Markov Process Rainfall Model


Using a Markov Process to Simulate Wet and Dry Periods


This model simulates a Markov process that randomly switches between a wet state and a dry state to simulate rainfall given some key historic statistics. When in the wet state, a 'WetState' conditional Container is activated, and a random pattern of rainfall is generated. When in the dry state, a 'DryState' conditional Container is activated (and in this model, no rain falls at all).


Making Better Decisions In An Uncertain World