Markov Process for Simulating Daily Point Rainfall

by Daniel I. Carey, Chf. Hydro.; Booker Assocs., Inc., Lexington, Ky.,
C. T. Haan, Prof.; Agr. Engrg. Dept., Univ. of Kentucky, Lexington, Ky.,

Serial Information: Journal of the Irrigation and Drainage Division, 1978, Vol. 104, Issue 1, Pg. 111-125

Document Type: Journal Paper

Abstract: A modified Markov Chain model is used to generate synthetic traces of daily rainfall amounts at a point. Mixed discrete-continuous distributions are used to model the state transition probabilities. The use of the modified model affords a considerable reduction in historical data requirements for parameter estimation. A two-parameter gamma distribution was used in the model with data from seven weather stations in Kentucky and provided a good representation of the daily point rainfall process.

Subject Headings: Markov process | Rainfall | Data processing | Parameters (statistics) | Gamma function | Probability distribution | Data analysis | North America | Kentucky | United States

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