Geostatistical ground water monitoring of a point source NO3(-)-N plume entering a restored riparian zone.

NO3(-)-N 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 NO3(-)-N 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 NO3(-)-N 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 NO3(-)-N concentration distributions in a riparian zone. Manipulation of SGS output provided graphical and quantitative estimates of the likelihood of exceeding a specified NO3(-)-N 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.