Modeling - Field Sampling: Principles and Practices in Environmental Analysis - page 172

7
Modeling
Many types of models can be made of the environment; for example, a static physical
model, showing the different parts in three dimensions, or a similar dynamic model,
which actually models changes in the environment when conditions change. Another
approach is to develop a mathematical model that models the movement or actions and
reactions of a single component or multiple components in the environment. The ideal
would be to have this model be as simple as possible.
Today most mathematical models are developed using computer programs. The
advantage of using computers is that models incorporating many variables and complex
calculations can be developed and will run quickly and easily on a computer.
Mathematical models can be three-dimensional and be presented as relatively simple
three-dimensional graphs. On the other hand, the output may be a three-dimensional
diagram of the environment showing the surface and subsurface location of the
components of interest. These can also be dynamic models and can be used to predict and
quantify changes in the environment when conditions change.
All models have two basic valuable characteristics. The first is to allow the
visualization of the situation as it exists. Seeing the situation in even a static model can
help in the development or modification of a sampling plan. The second is that the model
allows the prediction or estimation of changes in the future. Dynamic models allow for
changes, which make it possible to predict how these changes would change the
dynamics of that portion of the environment being modeled. For instance, a model of soil
moisture levels might be developed for a certain rainfall, perhaps 500 mm of rain spread
over 6 months. The model would allow prediction of the changes that would be expected
if, for example, rainfall was 1000 mm or 250 mm over the same length of time.
Such changes in rainfall will affect sampling. A soluble pollutant will move further and
deeper under heavier rainfall conditions and thus require more sampling and deeper
sampling. Under reduced rainfall less movement would occur, and thus less sampling is
needed. The predictive nature of a model can thus be of great benefit in designing a field
sampling plan. In conjunction with sampling, such models can be used in decision
making, such as whether or not a contaminated groundwater plume requires cleanup.
Such models can guide the location of sampling sites and the drilling of monitoring wells.
Models should never be used as the sole basis for location of sampling sites and wells in
a field sampling plan, however.
Many constants are needed for any modeling. Some are chemical constants and others
are physical constants. A list of common constants and variables used in environmental
modeling are given in Table 7.1.