Flood estimation at ungauged sites using artificial neural networks

Autor: Dawson, C.W., Abrahart, R.J., Shamseldin, A.Y., Wilby, R.L.

Publikováno v: In Journal of Hydrology 2006 319(1):391-409

Including spatial distribution in a data-driven rainfall-runoff model to improve reservoir inflow forecasting in Taiwan

Autor: Meng-Jung, T., Abrahart, R.J., Mount, Nick J., Chang, F.-J.

Multi-step ahead inflow forecasting has a critical role to play in reservoir operation and management in Taiwan during typhoons as statutory legislation requires a minimum of 3-hours warning to be issued before any reservoir releases are made. Howeve

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::cfd0adb29db618615f3c756f150c5a8a
http://eprints.nottingham.ac.uk/28053/

Correction of timing errors of artificial neural network rainfall - runoff models

Autor: de Vos, N.J., Rientjes, T.H.M., Abrahart, R.J., al., et

Publikováno v: Practical hydroinformatics : computational intelligence and technological developments in water applications (Water science and technology library ; 68), 101-112
STARTPAGE=101;ENDPAGE=112;TITLE=Practical hydroinformatics : computational intelligence and technological developments in water applications (Water science and technology library ; 68)

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=narcis______::07f7a22608749b32cc71cbe333b8a82b
https://research.utwente.nl/en/publications/correction-of-timing-errors-of-artificial-neural-network-rainfall--runoff-models(33ea78e9-8492-435e-935c-22f2288451df).html

HydroTest: Further development of a web resource for the standardised assessment of hydrological models

Autor: Dawson, C.W., Abrahart, R.J., See, L.M.

Publikováno v: In Environmental Modelling and Software 2010 25(11):1481-1482

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