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Vulnerability of Australian Houses to Riverine Inundation

Analytical and empirical vulnerability curves

GEOSCIENCE AUSTRALIA

RECORD 2017/10

M. Wehner, S. Canterford, N. Corby, M. Edwards and V. Juskevics

Department of Industry, Innovation and Science

Minister for Resources and Northern Australia: Senator the Hon Matthew Canavan

Assistant Minister for Industry, Innovation and Science: The Hon Craig Laundy MP

Secretary: Ms Glenys Beauchamp PSM

Geoscience Australia

Chief Executive Officer: Dr James Johnson

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Bibliographic reference: Wehner, M., Canterford, S., Corby, N., Edwards, M., Juskevics, V., 2017.

Vulnerability of Australian Houses to Riverine Inundation: Analytical and empirical vulnerability curves.

Record 2017/10. Geoscience Australia, Canberra.. http://dx.doi.org/10.11636/Record.2017.010

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Vulnerability of Australian Houses to Riverine Inundation iii

Contents

Executive Summary .................................................................................................................................. 1

1 Introduction ............................................................................................................................................ 2

2 Empirical source data ............................................................................................................................ 3

3 Building categorisation for vulnerability ................................................................................................. 4

4 Analytical development of vulnerability curves ...................................................................................... 9

4.1 Specification of repair work to components ..................................................................................... 9

4.2 Insurance regimes ........................................................................................................................... 9

4.3 Scale of repair .................................................................................................................................. 9

4.4 Reparation costing and vulnerability curve suite ...........................................................................10

5 Development of empirical vulnerability curves ....................................................................................11

5.1 Investigation of repair following deep inundation ...........................................................................12

6 Results .................................................................................................................................................13

7 Discussion ...........................................................................................................................................14

8 Conclusions .........................................................................................................................................15

Acknowledgements ................................................................................................................................16

References .............................................................................................................................................17

Appendix A Analytical vulnerability curves .............................................................................................18

A.1 Graphs of analytical vulnerability curves .......................................................................................18

A.2 Numerical definitions of analytical vulnerability curves .................................................................22

Appendix B Empirical vulnerability curves derived from the Brisbane-Ipswich postal survey ...............24

B.1 Graphs of empirical vulnerability curves ........................................................................................24

B.2 Scatter plots of empirical data .......................................................................................................28

B.3 Box plots of empirical data ............................................................................................................32

B.3.1 Box plots ..................................................................................................................................32

B.3.2 Numerical data describing box plots ........................................................................................36

Appendix C Empirical vulnerability curves derived from Bundaberg postal survey ...............................43

C.1 Graphs of empirical vulnerability curves .......................................................................................43

C.2 Scatter plots of empirical data .......................................................................................................46

C.3 Box plots of empirical data ............................................................................................................49

C.3.1 Box plots ..................................................................................................................................49

C.3.2 Numerical data describing box plots ........................................................................................52

Appendix D Empirical vulnerability curves derived from combined Brisbane-Ipswich and Bundaberg postal surveys ......................................................................................................................57

D.1 Graphs of empirical vulnerability curves .......................................................................................57

D.2 Scatter plots of empirical data .......................................................................................................60

D.3 Box plots of empirical data ............................................................................................................64

D.3.1 Box plots ..................................................................................................................................64

D.3.2 Numerical data describing box plots ........................................................................................67

Appendix E Example component level repair specification ....................................................................73

Vulnerability of Australian Houses to Riverine Inundation 1

Executive Summary

Vulnerability functions, that relate damage to hazard magnitude are used in risk and impact

assessments, mitigation studies and associated cost benefit analyses. The development of

vulnerability functions must address the variety of assets exposed to the hazard of interest and the

common scarcity of empirical data to calibrate any functions developed using heuristic or analytical

methods.

This record reports efforts to improve the knowledge of the vulnerability of Australian domestic

housing to riverine inundation. The research is focussed on housing types found in the south-east of

Queensland although the results can be applied to houses of similar type elsewhere in Australia.

In order to address the wide variety of housing types found in the Australian built environment, in this

research representative generic housing types are identified from surveyed building exposure.

Analytical vulnerability relationships are developed for each from assessments of repair works at

different inundation depths. Finally, the analytical vulnerability curves are compared to empirical data

derived from repair costs reported by postal surveys of dwellings affected by flooding in Brisbane-

Ipswich, January 2011, and Bundaberg, January 2013.

Analytical vulnerability curves are presented for twelve generic housing types and two insurance

regimes. The process of developing vulnerability curves analytically is compared to empirical data.

The empirical data shows that for insured houses, the analytically derived vulnerability curves provide

a reasonable estimate of direct losses. However, for uninsured houses the analytical vulnerability

curves are shown to overestimate direct losses. The difference may be due to uninsured residents

tolerating a greater level of residual damage or undertaking repairs themselves at cheaper rates than

those assumed for the analytical work.

Although the results display variability, the empirical data indicate that the presented analytical

methodology for constructing vulnerability curves yields reasonable curves that would be suitable for

modelling impact of riverine flooding on populations of houses provided that adjustments are made to

modelled losses for uninsured dwellings.

2 Vulnerability of Australian Houses to Riverine Inundation

1 Introduction

One of the methodologies used to assess risk to the built environment is the Hazard – Exposure –

Vulnerability paradigm where Hazard describes the severity and associated probability of annual

exceedance of local hazard; Exposure describes the nature (type and location) of the built

environment affected by the hazard and Vulnerability describes the susceptibility to damage of the

exposed structures. In the context of riverine inundation the hazard is expressed as maximum depth of

inundation above the lowermost habitable floor measured in metres. Vulnerability can be expressed as

a relationship between damage index and hazard magnitude where damage index is defined as the

repair cost divided by the replacement cost for an individual building.

A variety of methods have been used by previous authors to represent vulnerability curves for houses

exposed to inundation, for example: Smith (1994), Dale et al (2004), NSW Government (2007) and

Maqsood et al (2014). Some of these methods aimed to express loss as a dollar value while others

expressed loss as a Damage Index (Repair Cost divided by Replacement Cost). This work adopts the

latter definition of loss.

This record reports efforts to improve the knowledge of the vulnerability of domestic housing to riverine

inundation. The research is focussed on housing types found in the south-east of Queensland

although the results could be applied to houses of similar type elsewhere in Australia. The riverine

inundation considered is inundation by slowly rising river water where the water velocity is sufficiently

low as not to cause velocity-related damage. This represents the most common flood environment,

though some catchments may exhibit higher velocity regimes.

To address the wide variety of housing types found in the Australian built environment, representative

generic housing types are identified from surveyed exposure. Analytical vulnerability relationships are

developed from assessments of the repair works required at step-wise increasing inundation depths.

The analytical vulnerability curves are compared to empirical vulnerability results derived from repair

costs reported by postal surveys of dwellings affected by flooding in Brisbane-Ipswich, January, 2011

(Canterford et al, 2016) and in Bundaberg, January, 2013 (Canterford et al, in prep.).


2 Empirical source data

Flooding of the Bremer and Brisbane Rivers during January, 2011, affected approximately 17,100

dwellings. Following the event, Geoscience Australia led a field survey of residential building damage

in collaboration with other agencies. The survey recorded detailed information about the

characteristics of affected houses and the nature of flood damage sustained by visiting houses in a

door-to-door fashion. The survey captured data for 886 houses of which 754 were affected by riverine

inundation alone without incurring additional velocity related damage. The results of this survey were

used to develop the suite of generic house types used in this research.

Two follow-up surveys in the Brisbane-Ipswich area were undertaken in 2012 and 2013. A postal

survey was undertaken during April to June, 2012. This survey was dispatched to 5,000 dwellings

including those visited during the field survey and generated 1279 responses. The postal survey

asked questions relating to household composition, tenure, potential vulnerability, flood impacts, repair

work and funding. It also asked for the height of flood inundation above floor level and the cost

incurred in repairing damage to the dwelling and its contents. Responses to these questions provided

data to develop empirical vulnerability relationships and check the validity of curves developed by

other methods.

In order to gain some understanding of the nature of repair work following deep inundation a follow-up

survey was undertaken in February, 2013 to examine the nature of repairs to houses subjected to an

inundation depth of 2m or more.

Flooding in the Burnett and Kolan Rivers during January, 2013 affected approximately 1400 dwellings

in Bundaberg and surrounding settlements. A postal survey was undertaken during March and April,

2014. This survey was dispatched to 5,000 dwellings and generated 1288 responses. The postal

survey questions were based on the Brisbane-Ipswich postal survey but were refined and tailored to

the Bundaberg region. The Bundaberg survey population was different to the Brisbane-Ipswich survey

population in that the Bundaberg postal survey included dwellings that had not been flooded as well as

dwellings that had. The Bundaberg survey provided data that supplemented those obtained from the

Brisbane-Ipswich survey for empirical vulnerability relationship development.


3 Building categorisation for vulnerability

Typical Australian urban landscapes comprise many different types of houses. In order to provide a

reasonable estimation of risk and the variability in damage that may be expected within an affected

region, vulnerability relationships need to be developed that address the range of house types that

may be affected by inundation. This research addressed the problem by categorising surveyed houses

in the Brisbane-Ipswich area into 32 house types and then assigning each house type to one of 11

generic house types for which vulnerability relationships were developed. The survey region house

types are listed in Table 3.1 along with their frequency in the survey responses. The choice of 11

generic house types reflected a balance between containment of resources needed to develop

vulnerability relationships and the number of construction typologies encountered during the field

survey that would require distinctly different repair works after inundation. The generic house types are

listed in Table 3.2.

