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Hydrological Sciences Journal Volume 52, 2007 - Issue 3: Hydroinformatics
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Original Articles

Timing error correction procedure applied to neural network rainfall—runoff modelling

Procédure de correction des erreurs temporelles appliquées à la modélisation pluie—débit par réseaux de neurones

ROBERT J. ABRAHART School of Geography, University of Nottingham, Nottingham, NG7 2RD, UK E-mail: [email protected]
,
ALISON J. HEPPENSTALL School of Geography, University of Leeds, Leeds, LS2 9JT, UK
&
LINDA M. SEE School of Geography, University of Leeds, Leeds, LS2 9JT, UK
Pages 414-431 | Received 23 Mar 2006, Accepted 26 Mar 2007, Published online: 18 Jan 2010

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H. K. D. H. Bhadeshia, R. C. Dimitriu, S. Forsik, J. H. Pak & J. H. Ryu. (2009) Performance of neural networks in materials science. Materials Science and Technology 25:4, pages 504-510.
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DEMETRIS KOUTSOYIANNIS, HUAMING YAO & ARIS GEORGAKAKOS. (2008) Medium-range flow prediction for the Nile: a comparison of stochastic and deterministic methods / Prévision du débit du Nil à moyen terme: une comparaison de méthodes stochastiques et déterministes. Hydrological Sciences Journal 53:1, pages 142-164.
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LINDA SEE, DIMITRI SOLOMATINE, ROBERT ABRAHART & ELENA TOTH. (2007) Hydroinformatics: computational intelligence and technological developments in water science applications—Editorial. Hydrological Sciences Journal 52:3, pages 391-396.
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Lloyd H.C. Chua & Tommy S.W. Wong. (2011) Runoff forecasting for an asphalt plane by Artificial Neural Networks and comparisons with kinematic wave and autoregressive moving average models. Journal of Hydrology 397:3-4, pages 191-201.
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Holger R. Maier, Ashu Jain, Graeme C. Dandy & K.P. Sudheer. (2010) Methods used for the development of neural networks for the prediction of water resource variables in river systems: Current status and future directions. Environmental Modelling & Software 25:8, pages 891-909.
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M. K. Akhtar, G. A. Corzo, S. J. van Andel & A. Jonoski. (2009) River flow forecasting with artificial neural networks using satellite observed precipitation pre-processed with flow length and travel time information: case study of the Ganges river basin. Hydrology and Earth System Sciences 13:9, pages 1607-1618.
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R.J. Abrahart, L.M. See, A.J. Heppenstall & S.M. White. 2008. Practical Hydroinformatics. Practical Hydroinformatics 139 161 .
R. J. Abrahart & L. M. See. (2007) Neural network modelling of non-linear hydrological relationships. Hydrology and Earth System Sciences 11:5, pages 1563-1579.
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