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dc.contributor.authorGorugantula, Srikanth VLen_US
dc.date.accessioned2011-08-06T16:06:48Z
dc.date.available2011-08-06T16:06:48Z
dc.date.issued2003-05-15en_US
dc.identifier.otheretd-12302002-114005en_US
dc.identifier.urihttp://hdl.handle.net/10919/10145
dc.description.abstractThe mountainous western Virginia is the source of the headwater streams for the New, the Roanoke, and the James rivers. The region is prone to flash flooding, typically the result of localized precipitation. Fortunately, within the region, there is an efficient system of instruments for real-time data gathering with IFLOWS (Integrated Flood Observing and Warning System) gages, WSR-88D Doppler radar, and high precision GPS (Global Positioning System) receiver. The focus of this research is to combine the measurements from these various sensors in an algorithmic framework to determine the flash flood magnitude. It has been found that the trend in the GPS signals serves as a precursor for rain events with a lead-time of 30 minutes to 2 hours. The methodology proposed herein takes advantage of this lead-time as the trigger to initiate alert related calculations. It is shown here that the sum of the rates of change of total cloud water, water vapor contents and logarithmic profiles of partial pressure of dry air and temperature in an atmospheric column is equal to the rain rate. The total water content is measurable as the profiles of integrated precipitable water (IPW) from the GPS, the vertically integrated liquid (VIL) from the radar (representing different phases of the atmospheric water) and the pressure and temperature profiles are available. An example problem is presented illustrating the involving the calculations.en_US
dc.format.mediumETDen_US
dc.publisherVirginia Techen_US
dc.relation.haspartThesis_Final_ETD.pdfen_US
dc.rightsI hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Virginia Tech or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.en_US
dc.subjectradiosodeen_US
dc.subjectstatistical analysisen_US
dc.subjectGOES satelliteen_US
dc.titleA GPS-IPW Based Methodology for Forecasting Heavy Rain Eventsen_US
dc.typeThesisen_US
dc.contributor.departmentCivil Engineeringen_US
dc.description.degreeMaster of Scienceen_US
thesis.degree.nameMaster of Scienceen_US
thesis.degree.levelmastersen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineCivil Engineeringen_US
dc.contributor.committeechairLoganathan, G. V.en_US
dc.contributor.committeememberLohani, Vinod K.en_US
dc.contributor.committeememberYounos, Tamimen_US
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-12302002-114005en_US
dc.date.sdate2002-12-30en_US
dc.date.rdate2004-01-03
dc.date.adate2003-01-03en_US


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