A toy model for monthly river flow forecasting

Journal of Hydrology

Volumn 452-453, Issue , 2012, Pages 226-231

  Zeng, Xubin ^a   Kiviat, Kira L ^a   Sakaguchi, Koichi ^a   Mahmoud, Alaa M A ^b  

^a UNIVERSITY OF ARIZONA   (United States)

^b Al Azhar University   (Egypt)

Author keywords

Modified Nash Sutcliffe coefficient of efficiency; Neural network; River flow forecasting; Uncertainty quantification

Indexed keywords

BIAS CORRECTION; CORRELATION COEFFICIENT; COUPLED PROCESS; ENSEMBLE MEMBERS; HISTORICAL DATA; LAND MODEL; MODEL COEFFICIENT; MODEL EVALUATION; NASH-SUTCLIFFE COEFFICIENT; PHYSICALLY BASED; PREDICTION UNCERTAINTY; RIVER BASINS; RIVER FLOW; RIVER FLOW FORECASTING; SEASONAL CYCLE; SHORT PERIODS; STANDARD NEURAL; TOY MODELS; UNCERTAINTY QUANTIFICATIONS; WATER BALANCE;

EFFICIENCY; ERROR STATISTICS; FORECASTING; NEURAL NETWORKS;

STREAM FLOW;

ARTIFICIAL NEURAL NETWORK; CALIBRATION; DATA SET; FLOW MODELING; FORECASTING METHOD; NUMERICAL MODEL; PRECIPITATION (CLIMATOLOGY); RIVER BASIN; RIVER FLOW; UNCERTAINTY ANALYSIS;

EID: 84863091632     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2012.05.053     Document Type: Article

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