An integrated uncertainty and ensemble-based data assimilation approach for improved operational streamflow predictions

Hydrology and Earth System Sciences

Volumn 16, Issue 3, 2012, Pages 815-831

  He, M ^a,c,d   Hogue, T S ^a   Margulis, S A ^a   Franz, K J ^b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b IOWA STATE UNIVERSITY   (United States)

^c NOAA EARTH SYSTEM RESEARCH LABORATORY   (United States)

^d RIVERSIDE TECHNOLOGY INC   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANALYSIS ALGORITHMS; DATA ASSIMILATION; ENSEMBLE KALMAN FILTER; ENSEMBLE PREDICTION; FORECASTING METHODS; HIGH FLOW; MODEL PARAMETERS; OPERATIONAL BASINS; PARAMETER UNCERTAINTY; RAINFALL-RUNOFF MODELS; RIVER FORECAST CENTERS; SNOW WATER EQUIVALENT; STREAMFLOW PREDICTION; UNCERTAINTY STRUCTURE; US NATIONAL WEATHER SERVICE;

DATA PROCESSING; SNOW; STREAM FLOW; UNCERTAINTY ANALYSIS;

FORECASTING;

DATA ASSIMILATION; ENSEMBLE FORECASTING; INTEGRATED APPROACH; KALMAN FILTER; RAINFALL-RUNOFF MODELING; SNOW WATER EQUIVALENT; STREAMFLOW; UNCERTAINTY ANALYSIS;

EID: 84858714047     PISSN: 10275606     EISSN: 16077938     Source Type: Journal    
DOI: 10.5194/hess-16-815-2012     Document Type: Article

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