Flood estimation at ungauged sites using artificial neural networks

JOURNAL OF HYDROLOGY

卷:319

Article

Dawson, CW ; Abrahart, RJ ; Shamseldin, AY ; Wilby, RL

关键词: artificial neural networks;    flood estimation;    ungauged catchments;   

DOI  :  10.1016/j.jhydrol.2005.07.032

来源: Elsevier

【 摘 要 】

Artificial neural networks (ANNs) have been applied within the field of hydrological modelling for over it decade but relatively little attention has been paid to the use of these tools for flood estimation in ungauged catchments. This paper uses data from the Centre for Ecology and Hydrology's Flood Estimation Handbook (FEH) to predict T-year flood events and the index flood (the median of the annual maximum series) for 850 catchments across the UK. When compared with multiple regression models, ANNs provide improved flood estimates that can be used by engineers and hydrologists. Comparisons are also made with the empirical model presented in the FEH and a preliminary study is made of the spatial distribution of ANN residuals, highlighting the influence that geographical factors have on model performance. (C) 2005 Elsevier Ltd All rights reserved.

【 授权许可】

Free