Comprehensive tool for optimizing long-term monitoring programs

The Monitoring and Remediation Optimization System (MAROS) software was developed by GSI as a public-domain, data management and evaluation tool to improve long-term groundwater monitoring (LTM) programs.  It was originally developed in 1998 on behalf of the Air Force Center for Engineering and the Environment (AFCEE; now known as the Air Force Civil Engineering Center) to support their portfolio of groundwater sites.

MAROS includes both: i) optimization routines to help determine the appropriate number of sample locations, sampling frequency, and laboratory analytes for site monitoring objectives, and ii) statistical analysis tools to evaluate plume stability conditions and remedy performance.

The latest version of this software (MAROS 3.0) includes several new and improved algorithms to review groundwater networks for optimized data collection.  It is a Microsoft Access database application that employs simple statistics and decision frameworks to prioritize data collection efforts and link data to defensible site management decisions. The goal is to provide the user with more options to compare different network configurations. MAROS interactive, allowing the user more options to remove locations and review the resulting plume stability and concentration uncertainty metrics. Results generated from the software tool can be used to develop lines of evidence, which, in combination with professional judgment, can be used to inform site management decisions for safe and economical long-term monitoring of groundwater plumes. The MAROS tool can be used to help design and calculate remediation performance metrics and as a tool to evaluate progress toward site remedial goals.

Unlike many other software applications, MAROS uses the full analytical dataset over time, including both spatial (x,y coordinates) and temporal (all analyses over the time period of interest) data to evaluate contaminant plumes. The software can analyze data for up to five COCs and from 6 to over 100 wells in one run. The software contains modules that prioritize constituents, calculate summary statistics, determine temporal trends at individual wells (using both Mann-Kendall (MK) and Linear Regression (LR) techniques), and calculate plume stability metrics and their trends over time (i.e. total dissolved mass, center of mass and spread of mass). Spatial analysis of well distribution is performed using a Delaunay Triangulation/Voronoi Diagram spatial geometry algorithm. Optimization analyses include identification of redundant locations using a nearest neighbor and a qualitative approach exploiting statistics for spatial geometry, and estimation of plume concentration uncertainty to recommend new well locations and a sampling frequency module to recommend optimal sampling intervals based on the rate of concentration change.