of manure-borne bacteria on land and in streams with the APEX model. The bacteria model utilizes manure erosion rates to estimate the amount of edge-of-field bacteria export. Bacteria survival in manure is simulated as a two-stage process separately for each manure application event. In-stream microbial fate and transport processes include bacteria release from streambeds due to sediment resuspension during high flow events, active release from the streambed sediment during low flow periods, bacteria settling with sediment, and survival. Default parameter values were selected from published databases and evaluated based on field observations. The APEX model with the newly developed microbial fate and transport module was applied to simulate fate and transport of the fecal indicator bacterium Escherichia coli in the Toenepi watershed, New Zealand that was monitored for seven years. The stream network of the watershed ran through grazing lands with daily bovine waste deposition. Results show that the APEX with the bacteria module reproduced well the monitored pattern of E. coli concentrations at the watershed outlet. The APEX with the microbial fate and transport module will be utilized for predicting microbial quality of water as affected by various agricultural practices, evaluating monitoring protocols, and supporting the selection of management practices based on regulations that rely on fecal indicator bacteria concentrations.
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http://dx.doi.org/10.1016/j.scitotenv.2017.09.231DOI Listing
February 2018

Hydrological modeling of Fecal Indicator Bacteria in a tropical mountain catchment.

Water Res 2017 08 15;119:102-113. Epub 2017 Apr 15.

Géosciences Environnement Toulouse, Université de Toulouse, CNES, CNRS, IRD, UPS, 31400 Toulouse, France.

The occurrence of pathogen bacteria in surface waters is a threat to public health worldwide. In particular, inadequate sanitation resulting in high contamination of surface water with pathogens of fecal origin is a serious issue in developing countries such as Lao P.D.R. Despite the health implications of the consumption of contaminated surface water, the environmental fate and transport of pathogens of fecal origin and their indicators (Fecal Indicator Bacteria or FIB) are still poorly known in tropical areas. In this study, we used measurements of flow rates, suspended sediments and of the FIB Escherichia coli (E. coli) in a 60-ha catchment in Northern Laos to explore the ability of the Soil and Water Assessment Tool (SWAT) to simulate watershed-scale FIB fate and transport. We assessed the influences of 3 in-stream processes, namely bacteria deposition and resuspension, bacterial regrowth, and hyporheic exchange (i.e. transient storage) on predicted FIB numbers. We showed that the SWAT model in its original version does not correctly simulate small E. coli numbers during the dry season. We showed that model's performance could be improved when considering the release of E. coli together with sediment resuspension. We demonstrated that the hyporheic exchange of bacteria across the Sediment-Water Interface (SWI) should be considered when simulating FIB concentration not only during wet weather, but also during the dry season, or baseflow period. In contrast, the implementation of the regrowth process did not improve the model during the dry season without inducing an overestimation during the wet season. This work thus underlines the importance of taking into account in-stream processes, such as deposition and resuspension, regrowth and hyporheic exchange, when using SWAT to simulate FIB dynamics in surface waters.
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http://dx.doi.org/10.1016/j.watres.2017.04.038DOI Listing
August 2017

Release from Streambed to Water Column during Baseflow Periods: A Modeling Study.

J Environ Qual 2017 Jan;46(1):219-226

Streambed sediments can harbor large populations that are released into the water column during high-flow events. Few studies have been conducted on the rates of transfer from streambed sediment to water column in low-flow conditions in natural streams. The aim of this work was to apply the watershed-scale model SWAT (Soil and Water Assessment Tool) to a natural stream to evaluate the need to account for the release from streambed sediments during baseflow periods and to compare the results of simulating such a release by assuming predominantly passive transport, driven by groundwater influx, against simulations assuming predominantly active transport of random or chemotaxis-driven bacteria movement. concentrations in water during baseflow periods were substantially underestimated when release from the streambed was attributed only to streambed sediment resuspension. When considered in addition to the release due to sediment resuspension at high flows, the active and passive release assumptions provided 42 and 4% improvement, respectively, in the RMSE of logarithms of concentrations. Estimated fluxes to water column during the baseflow periods from June to November ranged from 3.3 × 10 colony-forming units (CFU) m d in the game land area to 1.4 × 10 CFU m d in the mixed pasture and cropland. Results demonstrate that release of from streambed sediments during baseflow periods is substantial and that water column concentrations are dependent on not only land management practices but also on in-stream processes.
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http://dx.doi.org/10.2134/jeq2016.03.0114DOI Listing
January 2017

