MAROS

TRRP Training: 2022 Program

presented by: GSI Environmetal Inc.

Texas Risk Reduction Program regulations (TRRP; 30 TAC 350) establish consistent risk-based protocols for assessment and response to soil, groundwater, or surface water impacts associated with environmental releases of regulated wastes or substances.

Presented by GSI Environmental Inc., this popular and informative training series is a must for professionals who need a working understanding of TRRP and those needing to stay up-to-date with the latest TCEQ TRRP guidance and policies.

TRRP Training Course (2 Days): Provides an overview of the TRRP framework and step-by-step training on property assessment and response action procedures established under the TRRP rule

Attendees will become acquainted with rules, key guidance and policies covering affected property assessments, protective concentration levels, and response actions. The course material presents strategies for efficient project management in compliance with TRRP and explains the various report forms adopted by TCEQ.

TAEP image

Sponsored by:
Texas Association of Environmental Professionals (TAEP) TAEP is the premier organization for environmental professionals in the State of Texas. The goals of TAEP include the advancement of the environmental profession and the establishment of a forum to discuss important environmental issues. TAEP members receive a 10% discount. Please call 713.522.6300 for the code.

Dates and Location

Dates

June 14th and 15th, 2022

Location

Crowne Plaza River Oaks 2712 SW Freeway Houston, Texas 77098 713.523.8448 http://www.crowneplaza.com/

Price and Registration

Early-Bird Price

(Paid by May 1, 2022)
$XXX

Standard Price

(Paid after May 1, 2022)
$XXX

TAEP Membership Price

$XXX

Government Price

$XXX
Lodging and meals are not
included in course cost

MAROS

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 as a Microsoft Access-based tool in 1998 on behalf of the Air Force Center for Engineering and the Environment (AFCEE; now known as the Air Force Civil Engineering Center) and was enhanced in subsequent releases through 2012.

In 2025, GSI released a new version – the MAROS Toolbox. Built using the R Shiny platform, the new toolbox includes the most popular features of legacy MAROS while leveraging the modern computing environment to add new functionality to make it easier to understand and visualize site data. Development of the MAROS Toolbox was funded by ESTCP Project ER22-7422.

The MAROS Toolbox 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 and data visualization tools to evaluate plume stability conditions and remedy performance.

MARDS is interactive, allowing the user to upload and explore site data, and calculate individual well and plume-wide summary statistics. Results generated from the software tool can be used ta 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 MARDS tool can be used to help design and calculate remediation performance metrics and as a tool to evaluate progress toward site remedial goals.

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.