Hydrol. Earth Syst. Sci., 17, 177–185, 2013 www.hydrol-earth-syst-sci.net/17/177/2013/ Hydrology and doi:10.5194/hess-17-177-2013 Earth System © Author(s) 2013. CC Attribution 3.0 License. Sciences Application of data-based mechanistic modelling for flood forecasting at multiple locations in the Eden catchment in the National Flood Forecasting System (England and Wales) D. Leedal1, A. H. Weerts2,4, P. J. Smith1, and K. J. Beven1,3 1Lancaster Environment Centre, Lancaster University, Lancaster, UK 2Deltares, P.O. Box 177, 2600 MH, Delft, The Netherlands 3Geocentrum, Uppsala University, Uppsala, Sweden 4Hydrology and Quantitative Water Management Group, Department of Environmental Sciences, Wageningen University, Wageningen, The Netherlands Correspondence to: D. Leedal (
[email protected]) Received: 8 May 2012 – Published in Hydrol. Earth Syst. Sci. Discuss.: 8 June 2012 Revised: 29 October 2012 – Accepted: 15 December 2012 – Published: 18 January 2013 Abstract. The Delft Flood Early Warning System provides a user is also given access to a sophisticated interface for visu- versatile framework for real-time flood forecasting. The UK alizing and interacting with forecasts and data. Environment Agency has adopted the Delft framework to de- This paper provides a description of the DBM real-time liver its National Flood Forecasting System. The Delft sys- flood forecasting method (Appendix A), a section describing tem incorporates new flood forecasting models very easily the design and implementation of the FEWS module, and a using an “open shell” framework. This paper describes how case study building a semi-distributed DBM representation we added the data-based mechanistic modelling approach to of the Eden catchment with forecast locations at Carlisle, the model inventory and presents a case study for the Eden which was extensively flooded in 2005 (Mayes et al., 2006; catchment (Cumbria, UK).