Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/105969
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Type: Journal article
Title: A hybrid approach to monthly streamflow forecasting: integrating hydrological model outputs into a Bayesian artificial neural network
Author: Humphrey, G.
Gibbs, M.
Dandy, G.
Maier, H.
Citation: Journal of Hydrology, 2016; 540:623-640
Publisher: Elsevier
Issue Date: 2016
ISSN: 0022-1694
1879-2707
Statement of
Responsibility: 
Greer B. Humphrey, Matthew S. Gibbs, Graeme C. Dandy, Holger R. Maier
Abstract: Abstract not available
Keywords: Monthly streamflow forecasting; Bayesian artificial neural networks; Conceptual hydrological models; uncertainty; hybrid modelling; South Australia
Rights: © 2016 Elsevier B.V. All rights reserved.
RMID: 0030050650
DOI: 10.1016/j.jhydrol.2016.06.026
Appears in Collections:Environment Institute Leaders publications

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