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Yakov A Pachepsky

Research Soil Scientist
Research Soil Scientist

Environmental Microbial and Food Safety Lab
10300 Baltimore Avenue
Building 303 Room 021A, BARC-East
Beltsville, MD 20705
Phone 301.504.6084

Member of the Beltsville Supergrade Committee

photo of Dr. Pachepsky with visitors to BARC Public Field Day

  • 1987 Dr. Sc. 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"

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 Junior Scientist, Institute of Agrochemistry and Soil Science, USSR Academy of Sciences, Puschino

Statement of Research

The purpose of the research is to discover, evaluate, and integrate knowledge about transport and fate of enteric pathogenic microorganisms affecting microbial quality of irrigation waters. New hypotheses and measurement strategies have to be developed to evaluate and quantify biological, chemical and physical factors and interactions affecting pathogen prevalence, fate and transport in irrigation waters. 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 fate and transport models for development, evaluation, comparison, and selection of management practices to reduce or eliminate risk of preharvest microbial contamination of foods.

Collaborating Scientists
  • Moon Kim, Jo Ann Van Kessel, Ali Sadeghi, Craig Daughtry, Thanh Dao, Gregory McCarty, Vangimalla Reddy, Dennis Timlin, USDA-ARS, Beltsville, MD
  • Scott Bradford, USDA-ARS, Riverside, CA
  • David Goodrich and Carl Unkrich, USDA-ARS, Tucson, AZ
  • Frederick Pierson, USDA-ARS, Boise, ID
  • Mark Welz, USDA-ARS, Reno, NV
  • Jaehak Jeong and Jimmy Williams, Texas AgriLife, Temple, TX
  • Bin Gao and Rafael Muñoz-Carpena, University of Florida, Gainesville, FL
  • Andrey Guber, Michigan State University, East Lansing, MI
  • Jiri Simunek, University of California, Riverside, CA
  • Robert Hill, University of Maryland, College Park, MD
  • Thomas Nicholson, US Nuclear Regulatory Commission, Rockville, MD
  • Marirosa Molina, US EPA, Athens, GA
  • Mikhail Kuznetsov and Alexander Yakirevich, Jakob Blaustein, Desert Research Institute, Sde Boker, Israel
  • Fariz Mikayilsoy, Igdir University, Igdir, Turkey
  • Martinus van Genuchten, University of Rio de Janeiro, Brazil
  • Miguel Angel Martin and Fernando San Jose Martinez, Technical University of Madrid, Spain
  • Krzysztof Lamorski and Cezary Slawinski, Institute of Agrophysics, Lublin, Poland
  • Karl Vanderlinden, IFAPA, Seville, Spain
  • Gonzalo Martinez, University of Cordoba, Spain
  • Javier Valdes Abellan, University of Alikante, Spain
  • David Oliver, University of Stirling, Stirling, UK
  • Richard Muirhead, AgResearch, Dunedin, New Zealand
  • Harry Vereecken, Heye Bogena, Johan Huisman, and Jan Vanderborght, Institute of Agrosphere, Jülich, Germany
  • Kyunghwa Cho, Ulsan National Institute of Science and Technology, Republic of Korea
  • Joonha Kim, Gwangju National Institute of Science and Technology, Republic of Korea
  • Maria Leonor R.C. Lopes Assad, University of Sao Carlos, Brazil
  • Abhijit Nagchaudhuri, University of Maryland Eastern Shore, Princess Anne, MD
  • Edward Wells and Dana Harriger, Wilson College, PA

Professional Affiliations
  • American Society of Agronomy
  • Soil Science Society of America
  • American Association for the Advancement of Science
  • American Geophysical Union
  • International Society of Ecological Modeling
  • International Union of Soil Sciences

Interagency Research


  • Interagency agreement: "Predictive Assessment for Microbial Fate, Transport, and Exposure of Manure-Borne Indicators and Pathogens at Plot, Field, and Watershed Scales"

