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Open AccessArticle

Evaluation of an Application of Probabilistic Quantitative Precipitation Forecasts for Flood Forecasting

1
Department of Geological and Atmospheric Sciences, Iowa State University, Ames, IA 50011, USA
2
Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, Norman, OK 73019, USA
3
NOAA/OAR/National Severe Storms Laboratory, Norman, OK 73019, USA
4
NOAA/NWS/Storm Prediction Center, Norman 73019, OK, USA
*
Author to whom correspondence should be addressed.
Water 2020, 12(10), 2860; https://doi.org/10.3390/w12102860
Received: 17 September 2020 / Revised: 8 October 2020 / Accepted: 12 October 2020 / Published: 14 October 2020
Probabilistic streamflow forecasts using precipitation derived from ensemble-based Probabilistic Quantitative Precipitation Forecasts (PQPFs) are examined. The PQPFs provide rainfall amounts associated with probabilities of exceedance for all grid points, which are averaged to the watershed scale for input to the operational Sacramento Soil Moisture Accounting hydrologic model to generate probabilistic streamflow predictions. The technique was tested using both the High-Resolution Rapid Refresh Ensemble (HRRRE) and the High-Resolution Ensemble Forecast version 2.0 (HREF) for 11 river basins across the upper Midwest for 109 cases. The resulting discharges associated with low probability of exceedance values were too large; no events were observed having discharges above the 10% exceedance value predicted from the technique applied to both ensembles, and no events were observed having discharges above the 25% exceedance value from the HREF-based forecast. The large differences are due to using the same precipitation exceedance value at all points; it is unlikely that all watershed points would experience the heavy rainfall associated with the 5% probability of exceedance. The technique likely can be improved through calibration of the basin-average precipitation forecasts based on typical distributions of precipitation within the convective systems that dominate warm-season precipitation events or calibration of the resulting probabilistic discharge forecasts. View Full-Text
Keywords: probabilistic forecasting; flood forecasting; quantitative precipitation forecasts; ensemble prediction systems; forecast verification probabilistic forecasting; flood forecasting; quantitative precipitation forecasts; ensemble prediction systems; forecast verification
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Goenner, A.R.; Franz, K.J.; Jr, W.A.G.; Roberts, B. Evaluation of an Application of Probabilistic Quantitative Precipitation Forecasts for Flood Forecasting. Water 2020, 12, 2860.

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