DWW 2005 009 Standard method 2004 Damage and Casualties...

Standard Method 2004 Damage and Casualties Caused by Flooding

DWW-2005-009

Authors: M. Kok H.J. Huizinga A.C.W.M. Vrouwenvelder A. Barendregt

Standard Method 2004 Damage and Casualties by Flooding Rijkswaterstaat

Road and Hydraulic Engineering Institute DWW-2005-009 2



Foreword We have the pleasure to present you the report Standard Method 2004 Damage and Casualties Caused by Flooding. This report is based on the Standard Method 2002 Damage and Casualties report caused by flooding [2002], supplemented with new insights acquired over the 2001 – 2004 period. These new insights relate to the adjustment of the casualty function on the basis of research carried out by DWW [Jonkman et al, 2004], and the addition of an evaluation factor on the basis of research carried out by the University of Twente and HKV LIJN IN WATER [Barendregt et al., 2002; Maarseveen, 2004]. Damage and casualties caused by flooding can be defined using the Standard Method, which are subsequently included in a risk analysis. In compiling the Standard Method, various studies in the area of damage and casualty determination have been used. The study described in the report is part of the 'Veiligheid van Nederland in Kaart (VNK)' and 'Hoogwater Informatie Systeem (HIS)' projects initiated by the Dept. of Public Works. The project was directly supervised by S.R. Holterman, M.R. van der Doef and A.M. Cappendijk-de Bok from the Highway and Hydraulic Engineering Department of the Department of Publics Works. The first Standard Method 2000 was realised jointly by dr. ir. M. Kok and ir. N. Vrisou van Eck of HKV LIJN IN WATER and prof. ir. A.C.W.M. Vrouwenvelder of TNO Bouw. Revision of the Standard Method 2000 to the Standard Method 2002 was carried out by drs. H.J. Huizinga and ir. T.C. Meijerink of HKV LIJN IN WATER. Revision of the Standard Method 2002 to the Standard Method 2004 (in combination with the revision of HIS-SSM v2.0.2 to HIS-SSM v2.1) was carried out by A. Barendregt and H.J. Huizinga.



Contents

1 Introduction .................................................................................................................7 1.2 General..............................................................................................................................7 1.3 Reader’s guide ..................................................................................................................7

2 Standard Method.........................................................................................................9 2.1 General..............................................................................................................................9 2.2 Diked area with probability of flooding ............................................................................10 2.3 Economic damage...........................................................................................................10

3 Establishing representative flood scenarios..........................................................13

4 Data ...........................................................................................................................15 4.1 Hydraulic data .................................................................................................................15 4.2 Area data.........................................................................................................................15

4.2.1 Land use..............................................................................................................15 4.2.2 Infrastructure .......................................................................................................16 4.2.3 Households..........................................................................................................16 4.2.4 Residents.............................................................................................................17 4.2.5 Companies ..........................................................................................................18 4.2.6 Other....................................................................................................................19

4.3 Evacuation data...............................................................................................................20

5 Determining flood damage.......................................................................................21 5.1 Damage in low-frequency flooded areas.........................................................................21

5.1.1 Damage calculation.............................................................................................21 5.1.2 Damage factors ...................................................................................................21 5.1.3 Dwellings damage factor .....................................................................................26 5.1.4 Maximum damage amounts ................................................................................30

5.2 Damage in high-frequency flooded areas .......................................................................31 5.3 Uncertainty in flood damage ...........................................................................................32

6 Determining the number of casualties....................................................................35 6.1 General............................................................................................................................35 6.2 Calculating casualty numbers .........................................................................................35

6.2.1 Casualty function .................................................................................................35 6.2.2 Evacuation factor.................................................................................................36

7 Determining flood risk ..............................................................................................37 7.1 General............................................................................................................................37 7.2 Example of river situation................................................................................................37 7.3 Example of sea situation .................................................................................................38

8 Reference...................................................................................................................39



Appendices Appendix A Definitions and abbreviations Appendix B Companies Appendix C Required files Appendix D Delphi implementation of dwelling damage functions Appendix E Delphi implementation of casualty function Appendix F Uncertainty in flood damage estimation

