Pre-Class - Stochastic Modeling

In this pre-class, we explore how stochastic simulations, including Monte Carlo and Gaussian Field approaches, account for uncertainty in groundwater models by running many equally probable realizations instead of relying on a single “best estimate.” This is important because it allows us to express results as probabilities, providing a more realistic and defensible understanding of potential outcomes like contaminant migration or well capture zones. We will also learn how to set up and analyze these simulations in GMS, including parameter randomization, spatial variability, and probabilistic output tools.

Slides (Stochastic Modeling - Basic Theory): stochastic-basic_theory.pptx
Slides (Stochastic Modeling - GMS Tools): stochastic-gms_tools.pptx