RISC-KIT: Resilience-Increasing Strategies for Coasts toolkit

Transcription

1 RISC-KIT: Resilience-Increasing Strategies for Coasts toolkit Ap van Dongeren, Paolo Ciavola, Christophe Viavattene, Simone de Kleermaeker, Grit Martinez, Oscar Ferreira, Cristina Costa and Robert McCall (18 EU partners incl 10 CSS) UK Case Study Partner: Tom Spencer, Anna McIvor, Elizabeth Christie and Iris Möller, Cambridge Coastal Research Unit, University of Cambridge. Case study site: North Norfolk (SMP5) Other UK partner: Christophe Viavattene, University of Middlesex (vulnerability, damage curves etc) This project has received funding from the European Union s Seventh Programme for Research, Technological Development and Demostration under Grant Agreement No This presentation reflects the views only of the authors, and the European Union cannot be considered liable for any use that may be made of the information contained therein.

2 The RISC-KIT concept Develop a Resilience-Increasing Strategies for Coasts toolkit (RISC-KIT) of methods tools management approaches to reduce risk and increase resilience to extreme events (storm surge flooding or riverine flash floods) Timeline: November 2013 to April 2017

3 Contents RISC-KIT summary UK case study site Coastal flood modelling Aims for the modelling Model train FEWS system Representing vegetation in a wave model Modifications to the SWAN Vegetation module Results

4 RISC-KIT summary Historical Storms (Storm database) Hotspot selection Modification of existing models Coastal numerical modelling and scenario testing Disaster Risk Reduction measures (DRR) Coastal Vulnerability library Bayesian model (Total impact)

5 Case study site 10 case study sites, representing different coastal environments UK case study site North Norfolk 45km stretch of coast Natural coastline with some towns and villages, important area for nature conservation Based on existing management unit (UK Shoreline Management 5) RISC-KIT Case Study Site NORTH SEA HUNSTANTON WELLS-NEXT-THE-SEA HOLT SHERINGHAM CROMER N Crown Copyright and Database Right (2014) Ordnance Survey (Digimap Licence) 2 km

6 Site Characteristics: Geomorphology Tide dominated Meso- to macro-tidal Complex topography Barrier islands Back barrier marshes Tidal channels Open marshes Shingle barriers Sand dunes Coastline formed during the Holocene, i.e. this coast is less than 10,000 years old Scolt Head Island, North Norfolk (Photo: Mike Payne)

7 Site Characteristics: Ecosystems FEWS workshop, Antwerp, April 2015

8 Historic Flooding 11/3/ /11/ /08/ /01/ /03/ /01/ /03/ /02/ /09/ /01/ /01/ /12/ /02/ /01/ /02/ /12/ /11/ /03/ /11/ /12/2013 John Tuck (Steers, 1953) John Tuck

9 Coastal Flood modelling Future Outputs: 1. Coupled meteo, wave and tide models are set up for the hotspot site within the coastal FEWS system. 2. The coupled coastal models will be used for scenario testing for Future climate change scenarios (2100) Historic storm surges Disaster Risk Reduction (DRR) plans A Bayesian based Decision support system (DSS) will be applied to the case study site with data of hazard forcing, density and value of receptors Maximum surge (cm) during 1953 storm using POL CS3 model (Wolf and Flather, 2005) 3. The scenarios will train the probabilistic relations in the Bayesian DSS

10 Coastal Flood model Aim of the modelling: 1) To determine hazards at the hotspot site 2) To help understand the hazard pathways with the case study site

11 Storm surge modelling: Tide and surge CS3X tidal surge model Run by the National Oceanography Centre (NOC) 12km grid resolution Assumes no flow normal to the boundary Data available from NOC

12 Storm surge modelling: Waves and Meteo MetOffice WaveWatch III (WWIII) model North Atlantic and European Configuration has a 12km grid resolution Deep water wave model, doesn t include some processes important in shallow waters Data available from Significant wave height (m) National Centre for Ocean Forecasting (

13 Numerical Models: TELEMAC Open source suite of solvers for free surface flows Multiple modules to represent various physical processes Designed for coastal and riverine domains TELEMAC-2D module for hydrodynamics Solves the shallow water equations : depth integration of the 3D Navier- Stokes equations Turbulence closure schemes Various options for source and sink terms

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15 Numerical Models: SWAN SWAN (Simulating WAves Nearshore) is a third generation wave model (Booij et al., 1999). Developed by TU Delft The energy density spectrum describes wave energy over frequencies and direction, it can be sued to obtain wave parameters SWAN solves the wave action balance equation and includes source and sink terms for energy generation, dissipation and nonlinear interactions. Holthuijsen (2007)

16 North Norfolk: Model Train Water levels/currents from CS3/CS3X (NOC) Wind Conditions (MetOffice) Wave Spectra WaveWatch III (MetOffice) TELEMAC 2D model Water levels Large SWAN wave model Large Scale TELEMAC and SWAN model extent Wave spectra Small SWAN wave model EurOtop overtopping Fine resolution SWAN model extent Discharge at fixed locations FEWS TELEMAC flood model (Wells-next-the-sea) TELEMAC flood model result

