Data Assessment and Assimilation to Evaluate Performance of Groundwater Remedies

Post-construction monitoring data at groundwater remediation sites need to be assessed to determine whether the remedies are performing satisfactorily and, if not, what might be done to improve performance. Such assessments may include determining whether there is adequate evidence that groundwater containment/restoration remedies contain the extent of target plumes of contamination when one analyzes all of the available information, including groundwater head and chemistry measurements, groundwater flow directions and travel-time frames derived from flow and transport simulation, and the constantly changing rates of pumping groundwater that are typical real-world conditions of pump and treat remediation. We discuss statistical and physics-based assessment of monitoring data from groundwater remedies. Our approaches are colored by the need to accommodate inconsistencies, errors, non-detects, and missing values present in real-world data sets. Statistical comparisons of pre- and post-construction data provide a starting point. Spatial correlation between field data may be used to evaluate redundancies. Data assimilation (DA) characterizes the true state of a groundwater system by appropriately (in some cases optimally) combining field data with predictions made by simulation models and error estimates. The field data set and flow and transport simulation programs are linked and coordinated through DA. The resulting analysis leads to improved estimates of state, which leads to improved performance evaluation on an ongoing basis and provides estimates that fill gaps in the information necessary for continuous optimization of remediation systems. Examples are presented from currently active sites.