How #Tableau Helps Visualize Environmental Cleanup Data



I spent over 10 years working on the remediation of contaminated groundwater in Cape Cod, MA (Figure 1). I loved doing this type of work by helping restore the environmental health of the groundwater and surface water systems. Spending time in Cape Cod wasn’t bad either!


Figure 1 – Western Cape Cod, the home of the Massachusettes Military Reservation (MMR).


The sites we worked on are located on the Massachusetts Military Reservation (MMR) in western Cape Cod, MA. The Otis Air National Guard Base (Figure 2) is where historical operations released chemicals to the groundwater system.


Figure 2 – The MMR base area as viewed in 2017.


Decades of rain and snow have provided the driving forces to move these contaminants downgradient such that the zones of contamination are miles long and wide and hundreds of feet thick. Figure 3 shows one of the plumes that is known as the Chemical Spill-10 plume (CS-10).


Figure 3 – The CS-10 plume area.


Many hundreds of millions of dollars were spent on environmental characterization studies to quantify the nature and extent of groundwater contamination. Geologic investigations were used to assess the 4D (x,y,z, and time) contaminant distributions (Figure 4). This information was used to build a 3d concentration field for numerical simulation of the CS-10 flow, transport, and predicted remediation effectiveness. The characterization work was necessary to design and build the groundwater pump and treat systems needed to perform the remediation. This is one of the largest groundwater restoration projects ever attempted in US history.


Figure 4 – The 3D wireframe portrayal of the TCE/PCE contaminant distribution of CS-10 in the mid-2000’s.


Using Tableau to Visualize Environmental Cleanup

In 2013, I used Tableau to evaluate the Chemical Spill-10 TCE mass removal history from 1999 to 2007. Unfortunately, I was not able to extend the data set beyond 2007 because I hadn’t worked on the project for many years.

The data in this example is real!  The actual mass removed at extraction wells was measured and a program titled the History of Operations and Modeling Evaluations (HOME) was used to produce the data shown in this demonstration.  Although HOME had a database back-end, it had an Excel front-end, which was state-of-the-art for producing these types of analytics back in 2004!

HOME was a computational framework I created to keep track of the actual remediation progress being made. The computations performed time integrations of contaminant mass removal times flow rate to estimate the total amount of contaminant mass removed. The code I wrote for computing the remediation progress can be viewed by clicking the following link:  Computing Contaminant Mass Capture in Modflow-Surfact.

I strongly encourage you to look at that code if (1) you like scientific programs, or (2) you like to see how pretty C code can look when it is properly formatted and colored (LOL!). Who says a data dork/programmer like me doesn’t have any style?

As shown in the video below, I used Tableau to visualize the remediation performance history.  An example animation of cumulative mass removal is completed as well as a couple of dashboards to show the mass removal performance of any or all extractions wells.


Update In 2017

It has been 10 years since I worked on the project, but I was able to find an updated report that gives additional details about the remediation history at CS-10. Additional contaminants were discovered after we completed the initial remediation system designs. The report that includes the new information can be found by clicking here.

The three figures shown below help visualize the nature and extent of the higher concentration contaminant masses that were discovered by additional drilling in the late 2000’s and early 2010’s.



Figure 1 – Differences in plume boundary outlines after 5 years of running the remediation systems.




Figure 2 – Differences in 3d contaminant plume distribution in 2007 and 2012.




Figure 3 – Contaminant distributions portrayed in plan view and in two vertical sections, to show the thickness of the plume.




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