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Improved Methods for Predicting Trash Loading at Culverts with Trash Screens

Improved Methods for Predicting Trash Loading at Culverts with Trash Screens. FRMRC 2 WP 4.1. Advances in Flood Risk Management Science The Royal Society 5 th September 2011. Nick Wallerstein & Scott Arthur (Heriot-Watt University). The problem.

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Improved Methods for Predicting Trash Loading at Culverts with Trash Screens

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  1. Improved Methods for Predicting Trash Loading at Culverts with Trash Screens FRMRC 2 WP 4.1 Advances in Flood Risk Management Science The Royal Society 5th September 2011 Nick Wallerstein & Scott Arthur (Heriot-Watt University)

  2. The problem • Culverts represent pinch-points in the river system which often have trash screens installed to prevent internal blockage. • However these can be a flood hazard in themselves if not cleared and maintained at an appropriate inspection interval. • Material delivered into the river system includes natural (organic) debris and also anthropogenic trash.

  3. Aims • Build on the current scientific knowledge base regarding trash screen blockage. • Develop evidence based decision support tools to aid with screen management. Specifically tools to help estimate the: • Probability of significant debris load delivery to screens • Potential screen area likely to block • Attempt to explicitly quantify the uncertainties associated with such tools. • Aim to use the findings to help update current best-practice guidance: • Culvert Design and Operation Guide (CDOG) (CIRIA, 2010)

  4. Analysis approach • Used detailed inspection records (25000) from 140 screens located in Belfast (supplied by NIRA) to determined (Pd)and (Sab) for each screen in the dataset. • Related these parameters to hypothesised driving variables using multiple regression analysis to generate predictive equations :- flow channel (screen) predictive equations Pd / Sab = f landuse social dep.

  5. Application (prob. delivery) select screens of concern obtain equation input data calculate Pdfor each screenusing the appropriate equation calculate associated risk: = Pd x blockage consequence rank screens according to risk and base inspection frequency upon rank

  6. Key collaborative partners • EA (lead end user) }key steer • FRMRC Industrial Partners • JBA }Bayesian analysis of dataset leading to research publication • Royal Haskoning }report on research needs + key output reviewer • HR Wallingford }report on integration of WP 4.1 outputs with FRM • Independent initiatives • Northern Ireland Rivers Agency (NIRA) • Edinburgh City Council • South Lanarkshire Council • EA (Bridgewater) • H.W. Uni. Dept. Maths }obtained EPSRC ‘Bridging the Gaps Fund’ grant facilitating joint research analysis leading to publication data-sets

  7. Conclusions • The installation of trash screens at culverts does not preclude flooding. • Screens must have both an effective inspection regime and an optimal design to minimise blockage potential. • Through WP 4.1 we have gained an improved understanding of the key variables driving debris delivery to, and blockage at, trash screens. • Exploration of this subject has led to internationally leading academic research. • Simple regression equations have been developed to act as decision support tools for assessing optimal screen inspection frequency and design.

  8. practical Outputs • FRMRC WP 4.1 Final Science Report • Technical note to accompany CDOG • Report on integration of science outputs with FRM • Report on trash screen research needs books / papers / conference proceedings • Chapter in forthcoming Flood Defence Design and Analysis Methods book • Four international journal publications (various stages of completion) • Papers in proceedings of five international conferences

  9. The research reported in this presentation was conducted as part of the Flood Risk Management Research Consortium with support from the: Engineering and Physical Sciences Research Council Department of Environment, Food and Rural Affairs/Environment Agency Joint Research Programme United Kingdom Water Industry Research Office of Public Works Dublin Northern Ireland Rivers Agency Data were provided by the EA and the Ordnance Survey Acknowledgement

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