List of tables Table 4-1: Relation between data from CBS land use and damage categories 16 Table 4-2: Relation between data from Nat. Wegen Bestand and damage categories 16 Table 4-3: Relation between data from Spoor_NS and damage categories 16 Table 4-4: Relation between data from Bridgis dwelling types and damage categories 17 Table 4-5: Relation data Geo-Marktprofiel people file – damage categories 18 Table 4-6: Relation between data from D&B file and damage categories 19 Table 4-7: Relation between data from WIS file and damage categories 19 Table 5-1: Relation between damage category, materials and critical flow rate 26 Table 5-2: Standard Method Damage in low- frequency flooded areas 31 Table 7-1: Probability of dike section 1and/or 2 failing 37

List of figures Figure 2-1: Standard Method Damage and Casualties........................................................... 9 Figure 5-1: Agriculture and recreation damage factor........................................................... 22 Figure 5-2: Pumping stations damage factor ........................................................................ 23 Figure 5-3: Vehicles damage factor ...................................................................................... 23 Figure 5-4: Roads and railways damage factor .................................................................... 24 Figure 5-5: Gas and water mains damage factor.................................................................. 24 Figure 5-6: Electricity and communication systems damage factor...................................... 25 Figure 5-7: Companies damage factor.................................................................................. 25 Figure 5-8: Single-family dwellings and farms damage factor (without storm or current)..... 28 Figure 5-9: Low-rise dwellings damage factor (without storm or flow).................................. 28 Figure 5-10: Intermediate dwellings damage factor (without storm or current) ...................... 29 Figure 5-11: High-rise dwellings damage factor (without storm or current) ............................ 29



1 Introduction

1.2 General

This section describes the Standard Method 2004 Damage and Casualties Caused by Flooding (hereinafter referred to as the Standard Method) which determines the damage and number of casualties caused by flooding. This standardised method makes it possible to compare the different studies. The method has been developed within the framework of the Department of Public Works’ study ‘Schade en Slachtoffers’, the aim being to create a broad based method for establishing damage and casualties caused by flooding.

For the backgrounds to the Standard Method and a more detailed explanation of its various components, reference is made to [Vrisou van Eck, Kok en Vrouwenvelder, 1999b] and [Briene et al, 2002].

1.3 Reader’s guide

Chapter 2 gives an overview of the process followed in applying the Standard Method. Each subsequent chapter describes a component of the Standard Method. The Standard Method is applied to a diked area. Chapter 2 describes how the risk of flooding for this area can be calculated. Since a diked area can flood in many different ways, and it is not desirable to calculate damage and casualty numbers for all these scenarios, a way must be found to limit the number of necessary calculations. To limit these calculations, a few representative scenarios have been suggested for all potential flood events. The way in which this is done is described in Chapter 3. To calculate damage and casualty numbers, area and flood scenario data are required. A description of these data is included in Chapter 4. Chapter 5 describes the way in which damage is calculated and Chapter 6 the way in which casualty numbers are calculated. Finally, Chapter 7 describes how flood risk is ascertained using flood probability, and damage and casualty number calculation results.



2 Standard Method

2.1 General

The 'Standard Method Damage and Casualties’ consists of all the steps which need to be completed per (diked) area with its corresponding flood probability, to arrive at a flood risk. These steps are shown in Figure 2-1.

Figure 2-1: Standard Method Damage and Casualties



The following paragraph describes how the probability of flooding for a given diked area can be approached; this forms the basis of the Standard Method. The Standard Method’s other components (the text blocks in Figure 2-1) are explained in the following chapters. For further information regarding the foundation of choices made and the use of the Standard Method reference is always made to [Vrisou van Eck, Kok en Vrouwenvelder, 1999b].

