Modeling Probability of Blockage at Culvert Trash Screens Using Bayesian Approach
Publication: Journal of Hydraulic Engineering
Volume 139, Issue 7
Abstract
Trash screens are commonly installed at culvert entrances to prevent the ingress of debris that might otherwise become lodged within the structure. However, these can be a hazard in themselves if not cleared at an appropriate interval. There are currently no tools available to support making decisions regarding screen inspection requirements based upon potential site-by-site blockage risks. The analysis reported here was performed to address this issue. The parameter considered as key in the decision-making process was the probability of screen blockage. To determine this for any screen under consideration, a stochastic predictive model was developed using inspection records, obtained from 140 screens in Belfast, Northern Ireland, to relate blockage probabilities to seven potential drivers extracted from channel, land-use, meteorological, temporal, and social deprivation factors, employing a logistic regression approach. To allow for randomness in the data set, a Bayesian framework was adopted through which the uncertainty associated with any prediction could be reported using appropriate credible intervals. The predictive accuracy of the model was also assessed using appropriate measures and, despite documented uncertainties, was shown to be well within acceptable limits.
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Acknowledgments
The research reported here was conducted as part of the Flood Risk Management Research Consortium (FRMRC). The FRMRC is supported by Grant EP/F020511/1 from the Engineering and Physical Sciences Research Council, in partnership with the Department for the Environment and Rural Affairs/Environment Agency Joint Research Programme on Flood and Coastal Defense, UK Water Industry Research, Office for Public Works (Ireland), and the Rivers Agency (Northern Ireland). The research was also supported by an Environment and Physical Sciences Research Council Bridging the Gaps Grant (EP/E018939/1). This financial support is gratefully acknowledged. The research is also part of the Strategic Alliance for integrated Water Management Action Interreg IVB project. Special thanks are extended to Jim Martin and associated staff at the Northern Ireland River Agency for supplying the data sets used in the analysis presented here.
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© 2013 American Society of Civil Engineers.
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Received: Oct 24, 2011
Accepted: Dec 18, 2012
Published online: Dec 21, 2012
Published in print: Jul 1, 2013
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