Enrichment of stream water with fecal indicator organisms during baseflow periods.

Environ Monit Assess 2017 Jan 6;189(2):51. Epub 2017 Jan 6.

USDA-ARS Environmental Microbial and Food Safety Laboratory, Beltsville, MD, USA.

Fecal indicator organisms (FIOs) are generally believed to be present in surface waters due solely to direct deposition of feces or through transport in runoff. However, emerging evidence points toward hyporheic exchange between sediment pore water and the overlying water column during baseflow periods as a source of FIOs is surface waters. The objective of this work was to (a) propose a mass balance-based technique for estimating changes of FIO concentrations in the same volume of water (or "slug") from the inlet to outlet of stream reaches in baseflow conditions and (b) to use such enumeration to estimate rate of the FIO release to stream water column. Concentrations of Escherichia coli (E. coli) and enterococci were measured in the slug while simultaneously monitoring the movement of a conservative tracer, Br that labeled the slug. Concentrations of E. coli in the slug were significantly larger (P = 0.035, P = 0.001, and P = 0.001, respectively) at the outlet reach in all three replications, while enterococci concentrations were significantly larger in two of three replications (P = 0.001, P < 0.001, and P = 0.602). When estimated without accounting for die-off in water column, FIO net release rates across replications ranged from 36 to 57 cells m s and 43 to 87 cells m s for E. coli and enterococci, respectively. These release rates were 5 to 20% higher when the die-off in water column was taken into account. No diurnal trends were observed in indicator concentrations. No FIO sources other than bottom sediment have been observed during the baseflow period. FIOs are released into stream water column through hyporheic exchange during baseflow periods.
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http://dx.doi.org/10.1007/s10661-016-5763-8DOI Listing
January 2017

Modeling the interannual variability of microbial quality metrics of irrigation water in a Pennsylvania stream.

J Environ Manage 2017 Feb 29;187:253-264. Epub 2016 Nov 29.

Farm Systems & Environment, AgResearch Ltd, Invermay Research Centre, Private Bag 50034, Mosgiel 9053, New Zealand.

Knowledge of the microbial quality of irrigation waters is extremely limited. For this reason, the US FDA has promulgated the Produce Rule, mandating the testing of irrigation water sources for many farms. The rule requires the collection and analysis of at least 20 water samples over two to four years to adequately evaluate the quality of water intended for produce irrigation. The objective of this work was to evaluate the effect of interannual weather variability on surface water microbial quality. We used the Soil and Water Assessment Tool model to simulate E. coli concentrations in the Little Cove Creek; this is a perennial creek located in an agricultural watershed in south-eastern Pennsylvania. The model performance was evaluated using the US FDA regulatory microbial water quality metrics of geometric mean (GM) and the statistical threshold value (STV). Using the 90-year time series of weather observations, we simulated and randomly sampled the time series of E. coli concentrations. We found that weather conditions of a specific year may strongly affect the evaluation of microbial quality and that the long-term assessment of microbial water quality may be quite different from the evaluation based on short-term observations. The variations in microbial concentrations and water quality metrics were affected by location, wetness of the hydrological years, and seasonality, with 15.7-70.1% of samples exceeding the regulatory threshold. The results of this work demonstrate the value of using modeling to design and evaluate monitoring protocols to assess the microbial quality of water used for produce irrigation.
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http://dx.doi.org/10.1016/j.jenvman.2016.11.054DOI Listing
February 2017

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

J Water Health 2016 Jun;14(3):443-59

Department of Environmental Science and Technology, University of Maryland at College Park, College Park, MD 20742, USA.