Table 3.1 House types identified based on constructional form and vulnerability to flood. SoG denotes Slab-on-

Grade; RF denotes Raised Floor; BV denotes Brick Veneer, CM denotes cavity masonry (or single skin block in

the instances of two storey Queenslander bottom storey infill); WB denotes WeatherBoard; RCF denotes

Reinforced Concrete Frame; PB denotes PlasterBoard; HB denotes HardBoard; Bwk denotes Brickwork.

HOUSE TYPE

NO. OF STOREYS

BOTTOM FLOOR

SYSTEM

EXTERIOR WALL TYPE

ROOF MATERIAL

INTEGRAL GARAGE

INTERNAL LINING TYPE

FREQUENCY

A 1 SoG BV Tile Yes PB 76

B 1 RF BV Tile No PB 22

C 1 RF CM Tile Yes RB 7

D 1 RF WB Tile No HB 49

E 1 RF WB Metal No HB 124

F 1 Highset WB Metal No HB 57

G 2 SoG WB Metal Yes (part) HB 39

H 2 SoG CM / WB Metal Yes PB 58

I 2 SoG CM / WB Metal No PB 24

J 2 SoG CM Tile Yes PB 81

K 2 SoG CM Fibro Yes PB 1

L 1 RF Rendered panel

Tile No HB 7

M 1 RF CM, framed internal

Tile No PB 1

N 1 RF Rendered panel

Fibro No PB 21

O 1 SoG BV Metal Yes PB 16

P 1 SoG BV Tile No PB 33

Q 1 RF WB Metal No Timber 2

R 2 SoG CM / WB Tile Yes PB 26


HOUSE TYPE

NO. OF STOREYS

BOTTOM FLOOR

SYSTEM

EXTERIOR WALL TYPE

ROOF MATERIAL

INTEGRAL GARAGE


FREQUENCY

S 2 SoG CM / WB Fibro Yes HB 1

T 2 SoG CM / panel Metal Yes HB 12

U 1 SoG CM Fibro No Bwk 5

V 2 SoG Metal / WB Metal No PB 4

W 1 SoG WB Metal No PB 10

X 1 SoG BV Metal No PB 2

Y 2 SoG Metal / WB Metal Yes HB 12

Z 2 SoG WB Metal No HB 15

ZA 1 RF WB Tile Yes PB 2

ZB 2 SoG WB Metal Yes PB 14

ZC 2 SoG RCF Metal Yes PB 5

ZD 2 SoG Panel Metal Yes PB 9

ZE 2 RF WB Metal Yes PB 15

ZF 2 SoG Panel / WB Metal No PB 4

Table 3.2 Generic house types selected for inundation damage costing. Abbreviations are the same as Table 3.1.

Type ZC is not covered by any generic house type because this is a highly variable and highly flood resistant form

of modern construction that was rarely encountered during the survey.

GENERIC HOUSE TYPE REPRESENTATIVE OF HOUSE TYPES DESCRIPTION

FCM1 ZA, N, D, F, E, L, M 1 storey, RF, WB or panel cladding, no garage, HB lining

FCM2 Q 1 storey, RF, WB or panel cladding, no garage, timber lining

FCM3 J, Z, ZF, V, ZD, I 2 storey, SoG, CM lower storey, WB upper storey, metal roof, no garage, PB

lining

FCM4 K, T, Y, H, R, S, ZB 2 storey, SoG, CM lower storey, WB upper storey, metal roof, garage, PB

lining

FCM5 G 2 storey, SoG, WB cladding, partial lower floor, PB lining

FCM6 ZE 2 storey, RF, WB cladding, no garage, PB lining

FCM7 A 1 storey, SoG, BV, garage, PB lining

FCM8 X, P, O, W 1 storey, SoG, BV, no garage, PB lining

FCM9 B 1 storey, RF, BV, no garage, PB lining

FCM10 U 1 storey, SoG, CM, no garage

FCM11 C 1 storey, RF, CM, no garage

The later Bundaberg survey encountered five types of houses not covered by the generic house types

in Table 3.2. However, these were not very common and hence no new generic house types were

developed as a result of the Bundaberg survey. The new types of houses encountered are listed in


Table 3.3. The Bundaberg survey form contained more questions relating to the nature of the

construction of the respondent’s house than the Brisbane-Ipswich survey form. The additional

exposure data obtained improved the classification of dwellings into the generic house types.

Table 3.3 House types encountered in Bundaberg that differed from the eleven generic house types developed

from the Brisbane-Ipswich surveys. Abbreviations as for Table 3.1.

HOUSE TYPE

NO. OF STOREYS

BOTTOM FLOOR

SYSTEM

EXTERIOR WALL TYPE

ROOF MATERIAL

INTEGRAL GARAGE


FREQUENCY

BB1 2 SoG BV / BV Tile Yes PB 4

BB2 1 SoG WB Metal Yes PB 11

BB3 2 SoG WB / WB Metal Yes PB 17

BB4 2 SoG CM / BV Tile Yes Bwk / PB 3

BB5 2 RF BV / BV Tile No PB 3

Figure 3.1 to Figure 3.3 show the mix of generic house types between the Brisbane-Ipswich and

Bundaberg surveys. It is noted that the Brisbane-Ipswich urban landscape has a greater proportion of

two storey houses than Bundaberg.

Figure 3.1 Proportion of ‘Insured’ postal survey responses by generic house type.


Figure 3.2 Proportion of ‘Uninsured’ postal survey responses by generic house type.

Figure 3.3 Proportion of all postal survey responses by generic house type.

Table 3.4 shows the proportion of postal survey responses binned by the proportion of the

respondent’s repair bill that was funded by insurance. The proportion of inundated houses that held

full flood insurance was much higher in Bundaberg than in Brisbane – Ipswich. Furthermore the

proportion of inundated houses whose repair was partly funded by insurance was lower in Bundaberg

than in Brisbane – Ipswich. These figures suggest that some of the uncertainty that existed after the

Brisbane – Ipswich floods concerning what was covered by insurance had been resolved by the time

of the Bundaberg flood.


Table 3.4 Proportion of postal survey responses by insurance funding of repairs.

Proportion of repair bill funded by insurance (%)

0 - 10 11 – 20 21 - 30 31 - 40 41 - 50 51 - 60 61 - 70 71 - 80 81 - 90 91 - 100

Brisbane - Ipswich

0.499 0.012 0.009 0.009 0.029 0.004 0.009 0.053 0.036 0.340

Bundaberg 0.199 0.000 0.004 0.008 0.012 0.004 0.000 0.012 0.033 0.728


4 Analytical development of vulnerability curves

For each generic house type, detailed plans of an example house were prepared and the building

fabric was divided into components such as substructure, floor covering, light switches, window

dressing, ceilings, etc. The number of components per house varied from 62 to 107 depending on the

generic house type. For each component of each generic house type, at each of ten inundation

depths, repair work was identified. Costing was then based on a detailed break-down of building work.

Different repair strategies were identified for when the house was insured and for when it was not, to

capture the difference in the behaviour of uninsured owners attempting to minimise reparation costs. A

total of 15,980 individual repairs that required costing were identified. Some of the repairs were ‘Nil’

when a particular inundation depth did not affect a particular component and others were duplicates of

that required for shallower depths of inundation. Once a component had been inundated, the required

repair tended to remain the same for deeper depths of inundation. An example of repair specifications

for one generic house type is provided in Appendix E.

4.1 Specification of repair work to components

The development of repair strategies for a particular component / inundation depth / insurance

combination was informed by a literature review (Growth Management Queensland, 2011;

Hawkesbury-Nepean Floodplain Management Steering Committee, 2006; Queensland Government

Natural Resources and Mines, 2002; Timber Queensland, 2011), by observations made during the

post-flood surveys and the engineering experience of the authors. All the repair strategies assumed

that efforts are made to expose the wetted structure to drying soon after the water had receded. This

is broadly representative of the actions observed during post-flood field survey activity. Hence no

requirement for replacement of structural timber has been included in the repair strategies.

4.2 Insurance regimes

For each generic house type two insurance regimes were considered as referred to earlier:

1. Fully insured where it is assumed that the owner’s insurance covers full repair of all items to an as-

new condition either through cleaning and reinstatement or removal and replacement.

2. Uninsured where it is assumed that the owner undertakes minor works such as cleaning and

accepts non-repair of some items with minor damage in order to constrain the repair costs to a

minimum.

In practice the analytical vulnerability curves for the two insurance regimes for a single generic house

type show only a small difference as flooding renders most components unusable and requiring

replacement whether insured or not, for example, plasterboard, electrical equipment and cabinetry.

4.3 Scale of repair

The scale of repair work to each component reflected the extent of work required to repair the damage

caused by the level of inundation under consideration. This was not necessarily limited to the wetted


portion. For example, half the height of wall lining requires replacement for inundation depths ranging

from 0.1m to 1.2m and at greater depths the full height of wall lining requires replacement.

4.4 Reparation costing and vulnerability curve suite

Costing of building replacement value and repair work to enable the calculation of damage indices

was undertaken by a professional Quantity Surveyor (Turner and Townsend, 2011). For a given

generic house type and inundation depth, the repair cost was calculated by summing the repair cost to

all components for that inundation depth and non-dimensionalised by dividing the repair cost by the

replacement cost for the house to produce a Damage Index. The Damage Index was plotted against

inundation depth to produce a Vulnerability Curve or Stage Damage Function. An example of

analytical vulnerability curves produced by the above process is presented in Figure 4.1. Graphs of

the vulnerability curves for all the generic house types are presented in Appendix A.1. Numerical

values describing the vulnerability curves for all generic house types are tabulated in Appendix A.2.

