Using self-organizing maps and wavelet transforms for space-time pre-processing of satellite precipitation and runoff data in neural network based rainfall-runoff modeling

Journal of Hydrology

Volumn 476, Issue , 2013, Pages 228-243

  Nourani, Vahid ^a,b   Baghanam, Aida Hosseini ^a,c   Adamowski, Jan ^c   Gebremichael, Mekonnen ^d  

^a UNIVERSITY OF TABRIZ   (Iran)

^b UNIVERSITY OF MINNESOTA   (United States)

^c MCGILL UNIVERSITY   (Canada)

^d UNIVERSITY OF CONNECTICUT   (United States)

Author keywords

Feed forward neural network; Gilgel Abay watershed; Rainfall runoff modeling; Satellite data; Self organizing map; Wavelet

Indexed keywords

AHEAD-TIME; AUTO-REGRESSIVE INTEGRATED MOVING AVERAGE; CLUSTERING TECHNIQUES; DETERMINATION COEFFICIENTS; ETHIOPIA; EXOGENOUS INPUT; FORECASTING METHODS; HOMOGENEOUS CLUSTER; INPUT VARIABLES; LEAD TIME; MODEL RAINFALL-RUNOFF; MULTI-SCALE FEATURES; MULTI-STEP; NONSTATIONARY; PEAK VALUES; PRE-PROCESSED DATA; PRE-PROCESSING; PRECIPITATION DATA; RAIN GAUGES; RAINFALL RUNOFF; RAINFALL-RUNOFF MODELING; RAINFALL-RUNOFF MODELS; REMOVE NOISE; RUNOFF DATA; RUNOFF PREDICTION; SATELLITE DATA; SATELLITE PRECIPITATION; SOM CLUSTERING; VALIDATION PHASE; WAVELET;

CONFORMAL MAPPING; FORECASTING; RAIN; SATELLITES; WATERSHEDS;

RUNOFF;

ARTIFICIAL NEURAL NETWORK; PRECIPITATION (CLIMATOLOGY); RAINFALL-RUNOFF MODELING; SATELLITE DATA; SELF ORGANIZATION; SPATIOTEMPORAL ANALYSIS; WAVELET ANALYSIS;

ETHIOPIA; GILGEL ABAY BASIN;

EID: 84871025948     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2012.10.054     Document Type: Article

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