17 Bayesian Decision Support System The numerical models compute the local hazard intensities for historic and future storm scenarios Information on receptors and the vulnerability libraries are applied to the hotspot in the DSS The Bayesian Network can then calculate the impact of the different hazards

18 Modification of existing models The case study site has a fairly natural coastline, with large areas of saltmarsh Large amount of field evidence of wave attenuation in saltmarsh, reed beds and other vegetation Adapted from Möller et al. 1999

19 Wave dissipation due to vegetation in SWAN SWAN is a spectral wave model and includes sources and sink terms for energy generation and dissipation. Dissipation due to vegetation, S ds,veg, is calculated within a vegetation module, SWAN-VEG (Suzuki et al., 2011). The current SWAN vegetation module uses a modified version of the Dalrymple (1984) wave dissipation formula by Mendez and Losada (2004) to calculate the wave dissipation due to vegetation (S veg ) Energy dissipation is based on plant characteristics: Plant height H v Vegetation diameter, D v Number of plants per m 2, N v Bulk drag coefficient, C D All the parameters can vary vertically, and N v can vary spatially.

20 Modifications to the vegetation module However, the drag coefficient, C D, has been shown to vary with the ambient wave conditions(kobayashi et al. (1993), Mendez et al. (1999), Mendez and Losada (2004), Mӧller et al. (2014)). Stem Reynolds number, Re v ; where U m is the maximum bottom orbital velocity, D is the vegetation diameter, and ν is the kinematic viscosity (ν = m 2 s -1 ) The drag coefficient expressed in terms of the stem Reynolds number, and is usually in the form: where a, b and c are empirically derived constants. Relationship between C D and vegetation Reynolds number, Re v. From Mӧller et al. 2014

21 Modifications to the vegetation module Mӧller et al. (2014) detailed wave dissipation measurements over a 40m section of saltmarsh in the large wave flume in Hannover. The experiment used storm surge conditions and a saltmarsh which is representative of those found in North West Europe. The drag coefficient was calculated using the Mendez and Losada (2004) formula and expressed as a function of the stem Reynolds number for regular and irregular waves. I Möller Irregular waves: (from Möller et al., 2014)

22 Modifications to the vegetation module SWAN MODEL MODIFICATIONS: Included a time varying drag coefficient based on the empirical equation of Mӧller et al. (2014) for irregular waves over a saltmarsh Included a time varying drag coefficient formula with empirical coefficients defined in the SWAN steering file Included the ability to vary the plant height spatially

23 Wave dissipation due to vegetation in SWAN The new variable drag coefficient formulation within SWAN is validated against the Mӧller et al. (2014) Large Wave Flume experiments. Which measured wave dissipation under storm conditions over a 40m test section of transplanted saltmarsh. Plant diameter = m Plant height = 0.7m Number of plants per m^2 = 1225 The new SWAN-VEG module gives a better fit to the experimental data, especially at high significant wave heights representing storm waves.

24 Validating the modified vegetation module Further validation over a 197m transect at the Stiffkey, North Norfolk saltmarsh using the wave dissipation measurements of Mӧller et al. (1999). Only the experimental data with onshore winds that run parallel to the transect included Möller et al. (1999) The vegetation height is derived from side-on photographs of the vegetation at Stiffkey (Mӧller et al. 1999), where H v = 0.11m The plant diameter is assumed to be D v = m, from Mӧller et al. (2014). The plant density is assumed to be similar to a saltmarsh transect at Tillingham, Essex, N v = The predicted wave height reduction shows a very good agreement with the measured results

25 Validating the modified vegetation module The new SWAN-VEG module is validated against the wave dissipation measurements of Mӧller (2006) at Tillingham, Essex coast, UK. Using 3 short transects of ~4m with differing vegetation types Transect Composition Mean Vegetation Height (m) 1 Spartina 86% Salicornia 11% 2 Spartina 73% Mean Vegetation Diameter (m) Mean number of plants per m x x Salicornia 25% 3 Salicornia 98% x Some of the vegetation characteristics have been derived

26 Validating the modified vegetation module Transect Composition Mean Vegetation Height (m) 1 Spartina 86% Salicornia 11% 2 Spartina 73% Mean Vegetation Diameter (m) Mean number of plants per m x x Salicornia 25% 3 Salicornia 98% x

27 Validating the modified vegetation module Next Step: Testing the new vegetation module in the 2D coastal wave model and assessing the impact of the vegetation on hazards at our site

28 Acknowledgements The Environment Agency, UK: Eleanor Heron, Michelle Partridge, David Welsh, David Kemp, Guy Cooper, Rebecca Brown and Mark Johnson The Flood Forecasting Centre, UK: David Cox The Meteorological Office, UK: Andy Saulter Various people who agreed to be interviewed about recent experiences of flooding and current practice in risk management on the North Norfolk Coast. AM