The Conditional Simulation, which has developed in the field of geostatistics, is one of the efficient methods to estimate the precision of parameter estimation. It is the method of creating the random fields that have the assumed stochastic characteristics and coincide with the observed data used for conditioning at sampling points. Conditional Simulation was applied to estimate the movement of fallout
137Cs in the environment, and following results were obtained. The uncertainty of the parameters that determined the movement of
137Cs in a paddy environment decreased more greatly by conditioning when the correlation of the parameters and the data used for conditioning was strong than by that when it was weak. There was the tendency for the estimated concentration of
137Cs in rice to come close to observed data as the number of data used for conditioning increased. Therefore, Conditional Simulation seemed to work effectively. The stochastic distribution of the concentration of
137Cs in rice estimated by Conditional Simulation was not normal at all. Therefore, the method that can estimate the stochastic distribution, such as Conditional Simulation, seems to be necessary for estimating the risk of
137Cs in rice.
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