Optimal Use of ALTM for Modelling Urban Floodplain Inundation

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James Brasington Aberystwyth University
New Directions in Fluvial Flood Risk Analysis
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Fluvial Flood Risk in the UK

• 2 m people in the UK live on the 100 year
  floodplain
• 2.2b in annual losses
• Flood decade
• Easter 1998
• 2000, 2001, 2002,
• Boscastle 2004
• Carlisle 2005
• Summer 2007
• Exacerbated by
• Population growth
• Reducing household size
• Urban runoff generation
• Impacts of climate change

Cambridge, UK 2001
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Quantifying Flood Risk
Cambridge, UK 2001
2d hydraulic model simulation of floods in
Cambridge, Oct 2001
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Themes

• New methodologies and tools for flood risk
  assessment

• Outline an end-to-end modelling strategy for
  forecasting strategic flood risk in urban areas
• Explore the role of uncertainty analysis in
  improving forecast methodologies and
  communicating risk
• Outline a new generation of visualization tools
  to help communicate flood risk to the end-user
  community

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End-to-End Modelling with Uncertainty

• Computer modelling of the physical processes
  leading from flood generation to floodplain
  inundation
• End-to-End Modelling
• Broad-Scale or Whole-System Modelling
• Aims
• Reduce dependence on short-term empirical records
• Provide a framework for scenario evaluation
  (links to drivers)
• Improve predictive performance in urban areas
• Quantify and communicate predictive uncertainty

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Continuous Simulation of Flood Hazards
Floodplain Hydraulics
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FLOW
END-TO-END MODELLING ? Stochastic Rainfall
Simulation ? Rainfall-Runoff Modelling ? T-period
Event Modelling ? Floodplain Inundation Modelling
Runoff Generation
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Predictive Uncertainty Spatial Risk
Rainfall-Runoff
n x m runoff series
n x rainfall series
Return Period and Event modelling
Probability Analysis
Probability of Inundation
0
1
0.5
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Opportunities and Challenges

• Continuous simulation
• Non-linear rainfall-runoff due to antecedent
  conditions
• Extreme events and storm clustering
• Improved hydraulic modelling in urban areas
• Localization of risk
• Uncertainty analysis - formal tool for risk
  management
• Economic appraisal

• Computational overhead
• n x m x k simulations
• (n stochastic rainfall, m rainfall-runoff
  parameter sets, k hydraulic model parameter
  sets)
• Complex urban floodplains
• Digital city models
• Efficient hydraulic modelling

Optimal complexity modelling strategies
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Data-Poor to Data-Rich Environment

• Last 10 years witnessed whole-scale change in
  availability of topographic and hydrometric data
  to support modelling studies
• Airborne lidar
• Terrestrial lidar

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Data Reduction Simplification Lidar

• Data overload for conventional modelling (1d and
  2d) approaches
• Strip away complexity
• bare earth lidar models
• large grid resolutions

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Problems Solutions for a Data Rich Era

• Too much data to handle
• Strip away complexity bare earth lidar models,
  large grid resolutions
• Implications tolerable for rural flood prediction
  but urban topography?
• Development of data intensive models

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3d Urban Surface Models (DSMs)
BARE EARTH
VECTOR OUTLINES
BUILDING MODELS
Raw Lidar Urban Digital Surface Model
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Reduced Complexity Hydraulic Modelling

• 1D Channel Hydraulic Model
• Predicts locations of overbank spill
• FD solver for the Kinematic Wave
• 2D Raster Storage Cell Model
• Floodplain represented as a matrix of cells
• Overbank flows predicted ignoring inertial terms
  of the force balance

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End to End Flood Risk River Cam
Linton (Bartlow-Babraham)
Two historically flood susceptible reaches of the
River Cam
Cambridge City Centre (Granchester-Bottisham)
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October 21-22nd 2001
Local 18 hour totals of 118 mm 1250 properties
flood in East Anglia 72 Linton 59 Cambridge City
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Model Calibration and Validation
Gauging records, register of flooded properties
and aerial photograph of flood extent
Gauging records, flood depths levels
from post-flood survey
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Rainfall-Runoff with Uncertainty
Monte Carlo simulation provides methodology to
quantify model reliability and evaluate
performance