Date of Award
A three dimensional subsurface contaminant transport model with advection, dispersion and reaction has been developed to predict transport of a reactive continuous source pollutant. Numerical Forward-Time-Central-Space (FTCS) scheme has been used to solve the advection-dispersion-reaction transport model and Kalman Filter (KF), Ensemble Kalman Filter (EnKF) and Ensemble Square Root Kalman Filter (EnSRKF) schemes have been used for data assimilation purpose. EnKF and EnSRKF both use Monte Carlo simulation in Bayesian implementation to propagate state estimation. The key difference between EnKF and EnSRKF is that EnSRKF does not require perturbation of observation during analysis stage. In this study, contaminant concentration is the state that has been propagated by this model. Reference true solution derived from analytical solution with added noise has been used to compare model results. Root Mean Square Error (RSME) profile shows that the EnSRKF concentration estimate can improve prediction accuracy better compared to numerical, KF and EnKF approaches.
Ghoshal, Torupallab, "Efficiency Of Ensemble Square-Root Kalman Filter In 3D Subsurface Contaminant Transport Modeling" (2014). Theses. 159.