Spatial properties of soil analyses and airborne measurements for reconnaissance of soil contamination by 137Cs after Fukushima nuclear accident in 2011

Abstract

Following Fukushima nuclear disaster, several data gathering campaigns surveyed the radionuclide propagation in the environment. However, the acquired datasets do not have the same sampling dimension. For example, the airborne measurements are some sort of averaging over a circular field of view, beneath the sensor; while the soil analyses are much more punctual. The objective of this work is to compare the soil samples and an airborne survey to investigate whether these two datasets reflect the same spatial patterns or not. This is prerequisite for combining the multiresolution data to create and update the contamination map in a post-accidental situation. The analyses were performed on square tiles of 20 km side to study large- and small-dimension variations in ¹³⁷Cs deposition. The former was modelled by fitting a plane (called trend) to the georeferenced data points; and the latter was modelled by computing the difference (called residual) between the trend and the initial data. Dip direction and dip angle of trends as well as minimum spatial correlation distance and anisotropy of residuals were computed for both the soil and airborne datasets and compared. Dip directions are compatible in 73% of the tiles and dip angles are generally close. Anisotropy directions are compatible in 49% of the tiles and minimum spatial correlation distances are significantly more marked for the airborne dataset. The soil samples and airborne measurements are therefore more in agreement in large-dimension (trend) rather than in small-dimension (residual) variations. More generally, both the datasets allow highlighting the main contamination plumes distinguishable because of high concentration values. The airborne dataset yet appears to be more powerful to quantify spatial correlations, which could be linked to the contamination mechanisms.