The “curves” display the typical stepped nature of flood damage functions resulting from an

incremental increase in required reparation work as the water level steadily increases. For example,

the required amount of interior wall lining repair remains the same whether the depth of inundation is

0.1m or 1.1m above floor level; it is not until the water level rises above half the wall height that the

amount of required repair increases to the full height of wall lining. The damage index does not rise to

1.0 because certain structural elements of the house such as foundations and structural framing can

be retained, irrespective of inundation depth, after drying. The vulnerability curves present the

expected damage for a population of similar houses. Within the population there will be some variation

in repair costs arising from:

the variety of housing represented by the generic house type;

the variety of repair work required to a single house type;

the variation in what building owners are prepared to retain following inundation, particularly for the

uninsured case. For example, one person may require the complete replacement of an internal

door which has had a small height of wetting at its base whilst another may regard the slightly

damaged door as acceptable.

The analytical vulnerability curves assume that the repairing builder is repairing a single house. In

major floods a single builder may repair several houses in close proximity leading to repair cost

economies of scale and a lower Damage Index.

Figure 4.1 Example analytical vulnerability curve for a single storey weatherboard clad dwelling with a timber floor raised off the ground on stumps.


5 Development of empirical vulnerability curves

Empirical damage indices were derived from data gathered via postal surveys of flood affected

dwellings. Amongst many other questions, the surveys requested home owners to nominate the depth

of inundation within their home, the cost to repair the flood damage to the building fabric and the

source of repair funds.

For homes from which a postal survey return was received, the house was assigned to a generic

house type based on aerial and street view imagery and, in the case of the Bundaberg survey,

responses to questions about the nature of the respondent’s dwelling construction. Some returns were

not useful for the analysis due to missing data or an inability to assign a generic house type. The

number of useful returns by generic house type is presented in Table 5.1. It was deemed that

sufficient returns were received from the Brisbane-Ipswich survey for generic house types FCM1,

FCM3, FCM4, FCM5, FCM7 and FCM8 to warrant analysis, and, from the Bundaberg survey for

generic house types FCM1, FCM2, FCM4, FCM7 and FCM8 to warrant analysis. Hence FCM6 and

FCM9 to FCM11 were not analysed further.

Table 5.1 Postal survey responses received by generic house type.

Generic house type

FCM1 FCM2 FCM3 FCM4 FCM5 FCM6 FCM7 FCM8 FCM9 FCM10 FCM11

Number of postal

returns – Brisbane –

Ipswich survey

245 0 121 218 61 23 118 86 21 2 3

Number of postal

returns – Bundaberg

survey

74 26 10 18 2 2 52 41 11 12 1

The postal survey data was transformed into empirical vulnerability data as follows:

1. The Repair Cost was taken directly from the survey returns. Where the respondent did not respond

to the repair cost question, the return was discarded for the purposes of this study.

2. The Replacement Cost was calculated as follows:

a. The roof area was determined by drawing a polygon around the house’s roof in aerial imagery

and calculating the area and perimeter;

b. Deductions were made for eave width and extent (determined by visual assessment from street

view imagery), exterior wall thickness, and verandas;

c. Additions were made for multiple storeys including upper storeys that were smaller than lower

storeys;

d. The resulting total Gross Floor Area (GFA) was multiplied by a rate per square metre

appropriate to the relevant generic house type obtained from Turner & Townsend (2011).

3. A Damage Index was calculated for each house by dividing the Repair Cost by the Replacement

Cost.


4. Each home was flagged as ‘Insured’ or’ Uninsured’ based on the proportion of repair cost that was

sourced from insurance: greater than 50% sourced from insurance was deemed ‘Insured’,

otherwise the house was deemed ‘Uninsured’.

5. The resulting data was plotted against inundation depth above floor level.

Note that by this methodology it is possible to obtain damage indices greater than unity. This is

interpreted as a misinterpretation of the Replacement Cost due to one or more of the following causes:

Physical nature of the house changing between the date of the aerial imagery used for determining

the house plan area and the time of the flood. The house may have been extended or replaced

with a larger house leading to an underestimate of the GFA and hence replacement cost;

Use of an inappropriate replacement rate to calculate the replacement cost. The replacement rates

provided by Turner and Townsend (2011) are for medium standard of internal finish. Thus if they

are applied to a house with a basic standard or a prestige standard of internal finish the

replacement cost will be over or underestimated respectively.

5.1 Investigation of repair following deep inundation

To investigate the nature of repair work following deep inundation, a follow-up survey was conducted

during February, 2013 whereby residences subjected to 2m or deeper inundation above floor level

were visually assessed from the street as to the nature of the repair work. The survey assessed 850

addresses. The results of the follow-up survey are presented in Figure 5.1. Houses which had been

reconstructed or the land resumed were assigned a damage index of 1.0. It can be seen that the

majority of inundated residences were repaired like for like, although the visual survey from the street

could not identify if more resilient materials had been employed in the repair.

Figure 5.1 Proportion of surveyed houses by repair strategy following 2m or greater inundation over floor level.


6 Results

Results from the Brisbane-Ipswich and Bundaberg postal surveys are presented in Appendix B and

Appendix C respectively. For each generic house type for which sufficient results were obtained to

warrant analysis, results were binned into one of ten inundation depth bins. For each survey the

following results are presented for the generic house types where sufficient returns were received to

warrant analysis:

empirical vulnerability curves consisting of average damage index at each inundation depth bin;

scatter plots of calculated damage index against inundation depth;

box plots describing the variability of damage index against inundation depth by bin;

numerical descriptors defining the box plots.

Statistical analysis indicated that the Brisbane-Ipswich and Bundaberg postal survey results were

obtained from similar populations. Hence the results from both postal surveys were combined and re-

analysed. The empirical vulnerability data for the combined survey results are presented in Appendix

D.


7 Discussion

The large scatter of results within a generic house type is expected of flood vulnerability. This may be

due to:

a generic house type representing an array of different, although broadly similar, houses;

a range of repairs undertaken for similar inundation depths. This is particularly so for the uninsured

case where households did not have sufficient resources to undertake full repair work. This is

qualitatively evidenced by some of the postal survey responses where households have reported

living in incompletely repaired dwellings, or in a number of instances, are still living away from

damaged houses;

a range of internal finish and fit-out qualities within a single generic house type.

The box plots give some guidance to the range of damage indices that may be expected when

modelling flood risk and impact.

Typically the analytical vulnerability curve for the uninsured single storey generic house types

overestimates the damage index compared to the empirical data. This may indicate that the level of

damage which an uninsured house owner may deem acceptable for occupation was underestimated

during the process of constructing the analytical vulnerability curves. It may also indicate repairs

undertaken more cheaply or incompletely, possibly by the home owner. Factoring the losses modelled

using the analytical vulnerability functions for uninsured dwellings was explored and multiplication

factors are presented in Table 7.1 that adjust the analytical vulnerability functions to match the

empirical data. The factors greater than unity reflect the issue discussed below regarding the

construction and usage of the lower storey of two storey houses.

Table 7.1 Factors that adjust losses for uninsured dwellings derived from the analytical functions to match

empirical data.

Generic house type

FCM1 FCM2 FCM3 FCM4 FCM5 FCM7 FCM8

Factor 0.55 0.3 1.0 1.7 2.0 0.7 0.66

The analytical vulnerability curves for two storey insured dwellings underestimate the damage index at

depths of inundation below the upper storey, as shown in Appendix Figure D.5. This indicates that the

type of lower storey construction (masonry walls) and lower storey usage adopted for the generic

house type does not accurately represent the variety of lower storey construction found in the building

population.

For some generic house types, the empirical data shows a slight peak in damage index at depths of

inundation around 0.3m as shown in Appendix Figure D.3. This is contrary to the intuitive expectation

that cost of repair will rise continuously with increasing inundation depth. This characteristic of the data

may be due to an extent of repair phenomena whereby more competitive rates are achieved for larger

scopes of repair work at deeper depths of inundation.


8 Conclusions

Analytical vulnerability curves are presented for eleven generic house types representative of housing

stock in south-east Queensland. Curves for seven of the generic house types are compared to

empirical values obtained from postal survey data. Although the results display a variability, the

empirical data indicates that the presented analytical methodology for constructing vulnerability curves

yields reasonable curves for insured dwellings that would be suitable for modelling the impact of

riverine flooding on the built environment. Adjustment is required to modelled losses for uninsured

dwellings to modify the analytical vulnerability functions to more closely match the empirical data. The

adjustment factor for each generic house type varied between 0.3 and 2.0 thereby highlighting the

challenge of establishing a general approach for doing so.


Acknowledgements

The authors acknowledge the generosity of the residents of Brisbane, Ipswich and the Bundaberg

region who made their time available to answer questions during the surveys and, on occasion,

permitted access into their homes.

The authors acknowledge the collaborative contributions of the National Institute for Water and

Atmospheric Science in New Zealand for their field survey support following the Brisbane floods.


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Melbourne, Australia.

Growth Management Queensland, 2011. Repairing your house after a flood.

Hawkesbury-Nepean Floodplain Management Steering Committee, 2006. Reducing Vulnerability of

Buildings to Flood Damage.

