Simulating Rainfall (May 2018)

A Markov process is a stochastic 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 an example implementation of a Markov process model to 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. These models are used in many industries including finance, actuarial, and music generation to simulate random but related sequences of values. Join us for a presentation that demonstrates a climate simulator built on the Markov process methodology.

Below is a video recording of the webinar presentation:

 

The model files used in this presentation can be downloaded from our library using the following links:

Stock growth model

WGEN Weather Generator