Development and application of a coupled-process parameter inversion model based on the maximum likelihood estimation method

The coupled flow-mass transport inverse problem is formulated using the maximum likelihood estimation concept. An evolutionary computational algorithm, the genetic algorithm, is applied to search for a global or near-global solution. The resulting inverse model allows for flow and transport paramete...

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Bibliographic Details
Published in:Advances in water resources 1999-06, Vol.22 (8), p.841-853
Main Authors: Mayer, Alex S., Huang, Changlin
Format: Article
Language:English
Subjects:
algorithms
Earth sciences
Earth, ocean, space
estimation
Exact sciences and technology
genetic algorithms
Groundwater flow
Hydrogeology
Hydrology. Hydrogeology
maximum likelihood
Maximum likelihood estimation
Parameter inversion
saturated hydraulic conductivity
Transport
transport processes
tritium
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Summary:The coupled flow-mass transport inverse problem is formulated using the maximum likelihood estimation concept. An evolutionary computational algorithm, the genetic algorithm, is applied to search for a global or near-global solution. The resulting inverse model allows for flow and transport parameter estimation, based on inversion of spatial and temporal distributions of head and concentration measurements. Numerical experiments using a subset of the three-dimensional tracer tests conducted at the Columbus, Mississippi site are presented to test the model's ability to identify a wide range of parameters and parametrization schemes. The results indicate that the model can be applied to identify zoned parameters of hydraulic conductivity, geostatistical parameters of the hydraulic conductivity field, angle of hydraulic conductivity anisotropy, solute hydrodynamic dispersivity, and sorption parameters. The identification criterion, or objective function residual, is shown to decrease significantly as the complexity of the hydraulic conductivity parametrization is increased. Predictive modeling using the estimated parameters indicated that the geostatistical hydraulic conductivity distribution scheme produced good agreement between simulated and observed heads and concentrations. The genetic algorithm, while providing apparently robust solutions, is found to be considerably less efficient computationally than a quasi-Newton algorithm.
ISSN:0309-1708
1872-9657
DOI:10.1016/S0309-1708(98)00049-9