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.
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http://dx.doi.org/10.2166/wh.2016.239DOI Listing
June 2016

Modeling fate and transport of fecally-derived microorganisms at the watershed scale: State of the science and future opportunities.

Water Res 2016 09 29;100:38-56. Epub 2016 Apr 29.

USDA-ARS, Environmental Microbial and Food Safety Laboratory, 10300 Baltimore Ave. Building 173, BARC-EAST, Beltsville, MD 20705, USA.

Natural waters serve as habitat for a wide range of microorganisms, a proportion of which may be derived from fecal material. A number of watershed models have been developed to understand and predict the fate and transport of fecal microorganisms within complex watersheds, as well as to determine whether microbial water quality standards can be satisfied under site-specific meteorological and/or management conditions. The aim of this review is to highlight and critically evaluate developments in the modeling of microbial water quality of surface waters over the last 10 years and to discuss the future of model development and application at the watershed scale, with a particular focus on fecal indicator organisms (FIOs). In doing so, an agenda of research opportunities is identified to help deliver improvements in the modeling of microbial water quality draining through complex landscape systems. This comprehensive review therefore provides a timely steer to help strengthen future modeling capability of FIOs in surface water environments and provides a useful resource to complement the development of risk management strategies to reduce microbial impairment of freshwater sources.
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http://dx.doi.org/10.1016/j.watres.2016.04.064DOI Listing
September 2016

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

J Environ Qual 2016 May;45(3):949-57

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.
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http://dx.doi.org/10.2134/jeq2015.08.0427DOI Listing
May 2016

Irrigation waters and pipe-based biofilms as sources for antibiotic-resistant bacteria.

Environ Monit Assess 2016 Jan 24;188(1):56. Epub 2015 Dec 24.

USDA-ARS Environmental Microbial and Food Safety Laboratory, Beltsville Agricultural Research Center, 10300 Baltimore Ave. Bldg. 173, Beltsville, MD, 20705, USA.

The presence of antibiotic-resistant bacteria in environmental surface waters has gained recent attention. Wastewater and drinking water distribution systems are known to disseminate antibiotic-resistant bacteria, with the biofilms that form on the inner-surfaces of the pipeline as a hot spot for proliferation and gene exchange. Pipe-based irrigation systems that utilize surface waters may contribute to the dissemination of antibiotic-resistant bacteria in a similar manner. We conducted irrigation events at a perennial stream on a weekly basis for 1 month, and the concentrations of total heterotrophic bacteria, total coliforms, and fecal coliforms, as well as the concentrations of these bacterial groups that were resistant to ampicillin and tetracycline, were monitored at the intake water. Prior to each of the latter three events, residual pipe water was sampled and 6-in. sections of pipeline (coupons) were detached from the system, and biofilm from the inner-wall was removed and analyzed for total protein content and the above bacteria. Isolates of biofilm-associated bacteria were screened for resistance to a panel of seven antibiotics, representing five antibiotic classes. All of the monitored bacteria grew substantially in the residual water between irrigation events, and the biomass of the biofilm steadily increased from week to week. The percentages of biofilm-associated isolates that were resistant to antibiotics on the panel sometimes increased between events. Multiple-drug resistance was observed for all bacterial groups, most often for fecal coliforms, and the distributions of the numbers of antibiotics that the total coliforms and fecal coliforms were resistant to were subject to change from week to week. Results from this study highlight irrigation waters as a potential source for antibiotic-resistant bacteria, which can subsequently become incorporated into and proliferate within irrigation pipe-based biofilms.
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http://dx.doi.org/10.1007/s10661-015-5067-4DOI Listing
January 2016

Predicting microbial water quality with models: Over-arching questions for managing risk in agricultural catchments.

