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Semi-Quantitative Direct-Push Data Can Improve Contaminant Delineation and Mass Discharge in Groundwater
Anton Bøllingtoft1, Wolfgang Nowak2, Poul L Bjerg1
1Department of Environmental and Resource Engineering, Technical University of Denmark, Kongens Lyngby, Denmark.
Ground Water
|November 21, 2025
Summary
This study introduces a probabilistic censoring method to improve contaminant plume mapping. The new approach enhances geostatistical interpolation using semi-quantitative subsurface data, leading to clearer plume delineation and more accurate contaminant mass discharge estimates.
Area of Science:
- Environmental Science
- Hydrogeology
- Geostatistics
Background:
- Accurate contaminant plume mapping and contaminant mass discharge (CMD) estimation are vital for contaminated site risk assessment and remediation.
- Traditional interpolation methods struggle with low-density sampling, leading to inaccurate plume delineation.
- Semi-quantitative data from direct push-probes offer high-resolution subsurface insights but are underutilized in traditional methods.
Purpose of the Study:
- To develop and validate a probabilistic censoring method for enhancing geostatistical interpolation of contaminant concentrations.
- To integrate semi-quantitative, high-resolution subsurface data with traditional groundwater sampling data.
- To improve the accuracy of contaminant plume delineation and contaminant mass discharge (CMD) estimation.
Main Methods:
- Developed a probabilistic censoring method using indicator kriging to interpolate binary presence-absence indicators from direct push-probe signals.
- Generated a probability field of contaminant distribution to censor a spatial concentration field from traditional groundwater sampling.
- Applied the method to a chlorinated solvent-contaminated site with varying sampling densities.
Main Results:
- The probabilistic censoring method resulted in more clearly defined plume fringes.
- The estimated area with low contaminant concentrations (<10 μg L⁻¹) increased by 41-85%.
- Contaminant mass discharge (CMD) estimates were reduced by 13-18% with largely unchanged relative uncertainty.
Conclusions:
- The probabilistic censoring method effectively integrates semi-quantitative field measurements into concentration interpolation and CMD estimation.
- This framework enhances plume delineation and provides more reliable CMD estimates at contaminated sites.
- The method is versatile and can be applied to other direct-push data types for improved subsurface characterization.
