Courses: The GoldSim Contaminant Transport Module:

# Unit 1 - Getting Started

# Lesson 2 - What is the GoldSim Contaminant Transport Module?

Now that we have introduced the Course, and before getting into any details, it is worthwhile to briefly take a step back and discuss exactly what the Contaminant Transport Module is, what it can be used for, and perhaps more importantly, what it *cannot *be used for.

As pointed out in the previous Lesson, the GoldSim Contaminant Transport Module is a program extension to GoldSim that allows you to simulate the release, transport and fate of mass within complex engineered and/or natural environmental systems. That is, it allows you to build * mass transport models*. In general terms, a mass transport model is a mathematical representation of an actual system (e.g., the subsurface environment near a waste disposal site, a lake, surface soils) that can be used to simulate (and hence predict) the release, transport (movement) and ultimate fate of mass within the system. The "mass" that is typically simulated is that of chemical contaminants (usually, but not necessarily, in the form of solutes in water) that have been accidentally released or intentionally disposed within the system. As a result, such models are often referred to as

**or**

*contaminant transport models***. For real-world systems, such models almost always require numerical methods to obtain approximate solutions to the differential equations representing mass transport (as opposed to the use of analytical solutions).**

*solute transport models*The fundamental output produced by the GoldSim Contaminant Transport Module consists of predicted * masses *and

*at specified locations within the system, and predicted*

**mass transfer rates****within environmental media (e.g., water, soil, air) throughout the system. If desired, concentrations in environmental media can be converted to impacts to receptors (e.g., doses and/or health risks) by assigning appropriate conversion factors.**

*concentrations*The fundamental objects that we will discuss (i.e., GoldSim elements) used to represent systems using the Contaminant Transport Module are ** transport pathways**. Pathways represent parts of the system that transport and store mass and represent things such as aquifers, streams, ponds, lakes, soil compartments, tanks, and the atmosphere.

Transport pathways consist of a number of transport and storage media (e.g., water, sand, air, soil, sediments), and a variety of transport processes can be directly simulated, including 1) * advection and dispersion via fluids* (e.g., movement of dissolved and/or suspended constituents in groundwater); 2)

**(e.g., movement of constituents adsorbed to and/or mixed with solids via physical transport of the solids); and 3)**

*advection via solids***(both molecular and turbulent) through fluids. Transport processes can incorporate**

*diffusion**and*

**solubility constraints****of contaminants between the media present in the system, and can include the effects of**

*partitioning***(e.g., radioactive decay and ingrowth).**

*chemical reactions*In broad terms, you could use these capabilities to apply GoldSim and the Contaminant Transport Module to a wide variety of environmental problems, such as:

- investigation of the transport and fate of contaminants (or natural components) in aquifers, wetlands, lakes and other complex environmental systems;
- evaluation of the performance of existing or proposed disposal facilities and hazardous waste sites;
- investigation of the potential impact of engineered facilities such mines, power plants, and processing facilities on the environment; and
- simulation of the transport and fate of pharmaceuticals and other compounds within biological systems (e.g., physiologically-based pharmacokinetic modeling).

Having described the types of problems that it can be applied to, it is also important to highlight the manner in which GoldSim can represent these kinds of systems (and the limitations that imposes).

As mentioned above, realistic contaminant transport models almost always require numerical methods to obtain approximate solutions to the differential equations representing mass transport (as opposed to the use of analytical solutions). When mass transport equations are solved numerically, it is necessary to ** discretize space** into

**or**

*discrete volumes***. Mass is spread out equally throughout any particular discretized volume instantaneously (i.e., the volume is instantaneously well-mixed).**

*compartments*

Note: Of course, it is also a necessity of numerical models tointo discrete intervals referred to asdiscretize time. (This was discussed in Unit 6 of the Basic GoldSim Course.)timesteps

In some cases, the chosen discretization may actually be a fairly accurate representation of the actual environmental subsystem. That is, the subsystem may be truly well-mixed over the timescale of interest (such as a well-mixed tank). In others, the discretization is a necessary approximation required to solve the equations for what is actually a system where concentrations are varying spatially in a continuous manner (such as an aquifer). The question then becomes: how much discretization (i.e., spatial resolution) is appropriate?

As an example, for a lake, at one extreme, you could discretize it using hundreds of layers and hundreds of areal sections (resulting in tens of thousands of discrete volumes). At the other extreme, the entire lake could be represented using a single discrete volume or compartment. Representing the lake as a single discrete volume is appropriate if the entire lake is always (within a timestep) well-mixed. Representing the lake as two horizontal layers (two discrete volumes representing a top layer and a bottom layer) is appropriate if each layer is always well-mixed (within a timestep), with transport between the layers being a much slower process (significantly longer than a timestep). Representing the lake as a large number (e.g., hundreds) of horizontal areas may be appropriate if the lake is vertically well mixed (e.g., very shallow) but significant concentration gradients exist horizontally that are important to capture. Representing the lake as a large number (e.g., thousands) of volumes in the form of a three-dimensional grid may be appropriate if the lake has significant concentration gradients both vertically and horizontally that are important to capture.

When building a model, it is critical to give thought to the appropriate level of spatial discretization. For a case like a lake, it is often easy to do so (e.g., it may be quite appropriate to assume well-mixed conditions over a layer or even the entire water body). For other systems in which continuous concentration gradients exist it is more difficult. For example, for systems involving advection, dispersion and/or diffusion along a path (e.g., mass transport through groundwater), the continuous nature of the spatially variable concentrations is important to represent to realistically simulate mass transport. Using a low level of discretization (e.g., representing an entire system using just a small number of discrete volumes) can result in unrealistic spreading of the mass (a phenomenon known as ** numerical diffusion**, which we will discuss in detail in a later Unit).

** As a general rule, GoldSim is designed to represent systems at a relatively low level of discretization** (i.e., a relatively low degree of spatial resolution). That is, referring to the example above, a lake might be represented in GoldSim as two well-mixed layers. More complex GoldSim models might have the equivalent of tens or at the most several hundred discrete volumes. Certainly, there are some kinds of applications for which a very high level of spatial discretization is required in order to represent the system accurately (and for some of these situations, GoldSim would not be the appropriate tool to use). As we will discuss in greater detail in Unit 3, however, for many types of problems, a lower level of discretization (such as that typically used within GoldSim) is, in fact,

**than a higher level of discretization. In particular, as we will describe in detail, such an approach has several important advantages: 1) the ability to build a single “total-system” model that integrates multiple components and processes; and 2) the ability to appropriately represent the (typically quite large) uncertainty in contaminant transport models.**

*more appropriate*One other point is also important to understand regarding the Contaminant Transport Module. The Contaminant Transport Module itself is used to model the movement of * contaminant mass* through the system. This movement is typically the result of movement of

**(e.g., water) through the system. This results in the**

*media***of mass through the system (e.g., dissolved or suspended in the moving water). The key point here is that the Contaminant Transport Module requires the media flows through the system as input. That is, it solves equations based on specified media flow rates. It does not itself solve for the media flow rates. This means that you are required to create a flow model (using the basic GoldSim framework) that produces the media flow rates that can subsequently be used by the Contaminant Transport Module.**

*advection*

Note: This requirement also imposes a further limitation on the kinds of problems that the Contaminant Transport Module can realistically be applied to. In particular, because the flow and contaminant transport are not solved in a coupled manner, unless you are able to simplify the system, it would typically be inappropriate to use GoldSim to model systems in which these processes were in fact tightly coupled (e.g., saline groundwater flow systems where density effects controlled the flow rates).