Uncertainty with Varying Subsurface Permeabilities Reduced Using Coupled Random Field and Extended Theory of Porous Media Contaminant Transport Models

To maximize the usefulness of groundwater flow models for protection aquifers and abstraction wells, it is necessary to identify decrease uncertainty associated with major parameters such as permeability. do this, there a need develop set estimates representing subsurface heterogeneity or representative soil permeability estimates. Here, we use coupled Random Field extended Theory Porous Media (eTPM) simulation robust model good predictive ability that reduces uncertainty. The then validated physical sandbox experiment. Uncertainty reduced by using 500 realisations parameter eTPM approach. A multi-layer contaminant transport scenario varying permeabilities, similar what could be expected shallow alluvial sediments, simulated. results show arrival time strongly affected random field realizations compared modelled homogenous parameter. breakthrough heterogeneous permeabilities shorter than homogeneous condition. Using 75% confidence interval (CI), average concentration shows 4.4% variation from values considered area 8.9% in case 95% interval.