Maqsood, T., Wehner, M., Ryu, H., Edwards, M., Dale, K. and Miller, V.. 2014. GAR15 Vulnerability

Functions: Reporting on the UNISDR/GA SE Asian Regional Workshop on Structural Vulnerability

Models for the GAR Global Risk Assessment, 11-14 November, 2013, Geoscience Australia,

Canberra, Australia. Record 2014/38. Geoscience Australia. Canberra.

http://dx.doi.org.11636/Record.2014.038

NSW Government, 2005. Floodplain Development Manual; the management of flood liable land.

NSW Government Department of Environment and Climate Change, 2007. Floodplain Risk

Management Guideline – Residential Flood Damages.

Queensland Government Natural Resources and Mines, 2002. Guidance on the Assessment of

Tangible Flood Damages.

Smith, D.I., 1994. Flood damage estimation – a review of urban stage damage curves and loss

functions. Water SA. 20(3), 231 – 238.

Timber Queensland, 2011. Guide to Assessment and Repair of Flood Damaged Timber and Timber

Framed Houses.

Turner & Townsend, 2011. Flood Damage Cost Module Development for Various Residential House

Types. Report prepared for Geoscience Australia

http://dx.doi.org/10.11636/Record.2016.030


Appendix A Analytical vulnerability curves

A.1 Graphs of analytical vulnerability curves

Appendix Figure A.1 Analytical vulnerability curves for generic house type FCM1.



A.2 Numerical definitions of analytical vulnerability curves

Appendix Table 1 Numerical definition for vulnerability curves for ‘Insured’ insurance regime by generic house

type.

Inundation depth (m)


-0.3 0.03 0.03 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00

0.0 0.06 0.06 0.00 0.00 0.00 0.05 0.03 0.02 0.04 0.02 0.03

0.1 0.33 0.33 0.09 0.07 0.04 0.27 0.39 0.42 0.40 0.31 0.34

0.3 0.38 0.38 0.14 0.08 0.05 0.32 0.43 0.46 0.43 0.35 0.37

0.5 0.38 0.38 0.14 0.09 0.05 0.32 0.43 0.46 0.43 0.35 0.37

1.0 0.42 0.42 0.18 0.12 0.06 0.35 0.47 0.50 0.47 0.39 0.40

1.5 0.58 0.59 0.20 0.13 0.09 0.63 0.65 0.61 0.45 0.46

2.0 0.59 0.60 0.22 0.14 0.09 0.47 0.66 0.68 0.63 0.47 0.48

2.4 0.12 0.53

2.5 0.67 0.67 0.80 0.82 0.75 0.59 0.58

2.7 0.27 0.18

2.8 0.36 0.69

3.0 0.78 0.80 0.39 0.69 0.87 0.92 0.84 0.68 0.64

3.1 0.47 0.39

3.3 0.50 0.41

4.0 0.60 0.51 0.52 0.74

5.1 0.66 0.81

5.4 0.68 0.61

Appendix Table 2 Numerical definition for vulnerability curves for ‘Uninsured’ insurance regime by generic house

type.



-0.3 0.02 0.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

0.0 0.03 0.03 0.00 0.00 0.00 0.03 0.03 0.02 0.04 0.02 0.03

0.1 0.18 0.19 0.05 0.03 0.04 0.13 0.19 0.20 0.27 0.19 0.24

0.3 0.32 0.32 0.10 0.05 0.05 0.26 0.38 0.40 0.43 0.31 0.33

0.5 0.33 0.33 0.10 0.05 0.05 0.26 0.38 0.40 0.43 0.31 0.33

1.0 0.38 0.39 0.16 0.09 0.06 0.32 0.42 0.44 0.46 0.34 0.36

1.5 0.56 0.57 0.17 0.10 0.09 0.58 0.60 0.60 0.40 0.41

2.0 0.57 0.58 0.18 0.10 0.09 0.46 0.60 0.62 0.62 0.42 0.43

2.4 0.12 0.50

2.5 0.61 0.62 0.74 0.76 0.75 0.54 0.54

2.7 0.24 0.15

2.8 0.24 0.62




3.0 0.72 0.74 0.35 0.63 0.76 0.85 0.82 0.62 0.56

3.1 0.34 0.23

3.3 0.40 0.32

4.0 0.53 0.45 0.48 0.68

5.1 0.57 0.75

5.4 0.59 0.52


Appendix B Empirical vulnerability curves derived from the Brisbane-Ipswich postal survey

B.1 Graphs of empirical vulnerability curves

The graphs below show the empirical vulnerability curves derived from the Brisbane-Ipswich postal

survey data in blue. For comparison purposes, the analytical vulnerability curves are shown in red.

Appendix Figure B.1 Empirical vulnerability curves for generic house type FCM1, Insured.

Appendix Figure B.2 Empirical vulnerability curves for generic house type FCM1, Uninsured.



B.2 Scatter plots of empirical data

The graphs below present the individual Brisbane-Ipswich survey responses plotted as blue dots. The

analytical vulnerability curve for the generic house type in question is plotted as a red line.

Appendix Figure B.13 Scatter plot of postal survey data for generic house type FCM1, Insured.

Appendix Figure B.14 Scatter plot of postal survey data for generic house type FCM1, Uninsured.



B.3 Box plots of empirical data

B.3.1 Box plots

The graphs below present the Brisbane - Ipswich survey responses as box plots. The survey

responses were binned into inundation depth bins defined in Appendix Table 3. The thick black bars

on each box denote the 25th

percentile, median and 75th percentile. The lower and upper whiskers

denote the minimum and maximum values respectively.

Appendix Table 3 Definition of inundation depth bins.

Inundation depth bin number

Lower limit of inundation depth (m)

Upper limit of inundation depth (m)

Inundation depth at which box is plotted (m)

1 -10.0 0.00 -0.1

2 0.001 0.40 0.2

3 0.401 0.75 0.575

4 0.751 1.25 1.0

5 1.251 1.75 1.5

6 1.751 2.25 2.0

7 2.251 3.25 2.7

8 3.251 20 3.5


Appendix Figure B.25 Box plot of Brisbane-Ipswich survey results for generic house type FCM1, Insured.

Appendix Figure B.26 Box plot of Brisbane-Ipswich survey results for generic house type FCM1, Uninsured.






B.3.2 Numerical data describing box plots

The tables below present the numerical data that define the box plots presented in Section B.3.1.


Appendix Table 4 Box plot data for Brisbane-Ipswich survey results for generic house type FCM1, Insured.

Inundation depth bin

1 2 3 4 5 6 7 8

Minimum value

0.0104 0.0058 0.0789 0.0120 0.0460 0.0006 0.1956 0.2950

25th percentile

0.0216 0.2878 0.2183 0.1869 0.1401 0.1581 0.3487 0.5286

Median 0.0351 0.3806 0.3723 0.3288 0.3324 0.4700 0.3914 0.6906

75th percentile

0.0402 0.4058 0.4597 0.4095 0.5336 0.6731 0.6549 0.7994

Maximum value

0.0489 1.0935 0.6594 0.6291 0.9778 1.0038 1.6864 1.4844

Mean 0.0311 0.3833 0.3435 0.3142 0.3820 0.4516 0.5842 0.7134

Standard deviation

0.0138 0.2824 0.1616 0.1726 0.2587 0.3239 0.4032 0.2923

Number of responses

7 11 17 17 17 22 17 14

Appendix Table 5 Box plot data for Brisbane-Ipswich survey results for generic house type FCM1, Uninsured.


