Geostatistical Ground Water Monitoring of a Point Source Plume Entering a Restored Riparian Zone

Abstract

concentrations associated with a point-source ground water plume were monitored as the plume entered a restored riparian zone (RRZ) on the University of Idaho campus in Moscow, Idaho. Seasonal data collected for a network of piezometers installed in the RRZ were analyzed geostatistically and then modeled spatially using the conditional simulation method of sequential Gaussian simulation (SGS). SGS was utilized to predict the spatial distribution of ground water concentrations at unsampled locations in the RRZ and to quantify the uncertainty associated with the prediction. Maps prepared using SGS results illustrate the short-scale variability, or patchiness, expected of concentration distributions in a riparian zone. Manipulation of SGS output provided graphical and quantitative estimates of the likelihood of exceeding a specified concentration threshold at a given confidence level for any location within the RRZ. Geostatistical simulation tools for quantifying uncertainty also provide a potential risk assessment methodology for making remediation decisions and reducing remediation costs.

Keywords:

• Riparian zone
• Point source
• Ground water monitoring
• Geostatistics
• NO₃ ⁻−N
• Sequential Gaussian simulation
• Probability
• Uncertainty