Subsurface Contaminant Transport Modeling Using an Adaptive Extended Kalman Filter Scheme

摘要

Contamination of groundwater is a serious environmental and health problem in numerous areas of the world. Accurate prediction and information about the contaminant in the subsurface is imperative in risk assessment and the remediation process. In predicting the fate of the pollutant, the use of subsurface contaminant transport model combined with stochastic data assimilation scheme can give accurate results. Observation data generated from an analytical solution are required to guide the deterministic system model to assimilate the true state of the contaminant. In this research, a two-dimensional transport model with advection and dispersion is used as the deterministic model of contaminant transport in the subsurface.