Real-Time Data Assimilation for Operational Ensemble Streamflow Forecasting
نویسندگان
چکیده
منابع مشابه
Real-Time Data Assimilation for Operational Ensemble Streamflow Forecasting
Operational flood forecasting requires that accurate estimates of the uncertainty associated with modelgenerated streamflow forecasts be provided along with the probable flow levels. This paper demonstrates a stochastic ensemble implementation of the Sacramento model used routinely by the National Weather Service for deterministic streamflow forecasting. The approach, the simultaneous optimizat...
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a State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China b School of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, OK 73072, USA Hydrometeorology and Remote Sensing Laboratory, National Weather Center Atmospheric Radar Research Center, Norman, OK 73072, USA NOAA/National Severe Storms ...
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Accurate streamflow predictions are crucial for mitigating flood damage and addressing operational flood scenarios. In recent years, sequential data assimilation methods have drawn attention due to their potential to handle explicitly the various sources of uncertainty in hydrologic models. In this study, we implement two ensemble-based sequential data assimilation methods for streamflow foreca...
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ژورنال
عنوان ژورنال: Journal of Hydrometeorology
سال: 2006
ISSN: 1525-7541,1525-755X
DOI: 10.1175/jhm504.1