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A High-Resolution National-Scale Hydrologic Forecast System from a Global Ensemble Land Surface Model.
Snow, Alan D; Christensen, Scott D; Swain, Nathan R; Nelson, E James; Ames, Daniel P; Jones, Norman L; Ding, Deng; Noman, Nawajish S; David, Cédric H; Pappenberger, Florian; Zsoter, Ervin.
Afiliação
  • Snow AD; Coastal and Hydraulics Laboratory US Army Engineer Research and Development Center 3909 Halls Ferry Rd Vicksburg MS 39180.
  • Christensen SD; Department of Civil and Environmental Engineering Brigham Young University Provo UT 84602.
  • Swain NR; Department of Civil and Environmental Engineering Brigham Young University Provo UT 84602.
  • Nelson EJ; Department of Civil and Environmental Engineering Brigham Young University Provo UT 84602.
  • Ames DP; Department of Civil and Environmental Engineering Brigham Young University Provo UT 84602.
  • Jones NL; Department of Civil and Environmental Engineering Brigham Young University Provo UT 84602.
  • Ding D; Esri Redlands CA 92373.
  • Noman NS; Esri Redlands CA 92373.
  • David CH; Jet Propulsion Laboratory California Institute of Technology Pasadena CA 91109.
  • Pappenberger F; European Centre for Medium-Range Weather Forecasts Shinfield Park Reading UK.
  • Zsoter E; European Centre for Medium-Range Weather Forecasts Shinfield Park Reading UK.
J Am Water Resour Assoc ; 52(4): 950-964, 2016 Aug.
Article em En | MEDLINE | ID: mdl-31423076
ABSTRACT
Warning systems with the ability to predict floods several days in advance have the potential to benefit tens of millions of people. Accordingly, large-scale streamflow prediction systems such as the Advanced Hydrologic Prediction Service or the Global Flood Awareness System are limited to coarse resolutions. This article presents a method for routing global runoff ensemble forecasts and global historical runoff generated by the European Centre for Medium-Range Weather Forecasts model using the Routing Application for Parallel computatIon of Discharge to produce high spatial resolution 15-day stream forecasts, approximate recurrence intervals, and warning points at locations where streamflow is predicted to exceed the recurrence interval thresholds. The processing method involves distributing the computations using computer clusters to facilitate processing of large watersheds with high-density stream networks. In addition, the Streamflow Prediction Tool web application was developed for visualizing analyzed results at both the regional level and at the reach level of high-density stream networks. The application formed part of the base hydrologic forecasting service available to the National Flood Interoperability Experiment and can potentially transform the nation's forecast ability by incorporating ensemble predictions at the nearly 2.7 million reaches of the National Hydrography Plus Version 2 Dataset into the national forecasting system.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: J Am Water Resour Assoc Ano de publicação: 2016 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: J Am Water Resour Assoc Ano de publicação: 2016 Tipo de documento: Article