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dc.contributor.authorTchaou, Marcel Kossien
dc.date.accessioned2014-03-14T21:46:19Zen
dc.date.available2014-03-14T21:46:19Zen
dc.date.issued1992en
dc.identifier.otheretd-09192009-040432en
dc.identifier.urihttp://hdl.handle.net/10919/44864en
dc.description.abstractDrought is perceived differently by different people, but in general, it is conceived as a period of below normal precipitation or moistur e deficiency that would affect the social and economic activities of a region. Many numerical indices are used to quantify the effect of drought. The Pahner Drought Severity Index (PDSI) is the most and widely used drought indicator parameter in most recent applications. The PDSI takes into account precipitation, temperature, and soil moisture and depicts prolonged abnormal dryness or wetness. A Markov chain model was developed to analyze the likelihood of occurrences of the seven types of weather spells, defmed by the National Oceanic and Atmospheric Administration (NOAA). The spells are classified, using the PDSI computed monthly by the NOAA. The model predicts both short and long term drought status over an entire climatic division. Twelve monthly transition matrices and one annual transition matrix were computed. The matrices show the transition patterns between months and between drought states. The model was applied to the Tidewater area (climatic division l) and the Southwest mountains (climatic division 6) of Virginia. The model predictions reflect the reality and compare very well with the observed data for these two climatic divisions. This model can potentially be used as a tool for water resource planning and design of drought assistance plans by water resource managers.en
dc.format.extentx, 164 leavesen
dc.format.mediumBTDen
dc.format.mimetypeapplication/pdfen
dc.language.isoenen
dc.publisherVirginia Techen
dc.relation.isformatofOCLC# 26088307en
dc.relation.haspartLD5655.V855_1992.T332.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subject.lccLD5655.V855 1992.T332en
dc.subject.lcshDrought forecastingen
dc.subject.lcshMarkov processesen
dc.titleA Markov chain approach for analyzing Palmer drought severity indexen
dc.typeThesisen
dc.contributor.departmentAgricultural Engineeringen
dc.description.degreeMaster of Scienceen
thesis.degree.nameMaster of Scienceen
thesis.degree.levelmastersen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.disciplineAgricultural Engineeringen
dc.contributor.committeechairMostaghimi, Saieden
dc.contributor.committeememberLoganathan, G. V.en
dc.contributor.committeememberRoss, Burton Blakeen
dc.type.dcmitypeTexten
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-09192009-040432/en
dc.date.sdate2009-09-19en
dc.date.rdate2009-09-19en
dc.date.adate2009-09-19en


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