Abstract
Multicomponent reactive transport modeling is a powerful tool for the comprehensive analysis of coupled hydraulic and biochemical processes. The performance of the simulation model depends on the accuracy of related model parameters whose values are usually difficult to determine from direct measurements. In this situation, estimates of these uncertain parameters can be obtained by solving inverse problems. In this study, an efficient data assimilation method, the iterative local updating ensemble smoother (ILUES), is employed for the joint estimation of hydraulic parameters, biochemical parameters and contaminant source characteristics in the sequential biodegradation process of tetrachloroethene (PCE). In the framework of the ILUES algorithm, parameter estimation is realized by updating local ensemble with the iterative ensemble smoother (IES). To better explore the parameter space, the original ILUES algorithm is modified by determining the local ensemble partly with a linear ranking selection scheme. Numerical case studies based on the sequential biodegradation of PCE are then used to evaluate the performance of the ILUES algorithm. The results show that the ILUES algorithm is able to achieve an accurate joint estimation of related model parameters in the reactive transport model.
Highlights
Tetrachloroethene (PCE), a common chlorinated solvent, has been widely used as a dry-cleaning solvent and a metal degreaser
process of tetrachloroethene (PCE) is known as a dense non-aqueous phase liquid (DNAPL)
The performance of the iterative local updating ensemble smoother (ILUES) algorithm was evaluated with several numerical examples and the results showed that ILUES could provide an accurate estimation of model parameters with multimodal distributions
Summary
Tetrachloroethene (PCE), a common chlorinated solvent, has been widely used as a dry-cleaning solvent and a metal degreaser. It is among the most widespread and persistent organic contaminants in groundwater resources [1]. As a result of these properties, traditional remediation approaches, such as pump-and-treat and vapor stripping, are very expensive and sometimes inapplicable for PCE contaminants in subsurface environments [2]. Multicomponent reactive transport modeling is an important tool for predicting the fate and transport of reactive contaminants in groundwater by integrating simulations of water flow, biochemical reaction and solute transport [7,8]. The uncertainty in related parameters of the reactive transport model poses a major challenge to reliable simulations [9].
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