A Markov process is a stochastic, or random, process for which future states of the process only depend on the present state. In hydrology, a Markov process method may be used to create a randomly generated sequence of stream flows or precipitation that accounts for the existence of persistence.
The purpose of this webinar is to present example implementations of Markov process models to describe and estimate both rainfall occurrence and intensity. Although the subject matter is specific to water resources, the implementation and GoldSim software features presented will be useful for any GoldSim user. And, Markov process representations are used in many industries, including finance, actuarial, and music generation industries, to generate random but related sequences of values.
Download the model files used during the presentation: Markov_Process_Rainfall_Models.zip