The dynamic nature of the environmental models make them very sensitive to input data. This means that with inconsistent parameter and time-series input data, the numerical solver might not be able to solve the equations or might end up with crazy results.
With the risk of annoying the reader, it must be re-iterated that the most common source of problems is that the user has started too big. By working in smaller increments many problems can be avoided.
If you experience problems with probabilistic simulations, before doing anything else, make sure that you can run a deterministic simulation and that the results are reasonable.
In a probabilistic simulations it is even harder to avoid inconsistent parameter values; when samples are randomly drawn from the parameter PDF's it is easy to end up with odd parameter combinations. It is also not uncommon for parameters to receive illegal values, like parameters that end up with negative values or zeroes. Even if a simulation completes, some iterations might take a long time to finish (this is a good indication that there is a problem with parameter values).
By default, the simulation is halted once an iteration cannot be run. The reason is, of course, to avoid a situation where the user is not aware that something has gone wrong during the simulation and that the results are not to be trusted. But when trying to find out what is causing the problem, it is sometimes useful to be able to run all of the iterations.
To remedy this problem, go to the advanced simulation settings tab and make sure that Halt on error is unselected.
Even with sound and healthy PDF's, some parameter combinations can cause make iterations take a long time. If one or two iterations take an hour each, then it doesn't matter if the remaining iterations take 1 second. Therefore, enter a (reasonable) time out, eg. 5 times the time for a normal deterministic simulation.
Finally, the software can help you with some output statistics. Make sure that this box is checked.
Your new best friend is the raw data table. For a given output, it shows all values that have been generated for a specific time point.
Another useful friend is the time chart, which can help you identify outliers for time dependent outputs. Before you proceed, be aware that if you have run many (>500) simulations, drawing the chart will take some time.
Finally, for parameters it is sometimes faster to quickly identify a problem using a histogram. The histogram will display the distribution for your parameter.