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United States Department of Agriculture

Agricultural Research Service


Location: Environmental Microbial & Food Safety Laboratory

2009 Annual Report

1a. Objectives (from AD-416)
The objective of this research effort is to develop a strategy for incorporating model abstraction techniques into ground-water monitoring and performance assessment programs. The enhanced abstraction strategies and models shall be tested using site-specific databases for specified contaminant sources introduced and monitored in shallow subsurface environments.

1b. Approach (from AD-416)
Analyze the OPE3 tracer experiment using highly-realistic model(s) and subsets of those model(s) with varying degrees of abstraction to simulate a range of model outcomes for comparison to the detailed monitoring datasets; conduct sensitivity analyses on various parameters which were monitored to determine the impact each has on the overall model; use the spatio-temporal geo-statistics and genetic algorithms to optimize the locations and types of sensors as required by different conceptual models; use the models abstraction to develop a screening approach for determining the appropriate model abstraction techniques for modeling a specific site.

3. Progress Report
The research consisted of data analysis and modeling according to the NRC Project research plan (objective 2) to “develop a highly detailed and realistic site-specific model of the OPE3 watershed site”. A detailed description of the site was developed using available data collected from a variety of sources and experiments conducted on the site, and a variety of model abstraction techniques. Specifically, we used ground penetrating radar (GPR) data, soil survey datasets, electric resistivity monitoring data, detailed digital elevation maps, over 500,000 volumetric water content measurements in time series, weather conditions for growth periods of 10 years from the micro-meteorological station and Class A weather stations, water and chemical (N, P, and pesticides) runoff fluxes, groundwater depth, corn grain yield patterns measured using a grain a yield monitor, and data from tracer experiments. We are analyzing tracer experiments using alternative conceptualizations of the site and the latest versions of HYDRUS and TOUGH software. Model abstraction is applied which is the 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. Model abstraction can help NRC determine whether a simple model can be used that is easy to understand and easily communicated to regulators, stakeholders, and the general public, while at the same time adequately representing their site. The balance between model complexity and model accuracy is extremely important in development of viable models of pathogen fate and transport. In addition, field training for NRC technical advisory staff was carried out as scheduled in the research plan.

4. Accomplishments

Last Modified: 10/19/2017
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