A model in which the various coefficients that represent material properties (e.g., porosity, permeability, dispersivity) are regarded as random phenomena. This stems from the realization of the uncertainty involved in assigning specific deterministic values to such coefficients.

An analysis involving a random variable. For example, a stochastic model may include a frequency distribution for one assumption. From the frequency distribution, possible outcomes for the assumption are selected randomly for use in an illustration.

A mathematical model which contains random (stochastic) components or inputs; consequently, for any specified input scenario, the corresponding model output variables are known only in terms of probability distributions. In contrast to a deterministic model.

A model involving or containing a random variable or variables; involving chance or probability.

a mathematical model that includes some random, or stochastic, processes (processes determined by chance)

The Stochastic Model describes the expected error distribution of the observations. The description stipulates that the mean value of the observations will be the 'true' value described by the mathematical model, that the observations will have a Normal error distribution, and that the expected variance in the observations will have a certain value.

model of a system that includes some sort of random forcing. In many cases, stochastic models are used to simulate deterministic systems that include smaller- scale phenomena that cannot be accurately observed or modeled. As such, these small-scale phenomena are effectively unpredictable. A good stochastic model manages to represent the average effect of unresolved phenomena on larger-scale phenomena in terms of a random forcing.