Efficiency of using 4DVar, 3DVar and EnKF data assimilation methods in groundwater contaminant transport modelling

Abstract

Groundwater contaminant has been a serious issue to environmental engineers for long time. To simulate groundwater contaminant flow condition, a three-dimensional subsurface contaminant transport model with advection, dispersion and reaction has been developed to predict transport of a continuous source pollutant. Numerical forward-time-central-space scheme has been used to solve the advection-dispersion-reaction transport model and three-dimensional variational data assimilation (3DVar) and four dimensional variational data assimilation (4DVar) schemes have been used for data assimilation purpose. Then these two schemes were compared with previously implemented ensemble Kalman filter (EnKF) scheme. In this study, contaminant concentration is the state that has been propagated by this model. Reference true solution derived from numerical solution with added noise has been used to compare model results. The results showed that the computational cost of 3DVar and 4DVar were justified in this case. Finally, sensitivity analysis has been performed with different standard deviation and it was seen that 3DVar and 4DVar perform better in contrast to the noise sensitive EnKF.

Keywords:

• 4DVar
• 3DVar
• ensemble Kalman filter
• data assimilation
• groundwater contaminant
• modelling
• prediction

Acknowledgments

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