A probabilistic approach to the estimation of radioactive contaminant inventories at a nuclear waste disposal site

Abstract

Routine site inspections are often conducted to gather data on radiation contamination on the surface and below ground near nuclear waste disposal areas. These observations are used to calculate total radiation inventory and its spatial delineation. The statistical kriging approach is often used to spatially interpolate contamination data, and it generates predictions at unsampled sites that are then utilized to calculate the contaminated site's radiation inventory. The kriging output, however, creates a point estimate of the inventory that omits the potential uncertainties from other sources. This paper presents a method for assessing the uncertainty of radiation inventories based on the geostatistical conditional simulation method - a simulation methodology that takes into account the observations made at the sampled sites. The radiation inventories' histograms are generated by conducting many conditional simulations of the projection map using a fitted kriging model. A practical implementation of the suggested approach is shown by evaluating total beta inventories and their spatial delineation using groundwater monitoring data at a nuclear waste disposal site.

Keywords: Beta activity; Conditional simulation; Kriging; Nuclear waste disposal; Radiation contamination; Spatial data modeling.