1 2 3 4 5 6 7 8

Minimum value

0.0006 0.0032 0.0121 0.0342 0.0093 0.0744 0.0027 0.0003

25th percentile

0.0016 0.0101 0.0558 0.0843 0.0738 0.1584 0.2132 0.2183

Median 0.0026 0.0219 0.2143 0.1990 0.1119 0.2891 0.2735 0.3870

75th percentile

0.0080 0.0651 0.3303 0.2498 0.3580 0.3875 0.4647 0.7960

Maximum value

0.0809 0.5365 1.1781 0.4646 0.5353 1.5682 1.1142 1.8769

Mean 0.0148 0.1204 0.3009 0.1872 0.2056 0.3779 0.3701 0.5809

Standard deviation

0.0293 0.2060 0.3488 0.1191 0.1787 0.3499 0.2957 0.5301

Number of responses

7 10 18 15 15 20 24 29



1 2 3 4 5 6 7 8

Minimum value

0.0016 0.0550 0.0599 0.1122 0.0583 0.1285 0.0943

25th percentile

0.0198 0.1206 0.0646 0.1593 0.1855 0.2046 0.2756

Median 0.1663 0.2168 0.0841 0.2373 0.2470 0.2848 0.6235



1 2 3 4 5 6 7 8

75th percentile

0.1735 0.2497 0.3125 0.4337 0.3690 0.3936 0.9211

Maximum value

1.5330 0.3000 0.3512 0.7203 0.4775 1.7112 0.9516

Mean 0.2982 0.1875 0.1745 0.3326 0.2777 0.3852 0.5732

Standard deviation

0.5502 0.0970 0.1446 0.2491 0.1381 0.3426 0.4254

Number of responses

0 7 7 5 5 11 22 4



1 2 3 4 5 6 7 8

Minimum value

0.0046 0.0049 0.0327 0.0701 0.0162 0.0773 0.2039

25th percentile

0.0137 0.0312 0.0961 0.1227 0.0729 0.1792 0.2416

Median 0.0822 0.0972 0.1841 0.1264 0.1675 0.2581 0.3111

75th percentile

0.2001 0.1899 0.3035 0.1660 0.1920 0.4500 0.3677

Maximum value

0.2262 0.3865 0.3429 0.1870 0.3127 0.8023 0.5264

Mean 0.1031 0.1365 0.1941 0.1373 0.1477 0.3154 0.3262

Standard deviation

0.0941 0.1282 0.1280 0.0409 0.0908 0.2153 0.1185

Number of responses

0 8 10 7 7 10 16 6



1 2 3 4 5 6 7 8

Minimum value

0.0000 0.0367 0.0461 0.0875 0.0040 0.0185 0.0286 0.1395

25th percentile

0.0000 0.1081 0.1398 0.2242 0.1196 0.1194 0.1889 0.4118

Median 0.0000 0.1384 0.2180 0.2610 0.1736 0.2052 0.2856 0.5214

75th percentile

0.0000 0.2954 0.3636 0.2867 0.4059 0.3301 0.3703 0.7631

Maximum value

0.0000 0.6369 1.5683 1.6110 0.7796 0.7968 0.7240 1.2049

Mean 0.0000 0.2221 0.3361 0.3556 0.2611 0.2562 0.3125 0.5857

Standard deviation

0.0000 0.1822 0.3702 0.3899 0.2130 0.2149 0.1857 0.2737



1 2 3 4 5 6 7 8

Number of responses

0 11 17 13 17 11 17 14



1 2 3 4 5 6 7 8

Minimum value

0.0000 0.0001 0.0202 0.0116 0.0222 0.0089 0.0132 0.1015

25th percentile

0.0000 0.0079 0.0846 0.0640 0.1256 0.0621 0.0463 0.2230

Median 0.0000 0.0464 0.1152 0.1008 0.1691 0.0889 0.2006 0.2680

75th percentile

0.0000 0.1609 0.2603 0.1599 0.2579 0.2064 0.3574 0.3871

Maximum value

0.0000 0.4718 0.3388 0.2822 0.9484 0.4391 0.6067 0.5223

Mean 0.0000 0.1177 0.1551 0.1166 0.2038 0.1379 0.2141 0.2934

Standard deviation

0.0000 0.1458 0.1031 0.0768 0.1926 0.1059 0.1767 0.1336

Number of responses

0 16 19 19 20 18 20 14



1 2 3 4 5 6 7 8

Minimum value

0.2128 0.0041 0.0026 0.0465 0.1166 0.3265

25th percentile

0.2128 0.0041 0.0645 0.1479 0.3139 0.6692

Median 0.2128 0.0041 0.2150 0.1891 0.3480 0.7965

75th percentile

0.2128 0.0041 0.3213 0.2172 0.4833 0.8572

Maximum value

0.2128 0.0041 1.8393 0.8124 0.6912 1.0000

Mean 0.2128 0.0041 0.3281 0.2570 0.3929 0.7299

Standard deviation

0.4997 0.2324 0.1819 0.2857

Number of responses

0 1 1 12 11 7 0 4




1 2 3 4 5 6 7 8

Minimum value

0.0146 0.0030 0.0073 0.0010 0.1489

25th percentile

0.0146 0.0168 0.0851 0.0147 0.3586

Median 0.0146 0.0638 0.0984 0.1610 0.4470

75th percentile

0.0146 0.2032 0.1897 0.2198 0.4674

Maximum value

0.0146 0.3946 0.8878 0.4070 0.6773

Mean 0.0146 0.1288 0.2204 0.1579 0.4198

Standard deviation

0.1654 0.3018 0.1454 0.1913

Number of responses

0 1 0 7 7 12 0 5



1 2 3 4 5 6 7 8

Minimum value

0.0707 0.1154 0.0433 0.5667 0.3775 0.3667 0.9349

25th percentile

0.1839 0.1829 0.2673 0.5771 0.5187 0.4390 0.9349

Median 0.2712 0.2937 0.3698 0.6909 0.6489 0.6109 0.9349

75th percentile

0.4042 0.3702 0.3920 0.8083 0.6646 0.8166 0.9349

Maximum value

0.6547 0.6523 0.6314 0.8297 0.9238 1.0245 0.9349

Mean 0.3169 0.3008 0.3375 0.6945 0.6167 0.6459 0.9349

Standard deviation

0.2475 0.1432 0.1414 0.1402 0.1717 0.2476

Number of responses

0 4 13 16 4 7 9 1



1 2 3 4 5 6 7 8

Minimum value

0.0622 0.0866 0.0891 0.2217 0.1121 0.2774 0.3079

25th percentile

0.1060 0.2377 0.1851 0.3071 0.3004 0.3402 0.5149

Median 0.1247 0.3179 0.2899 0.3929 0.3405 0.4241 0.7218



1 2 3 4 5 6 7 8

75th percentile

0.1974 0.3280 0.3860 0.4137 0.6192 0.6384 0.9287

Maximum value

0.4032 0.6343 0.6238 0.5750 1.0000 0.7404 1.1356

Mean 0.1787 0.3094 0.3092 0.3803 0.4438 0.4752 0.7218

Standard deviation

0.1526 0.1530 0.1494 0.1220 0.2834 0.1591 0.5853

Number of responses

0 4 9 16 6 9 18 2



1 2 3 4 5 6 7 8

Minimum value

0.0651 0.3614 0.1664 0.1492 0.2891 0.9448 0.3399

25th percentile

0.0834 0.4884 0.3846 0.5382 0.4296 0.9724 0.6544

Median 0.1017 0.6153 0.4904 0.5855 0.5488 1.0000 0.7067

75th percentile

0.5140 0.7423 0.9420 0.7513 0.7594 1.0812 0.8548

Maximum value

0.9263 0.8693 1.2262 1.1552 1.0000 1.1624 0.9113

Mean 0.3644 0.6153 0.6359 0.6359 0.6017 1.0357 0.7010

Standard deviation

0.4870 0.3592 0.4189 0.3647 0.2519 0.1131 0.2096

Number of responses

0 3 2 6 5 8 3 6



1 2 3 4 5 6 7 8

Minimum value

0.1557 0.1560 0.1839 0.0844 0.0822 0.1850 0.1680

25th percentile

0.1695 0.2212 0.2039 0.3620 0.3039 0.4337 0.2502

Median 0.1832 0.2766 0.3113 0.4525 0.4765 0.5198 0.3438

75th percentile

0.1969 0.3125 0.5039 0.5818 0.6126 0.6719 0.4279

Maximum value

0.2106 0.3963 0.6149 0.6806 1.2559 1.0000 0.4817

Mean 0.1832 0.2709 0.3596 0.4358 0.5146 0.5634 0.3343

Standard deviation

0.0388 0.0802 0.1859 0.1968 0.3135 0.2756 0.1394



1 2 3 4 5 6 7 8

Number of responses

0 2 7 6 8 11 12 4


Appendix C Empirical vulnerability curves derived from Bundaberg postal survey

C.1 Graphs of empirical vulnerability curves

The graphs below show the empirical vulnerability curves derived from the Bundaberg postal survey

data in blue. For comparison purposes, the vulnerability curves derived from the Brisbane-Ipswich

postal survey data are shown in purple and the analytical vulnerability curves are shown in red.

Appendix Figure C.1 Empirical vulnerability curves for generic house type FCM1, Insured.

Appendix Figure C.2 Empirical vulnerability curves for generic house type FCM1, Uninsured.



C.2 Scatter plots of empirical data

The graphs below present the individual Bundaberg survey responses plotted as blue dots. The

analytical vulnerability curve for the generic house type in question is plotted as a red line.

Appendix Figure C.10 Scatter plot of postal survey data for generic house type FCM1, Insured.

Appendix Figure C.11 Scatter plot of postal survey data for generic house type FCM1, Uninsured.



C.3 Box plots of empirical data

C.3.1 Box plots

The graphs below present the Bundaberg survey responses as box plots. The survey responses were

binned into inundation depth bins defined in Appendix Table 16. The thick black bars on each box

denote the 25th

percentile, median and 75th percentile. The upper and lower whiskers denote the

minimum and maximum values respectively.






1 -10.0 0.00 -0.1

2 0.001 0.40 0.2

3 0.401 0.75 0.575

4 0.751 1.25 1.0

5 1.251 1.75 1.5

6 1.751 2.25 2.0

7 2.251 3.25 2.7

8 3.251 20 3.5


Appendix Figure C.19 Box plot of Bundaberg survey results for generic house type FCM1, Insured.

Appendix Figure C.20 Box plot of Bundaberg survey results for generic house type FCM1, Uninsured.






C.3.2 Numerical data describing box plots

The tables below present the numerical data that define the box plots presented in Section C.3.1.


Appendix Table 17 Box plot data for Bundaberg survey results for generic house type FCM1, Insured.


1 2 3 4 5 6 7 8

Minimum value

0.0002 0.0385 0.0434 0.0324 0.2863 0.1069 0.3877 0.5384

25th percentile

0.0177 0.1611 0.3573 0.4598 0.3385 0.5147 0.4072 0.5384

Median 0.0352 0.2567 0.3919 0.5206 0.4645 0.6762 0.4193 0.5384

75th percentile

0.0526 0.3695 0.5993 0.5855 0.6018 0.8043 0.4920 0.5384

Maximum value

0.0701 1.1405 1.1104 1.0848 0.6879 0.9546 0.6938 0.5384

Mean 0.0352 0.3218 0.4774 0.5327 0.4758 0.6116 0.4800 0.5384

Standard deviation

0.0494 0.3012 0.2750 0.2808 0.1869 0.2718 0.1434 0.0000

Number of responses

2 11 14 15 4 9 4 1

Appendix Table 18 Box plot data for Bundaberg survey results for generic house type FCM1, Uninsured.


