Estimating the Spatial Distribution of a First-Order Solute Decay Constant in Groundwater Systems

Numerical models capable of simulating solute reactive transport in groundwater systems are often used as tools to assess the state of contaminated aquifer systems. Accurately simulating the fate and transport of solutes, however, is often hindered by a lack of information regarding the chemical reactions parameters that govern the fate of the solute. Furthermore, field and laboratory methods used to determine these parameters are often laborand resource-intensive, and often cannot be translated to numerical models due to differences in scale, especially for largescale aquifer systems. In this study, we employ a steady-state Ensemble Kalman Filter (EnKF), a data assimilation algorithm, to provide improved estimates of a spatially-variable first-order rate constant λ through assimilation of solute concentration C measurement data into reactive transport simulation results. The numerical model establishes correlation between λ and the calculated C values throughout the model domain. This correlation, along with model results and measured C values from a reference field, are used by the EnKF to correct model-calculated C values as well as λ in adjacent locations in the model domain. The methodology is applied in a steady-state, synthetic aquifer system in which a contaminant is leached to the saturated zone and undergoes advection, dispersion, and first-order decay in the aquifer system. Uncertainty regarding the hydraulic conductivity of the aquifer is also included. Results from all simulations show that the filter scheme is successful in conditioning the λ ensemble to a reference λ field.