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WP1.2: Inundation modelling to support uncertainty analysis

WP1.2: Inundation modelling to support uncertainty analysis. Jeff Neal 1 , Ignacio Villanueva 2 , Nigel Wright 3 , Thomas Willis 3 , Timothy Fewtrell 4 , Paul Bates 1, Caroline Keef 5 , Keith Beven 6 and David Leedal 6.

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WP1.2: Inundation modelling to support uncertainty analysis

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  1. WP1.2: Inundation modelling to support uncertainty analysis Jeff Neal1, Ignacio Villanueva2, Nigel Wright3, Thomas Willis3, Timothy Fewtrell4, Paul Bates1, Caroline Keef5, Keith Beven6and David Leedal6 1School of Geographical Sciences, University of Bristol, Bristol. BS8 1SS. UK, 2Ofiteco Ltd., Avenida de Portugal, 81. 28071, Madrid. Spain. 3School of Civil Engineering, University of Leeds, Leeds. LS2 9JT. UK 4Willis Research Network, Willis Re, Willis Building, 51 Lime Street, London. EC3M 7DQ. UK 5JBA Consulting, South Barn, Broughton Hall, Skipton, N Yorkshire, BD23 3AE, UK. 6Lancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ, UK.

  2. Why develop and benchmark models to support uncertainty analysis? • Two-dimensional models of floodplain hydraulics require a lot of computation time. • Increasing resolution requires increased computation. • Monte Carlo… also increases computation • Simple models: • Require less computation per time-step than a shallow water models. • Force modellers to think about the minimum process representation necessary to predict particular quantities. • Are generally not as widely applicable as shallow water models – thus we need to understand their limits. • Some may require shorter time-steps to remain stable especially at 1-10 m resolutions (Hunter et al., 2005).

  3. i j LISFLOOD-FP (ACC) formulation • Continuity Equation • Continuity equation relating flow fluxes and change in cell depth • Momentum Equation • Flow between two cells is • calculated using: • Time stepping hflow j i Representation of flow between cells in LISFLOOD-FP

  4. EA 2D model benchmarking • Taken from Environment Agency 2D model benchmarking project • Simulation results from commercial codes available • ISIS2D, TUFLOW, SOBEK, MIKE FLOOD, InfoWorks2D • FlowRoute, JFLOW-GPU, Dynamic RFSM

  5. Results – Valley filling following dam failure

  6. Results – Valley filling following dam failure The frequently of velocity output had as much impact on hazards assessment as model physical complexity.

  7. Carlisle: Probabilistic flood risk mapping. www.lancs.ac.uk/staff/leedald/Carlisle/visualisation.html

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