Sci Total Environ 2016 Feb 3;544:39-47. Epub 2015 Dec 3.

Biological & Environmental Sciences, School of Natural Sciences, University of Stirling, Stirling FK9 4LA, UK.

The application of models to predict concentrations of faecal indicator organisms (FIOs) in environmental systems plays an important role for guiding decision-making associated with the management of microbial water quality. In recent years there has been an increasing demand by policy-makers for models to help inform FIO dynamics in order to prioritise efforts for environmental and human-health protection. However, given the limited evidence-base on which FIO models are built relative to other agricultural pollutants (e.g. nutrients) it is imperative that the end-user expectations of FIO models are appropriately managed. In response, this commentary highlights four over-arching questions associated with: (i) model purpose; (ii) modelling approach; (iii) data availability; and (iv) model application, that must be considered as part of good practice prior to the deployment of any modelling approach to predict FIO behaviour in catchment systems. A series of short and longer-term research priorities are proposed in response to these questions in order to promote better model deployment in the field of catchment microbial dynamics.
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http://dx.doi.org/10.1016/j.scitotenv.2015.11.086DOI Listing
February 2016

Release and Removal of Microorganisms from Land-Deposited Animal Waste and Animal Manures: A Review of Data and Models.

J Environ Qual 2015 Sep;44(5):1338-54

Microbial pathogens present a leading cause of impairment to rivers, bays, and estuaries in the United States, and agriculture is often viewed as the major contributor to such contamination. Microbial indicators and pathogens are released from land-applied animal manure during precipitation and irrigation events and are carried in overland and subsurface flow that can reach and contaminate surface waters and ground water used for human recreation and food production. Simulating the release and removal of manure-borne pathogens and indicator microorganisms is an essential component of microbial fate and transport modeling regarding food safety and water quality. Although microbial release controls the quantities of available pathogens and indicators that move toward human exposure, a literature review on this topic is lacking. This critical review on microbial release and subsequent removal from manure and animal waste application areas includes sections on microbial release processes and release-affecting factors, such as differences in the release of microbial species or groups; bacterial attachment in turbid suspensions; animal source; animal waste composition; waste aging; manure application method; manure treatment effect; rainfall intensity, duration, and energy; rainfall recurrence; dissolved salts and temperature; vegetation and soil; and spatial and temporal scale. Differences in microbial release from liquid and solid manures are illustrated, and the influential processes are discussed. Models used for simulating release and removal and current knowledge gaps are presented, and avenues for future research are suggested.
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http://dx.doi.org/10.2134/jeq2015.02.0077DOI Listing
September 2015

Rainfall intensity effects on removal of fecal indicator bacteria from solid dairy manure applied over grass-covered soil.

Sci Total Environ 2016 Jan 18;539:583-591. Epub 2015 Sep 18.

USDA-ARS Environmental Microbial and Food Safety Laboratory, Beltsville Agricultural Research Center, Beltsville, MD, USA.

The rainfall-induced release of pathogens and microbial indicators from land-applied manure and their subsequent removal with runoff and infiltration precedes the impairment of surface and groundwater resources. It has been assumed that rainfall intensity and changes in intensity during rainfall do not affect microbial removal when expressed as a function of rainfall depth. The objective of this work was to test this assumption by measuring the removal of Escherichia coli, enterococci, total coliforms, and chloride ion from dairy manure applied in soil boxes containing fescue, under 3, 6, and 9cmh(-1) of rainfall. Runoff and leachate were collected at increasing time intervals during rainfall, and post-rainfall soil samples were taken at 0, 2, 5, and 10cm depths. Three kinetic-based models were fitted to the data on manure-constituent removal with runoff. Rainfall intensity appeared to have positive effects on rainwater partitioning to runoff, and removal with this effluent type occurred in two stages. While rainfall intensity generally did not impact the parameters of runoff-removal models, it had significant, inverse effects on the numbers of bacteria remaining in soil after rainfall. As rainfall intensity and soil profile depth increased, the numbers of indicator bacteria tended to decrease. The cumulative removal of E. coli from manure exceeded that of enterococci, especially in the form of removal with infiltration. This work may be used to improve the parameterization of models for bacteria removal with runoff and to advance estimations of depths of bacteria removal with infiltration, both of which are critical to risk assessment of microbial fate and transport in the environment.
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http://dx.doi.org/10.1016/j.scitotenv.2015.07.108DOI Listing
January 2016