1 2 3 4 5 6 7 8

Minimum value

0.0018 0.0121 0.1115 0.0349 0.2686

25th percentile

0.0147 0.0392 0.1115 0.0628 0.2686

Median 0.0161 0.0663 0.1115 0.0907 0.2686

75th percentile

0.0730 0.0750 0.1115 0.1186 0.2686

Maximum value

1.1512 0.0838 0.1115 0.1465 0.2686

Mean 0.1921 0.0541 0.1115 0.0907 0.2686

Standard deviation

0.4240 0.0374 0.0000 0.0789 0.0000

Number of responses

0 7 3 1 2 0 1 0



1 2 3 4 5 6 7 8

Minimum value

0.0375 0.2892 0.0952 0.5338 0.5142 0.8585

25th percentile

0.0489 0.3610 0.3261 0.5953 0.5142 0.9557

Median 0.2781 0.4074 0.5570 0.6568 0.5142 1.0529



1 2 3 4 5 6 7 8

75th percentile

0.4673 0.4743 0.7880 0.7183 0.5142 1.1501

Maximum value

0.6814 0.6074 1.0189 0.7798 0.5142 1.2474

Mean 0.3026 0.4279 0.5570 0.6568 0.5142 1.0529

Standard deviation

0.2765 0.1333 0.6532 0.1740 0.2750

Number of responses

0 5 4 2 2 1 2 0



1 2 3 4 5 6 7 8

Minimum value

0.0237 0.0058 0.0450 0.0985 0.1988 0.3455

25th percentile

0.0237 0.0079 0.0564 0.0985 0.2186 0.3455

Median 0.0237 0.0727 0.0678 0.0985 0.2383 0.3455

75th percentile

0.0237 0.1532 0.0791 0.0985 0.2581 0.3455

Maximum value

0.0237 0.3258 0.0905 0.0985 0.2779 0.3455

Mean 0.0237 0.1131 0.0678 0.0985 0.2383 0.3455

Standard deviation

0.1333 0.0321 0.0559

Number of responses

1 5 2 1 2 1



1 2 3 4 5 6 7 8

Minimum value

0.0324 0.0194 0.3329 0.0907 0.5134 0.0268

25th percentile

0.0489 0.1519 0.3410 0.2341 0.5318 0.0855

Median 0.0654 0.2844 0.3491 0.3775 0.5502 0.1442

75th percentile

0.0820 0.4828 0.5405 0.5819 0.5686 0.2029

Maximum value

0.0985 0.6813 0.7320 0.7863 0.5870 0.2616

Mean 0.0654 0.3284 0.4713 0.4182 0.5502 0.1442

Standard deviation

0.0468 0.3331 0.2259 0.3496 0.0521 0.1660



1 2 3 4 5 6 7 8

Number of responses

0 2 3 3 3 2 2 0



1 2 3 4 5 6 7 8

Minimum value

0.1295 0.0622 0.3045 0.2868 0.4344

25th percentile

0.3477 0.3626 0.4875 0.5839 0.4563

Median 0.4841 0.4204 0.5181 0.6709 0.4782

75th percentile

0.5577 0.5476 0.6473 0.9352 0.5000

Maximum value

0.6250 0.6640 1.0410 1.2311 0.5219

Mean 0.4299 0.4094 0.5849 0.7467 0.4782

Standard deviation

0.1722 0.1866 0.2091 0.3117 0.0618

Number of responses

0 10 10 13 7 2 0 0



1 2 3 4 5 6 7 8

Minimum value

0.0029 0.0083 0.3043

25th percentile

0.0914 0.1381 0.3278

Median 0.1371 0.2357 0.3513

75th percentile

0.2095 0.2612 0.3748

Maximum value

0.2621 0.3028 0.3983

Mean 0.1415 0.1892 0.3513

Standard deviation

0.0957 0.0000 0.0665

Number of responses

0 6 0 5 2 0 0 0




1 2 3 4 5 6 7 8

Minimum value

0.0065 0.2401 0.4198 0.4194 1.2258 1.0244 0.7869

25th percentile

0.2471 0.3037 0.5155 0.4561 1.2258 1.0244 0.7869

Median 0.4755 0.3906 0.6337 0.5167 1.2258 1.0244 0.7869

75th percentile

0.5996 0.4805 0.6819 0.5724 1.2258 1.0244 0.7869

Maximum value

0.8822 0.5190 0.7607 0.5942 1.2258 1.0244 0.7869

Mean 0.4265 0.3876 0.6037 0.5118 1.2258 1.0244 0.7869

Standard deviation

0.2645 0.1153 0.1290 0.0818

Number of responses

0 12 6 6 4 1 1 1



1 2 3 4 5 6 7 8

Minimum value

0.0057 0.0904 0.0625 0.1441 0.6544

25th percentile

0.0204 0.0962 0.0952 0.1441 0.6544

Median 0.0350 0.1021 0.1656 0.1441 0.6544

75th percentile

0.0497 0.1079 0.2266 0.1441 0.6544

Maximum value

0.0643 0.1138 0.2315 0.1441 0.6544

Mean 0.0350 0.1021 0.1563 0.1441 0.6544

Standard deviation

0.0415 0.0166 0.0850

Number of responses

0 2 2 4 1 0 1 0


Appendix D Empirical vulnerability curves derived from combined Brisbane-Ipswich and Bundaberg postal surveys

D.1 Graphs of empirical vulnerability curves

The graphs below show the empirical vulnerability curves derived from the combined Brisbane-Ipswich

and Bundaberg postal surveys data in blue. For comparison purposes the analytical vulnerability

curves are shown in red.

Appendix Figure D.1 Empirical vulnerability curves for generic house type FCM1, Insured.

Appendix Figure D.2 Empirical vulnerability curves for generic house type FCM1, Uninsured.



Appendix Figure D.7 Empirical vulnerability curves for generic house type FCM7 Insured.





D.2 Scatter plots of empirical data

The graphs below present the individual Brisbane-Ipswich and Bundaberg survey responses plotted

as blue dots. The analytical vulnerability curve for the generic house type in question is plotted as a

red line.

Appendix Figure D.11 Scatter plot of postal survey data for generic house type FCM1, Insured.


Appendix Figure D.12 Scatter plot of postal survey data for generic house type FCM1, Uninsured.




D.3 Box plots of empirical data

D.3.1 Box plots

The graphs below present the combined Brisbane – Ipswich and Bundaberg survey responses as box

plots. The survey responses were binned into inundation depth bins defined in Appendix Table 26.

The thick black bars on each box denote the 25th

percentile, median and 75th percentile. The lower

and upper whiskers denote the minimum and maximum values respectively.






1 -10.0 0.00 -0.1

2 0.001 0.40 0.2

3 0.401 0.75 0.575

4 0.751 1.25 1.0

5 1.251 1.75 1.5

6 1.751 2.25 2.0

7 2.251 3.25 2.7

8 3.251 20 3.5

Appendix Figure D.21 Box plot of Brisbane-Ipswich and Bundaberg survey results for generic house type FCM1, Insured.


Appendix Figure D.22 Box plot of Brisbane-Ipswich and Bundaberg survey results for generic house type FCM1, Uninsured.







D.3.2 Numerical data describing box plots

The tables below present the numerical data that define the box plots presented in Section D.3.1.


Appendix Table 27 Box plot data for Brisbane-Ipswich and Bundaberg survey results for generic house type

FCM1, Insured.


1 2 3 4 5 6 7 8

Minimum value

0.0002 0.0058 0.0434 0.0120 0.0460 0.0006 0.1956 0.2950

25th percentile

0.0197 0.1890 0.2410 0.2339 0.2268 0.2174 0.3589 0.5286

Median 0.0351 0.2998 0.3761 0.4234 0.3559 0.5583 0.4138 0.6698

75th percentile

0.0440 0.4143 0.5115 0.5346 0.5731 0.7074 0.6549 0.7817

Maximum value

0.0701 1.1405 1.1104 1.0848 0.9778 1.0038 1.6864 1.4844

Mean 0.0320 0.3525 0.4040 0.4166 0.3998 0.4981 0.5644 0.7017

Standard deviation

0.0212 0.2867 0.2265 0.2515 0.2454 0.3140 0.3673 0.2853

Number of responses

9 22 31 32 21 31 21 15


FCM1, Uninsured.


1 2 3 4 5 6 7 8

Minimum value

0.0006 0.0018 0.0121 0.0342 0.0093 0.0744 0.0027 0.0003

25th percentile

0.0016 0.0144 0.0509 0.0849 0.0541 0.1584 0.2193 0.2054

Median 0.0026 0.0161 0.0963 0.1948 0.1241 0.2891 0.2705 0.3823

75th percentile

0.0080 0.0742 0.2906 0.2382 0.3497 0.3875 0.4641 0.7412

Maximum value

0.0809 1.1512 1.1781 0.4646 0.5353 1.5682 1.1142 1.8769

Mean 0.0148 0.1499 0.2656 0.1825 0.1971 0.3779 0.3661 0.5623

Standard deviation

0.0293 0.3043 0.3337 0.1166 0.1770 0.3499 0.2902 0.5308

Number of responses

7 17 21 16 16 20 25 30


FCM3, Insured.


