Calibration of forest ~(137)Cs cycling model 'FoRothCs' via approximate Bayesian computation based on 6-year observations from plantation forests in Fukushima

摘要

Predicting the environmental fate of Cs-137 in forest ecosystems along with the concentrations of Cs-137 in tree parts are important for the managements of radioactively contaminated forests. In this study, we calibrate the Forest RothC and Cs model (FoRothCs), a forest ecosystem Cs-137 dynamics model, using observational data obtained over six years from four forest sites with different levels of Cs-137 contamination from Fukushima Prefecture. To this end, we applied an approximate Bayesian computation (ABC) technique based on the observed Cs-137 concentrations (Bq kg(-1)) of five compartments (leaf, branch, stem, litter, and soil) in a Japanese cedar plantation. The environmental decay (increment) constants of the five compartments were used as the summary statistics (i.e., the metric for model performance) to infer the five parameters related to Cs-137 transfer processes in FoRothCs. The ABC technique successfully reconciled the model outputs with the observed trends in Cs-137 concentrations at all sites during the study period. Furthermore, the estimated parameters are in agreement with the literature values (e.g., the root uptake rates of Cs-137). Our study demonstrates that model calibration with ABC based on the trends in Cs-137 concentrations of multi compartments is useful for reducing the prediction uncertainty of Cs-137 dynamics in forest ecosystems.