2.2 Diked area with probability of flooding

The basis of the Standard Method Damage and Casualties is the flooding of a (diked) area, caused by dam, dike or weir collapse, for example. The probability of a flood scenario is taken for granted in the Standard Method. For diked areas, this flooding probability is established using a calculation program such as PC-Ring. However, an area can flood in various different ways; the dike can burst in one or more places, for example, and outer water levels which cause the burst can differ. The conditions under which a flooding occurs are called flood scenario. Each scenario results in a specific flood pattern of water levels and flow rates at all locations in the diked area. For areas situated along rivers without dams, weirs or dikes, flood depth and flow rates strongly depend on the duration and volume of discharge. The probability of a given flood scenario is equal to the probability of corresponding dike burst(s) during a certain outer water level, which persists for a certain period, combined with the probability of a storm (causing waves) occurring during the flood.

2.3 Economic damage

Various different types of damage are caused by floods. A distinction is made in the definition study of the Standard Method Damage and Casualties project [WL, TNO and Bouwdienst, 1999] between damage having an assessable monetary value and damage with a non-monetary assessable value. Regarding damage, the Standard Method mainly concerns assessable monetary value. Until now, only the number of fatal casualties has been included under non-monetary assessable value. Furthermore, a distinction is made between primary, secondary and induced damage. This distinction is made on the basis of the location where the damage occurs. Primary damage occurs within the flooded area; secondary damage occurs outside the flooded area and induced damage is damage that cannot be directly connected to the flooded area (salvage costs, for example). There are three distinct types of damage in the Standard Method [Briene et al, 2002]: 1. direct damage; 2. direct damage as a result of operational failure; 3. indirect damage as a result of flood;



Sub 1 Direct damage includes damage occurring to objects, capital goods and personal effects due to direct contact with water. This includes the following:

• repair of damaged real estate (both freehold and rented); premises and structures; • repair of damaged means of production such as machinery, equipment, process installations

and means of transport; • damage to home contents; • damage caused by loss of personal effects such as raw materials, auxiliary materials and

products (including damage to harvest).

Sub 2 Direct damage as a result of interruption of operations is damage ensuing from commercial losses through production stoppage.

Sub 3 Indirect damage consists of two categories: • Damage to suppliers and customers outside the diked area due to (partial) reduction in

turnover. This damage is calculated by means of multiplying the added value per job or hectare using a sector specific multiplier. Calculated at national level, the multiplier takes into account both substitution effects outside the diked area and suppliers within the diked area (these are already processed in the direct damage of the diked area). This means that application of the multiplier can create an overestimation of the actual damage. The larger the flooded area, the greater the overestimation will be. The Standard Method can, therefore, be provided with a reduction factor for indirect damage. The standard value of this reduction factor for indirect damage is fixed at 0.25.

• Damage caused by severed transport routes on the basis of journey-time lost.

BASIS OF VALUATION

The following choices were made when compiling the Standard Method damage functions: - Damage functions and maximum damage amounts are the same for the whole of the

Netherlands. This means that, for given hydraulic conditions, damage to a dwelling in Limburg is equal to damage to an identical dwelling in the middle of the Netherlands.

- there is (still) no distinction made in the modelling between damage in high- and low-frequency flooded areas. all functions and damage amounts apply to low-frequency flooded areas;

- no distinction is made between damage resulting from flooding with fresh or salt water; - maximum damage amounts are based on replacement value or reconstruction value; - damage is determined by flood depth, waves and flow rate; casualty numbers are also based

on rise rate.

Lesser damage caused by flooding in a high-frequency flooded area is expressed in a lower maximum damage amount or a lower damage factor; the way in which the learning effect is best expressed in the damage to be calculated is indicated per damage category. However, literature contains little information about this. It is suggested to select a frequency of once every 25 years for the line dividing low-frequency flooded areas and high-frequency flooded areas. The Standard Method does not distinguish between salt water and fresh water as this difference only applies to a limited number of categories (agriculture and vehicles) and the difference between amounts is relatively small. The following principles are employed when defining the maximum damage amounts [Briene et al., 2002]:



Direct damage • The reconstruction value is the basis for objects such as dwellings; that is to say, the amount

necessary to rebuild the object to its original state at the same location in case it is damaged; • replacement value is the basis for damaged capital goods, home contents, vehicles and

suchlike; this actually concerns the market value of comparable goods, insofar as this is not disrupted by subsidies and suchlike;

• in addition, loss of harvest and/or loss of cattle should also be taken into account for agriculture; production value is used as basis for determining related direct damage; this actually concerns the market value of comparable products and animals.

