Radioactive Contaminanant Transport in Subsurface Porous Environment
The deterministic model is developed based on the discrete advection-dispersion-adsorption equations with radioactive decay mechanism. The data assimilation scheme is designed to utilize the Kalman Filter (KF) to incorporate the knowledge of uncertainties in both the model and the measurement. Spatially correlated regional noise structures are proposed and integrated into a data assimilation scheme. This model demonstrates that the data assimilation scheme reduces the uncertainty and predicts more accurately than a deterministic model. Through absorbing information from observation, the predictive plumes of radioactive contamination from the assimilation system can follow the change of a randomized irregular plume shape in the real world more closely than a non-assimilation deterministic model.
KeywordsRoot Mean Square Error Kalman Filter Data Assimilation Deterministic Model Retardation Factor
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