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Simulation

What is a Simulation?

The technique of representing the real world by a computer program; "a simulation should imitate the internal processes and not merely the results of the thing being simulated"
Source: WordNet 2.0, 2003 Princeton University
Attempting to predict aspects of the behaviour of some system by creating an approximate (mathematical) model of it. This can be done by physical modelling, by writing a special-purpose computer program or using a more general simulation package, probably still aimed at a particular kind of simulation (e.g. structural engineering, fluid flow).
Source: The Free On-line Dictionary of Computing
A mathematical exercise in which a model of a system is established, then the model's variables are altered to determine the effects on other variables.
Source: Dictionary.com
Hmmm, all these definitions of simulations are true but they leave me a bit cold. Let me try. A simulation is
like asking a question of your model, like "What should I do if there's little rain next year?" or "Do I get more money if I sell half of my female cattle as well as my normal sales?"
Source: me
How does that look? Better? Ok, so I cheated and used a farming context, but the message is the same, simulations are great ways to interrogate your model which is the set of parameters and other data about your site that you collect together and test using the windows of this modelling software. Once you are confident that your model is performing well, you will be confident in the results it gives you when you change the parameters a little. This sets up different conditions with which you can ask different questions by creating a new simulation scenario.

Changing the parameters a lot might produce unexpected results and strange behaviour from your model but this modelling software has been tested and validated against a trusted source (e.g., Fritz and Duncan, 1994) and should be tolerant of the range of parameter values occurring naturally for semi-arid grazing systems. However,
[w]hen conducting a simulation or contriving a model, certain limitations must be acknowledged. Primary among these is the ability to create a model that accurately represents the system to be simulated. Real systems are extremely complex and a determination must be made about the details that will be captured in the model. Some details must be omitted and their effects lost or aggregated into other variables that are included in the model. In both cases, an inaccuracy has been introduced and the ramifications of this must be evaluated and accepted by the model developers. Another limitation is the availability of data for describing the behavior of the system. It is common for a model to require input data that is scarce or unavailable. This issue must be addressed prior to the design of the model to minimize its impact once the model is completed.
Source: Simulation Article by Roger D. Smith, modelbenders.com
So, even with good trustworthy models you should be aware of the potential difficulties when you use them to ask questions about natural systems.

Meanwhile, all that is left for you to do is modify the default model or example projects to suit your circumstances, run a few test simulations to check your data is going into the modelling software OK and that you're getting the output you need, and away you go. Your test simulations don't need to be run for the whole model duration (10, 20, 30 years or however long you want / have relevant data for). No, they can be just a few iterations long, where an iteration is the sequence of simulation processes that comprise a single day within your model. That is the iteration period of this modelling software, a single day, but there's no limit written into the software for the number of days that you can have.

So, using SimSAGS, a simulation to you should be a quick way to test ideas and ask questions about your site, including many aspects of livestock and wildlife, grasses and shrubs and trees, and even rainfall flow over the land's surface.
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