Water resources and hydrological modeling projects typically involve simulating systems made up of many component parts that are interrelated, and in some cases, poorly characterized. In most situations, the hydrological system is driven by stochastic variables (i.e., precipitation, evaporation, demand) and involves uncertain processes, parameters, and events.
The challenge when evaluating water supply and resource systems is to find an approach that can incorporate all the knowledge available to planners and management into a quantitative framework that can be used to simulate and predict the outcome of alternative approaches and policies. To be effective, the simulation framework needs to be flexible (so that it can accurately represent the systems), transparent (so the models can be easily explained to decision-makers and stakeholders), and able to explicitly represent the uncertainties and stochastic processes inherent in such systems.