Geostatistical Analysis in Mapping MTBE Contamination
San Mateo County Building and Planning Division and
Department of Civil Engineering, California State Polytechnic University
By Ms. Jie Y He, GIS Analyst and
Dr. Xudong Jia, Department of Civil Engineering
Methyl-tertiary-butyl ether (MTBE) is an oxygenated fuel additive for reformulated gasoline. It is highly soluble in water and is chemically inert with low biodegradability. Once dissolved in water, it will persist and spread throughout the environment, becoming a significant contaminant of surface water and groundwater resources.
Recent studies have shown that MTBE continues to be a problem for the public. The United States Environmental Protection Agency (USEPA), Cal-EPA, and the California Department of Health Services have issued drinking water health advisory values for MTBE. The United States Geological Survey has deemed MTBE the second-most frequently detected groundwater contaminant in its National Water Quality Assessment Program. In the city of Denver, Colorado, 79 percent of the shallow urban wells that were tested revealed harmful concentrations of MTBE.
In the city of Santa Monica, California, MTBE has been detected in groundwater with concentrations of hundreds of parts per million. Because the MTBE concentrations were tens of thousands of times higher than the regulatory drinking water advisory values, three of the five wells that provided water to 40 percent of the city's population were shut down. The city had to purchase additional water from the Metropolitan Water District of Southern California at a cost of $2 million per year.
A good understanding of how MTBE is transported and distributed in groundwater is critical to the MTBE investigation and cleanup. This aim of the project was to monitor and analyze spatial patterns of MTBE in groundwater using GIS and geostatistical technologies.
STUDY AREA
A groundwater basin located in the city of Temecula, California was selected for this project (see Figure 1). Because severe MTBE contamination in the basin was found in the drinking water supply wells, the Rancho California Water District immediately shut down the wells that draw water from the basin and investigated the extent of MTBE impacts. This project used the sample data collected by the San Diego Regional Water Quality Control Board, GeotrackerTM and other consulting firms for the groundwater basin.
 Figure 1 shows six open gas stations in the vicinity of a highly contaminated production well. Each gas station site has approximately 10 monitoring wells.
MTBE ASSESSMENT
The MTBE distributions in groundwater were assessed using ArcGIS Geostatistical Analyst. The assessment process involved the following steps.
- Step 1—Exploratory Spatial Data Analysis
The exploratory spatial data analysis determined the MTBE distribution pattern. It also identified data trend and calculated semivariogram values to explore spatial autocorrelation of the MTBE data. This process is useful in getting a better understanding of the sample MTBE data and preparing for further spatial data analysis and best-fit modeling of MTBE concentrations.
- Step 2—Structural Data Analysis
The structural data analysis used the simple kriging technique to generate surface maps that represent the spatial distribution of MTBE concentrations in groundwater. Kriging is a data interpolation method for creating prediction surface. It weighs the surrounding measured values to predict the MTBE concentration for an unmeasured location. Weights are based on distance between the measured points, the prediction location, and the overall spatial arrangement among the measured points.
- Step 3—Cross Validation
Before a final surface map is produced for practical use, the cross validation tool from ArcGIS Geostatistical Analyst was employed to examine “how well” the surface predicts an unknown MTBE concentration at a specific location. The cross validation tool compared measured MTBE values with predicted values derived from the surface model and used statistical measures to assess the surface model’s performance.
MTBE CONCENTRATION PREDICTION MAP
With the best surface map determined from the cross validation process, the MTBE concentration prediction map that shows the MTBE distribution in groundwater was generated. Figure 2 shows an MTBE prediction map in which the dark color represents high concentrations; the light color represents low concentrations.
 Figure 2 shows the prediction map of MTBE concentrations generated from a simple kriging model.
Because uncertainties and limitations were embedded in the MTBE prediction, care was taken when using the predicted MTBE concentration map for regulatory or remediation decisions. ArcGIS Geostatistical Analyst provides a tool to help users create a map that shows the MTBE concentration of a given point exceeding a predefined threshold.
 Figure 3 is a probability map whose colored contour lines indicate the probability of MTBE concentration exceeding the defined threshold of 20 parts per billion (ppb). The tool also allows you to move the cursor over the map, identifying the MTBE concentration and its probability of exceeding a defined threshold.
This probability map can visually aid regulators and environmental consultants in making rational decisions. For example, if drinking water wells were to be located within the green contour lines, chances are that in more than 60 percent of the cases the MTBE concentration in the well would exceed the 20 ppb threshold, and actions such as shutdown or cleanup would be needed to solve the problem.
Another use of the probability map would be monitoring wells placed along the western boundary of the site in the high concentration zone (second darkest color zone in Figure 3). If concentrations in these monitoring wells were to increase, they would impact the water production well. Regulators may view this as a high priority task and ask the owner to clean up the well. The owner in turn would need to know the costs and duration of the MTBE cleanup. The owner’s consultant could use this map to estimate the total mass of MTBE within the site boundary, and calculate the costs and time based on existing cleanup technologies and removal rates. The consultant may further use this map to design a remedial system to maximize the removal efficiency by placing extraction wells at appropriate locations.
In addition, regulators would be able to assess the effectiveness of the remedial system and make necessary adjustments by generating sequential MTBE maps using new monitoring data. When the MTBE concentrations are reduced to a certain level, regulators can use the probability map to determine, with a predefined confidence level, when cleanup action is complete.
For more information about this project, contact
Ms. Jie Y He
GIS Analyst
San Mateo County Building and Planning Division
455 County Center
Redwood City, CA 94063
Tel: 650-363-1827
E-mail: jhe@co.sanmateo.ca.us
Dr. Xudong Jia
Department of Civil Engineering
California State Polytechnic University
Pomona, CA 91768
Tel: 909-869-4312
E-mail: xjia@csupomona.edu
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