Application of ambient dose equivalent estimation models in remediated cedar forests of Kawauchi Village Japan

Abstract

Many regions contaminated by the release of radionuclides following the 2011 Fukushima Daiichi Nuclear Power Plant disaster are still being investigated today. The mountainous forest areas surrounding Fukushima prefecture were most affected by fallout radionuclides, primarily radiocesium (Cs134 and Cs137), and remain a focus area for remediation and scientific research. Several models have been developed to estimate ambient dose equivalent rates (H*(10)) using data on the depth distribution of fallout radiocesium in the forest soils. Our hypothesis is that two different models will accurately predict radiation doses within 20% based on soil samples. The hypothesis was tested by applying the two models to a research plot in Kawauchi Village Japan, where forestry remediation such as clear-cutting and litter removal has been conducted. Using soil sampling data for radiocesium at the Kawauchi test site, these models were used to estimate H*(10) and compared to measurements taken using handheld instrumentation. The distribution of radiocesium in soil for each sampling locations at the test site was determined using an exponential expression of vertical distribution. These distribution values were then used in two different models, one estimating H*(10) using conversion coefficients from Bq/m2 to μSv/hr, and the other model estimating H*(10) using a "field of view" approach, estimating a surrounding area's contribution to total H*(10) measured at a central point within the test area. The results from this comparison provide a real-world test of computer model effectiveness. The conclusion was that both models could accurately predict radiation levels based on soil samples within 20% of measured values using field instrumentation but could improve if experimental conditions more closely matched those assumed in the model's design.