2009 Annual Report
1a.Objectives (from AD-416)
Objective 1: Determine dominant environmental parameters and processes involved in the fate and transport of manure-borne coliform bacteria at field and watershed scales in a hydrological context. Develop predictive models of the fate and transport of manure-borne coliform bacteria at field and watershed scales.
Objective 2: Determine prevalence and diversity of pathogenic E. coli and Salmonella in watersheds with different land uses (urban/suburban, forested, animal agriculture) in the mid-Atlantic area. Measure airborne dissemination and survival of pathogenic bacteria and endotoxin from manures, compost, and wastewater treatment plant sludge. Evaluate methods combining immunological and genetic techniques for detection of water-borne pathogenic E. coli.
1b.Approach (from AD-416)
An integrated laboratory research, field research at hillslope and watershed scales, and mathematical modeling will be used. The experimental research will include evaluating effect of manure particulates on transport of coliform microorganisms in soil, relating partitioning of coliform microorganisms between sediment and runoff to soil texture, manure properties and flow rate, establishing dependencies of coliform release rates from manure on rain intensity, manure type and composition, and manure application method, evaluating predictive efficiency of laboratory data on manure-borne coliform survival data for the field conditions, assessing phosphorus as a tracer of manure-borne transport in runoff; determining effect of background coliform populations and field manure application on coliform concentrations in runoff from fields and in a perennial creek in a riparian zone. Modeling research will include determining dominant mechanisms of manure-borne coliform transport at pedon, field, and watershed scales; develop and test models to simulate those mechanisms, performing uncertainty analysis to evaluate the reliability of coliform transport model predictions given available data on variation in input parameters, transforming model computers codes to make them compatible to existing and under-development user-friendly decision support tools.
E. coli and chemical tracer breakthrough to shallow groundwater was monitored in a four-month experiment at the OPE3 experimental watershed at the Beltsville Agricultural Research Center. The site was instrumented with replicated multiple capacitance probes, multilevel sampling wells, tensiometers, and a rainfall simulation system. In addition, E. coli concentrations were monitored in the runoff from manured fields.
Artificial flood experiments were performed at the OPE3 creek to evaluate the effect of sediment-borne E. coli. This allowed the action of sediment resuspension and settling to be documented while excluding microbial inputs from runoff. In addition, E. coli concentrations in water and sediment were monitored weekly by grab sampling in summer, and with refrigerated samplers during natural high-flow events.
Uncertainty analysis was performed for the previously developed E. coli transport model (STWIR) at the field scale using data from four years of manure application and runoff monitoring at the OPE3 field site. The analysis demonstrated that the very high variability in E. coli distribution across the field is the leading uncertainty factor, and that this variability essentially precludes using average bacterial concentration values in estimating bacterial runoff at the edge of the field.
A new experimental protocol was designed and implemented to evaluate the effect of temperature, sediment particle size and organic matter content on E. coli survival in sediment. A series of experiments in controlled environment chambers demonstrated the dominant role of particle size and the applicability of the food microbiology models to the dependencies of E. coli survival rates on temperature.
The Cove Mountain Creek Watershed in Southern Pennsylvania was monitored year-round to provide datasets for validation and improvement of the bacterial transport submodel in the ARS watershed model SWAT. Hydrologic variables, and concentrations of both generic and potentially pathogenic E. coli were measured.
A new submodel was developed for the SWAT model to address the pressing need to incorporate the effects of bacterial release from sediment resuspension on microbiological water quality and water quality prediction and assessment tools. This model was calibrated and tested with the three-year monitoring dataset from the Cove Mountain Creek Watershed in Southern Pennsylvania. Also, a new method was developed to account for missing weather data.
The first database of E. coli survival in manure, soil, water, and sediment was designed, implemented and populated with data from about 1,500 published experiments. The user-friendly interface for the database was designed.
A pioneer modeling project was initiated to develop tools for evaluation of the effect of nutrient concentrations and water velocity on biofilm stability in irrigation water distribution systems.
Model developed to simulate the effect of streambed bacteria on microbial water quality. Streambed sediments are increasingly recognized as major reservoirs for water-borne bacteria, including pathogenic strains. However, the effects of E. coli release due to sediment resuspension on microbiological quality of surface waters has not been addressed in water quality prediction and assessment tools. We developed the first bacterial release and deposition module for the ARS-USDA model SWAT and applied it to model bacterial water quality in the rural Little Cove Creek watershed in Southern Pennsylvania. Simulations indicated that the predominant source of water-borne bacteria in the watershed throughout most of the year was from sediment-borne bacteria in the streambed, rather than from runoff. These results are important for the design, evaluation and implementation of conservation and best management practices nationwide in that the work has identified an important source of water-borne bacteria in freshwater streams that is currently overlooked.
E. coli survival in stream bottom sediments measured. E. coli is the most common indicator bacteria used to evaluate microbiological impairment of streams. It can reach streams with manure particles in runoff and become trapped in stream sediments. It is not known whether and how long manure-borne E. coli can survive in sediment and appear in stream water due to sediment resuspension. We demonstrated that sediments can provide a hospitable habitat for manure-borne E. coli. E. coli can survive in sediments during winter and contribute to water impairment in subsequent warm seasons. This research will conceptually impact methods of evaluating rural stream water quality that currently neglect sediments as reservoirs of pathogen and indicator microorganisms.
Database of E. coli survival in manure, soil, water, and sediment created. Data on E. coli inactivation in environmental media are spread over a myriad of publications. There is a pressing need in creating a single source of E. coli inactivation parameters in environmental media for the design and evaluation of best management practices. We created a database of published data on E. coli inactivation and linked it with software to estimate inactivation rates. Results of this research are expected to be widely used by environmental and agricultural engineers in projects dealing with assessment and mitigation of manure-borne pathogen and indicator organisms.
Model developed to simulate the runoff transport of manure-borne microorganisms. Overland transport of manure-borne microorganisms is an important factor affecting surface water quality. We developed the first field-scale event-based model STWIR, linked to the USDA-ARS runoff and erosion model KINEROS, to assess bacterial fluxes at the edge of manured fields. The model was validated with data from multi-year manure application experiments at the OPE3 field site at BARC. Further parameterization of this model will create a tool to assess the potential impact of microbial contamination on surface waters due to manure applications, and the value of conservation practices aimed at preventing this contamination.
Guber, A.K., Gish, T.J., Pachepsky, Y.A., Van Genuchten, M.T., Daughtry, C.S., Nicholson, T., Cady, R. 2008. Temporal stability of estimated soil water flux patterns across agricultural fields. International Agrophysics. 22:209-214.
San Jose Martinez, F., Pachepsky, Y.A., Rawls, W.J. 2009. The advective-dispersive equation with spatial fractional derivatives as a model for tracer transport in structured soil. Vadose Zone Journal. 8:242-249.
Guber, A.K., Yakirevich, A.M., Sadeghi, A.M., Pachepsky, Y.A., Shelton, D.R. 2009. Uncertainty Evaluation of Coliform Bacteria Removal from Vegetated Filter Strip under Overland Flow Condition. Journal of Environmental Quality. 38:1636-1644.
San Jose Martinez, F., Caniego, J., Guber, A.K., Pachepsky, Y.A., Reyes, M. 2009. Multifractal modeling of soil microtopography with multiple transects data. Ecological Complexity. 6(3):240-245.
Kim, J., Choi, H., Pachepsky, Y.A. 2009. Biofilm morphology as related to the porous media clogging. Water Research. http://dx.doi.org/10.1016j.watres.2009.05.049.