Utilizing the Basic GoldSim Elements in a Contaminant Transport Model

Nearly all of the inputs to the GoldSim Contaminant Transport Module elements accept links from other GoldSim elements (with compatible data type and dimension). For example, you could define the length of a pathway using an Expression, or the partition coefficient of a species The chemical (or non-chemical, such as bacterial or viral) constituents that are stored and transported through an environmental system in a contaminant transport model. In GoldSim, the Species element defines all of the contaminant species being simulated (and their properties). for a particular medium using a Look-Up Table.

If necessary, you can even link an external DLL to your model using GoldSim's External element. This, for example, would allow you to dynamically define the solubilities using a geochemical equilibrium code.

GoldSim's Extrema element A function element that computes the maximum value (peak) or minimum value (valley) achieved by its input during a simulation. is also likely to be useful when carrying out contaminant transport simulations. The Extrema element allows you to compute the highest or lowest value achieved by a particular output over the course of a simulation. For example, you could use an Extrema element to compute the peak concentration in a particular medium in a pathway, or the peak impact to a receptor A group (usually of people) that could potentially receive impacts from contaminants in the environment. In GoldSim, a Receptor is an element that converts contaminant concentrations in the environment to impacts to a receptor group..

Perhaps the most powerful feature of the GoldSim simulation framework is the ability to describe inputs as probability distributions using Stochastic elements. This is particularly appropriate when simulating contaminant transport through the subsurface, as many of the controlling parameters will necessarily be uncertain. If you describe your inputs using probability distributions, the output of your model will be in the form of probabilistic contaminant transport predictions (e.g., the probability distribution of the peak concentration in a particular pathway).