Recent Reviews


  • Hong, E., Pachepsky, Y., Whelan, G., Nicholson, T. (2017): Simpler models in environmental studies and predictions, Critical Reviews in Environmental Science and Technology, DOI: 10.1080/10643389.2017.1393264
  • Oliver, D.M., Porter, K.D., Pachepsky, Y.A., Muirhead, R.W., Reaney, S.M., Coffey, R., Kay, D., Milledge, D.G., Hong, E., Anthony, S.G. and Page, T. (2016). Predicting microbial water quality with models: Over-arching questions for managing risk in agricultural catchments. Science of the Total Environment, 544, pp.39-47.
  • Cho, K. H., Pachepsky, Y. A., Oliver, D. M., Muirhead, R. W., Park, Y., Quilliam, R. S., & Shelton, D. R. (2016). Modeling fate and transport of fecally-derived microorganisms at the watershed scale: State of the science and future opportunities. Water research, 100, 38-56.
  • Vereecken, H., Pachepsky, Y., Simmer, C., Rihani, J., Kunoth, A., Korres, W., Graf, A., Franssen, H.H., Thiele-Eich, I. and Shao, Y., 2016. On the role of patterns in understanding the functioning of soil-vegetation-atmosphere systems. Journal of Hydrology 542 (2016) 63–86.
  • Pachepsky, Y., Shelton, D., Dorner, S., and Whelan, G. (2014). Can E. coli or thermotolerant coliform concentrations predict pathogen presence or prevalence in irrigation waters? Critical Reviews in Microbiology, DOI: 10.3109/1040841X.2014.954524
  • Pachepsky, Y.A., and Shelton, D.R. (2011) 'Escherichia Coli and Fecal Coliforms in Freshwater and Estuarine Sediments', Critical Reviews in Environmental Science and Technology, 41:12, 1067-1110. (DOI: 10.1080/10643380903392718)
  • Pachepsky, Y.A., Shelton, D.R., McLain, J.E.T., Patel, J., and Mandrell, R.E. 2011. Irrigation Waters as a Source of Pathogenic Microorganisms in Produce: A Review. In: Advances in Agronomy, Vol. 113, pp. 73-138, D. Sparks, editor. Academic Press, Burlington.

Recent Publications

Click here to see a full list of publications drawn from the ARS database for Yakov Pachepsky, with access to an abstract/summary for each publication.

Current Parent Project
Design and Implementation of Monitoring and Modeling Methods to Evaluate Microbial Quality of Surface Water Sources Used for Irrigation

The 2011 Food Safety Modernization Act (FSMA) mandates that FDA promulgates regulations to ensure the safety of fresh produce (FDA Rule for Produce Safety). This includes a requirement for surveying irrigation waters for microbial quality based on generic Escherichia coli concentrations. E. coli concentrations are highly variable in space and time; understanding the factors responsible for this variability is a prerequisite for reliably surveying and monitoring microbial water quality. This project focuses on (1) elucidating spatial variability of E. coli concentrations in surface waters (e.g., streams, ponds, reservoirs) and describing the factors responsible; and (2) elucidating temporal variability of E. coli concentrations in watersheds as dependent on land use, meteorological conditions, and farm management practices. An integrated approach including laboratory and field research, and mathematical modeling will be used. Experiments and monitoring will be performed to (a) understand and quantify spatial patterns of indicator concentrations in ponds and reservoirs, and the effect of those patterns on indicator concentrations at water intake, (b) assess the value of remotely sensed parameters of water quality as environmental covariates to estimate indicator bacteria concentrations, and (c) assess the effect of soil and bottom sediment microbial reservoirs on microbial water quality of runoff and stream baseflow. The APEX (Agricultural Policy/Environmental Extender) model will be used along with our microbial fate and transport model to determine the optimal stream water monitoring strategy for a predetermined number of samples. Collaboration is envisaged to conduct monitoring and survey studies, and for model assessment. Results will be directly applicable to the implementation of the water component of FSMA directed towards food safety and irrigated agriculture sustainability.

Explanatory figure of microbial quality monitoring processes for a pond/reservoir and a stream

Interagency project:
Model Abstraction Techniques for Soil Water Flow and Transport
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:
  1. defining the conceptualization of the hydrologic model and the questions to be answered
  2. determining the significant features, events and processes to be abstracted
  3. selecting applicable MA techniques
  4. identifying MA simplifications of complex representations that may provide substantial gain
  5. 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

Environmental Fate and Transport Research - Download Code

Computer code mentioned and used in peer-reviewed publications authored by the EMFSL Environmental Fate and Transport research group is now available online. Written mostly in FORTRAN, the code is available for reuse and modifications. PC executables, source code, and PDF files for manuals and article reprints are provided.

Environmental Research to Improve Food Safety
a film by Ludmila Pachepsky

In this 15-minute film about research on the fate and transport of pathogenic bacteria in the environment, EMFSL scientists describe their research that uses a rainfall simulator and a special lysimeter site to investigate how bacteria can infiltrate into soil or run off with surface water depending on rainfall and vegetation conditions.

Click here to watch the film or read the film transcript.

image of Dr. Dan Shelton image of overhead view of experimental lysimeter site image of researchers working at experimental site image of Dr. Yakov Pachepsky

Quick links to information from the ARS database

Click here to see a list of current projects for Yakov Pachepsky

Click here to see a list of publications for Yakov Pachepsky

Click here to see a list of ARS News articles for Yakov Pachepsky

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