* It is impossible to actually validate models. Why is that so?
    * Does this mean we can't use models for prediction?
    * Be explicit about how each model you use relates to the real world
          o What does it incorporate?
          o What does it leave out?
          o Why doesn't it include everything?
    * What are the differences between the output from your model and real data?
    * Why do those differences occur? Are they due to:
          o Errors in the model?
          o Errors or uncertainty in the real-world data?
          o Assumptions in the model?
    * Is this model too simple? If so, what other processes or reservoirs should it include?
    * Would this system be better modeled using a different technique?