Solid Manure As a Source of Fecal Indicator Microorganisms: Release under Simulated Rainfall.

Environ Sci Technol 2015 Jul 8;49(13):7860-9. Epub 2015 Jun 8.

‡USDA-ARS Environmental Microbial and Food Safety Laboratory, Beltsville Agricultural Research Center, Beltsville, Maryland 20705, United States.

Understanding and quantifying microbial release from manure is a precondition to estimation and management of microbial water quality. The objectives of this work were to determine the effects of rainfall intensity and surface slope on the release of Escherichia coli, enterococci, total coliforms, and dissolved chloride from solid dairy manure and to assess the performance of the one-parametric exponential model and the two-parametric Bradford-Schijven model when simulating the observed release. A controlled-intensity rainfall simulator induced 1 h of release in runoff/leachate partitioning boxes at three rainfall intensities (30, 60, and 90 mm h(-1)) and two surface slopes (5% and 20%). Bacterial concentrations in initial release were more than 1 order of magnitude lower than their starting concentrations in manure. As bacteria were released, they were partitioned into runoff and leachate at similar concentrations, but in different volumes, depending on slope. Bacterial release occurred in two stages that corresponded to mechanisms associated with release of manure liquid- and solid-phases. Parameters of the two models fitted to the bacterial release dependencies on rainfall depth were not significantly affected by rainfall intensity or slope. Based on model performance tests, the Bradford-Schijven model is recommended for simulating bacterial release from solid manure.
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http://dx.doi.org/10.1021/acs.est.5b01095DOI Listing
July 2015

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

Crit Rev Microbiol 2016 May 8;42(3):384-93. Epub 2014 Sep 8.

c US Environmental Protection Agency, National Exposure Research Laboratory , Athens , GA , USA.

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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http://dx.doi.org/10.3109/1040841X.2014.954524DOI Listing
May 2016

Colloid filtration in surface dense vegetation: experimental results and theoretical predictions.

Environ Sci Technol 2014 Apr 14;48(7):3883-90. Epub 2014 Mar 14.

Department of Agricultural and Biological Engineering, University of Florida , Gainesville, Florida 32611, United States.

Understanding colloid and colloid-facilitated contaminant transport in overland flow through dense vegetation is important to protect water quality in the environment, especially for water bodies receiving agricultural and urban runoff. In previous studies, a single-stem efficiency theory for rigid and clean stem systems was developed to predict colloid filtration by plant stems of vegetation in laminar overland flow. Hence, in order to improve the accuracy of the single-stem efficiency theory to real dense vegetation system, we incorporated the effect of natural organic matter (NOM) on the filtration of colloids by stems. Laboratory dense vegetation flow chamber experiments and model simulations were used to determine the kinetic deposition (filtration) rate of colloids under various conditions. The results show that, in addition to flow hydrodynamics and solution chemistry, steric repulsion afforded by NOM layer on the plants stem surface also plays a significant role in controlling colloid deposition on vegetation in overland flow. For the first time, a refined single-stem efficiency theory with considerations of the NOM effect is developed that describes the experimental data with good accuracy. This theory can be used to not only help construct and refine mathematical models of colloid transport in real vegetation systems in overland flow, but also inform the development of theories of colloid deposition on NOM-coated surfaces in natural, engineered, and biomedical systems.
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http://dx.doi.org/10.1021/es404603gDOI Listing
April 2014
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