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United States Department of Agriculture

Agricultural Research Service

Research Project: INTEGRATING MODEL ABSTRACTION INTO MONITORING STRATEGIES
2011 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 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 Task 3 “Develop and Implement a Systematic Approach to Simplifying the Model of the OPE3 Watershed” and Task 4 “Develop a Series of Simplifications to Mimic Specified Conditions using data and models from the OPE3 Watershed” of the research plan. Model simplifications, or model abstractions, have been developed including corrections for laboratory-determined parameters to be used in the field. Model abstraction 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. Evaluation of abstractions depends on the performance indicators, and comparisons of model results have been carried using all data, filtered data, and derived data, as stated in the statement of the work. A series of new information-theory based performance indicators was developed and tested as the complement to the accuracy-based indicators. The novel method of optimal augmentation of the monitoring networks was proposed. Tests were designed to evaluate this method. The progress of the work has been monitored by monthly teleconferences, three meetings with the NRC technical advisory group, and weekly group meetings. Additionally the field training for NRC technical advisory staff was carried out as scheduled in the research plan.


Review Publications
Pan, F., Zhu, J., Ye, M., Pachepsky, Y.A., Wu, Y. 2010. Sensitivity Analysis of Unsaturated Flow and Contaminant Transport with Correlated Parameters. Journal of Hydrology. 397:238-249.

Nemes, A., Pachepsky, Y.A., Timlin, D.J. 2011. Toward improving global estimates of field soil water capacity. Soil Science Society of America Journal. 75(3):807-812.

Last Modified: 12/19/2014
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