Research Soil Scientist
Environmental Microbial and Food Safety Lab
USDA, ARS, BA, ANRI, EMFSL
10300 Baltimore Avenue
Building 173 Room 203, BARC-East
Beltsville, MD 20705
Phone 301.504.7468
www.ars.usda.gov/ba/anri/emfsl/pachepsky
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Education
- 1987 Ph. D. in Soil Science. Soil Science Department, Moscow State University,
Russia. Dissertation title: "Regularities and models of chemical transport
in soils of arid and semiarid regions"
- 1973 Ph. D. in Physics and Mathematics, Department of Mechanics and Mathematics,
Moscow State University, Russia. Dissertation title: " One-dimensional
problems in rock mechanics "
- 1969 M. Sci. in Mechanics, Department of Mechanics and Mathematics, Moscow
State University, Russia. Dissertation title: "One-dimensional problems
of ground mechanics"
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Professional Experience
- 2001-pres. Soil Scientist, USDA-ARS Environmental Microbial & Food
Safety Laboratory, Beltsville Agricultural Research Center, Beltsville,
MD
- 1999-2001 Research Physical Scientist, USDA-ARS Hydrology and Remote Sensing
Laboratory, Beltsville Agricultural Research Center, Beltsville, MD
- 1994-1999 Senior Research Scholar, Phytotron, Duke University, Durham,
NC
- 1992-1993 Visiting Research Scientist, University of Maryland, College
Park, MD
- 1990-1992 Professor, Soil Science Department, Moscow State University,
Moscow, USSR.
- 1988-1991 Research Leader , Institute of Soil Science and Photosynthesis,
USSR Academy of Sciences, Puschino
- 1985-1988 Lead Scientist, Institute of Soil Science and Photosynthesis,
USSR Academy of Sciences, Puschino
- 1975-1982 Senior Scientist, Institute of Agrochemistry and Soil Science,
USSR Academy of Sciences, Puschino
- 1972-1975 Minor Scientist, Institute of Agrochemistry and Soil Science,
USSR Academy of Sciences, Puschino
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Statement of Research
The purpose of the research is to discover, evaluate, and integrate knowledge
about transport and fate of enteric pathogenic microorganisms in soils
and landscapes. New hypotheses and measurement strategies have to be developed
to evaluate and quantify biological, chemical and physical factors and
interactions affecting surface and subsurface pathogen transport, and pathogen
survival. The research uses hydrologic and contaminant transport modeling,
soil-landscape analysis, scaling methods, data mining, geographic information
systems, and other relevant technologies to integrate pathogen fate and
transport information in pathogen transport models for comparison, evaluation,
and selection of management practices to reduce or eliminate risk of surface
and ground water contamination.
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Collaborating Scientists
- Daniel Shelton, Jeffery Karns, Jo Ann van Kessel, Ali Sadeghi, Craig Daughtry,
Timothy Gish, Thanh Dao, Gregory McCarty, James Reeves, III, Charles Walthall,
Jerry Ritchie, Vangimalla Reddy, Dennis Timlin, USDA-ARS, Beltsville
- Scott Bradford, USDA-ARS, Riverside, CA
- Elaine Berry an Bryan Woodbury, USDA-ARS, Clay Center, NE
- David Goodrich and Carl Unkrich, USDA-ARS, Tucson
- Jeffery Arnold, USDA-ARS, Temple, TX
- Carl Bolster, USDA-ARS Bowling Green, KY
- Dennis Flanagan and James Frankenberger, USDA-ARS, West Lafayette, IN
- Michael Jenkins, USDA-ARS, Watkinsville, GA
- Thomas Moorman and Mark Tomer, USDA-ARS, Ames, IA
- Thomas Nicholson and Ralph Cady, US NRC, Washington, DC
- Edmund Perfect, University of Tennessee, Knoxville, TN
- Teferi Tsegaye, Alabama A&M, Huntsville, AL
- Jiri Simunek, University of California, Riverside, CA
- Naraine Persaud and Brian Benham, Virginia Tech, Blacksburg, VA
- Robert Hill, Adel Shirmohammadi, and Attila Nemes, University of Maryland,
College Park
- Michail Kouznetsov, Alexander Yakirevich, Jakob Blaustein, Desert Research
Institute, Sde Boker, Israel
- Diederik Jacques, SCK-CEN, Mol, Belgum
- Eugeny Shein and Boris Devin, Moscow State University, Moscow, Russia
- Fariz Mikayilsoy, Selchuk University, Adana, Turkey
- Rien van Genuchten, University of Rio de Janeiro, Brazil
- John Crawford, University of Sydney, Australia
- Miguel Angel Martin and Fernando San Jose Martinez, Technical University
of Madrid, Spain
