A Markov Chain Approach for Analyzing Palmer Drought Index

by Marcel K. Tchaou, Virginia Polytechnic Inst and State, Univ, Blacksburg, United States,
Saied Mostaghimi, Virginia Polytechnic Inst and State, Univ, Blacksburg, United States,
G. V. Loganathan, Virginia Polytechnic Inst and State, Univ, Blacksburg, United States,



Document Type: Proceeding Paper

Part of: Irrigation and Drainage: Saving a Threatened Resource—In Search of Solutions

Abstract: Drought is conceived as a period of below normal precipitation or moisture deficiency that would affect the social and economic activities of a region. The Palmer Drought Index (PDI) is the most widely used drought indicator parameter. A monthly Markov chain model has been developed to analyze the likelihood of occurrences of the seven types of drought conditions. The spells are classified, using the PDI computed monthly by the NOAA. The model predicts month to month drought status over an entire climatic division. Twelve monthly transition matrices are computed. The model is applied to two Virginia climatic divisions, the Tidewater area (climatic division 1) and the Southwest mountains region (climatic division 6). The model predictions reflect the reality and compare very well with the observed data for these two climatic divisions.

Subject Headings: Droughts | Markov process | Mathematical models | Data processing | Matrix (mathematics) | Moisture | Precipitation | North America | Virginia | United States

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