A Review of Quantitative Precipitation Forecasts and Their Use in Short- to Medium-Range Streamflow Forecasting

Unknown future precipitation is the dominant source of uncertainty for many streamflow forecasts. Numerical weather prediction (NWP) models can be used to generate quantitative precipitation forecasts (QPF) to reduce this uncertainty. The usability and usefulness of NWP model outputs depend on the a...

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Bibliographic Details
Published in:Journal of hydrometeorology 2011-10, Vol.12 (5), p.713-728
Main Authors: Cuo, Lan, Pagano, Thomas C., Wang, Q. J.
Format: Article
Language:English
Subjects:
Forecasting models
Hydrological modeling
Hydrology
Modeling
Numerical weather forecasting
Precipitation
Probability forecasts
REVIEW
Stream flow
Time series forecasting
Weather forecasting
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Summary:Unknown future precipitation is the dominant source of uncertainty for many streamflow forecasts. Numerical weather prediction (NWP) models can be used to generate quantitative precipitation forecasts (QPF) to reduce this uncertainty. The usability and usefulness of NWP model outputs depend on the application time and space scales as well as forecast lead time. For streamflow nowcasting (very short lead times; e.g., 12 h), many applications are based onmeasured in situ or radar-based real-timeprecipitation and/or the extrapolation of recent precipitation patterns. QPF based on NWP model output may be more useful in extending forecast lead time, particularly in the range of a few days to a week, although low NWP model skill remains a major obstacle. Ensemble outputs from NWP models are used to articulate QPF uncertainty, improve forecast skill, and extend forecast lead times. Hydrologic prediction driven by these ensembles has been an active research field, although operational adoption has lagged behind. Conversely, relatively little study has been done on the hydrologic component (i.e., model, parameter, and initial condition) of uncertainty in the streamflow prediction system. Four domains of research are identified: selection and evaluation of NWP model–based QPF products, improved QPF products, appropriate hydrologic modeling, and integrated applications.
ISSN:1525-755X
1525-7541
DOI:10.1175/2011JHM1347.1