1 2 3 4 5 6 7 8

Minimum value

0.0016 0.0550 0.0599 0.0273 0.0583 0.1285 0.0943

25th percentile

0.0273 0.1206 0.0646 0.1122 0.1765 0.2046 0.2756



1 2 3 4 5 6 7 8

Median 0.1010 0.2168 0.0841 0.2148 0.2748 0.2848 0.6235

75th percentile

0.1727 0.2497 0.3125 0.3080 0.4643 0.3936 0.9211

Maximum value

1.5330 0.3000 0.3512 0.7203 0.9996 1.7112 0.9516

Mean 0.2654 0.1875 0.1745 0.2530 0.3541 0.3852 0.5732

Standard deviation

0.5178 0.0970 0.1446 0.2154 0.2563 0.3426 0.4254

Number of responses

0 8 7 5 9 14 22 4


FCM3, Uninsured.


1 2 3 4 5 6 7 8

Minimum value

0.0046 0.0049 0.0327 0.0701 0.0162 0.0773 0.2039

25th percentile

0.0137 0.0312 0.0465 0.1101 0.0729 0.1792 0.2416

Median 0.0822 0.0972 0.1690 0.1245 0.1675 0.2581 0.3111

75th percentile

0.2001 0.1899 0.2995 0.1557 0.1920 0.4500 0.3677

Maximum value

0.2262 0.3865 0.3429 0.1870 0.3127 0.8023 0.5264

Mean 0.1031 0.1365 0.1760 0.1291 0.1477 0.3154 0.3262

Standard deviation

0.0941 0.1282 0.1291 0.0443 0.0908 0.2153 0.1185

Number of responses

0 8 10 8 8 10 16 6


FCM4, Insured.


1 2 3 4 5 6 7 8

Minimum value

0.0324 0.0194 0.0875 0.0040 0.0185 0.0268 0.1395

25th percentile

0.0985 0.1349 0.2314 0.1178 0.1430 0.1837 0.4118

Median 0.1354 0.2234 0.2813 0.1889 0.2475 0.2616 0.5214

75th percentile

0.2575 0.3800 0.3626 0.4111 0.3920 0.3702 0.7631

Maximum value

0.6369 1.5683 1.6110 0.7863 0.7968 0.7240 1.2049



1 2 3 4 5 6 7 8

Mean 0.1980 0.3350 0.3773 0.2847 0.3014 0.2948 0.5857

Standard deviation

0.1770 0.3565 0.3613 0.2332 0.2256 0.1871 0.2737

Number of responses

0 13 20 16 20 13 19 14


FCM4, Uninsured.


1 2 3 4 5 6 7 8

Minimum value

0.0005 0.0001 0.0202 0.0116 0.0222 0.0089 0.0132 0.0004

25th percentile

0.0005 0.0079 0.0846 0.0531 0.0994 0.0642 0.0463 0.1583

Median 0.0005 0.0464 0.1152 0.1006 0.1612 0.0872 0.2006 0.2494

75th percentile

0.0005 0.1609 0.2603 0.1565 0.2572 0.2016 0.3574 0.3669

Maximum value

0.0005 0.4718 0.3388 0.2822 0.9484 0.4391 0.6067 0.5223

Mean 0.0005 0.1177 0.1551 0.1115 0.1953 0.1345 0.2141 0.2666

Standard deviation

0.1458 0.1031 0.0782 0.1917 0.1040 0.1767 0.1522

Number of responses

1 16 19 20 21 19 20 14


FCM7, Insured.


1 2 3 4 5 6 7 8

Minimum value

0.0707 0.0622 0.0433 0.2868 0.3775 0.3667 0.9349

25th percentile

0.2464 0.2050 0.3045 0.5736 0.5054 0.4390 0.9349

Median 0.4184 0.3464 0.4283 0.6709 0.5319 0.6109 0.9349

75th percentile

0.5577 0.4040 0.5181 0.8814 0.6544 0.8166 0.9349

Maximum value

0.6547 0.6640 1.0410 1.2311 0.9238 1.0245 0.9349

Mean 0.3977 0.3342 0.4484 0.7277 0.5859 0.6459 0.9349

Standard deviation

0.1936 0.1588 0.2124 0.2547 0.1622 0.2476

Number of responses

0 14 22 29 11 9 9 1



FCM7, Uninsured.


1 2 3 4 5 6 7 8

Minimum value

0.0035 0.0029 0.0866 0.0083 0.2217 0.1121 0.2774 0.3079

25th percentile

0.0035 0.0892 0.2377 0.1808 0.2946 0.3004 0.3402 0.5149

Median 0.0035 0.1206 0.3179 0.2559 0.3738 0.3405 0.4241 0.7218

75th percentile

0.0035 0.1761 0.3280 0.3615 0.4132 0.6192 0.6384 0.9287

Maximum value

0.0035 0.4032 0.6343 0.6238 0.5750 1.0000 0.7404 1.1356

Mean 0.0035 0.1492 0.3094 0.2829 0.3694 0.4438 0.4752 0.7218

Standard deviation

0.1196 0.1530 0.1527 0.1150 0.2834 0.1591 0.5853

Number of responses

1 9 9 20 7 9 18 2


FCM8, Insured.


1 2 3 4 5 6 7 8

Minimum value

0.0200 0.0065 0.2401 0.0000 0.1492 0.2891 0.9448 0.3399

25th percentile

0.0200 0.1371 0.3400 0.0146 0.4684 0.4481 0.9862 0.7042

Median 0.0200 0.4227 0.3906 0.4194 0.5651 0.6238 1.0122 0.7869

75th percentile

0.0200 0.6033 0.5119 0.7163 0.5942 0.8887 1.0589 0.9113

Maximum value

0.0200 0.9263 0.8693 2.4177 1.1552 1.2258 1.1624 2.4177

Mean 0.0200 0.4141 0.4445 0.4741 0.5807 0.6711 1.0329 1.0457

Standard deviation

0.2992 0.1976 0.4573 0.2707 0.3143 0.0925 0.6886

Number of responses

1 15 8 85 9 9 4 9


FCM8, Uninsured.


1 2 3 4 5 6 7 8

Minimum value

0.0057 0.0904 0.0625 0.0844 0.0822 0.1850 0.1680

25th percentile

0.0497 0.1560 0.1846 0.2375 0.3039 0.4880 0.2502



1 2 3 4 5 6 7 8

Median 0.1100 0.2453 0.2282 0.4422 0.4765 0.5211 0.3438

75th percentile

0.1695 0.3079 0.3391 0.5757 0.6126 0.6544 0.4279

Maximum value

0.2106 0.3963 0.6149 0.6806 1.2559 1.0000 0.4817

Mean 0.1091 0.2334 0.2783 0.4034 0.5146 0.5704 0.3343

Standard deviation

0.0916 0.1020 0.1807 0.2082 0.3135 0.2650 0.1394

Number of responses

0 4 9 10 9 11 13 4


Appendix E Example component level repair specification

Appendix Table 37 Example component level repair specification for generic house type FCM7 (single storey brick veneer residence with slab-on-ground foundation).

FCM7 Insured

No.

Component

Description

Required repairs for inundation depth relative to floor level (m)

-0.3 0 0.1 0.3 0.5 1 1.5 2 2.5 3

1 Substructure Stiffened raft consisting of 100 thk slab on grade on DPM on 20 sand on 100 hardcore. 600 dp x 300 wide rc beams at 4m ctrs each way.

Nil Nil Nil Nil Nil Nil Nil Nil Nil Nil

2 External walls Face brick veneer Nil Nil Jet clean and allow to dry. Remove one brick in 20 on one course to facilitate cavity drying and replace

Jet clean and allow to dry. Remove one brick in 20 on one course to facilitate cavity drying and replace







3 Timber framing to external walls

90 x 45 MGP10 studs @ 450 ctrs with similar top & btm plates, 2 rows of noggings

Nil Nil Jet clean and allow to dry

Jet clean and allow to dry







4 Timber framing to internal walls

75 x 35 MGP10 studs @ 600 ctrs with similar top and btm plates, 2 rows of noggings









5 General lining to interior of exterior walls and interior walls

13mm plasterboard Nil Nil Remove 1/2 height of sheeting and replace

Remove 1/2 height of sheeting and replace



Remove full height of sheeting and replace




6 Lining to bathroom, toilet, ensuite and laundry walls

Fibre cement sheeting Nil Nil Remove 1/2 height of sheeting and replace








7 Lining to kitchen walls

Fibre cement sheeting Nil Nil Remove 1/2 height of sheeting and replace








8 Skirting boards Moulded mdf skirting, paint finish

Nil Nil Remove and replace

Remove and replace

Remove and replace

Remove and replace

Remove and replace

Remove and replace

Remove and replace

Remove and replace

9 Cornices Preshaped plaster cornice Nil Nil Nil Nil Nil Nil Remove and replace

Remove and replace

Remove and replace

Remove and replace

10 Ceiling 13mm plasterboard on timber battens

Nil Nil Nil Nil Nil Nil Nil Nil Remove and replace. Allow to refix 25% of battens

Remove and replace. Allow to refix 25% of battens


FCM7 Insured

No.

Component

Description


-0.3 0 0.1 0.3 0.5 1 1.5 2 2.5 3

11 Timber roof structure

Prefabricated softwood trusses

Nil Nil Nil Nil Nil Nil Nil Nil Nil Jet clean and allow to dry

12 Roofing Glazed concrete tiles on timber battens with sarking

Nil Nil Nil Nil Nil Nil Nil Nil Nil Allow to remove 10% to assist roof space drying and refix. Allow for temporary tarps. Jet clean.

