Graduation Semester and Year

2013

Language

English

Document Type

Thesis

Degree Name

Master of Science in Civil Engineering

Department

Civil Engineering

First Advisor

Dong-Jun Seo

Abstract

By 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.

Disciplines

Civil and Environmental Engineering | Civil Engineering | Engineering

Comments

Degree granted by The University of Texas at Arlington

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