Stepwise inversion of a groundwater flow model with multi-scale observation data

Abstract

Based on the regional hydrogeology and the stratigraphy beneath the Los Alamos National Laboratory (LANL) site, New Mexico (USA), a site-scale groundwater model has been built with more than 20 stratified hydrofacies. A stepwise inverse method was developed to estimate permeabilities for these hydrofacies by coupling observation data from different sources and at various spatial scales including single-well test, multiple-well pumping test and regional aquifer monitoring data. Statistical analyses of outcrop permeability measurements and single-well test results were used to define the prior distributions of the parameters. These distributions were used to define the parameter initial values and the lower and upper bounds for inverse modeling. A number of inverse modeling steps were performed including the use of drawdown data from the pump tests at two wells (PM-2 and PM-4) separately, and a joint inversion coupling PM-2 and PM-4 pump test data and head data from regional aquifer monitoring. Parameter sensitivity coefficients for different data sets were computed to analyze if the model parameters can be estimated accurately with the data provided at different steps. The joint inversion offers a reasonable fit to all data sets. The uncertainty of estimated parameters for the hydrofacies is addressed with the parameter confidence intervals.