Transcript What are the goals? - frontpage — Mallee CMA

Risk Frontiers
Flood Hazard Data
Flood Forum Victoria
Nov 2014
About Risk Frontiers
• Risk Frontiers is an independent Research & Development
company based at Macquarie University
• Our mission is to improve the pricing of impacts of natural
perils, and decision making in respect to the management of
natural hazard risks through scientific research and analysis
• We have been working closely with the (re)insurance industry
and emergency managers since our inception in 1994
Insured cost of weather-related perils:
1967 - present
In the dollars of the day - - -
Normalised insurance costs of weatherrelated perils:
2011 societal conditions
Updated from Crompton and McAneney (2008)
Australia: Coastal Development
Gold Coast Main Beach
circa 1970
Local Studies Library, Gold Coast City Council
Gold Coast Main Beach
2003
Local Studies Library, Gold Coast City Council
NAT CAT Loss Models for Australian key perils
Event
Sydney
Hailstorm
Tropical Cyclone
Tracy
Ranking
1
2
Year
1999
1974
Normalised
cost
$4.3 Billion
$4.1 Billion
HailAUS6.1
CyclAUS3.0
Newcastle
Earthquake
3
1989
$3.2 Billion
QuakeAUS4.0
QLD Floods
5
2011
$2.5 Billion
FloodAUS3.0
Ash Wednesday
Bushfires
7
1983
$1.8 Billion
FireAUS2.0
Normalised insured losses as if all events were to impact upon 2011 societal conditions
(Source: ICA/Risk Frontiers)
Flood Modelling
Depending upon the application, areal coverage, data availability, output detail
required and budget, flood mapping can be examined at various levels:
1: Broad-scale mapping to delineate floodplains and those areas not subject to
flooding. Risk Frontiers’ Flood Exclusion Zones, FEZ, is an example of this sort
of modelling.
2: Medium-level mapping based on observed historical water levels and flows.
3: Detailed mapping with full hydrodynamic analysis. Only practical if study
area is relatively small.
Flood inundation modelling: water
depth and 2011 flood extent (Brisbane)
8
National Flood Information
Database
Data integration from two dozen sources
Flood surface
DTM
Water Depth
Maribyrnong
Release history of NFID
Version
Date
Addresses with Flood Risk Data
1
17-Dec-08
672,270
1.1
23-Dec-08
1,185,367
1.2
11-Mar-09
1,436,261
1.3
18-May-09
1,436,261
2
15-Jul-09
1,556,300
2.1
21-Dec-09
1,631,219
2.2
30-Mar-10
2,570,024
2.3
30-Jun-10
4,635,006
2.4
3-Dec-10
4,965,681
2.5
2-May-11
5,151,259
2.6
30-Sep-11
5,630,504
3
4-May-12
5,714,116
3.1
2-Oct-12
5,742,041
3.2
3-May-13
5,870,500
3.3
30-Sep-13
5,928,934
4
28-May-14
6,038,672
Validation – NFID vs 2011 Floods
Comparison between modelled flood extent in NFID (white areas) and the 2011 Brisbane
Flood inundation extent (red polygon)
Central Kempsey showing Address points over closed road regions and
FloodAUS 2001 Design flood ARI=20 yr depth map
Maitland
Gosford
FEZ: Alternative to statistical modelling
Other companies pursuing
(Statistical modelling)
FEZ™
White: modelled floodplain in FEZ
Red: PMF extent from trad. flood modelling
Evidence-based spatial integration / filtering process
Lots of attributes:
1 - Distance to river network
(at Drainage Division group level)
2 – Water depth at PMF level
(at Drainage Division group level)
3 – Same two attributes
(at catchment level)
4 – Average slopes in known flood extents
5 – River stream orders (determined from
average slopes of waterways)
6 - Distance to shoreline
Distance to river networks: comparison
Group A
Group B
Risk Selection: e.g. Bundaberg
In absence of NFID data or flood studies for Bundaberg
•
•
•
Red outline – observed flood extent from 2010-2011 flooding
Blue outline – flood-prone areas delineated by QRA flood overlay project
White area – flood-prone areas in FEZ classification
Bundaberg flooding
(imagery 29/01/2013, 50cm-resolution, Qld govt)
• Yellow – observed flood
extent
• Red – modelled flood plain in
Risk Frontiers’ Flood
Exclusion Zones (FEZ)
FEZ boundary, as a conservative
estimate, captures current flood
extent well.
FloodAUS Loss Model -- Main
Features
• Uses National Flood Information Database (NFID)
– Flood surfaces created by hydraulic engineers for state and
local governments
– High resolution address data and digital terrain model (DTM)
to assess water depth
• Claims data on residential flood damage used for deriving
vulnerabilities (Brisbane, 1974; Katherine, 1998; Central
Coast, 2007; validated against 2011 Queensland events)
• Inter-catchment correlations included from stream gauge
data
Conclusions
• Flood – equations are well known but computationally difficult and
data constrained -- need catchment scale modelling
• Insurers have a suite of tools for risk selection – FEZ, NFID and, in
some cases, in-house modelling
• Some local councils still hostile to release of data
• In case of Tweed, release of newer modelling reduced number of at
risk homes from ~16,000 to ~8,000
• Victoria – Melbourne Water and CMA have been very good at
releasing data
• Victoria – mostly the 1-in-100 extents from State Governments