Direct damage due to interruption of operations Maximum damage amounts in diked areas are (where relevant) determined on the basis of added value (i.e. turnover minus the value of purchased goods). After all, production will (temporarily) be interrupted, which causes the purchase of necessary goods and services (for the production process) to cease. Indirect damage Maximum damage amounts for indirect damage occurring outside effected diked areas are also determined on the basis of the loss of added value. An Input/Output analysis is performed to establish the extent of this damage. Related damage is not discounted in the figures.



3 Establishing representative flood scenarios To limit the number of flood scenarios to be calculated, a number of representative scenarios have to be established for potential flood scenarios. The probability of a flood scenario, and therefore of certain damage, is the aggregate probability of scenarios with comparable consequences. When establishing representative flood scenarios, the area’s different patterns of maximum flood depth and flow rate must be considered. A flood scenario can be established as being representative for other scenarios if the patterns of maximum flow rates and maximum flood depths are comparable. The factors that determine damage have therefore to be taken into account when establishing representative flood scenarios, these factors are: 1. outer water level movement; 2. wind; 3. the mechanism (i.e. slip, wave power, non-enclosed culvert; 4. time of burst (before, during or after highwater); 5. breach growth rate (dependent on dike material, amongst other things); 6. burst(s) location.

Another damage calculation, therefore, only needs to be started if a substantially different flood pattern occurs with different flow rates and water depths at locations where these have different consequences. Since there is little experience with establishing representative flood scenarios, and since the method has not yet entirely taken shape, the choice of flood scenario is left to the user. The user must, therefore, wander along the diked area and answer the following questions: - Are there intermediate barriers? - Are there strong height differences in ground level? - Does the hydraulic regime change? - Are there buildings?

For every question answered with a yes, it is in principle necessary to consider an extra flood scenario. A more detailed explanation of the way in which flood scenarios can be established as being representative is included in [Vrisou van Eck, Kok en Vrouwenvelder, 1999b]. This document also indicates the principles to determine the probability of a breach (or breaches) in a diked area. Damage and casualty numbers can be calculated on the basis of representative flood scenarios. The following data are necessary per flood scenario: - burst location(s), burst time(s), outer water level during burst(s) and breach growth acceleration

for the purpose of hydrodynamic calculations; - maximum breach width, and whether or not there is a storm, for the purpose of the damage

and casualty calculation; - the conditional probability required for a flood scenario for the purpose of determining the flood

risk.



4 Data

4.1 Hydraulic data

To be able to calculate the expected economic damage and casualty numbers, a scenario should be compiled containing the following data: maximum flood depth per location, maximum flow rate (average or per location), rise rate (average or per location), shelter factor (average or per location) and the presence of storm (waves) in the area. Flood depth, rise rate and possibly also flow rate all follow from the results of a hydrodynamic calculation with DELFT-FLS/ DELFT-1D2D. Remaining data should be estimated by the user.

4.2 Area data

Geographical oriented data for the area is used to calculate damage and casualty numbers caused by flooding using the Standard Method. An inventory can be made using these data, for any given area in the Netherlands, the number of dwellings, residents, companies, area of agricultural land, etc. So-called interface files are needed, such as the postcode file, for the postcode-area related files containing area data. Table 5-2 shows an overview of the data to be used. All geographical oriented data are converted to the standard dataset. The standard dataset is called SSM100NL2004. This standard dataset is used in combination with the 'HIS Schade en Slachtoffer Module version 2.1'.

4.2.1 Land use

The Standard Method uses the file CBS bodembestand 1996, codes bg_93. The file was created on 16 December 1999. The following CBS catagories are used in the Standard Method: agricultural ground, built-up areas, woodland, recreation and transport. The relation between the sub categories of the data files and the damage catagories from the Standard Method are shown in Table 4-1.