- Krzisztof Lamorsi and Cezary Slawinski, Institute of Agrophysics, Lublin,
Poland
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Professional Affiliations
- American Society of Agronomy
- Soil Science Society of America
- Soil and Water Conservation Society
- American Geophysical Union
- International Society of Ecological Modeling
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Grants and Contracts
- The interagency agreement "Model Abstraction Techniques for Soil Water
Flow and Transport"
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Current Projects
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CRIS Project "Fate and Transport of Manure-Borne Pathogenic Microorganisms"
Utilization of manures containing pathogenic microorganisms is considered
to be an important factor in the occurrence of water- and food-borne diseases.
Currently many of the essential pathogen fate and transport processes are
not understood or modeled well. This project focuses on manure-borne pathogenic
coliform bacteria and has objectives of (a) determining 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,
and (b) developing predictive models of the fate and transport of manure-borne
coliform bacteria at field and watershed scales. An integrated approach
including laboratory research, field research at hillslope and watershed
scales, and modeling, is used. Experiments and monitoring are carried out
to elucidate and quantify survival and release of manure-borne pathogens
in field conditions, interactions of pathogens and manure particulates,
pathogen partitioning between runoff and infiltration and between sediment
and water, suitability of manure-borne phosphorus and organic matter to
serve as useful tracers of E. coli transport, and significance of background
concentrations of E. coli for understanding fate and transport of manure-borne
E. coli. Sub-models are being developed to explain or predict the efficiency
of vegetated filter strips in retention of manure-borne pathogenic E. coli,
and to be included in user-friendly tools for evaluating effects of management
practices on pathogenic E. coli fate and transport at the watershed scale.
A broad collaboration is initiated on developing methods of manure characterization,
on monitoring studies, and for compiling databases for model validation
and assessment.
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| Manure particulates serve as carriers, abode, and food source for pathogens.
Relatively high survival rates are found for manure-borne coliforms in
Maryland conditions.
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| The VFS efficiency depends on infiltration capacity, status of vegetation,
and contributing area. The pathogen input from wildlife and survival of
pathogens in stream and lake sediments remain the substantial sources of
uncertainty. The bacteria transport submodel for the USDA-ARS Soil Water
Assessment Tool (SWAT) was developed for the watershed scale. Currently
a program is in place to develop and test the VSF-scale and the field-scale
models.
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Development of best management practices requires assessment of fate and
transport of manure-borne pathogens at several scales:
- Small-scale assessment is needed to evaluate the efficiency of vegetated
filter strips (VFS)
- Field scale assessment is needed to time manure applications
- Watershed-scale assessments are needed to evaluate the efficiency of BMPs
with respect to the water quality
Development and comparison of predictive models are the necessary steps
in providing decision support tools for efficient evaluation of BMPs. We
are collecting data for model development and testing at the:
- Patuxent lysimeter site
- Beltsville OPE3 experimental watershed
- Cove Mountain Creek watershed
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Research Components for
Model Development and Testing
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| Phosphorous as an Indicator of Pathogen Transport
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MBP populations in fresh manure frequently increase due to the availability
of nutrients and a favorable habitat and then may remain stable for up
to a month. Subsequent mortality rates are highly variable depending on
the animal diet, temperature and rainfall/drying conditions.