13 Wall insulation Fibreglass batts (thermal to exterior walls, sound to interior walls)

Nil Nil Remove and replace batts over bottom half of wall height

Remove and replace batts over bottom half of wall height



Remove and replace batts over full wall height




14 Roof insulation Fibreglass batts Nil Nil Nil Nil Nil Nil Nil Nil Remove and replace

Remove and replace

15 Windows Aluminium framed, double glazed, mix of sliding and awning types

Nil Nil Nil Jet clean affected units and allow to dry

Jet clean affected units and allow to dry

Jet clean affected units and allow to dry



Remove and replace

Remove and replace

16 Window surrounds

Moulded mdf, painted Nil Nil Nil Remove and replace affected units

Remove and replace affected units






17 Window sills Brick set on incline Nil Nil Nil Jet clean and allow to dry







18 External doors Solid core timber front door with deadlock, ditto to laundryr door, varnish finish

Nil Nil Clean and paint

Clean and paint

Clean and paint

Clean and paint

Remove and replace

Remove and replace

Remove and replace

Remove and replace

19 External doors 1 No. Panel-lift garage door, motorised operation

Nil Wash clean Wash clean Wash clean Wash clean Wash clean Take down, wash clean and refix with new mechanism and controller

Take down, wash clean and refix with new mechanism and controller



20 External doors Sliding aluminium framed double glazed patio door to family room






Remove and replace

Remove and replace

Remove and replace

21 External door frames

Hwd timber door frames, varnish finish

Nil Nil Clean and paint

Clean and paint

Clean and paint

Clean and paint

Remove and replace

Remove and replace

Remove and replace

Remove and replace

22 Internal doors Hollowcore doors, paint finish

Nil Nil Remove and replace reusing door hardware

Remove and replace reusing door hardware



Remove and replace

Remove and replace

Remove and replace

Remove and replace


FCM7 Insured

No.

Component

Description


-0.3 0 0.1 0.3 0.5 1 1.5 2 2.5 3

23 Internal door frames

Mdf door frames, paint finish Nil Nil Remove and replace

Remove and replace

Remove and replace

Remove and replace

Remove and replace

Remove and replace

Remove and replace

Remove and replace

24 Eaves lining Fibre cement sheeting with timber beading at sheet joins

Nil Nil Nil Nil Nil Nil Nil Nil Nil Remove and replace

25 Guttering and downpipes

Colourbond rainwater goods Nil Nil Nil Nil Nil Nil Nil Nil Nil Jet clean

26 Floor covering (garage)

Bare concrete Nil Jet clean Jet clean Jet clean Jet clean Jet clean Jet clean Jet clean Jet clean Jet clean

27 Floor covering (bedrooms, lounge, dining and family)

Carpet with rubber underlay Nil Nil Remove and replace.

Remove and replace.

Remove and replace.

Remove and replace.

Remove and replace.

Remove and replace.

Remove and replace.

Remove and replace.

28 Floor covering (bathroom, toilet, ensuite, laundry)

6mm floor tiles Nil Nil Remove tiles and replace

Remove tiles and replace







29 Floor covering (kitchen)

Linoleum tiles glued to hardboard sheet

Nil Nil Remove lino and sheet and replace

Remove lino and sheet and replace







30 Wall finishes (general)

Undercoat + 2 top coats paint

Nil Nil Undercoat lower half of walls and apply 2 top coats to whole wall

Undercoat lower half of walls and apply 2 top coats to whole wall



Undercoat and apply 2 top coats to whole wall




31 Wall finishes (bathroom and ensuite)

Full height wall tiles adhesive fixed to FC sheet

Nil Nil Remove tiles from full height of walls and replace

Remove tiles from full height of walls and replace







32 Wall finishes (toilet)

200mm height skirt tiles, paint above

Nil Nil Remove tiles and replace

Remove tiles and replace, repaint above







33 Wall finishes (laundry)

0.5m2 tile splashback, 200mm height skirt tiles, paint elsewhere

Nil Nil Remove skirt tiles and replace. Repaint above

Remove skirt tiles and replace. Repaint above

Remove skirt tiles and replace. Repaint above

Remove all tiles and replace. Repaint





34 Wall finshes (kitchen)

Tile splashback to all benches, 800 high. Paint elsewhere

Nil Nil Remove tiles and replace, repaint (to enable wall sheeting replacement)

Remove tiles and replace, repaint (to enable wall sheeting replacement)







35 Ceiling finishes Undercoat + 2 top coats paint

Nil Nil Nil Nil Nil Nil Repaint Repaint Repaint Repaint


FCM7 Insured

No.

Component

Description


-0.3 0 0.1 0.3 0.5 1 1.5 2 2.5 3

36 Bathroom and ensuite joinery

Melamine covered mdf vanities, FC sheet skirting around bath.

Nil Nil Remove vanity kickboard and bath skirting and replace. Refix vanity

Replace vanity and bath skirting







37 Bathroom and ensuite basins and tapware

Ceramic basins, connecting hydraulics and chrome taps

Nil Nil Recover, clean and refix

Recover, clean and refix







38 Bath Enamelled steel and chrome taps









39 Bathroom and ensuite fixtures

Chrome towel rails and soap dishes









40 Shower recesses Frameless glass 0.9m2 shower cubicle and chrome taps









41 Shower recess hobs

Masonry hob finished to accept waterproofing and tiles

Nil Nil Demolish and reconstruct to allow wall sheet removal

Demolish and reconstruct to allow wall sheet removal







42 Shower water proofing

Paint-on waterproof membrane

Nil Nil Replace Replace Replace Replace Replace Replace Replace Replace

43 Toilet and ensuite fixtures

Ceramic dual flush toilet and connecting hydraulics, chrome toilet paper holder









44 Laundry fixtures Stainless steel tub with chrome taps, chrome taps for washing machine









45 Laundry joinery Melamine covered mdf broom cupboard

Nil Nil Remove and replace

Remove and replace

Remove and replace

Remove and replace

Remove and replace

Remove and replace

Remove and replace

Remove and replace

46 Kitchen joinery Melamine covered mdf kitchen under bench cupboards, high level cupboards, laminex covered benchtops

Nil Nil Remove and replace low level cupboard kickboards. Refix cupboards.

Remove and replace low level cupboards, reusing extg benchtops

Remove and replace low level cupboards, reusing extg benchtops

Remove and replace low level cupboards and benchtops

Remove and replace low level cupboards and benchtops

Remove and replace all



47 Kitchen fixtures Stainless steel basin and chrome mixer tap

Nil Nil Nil Recover and refix

Recover and refix






48 Kitchen appliances

Gas cooktop, electric underbench oven, dishwasher, electric rangehood

Nil Nil Replace dishwasher

Replace oven and dishwasher, recover others and reuse

Replace oven and dishwasher, recover others and reuse

Replace all except rangehood

Replace all Replace all Replace all Replace all


FCM7 Insured

No.

Component

Description


-0.3 0 0.1 0.3 0.5 1 1.5 2 2.5 3

49 Mechanical Bathroom and ensuite extraction fans

Nil Nil Nil Nil Nil Nil Nil Nil Replace Replace

50 Mechanical 2.5hp A/C system mounted back to back with external unit on ground

Nil Replace external unit

Replace external unit





Replace all Replace all Replace all

51 Mechanical Check gas supply to kitchen Nil Item Item Item Item Item Item Item Item Item

52 Electrical - lighting

Central ceiling mounted light fitting (25 No) + ceiling mounted fluorescent fitting to kitchen

Nil Nil Nil Nil Nil Nil Nil Nil Replace all Replace all

53 Electrical lighting Wall mounted light switches (30 No)

Nil Nil Nil Nil Nil Nil Remove and replace

Remove and replace

Remove and replace

Remove and replace

54 Electrical exterior lighting

Two No external sensor lights mounted under eaves

Nil Nil Nil Nil Nil Nil Nil Nil Remove and replace

Remove and replace

55 Electrical - power 19 No. double GPO Nil Nil Nil Remove and replace

Remove and replace

Remove and replace

Remove and replace

Remove and replace

Remove and replace

Remove and replace

56 Electrical - power Meter box Nil Nil Nil Nil Nil Nil Remove and replace

Remove and replace

Remove and replace

Remove and replace

57 Electrical - general

Test electrical cabling for faults (item) (assume no rewiring necessary for all depths)

Nil Test Test Test Test Test Test Test Test Test

58 Hydraulic - HWS Electrical 250l HWS mounted externally on ground

Nil Test Remove and replace

Remove and replace

Remove and replace

Remove and replace

Remove and replace

Remove and replace

Remove and replace

Remove and replace

59 Hydraulic - water supply piping

Copper 15mm diameter Nil Flush Flush Flush Flush Flush Flush Flush Flush Flush

60 Hydraulic - sanitary drainage

100mm UPVC Nil Flush Flush Flush Flush Flush Flush Flush Flush Flush

61 Hydraulic - SW drainage

100mmUPVC Nil Flush Flush Flush Flush Flush Flush Flush Flush Flush

62 Window furnishing

Fabric curtains to bedroom, dining, family & lounge windows. Plastic Venetian blinds to laundry, toilet, ensuite and bathroom windows.

Nil Nil Nil Nil Nil Remove and replace all





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