Streamlined data collection
dataCAST™ by Trinnex centralizes soil, groundwater and surface water data into a digital hub for simplified dataset management.
Client
U.S. Air Force
Location
Dover, DE
Markets
Priorities
Streamlined PFAS data management and analytics
PFAS contamination from aqueous film-forming foam (AFFF) fire suppression poses risks to human health and the environment. Working with CDM Smith, the U.S. Air Force Civil Engineer Center (AFCEC) deployed advanced data visualization tools to enable more effective decision-making and long-term remediation planning.
AI tools for PFAS analysis
The platform applies advanced analytics to assess PFAS fate, transport, and environmental risks.
Contamination visualization
A sophisticated integration of 3D Leapfrog modeling presents contamination patterns through maps, charts, and graphs.
Secure, enhanced collaboration
Cloud-based systems allow for secure and transparent sharing among scientists, engineers, and decision-makers.
At Dover Air Force Base in Delaware, the challenge was clear: how do you make sense of massive PFAS datasets when traditional data management approaches keep slowing down remediation decisions? For CDM Smith product manager Josh Soper, who started his career as a water resources engineer before moving into data engineering and software development, the answer required rethinking how the Air Force interacts with their own data.
Making sense of massive PFAS datasets
The Department of War has worked diligently to understand and reduce the spread of PFAS contamination at military bases nationwide, largely due to its use of AFFF to extinguish fires. The Department has completed thousands of investigations of potentially contaminated sites at more than 700 active military installations, with many more investigations on the horizon to implement remediation programs. The current challenge is analyzing all this data to develop effective short- and long-term remediation programs.
The AFCEC has been investigating the occurrence and environmental distribution of PFAS at sites where AFFF was used. In these efforts, AFCEC identified a critical need for data analytics tools that can more effectively manage large historical and new datasets to build effective conceptual site models in support of remediation decision-making.
"Overcoming the challenge of managing large amounts of data and presenting it clearly and concisely is essential to the success of PFAS remediation programs," says Tamzen Macbeth, our remediation practice leader.
Overcoming the challenge of managing large amounts of data and presenting it clearly and concisely is essential to the success of PFAS remediation programs.
Tamzen Macbeth
Remediation practice leader
Client
U.S. Air Force
Location
Dover, DE
Markets
Priorities
Advanced data analytics and forensics framework
AFCEC is currently testing CDM Smith's Advanced Data Analytics and Forensics Framework (ADAFF) at Dover Air Force Base. ADAFF is a process-based framework for compiling, organizing, and integrating data using digital tools for visualization and interpretation.
To deliver a streamlined data management and analytics solution, CDM Smith's subsidiary, Trinnex, implemented dataCAST™ to compile, analyze, and visualize AFCEC data for Dover AFB. dataCAST is a cloud-based platform for managing large and complex data and includes tools for AI and analytics. It provides data presentation via spatial and graphical digital dashboards to assess PFAS contamination at the former fire training area, integrating sampling data from soil, groundwater, and surface water.
The platform integrates 3D Leapfrog modeling to visualize PFAS distribution, fate, and transport to support risk assessment and selection of remedial technologies. For analytics, dataCAST includes a custom leaching model to assess leaching of PFAS from the vadose zone to the underlying groundwater table. The leaching model incorporates traditional principles for modelling hydraulic flux in the vadose zone in a simplified, mass balance framework. Like other popular screening models (i.e. EPA-DAF model, Remchlor-MD), this model has been experimentally validated and can provide a reasonably accurate approximation of PFAS mass flux from the vadose zone with minimal data requirements and less intensive calibration than traditional vadose zone models.