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| Pathogen Mortality Rates
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| The availability of a manure-borne indicator, which behaves similarly
to manure-borne bacterial pathogen (MBP), would be very useful due to the
high cost analysis for MBPs. Our data indicate that both release rate coefficients
and subsequent overland transport are very similar for phosphorous and
MBPs. Therefore, the substantial data base which exists for phosphorous
transport may be applicable to MBP transport.
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| Pathogen Attachment to Soil
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Partitioning of manure-borne bacterial pathogens (MBP) between solution
and solids in runoff is important in evaluating the contribution of soil
erosion in MBP transport. Our data show that the "solution-solids" distribution
coefficient (Kd) is highly variable and is dependent on soil texture and
manure consistency.
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| Factors Affecting Pathogen Transport
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| The extent of overland transport of manure-borne bacterial pathogens (MBP)
is primarily affected by rates of infiltration into the soil profile. Infiltration
rates are largely dependent on vegetation, which can both loosen soil and
create plant litter that can filter runoff water. Using the novel heuristic
method of data analysis - regression trees - allows us to define the relative
importance of various factors affecting infiltration rates. Our results
illustrate the need of properly designing and managing vegetation in grass
buffers to mitigate MBP transport.
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| Management Practices to Minimize Pathogen Run-off
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Our data demonstrate that riparian zones, i.e. vegetated corridors adjacent
to stream channels, can effectively prevent runoff of manure-borne bacterial
pathogens from land-applied manures to surface waters. However, riparian
zones may harbor wildlife that contribute to contamination of surface waters
by bacterial pathogens.
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| Sources of Water-borne Pathogens
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Estimating fate and transport of manure-borne bacterial pathogens (MBP)
has a built-in uncertainty related to the wildlife input. Monitoring data
from an agricultural watershed shows that stream segments affected only
by wildlife may have higher concentrations of MBPs than agricultural segments
of the watershed. Another source of uncertainty is the background concentrations
of MBPs in sediments. This uncertainty does not preclude the modeling of
MBP fate and transport, however, it does need to be factored into the modeling
process.
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| Modeling Pathogen Fate and Transport
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Combining mathematical descriptions of microbial fate and transport processes
leads to the development of predictive fate and transport models. The model
STIR was developed to simulate the coupled surface and subsurface flow
and transport of bacteria in grass buffers. We combined the three-dimensional
FEMWATER model of saturated-unsaturated subsurface flow and transport with
the Saint-Venant model for runoff and convective-dispersive transport with
retention in the overland flow. The model was successfully tested with
data on rainfall-induced fecal coliforms (FC) and bromide (Br) transport
from manure applied at vegetated and bare 6-m long plots.
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Interagency project:
Model Abstraction Techniques for Soil Water Flow and Transport
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This project tests the model abstraction (MA) at the watershed scale.
The MA is defined as a methodology for reducing the complexity of a simulation
model while maintaining the validity of the simulation results with respect
to the question that the simulation is being used to address. MA explicitly
addresses uncertainties in both model structure and parameters. We are
using the systematic and comprehensive protocol for implementing the MA
that includes:
- defining the conceptualization of the hydrologic model and the questions
to be answered
- determining the significant features, events and processes to be abstracted
- selecting applicable MA techniques
- identifying MA simplifications of complex representations that may provide
substantial gain
- evaluating the base model for additional simplifications of complex representations.
MA can resolve:
- difficulties in obtaining reliable calibration of the base model
- error propagation by introducing uncertainties into the key outputs
- difficulties in understanding errant simulations results of the base model
- excessive resource requirements for simulating complexities in base model
- the need for incorporating the base model in repetitive risk assessments
of multimedia environmental model
- the goal for making the modeling process more transparent and tractable
- the need in justifying the use simpler model rather than overly complex
model
The MA benefits include:
- improving reliability of modeling results
- making the data selection and input more efficient
- enabling risk assessments to be run and analyzed with much quicker turnaround,
with the potential for allowing further analyses of problem sensitivity
and uncertainty
- enhancing communication of simplifications resulting from appropriate
model abstractions which facilitates decision-making and informing the
public
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