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dc.contributor.authorSaharia, Manabendraen_US
dc.date.accessioned2013-10-22T23:59:46Z
dc.date.available2013-10-22T23:59:46Z
dc.date.issued2013-10-22
dc.date.submittedJanuary 2013en_US
dc.identifier.otherDISS-12348en_US
dc.identifier.urihttp://hdl.handle.net/10106/23926
dc.description.abstractBy allowing for routine use of longer-lead quantitative precipitation forecast (QPF) in hydrologic prediction, ensemble forecasting offers hope for extending the lead time for short-range streamflow forecasting. In this work, this potential is assessed by comparatively evaluating ensemble streamflow hindcasts forced by Day 1-3 QPF with those forced by Day 1 QPF for five headwater basins in the Upper Trinity River Basin in North Texas. The hindcasts are generated for a 7-year period of 2004 to 2010 using the Hydrologic Ensemble Forecast Service (HEFS), which operates on the Community Hydrologic Prediction System (CHPS) of the National Weather Service (NWS). HEFS includes the Meteorological Ensemble Forecast Processor (MEFP), Ensemble Postprocessor (EnsPost) and Ensemble Verification System (EVS). In this study, MEFP is used to generate ensemble QPFs from the West Gulf River Forecast Center (WGRFC)-produced single-valued QPFs, EnsPost is used to post-process the streamflow hindcasts in terms of correcting hydrologic bias involved and EVS is used to verify the precipitation and streamflow ensemble hindcasts. The results show that: (1) The ensemble QPFs produced from single-valued QPFs using MEFP are generally skillful and reliable, (2) Using Day 1-3 single-valued QPF via HEFS significantly increases the skill in short-range Ensemble Streamflow Prediction (ESP) forecasts; and (3) Post-processing of ESP ensembles via EnsPost improves discrimination and reliability of the raw ESP ensembles. Finally, the issues and challenges are identified and future research recommendations are provided.en_US
dc.description.sponsorshipSeo, Dong-Junen_US
dc.language.isoenen_US
dc.publisherCivil & Environmental Engineeringen_US
dc.titleEnsemble Streamflow Forecasting For The Upper Trinity River Basin In Texasen_US
dc.typeM.S.en_US
dc.contributor.committeeChairSeo, Dong-Junen_US
dc.degree.departmentCivil & Environmental Engineeringen_US
dc.degree.disciplineCivil & Environmental Engineeringen_US
dc.degree.grantorUniversity of Texas at Arlingtonen_US
dc.degree.levelmastersen_US
dc.degree.nameM.S.en_US


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