Formatted Title

Remediation Monitoring, Technology Transitions, and Site Closure: Multiple Lines-of-Evidence Approach

Background/Objectives

The demonstration of plume stability for either non-aqueous phase liquids (NAPLs) or dissolved-phase constituents is a common requirement in many regulatory jurisdictions for the transition from active treatment technologies to monitored natural attenuation (MNA).  In addition, some jurisdictions permit the closure of low-risk sites with remaining NAPL or dissolved-phase groundwater plumes if plume stability can be demonstrated.  Traditionally, plume stability has been analyzed by considering the trends of individual constituents over time in each monitoring well at a site or, less commonly, the spatial extent of the plume over time.  However, including estimates of the temporal trends of plume mass, the distance to the center of mass, and the mass flux/discharge of groundwater may provide compelling additional lines of evidence.  Furthermore, the compilation and analysis of site data for these types of analysis has typically been a time-consuming process, often relying on proprietary software.  The objective of this presentation is to demonstrate the use of multiple software tools that are freely-available in the public domain to accelerate the data analysis process and provide novel use of computational and visualization products in a multiple lines-of-evidence approach to demonstrate the viability of technology transitions or site closure.  Case studies from several sites will be used to demonstrate the use of these tools.

Approach/Activities

Several software tools were utilized, each of which is freely available: the Monitoring and Remediation Optimization System (MAROS; Aziz et al. 2003, 2006), the Mann-Kendall Toolkit (Connor et al. 2014), the Mass Flux Toolkit (Farhat and Newell 2011), the BIOSCREEN Natural Attenuation Decision Support System (Newell et al. 1996), GWSDAT (Jones et al. 2014, 2015), and Python.  MAROS was utilized to calculate the total mass of dissolved phase constituents over time, and trends in plume center of mass were also tracked.  Trends in these parameters were analyzed with the Mann-Kendall Toolkit.  The Mass Flux Toolkit was utilized to compute the mass flux and decay rate in an untreated portion of the plume.  An analysis of plume biodegradation and migration was performed in BIOSCREEN.  GWSDAT, which provides a simple spreadsheet interface to a variety of data visualization plots, was utilized to generate a series of animations of the plume extent over time.  Custom data analyses and visualization routines were also written in the Python programming language, which is a freely available language with a robust ecosystem of numerical data analysis and visualization packages to support a variety of use cases.

Results/Lessons Learned

The combination of spatial and temporal datasets provides an intuitive ability to visualize key trends in NAPL and dissolved-phase plumes over time in a multiple lines-of-evidence framework.  At one site, the demonstration of key indicator trends (total mass, constituent concentrations) in relation to an active treatment system, combined with a plume biodegradation and migration analysis, helped transition the site to a monitored natural attenuation remedy.  At another site, ongoing semi-annual monitoring presented a unique challenge to efficiently incorporate new data into a framework to assess the efficacy of the remediation systems.  In this case, one primary advantage of Python is the ability to rapidly prototype and generate time-series and geospatial plots.  For example, after generating a simple scripting routine, time-series plots of 15 constituents in 167 separate monitoring wells were generated (2,505 individual plots), with the time to update these plots on a routine basis taking less than an hour.  Likewise, non-parametric Mann-Kendall trends could be instantaneously updated with new monitoring data and plotted geospatially for each of the monitored constituents.