Damage category CBS no.

CBS code CBS Category CBS Sub category

greenhouse horticulture

11 bg_93 agricultural land greenhouse horticulture

agriculture 12 bg_93 agricultural land other agricultural use urban area 31 bg_93 built-up area residential area

21 bg_93 forests woodland 51 bg_93 recreation parks and gardens

extensive recreation

52 bg_93 recreation sports fields 53 bg_93 recreation day-trip recreation objects and

facilities 54 bg_93 recreation allotment gardens

intensive recreation

55 bg_93 recreation residential recreation airports 44 bg_93 traffic airports Table 4-1: Relation between data from CBS land use and damage categories

4.2.2 Infrastructure

To determine damage to various categories of road, the Standard Method uses the file Nationaal Wegen Bestand of the Adviesdienst Verkeer en Vervoer AVV (AVV Transport Research Centre) of Dept. of Public Works. Use is made of the NWB-W file 2002_2 from June 2002. The roads in the Nationaal Wegen Bestand are subdivided into road managers (state, province, municipality or water board); the file is derived from the Top10vector. It is assumed that a motorway is managed by the province and remaining roads by municipalities and water boards. The following data from the Nationaal Wegen Bestand are used in the Standard Method.

Damage category NWB type road manager national trunk roads R motorway P other roads G other roads W Table 4-2: Relation between data from Nat. Wegen Bestand and damage categories

The Standard Method uses the file Spoor_NS from the Nederlandse Spoorwegen (Dutch Railways) to determine the damage to railways. The SPOOR_NS file was created on 20 October 1998. The following data from the Spoor_NS file are used in the Standard Method. Damage category type railways all Table 4-3: Relation between data from Spoor_NS and damage categories

4.2.3 Households

To determine the damage to dwellings, use is made of a file offered by Bridgis containing data about the number of dwellings per geographical unit and type of dwelling; the WOONTYPE.TXT file was created on 27 January 2000. Fourteen dwelling types are differentiated in this file: detached house/bungalows, semi-detached house, terraced/single-family dwelling, flats with 4 or less floors, flats with more than 4 floors, apartment/maisonette, apartment/flat in canalside house, canalside



town house, (self-reliant) old people’s flat, farm/market garden, students residence/flat, houseboat, caravan, sundries.

To calculate the damage to the different home types, they are divided into five different damage catagories: low-rise, intermediate, high-rise, single-family dwellings and farms. The relationship between damage catagories and home types in Bridgis are shown in Table 4-4.

It has been assumed that, when calculating residential damage, low-rise consists of 2 floors, intermediate of 4 floors and high-rise of 6 floors. To calculate home contents damage, each dwelling is allotted one home contents. Damage to a dwelling as calculated by the Standard Method therefore concerns both buildings damage and contents damage. To include damage to vehicles in the damage calculation, the user must enter the average car ownership per person. The Standard Method makes use of data which are also used in the ‘Maxschadekaarten’ (max. damage charts) project. The average Dutch car ownership in this project is 0.38 car per person. Data from Centraal Bureau voor Statistiek (Statistics Netherlands) show that in 1999 an average of 38.8% of people owned a car. Damage category Bridgis

no. Bridgis dwelling type

6 apartment/maisonette low-rise 7 apartments/flats/canalside house 4 flats <=4 floors intermediate 11 students residence/flat

high-rise 5 flats > 4 floors farm 10 farm/market garden

1 detached house/bungalow 2 semi-detached 3 terraced house/single-family

dwelling 8 canalside town house 9 (self-reliant) old people’s flat 13 caravans 0 unknown

single-family dwelling

14 sundries Table 4-4: Relation between data from Bridgis dwelling types and damage categories

4.2.4 Residents

A new database has been created (SSM100NL2004) to determine the number of casualties. This dataset is the same as dataset SSM100NL2002 with the exception of the number of residents. When calculating the number of casualties with the Standard Method, use is made of the file of persons Geo-Marktprofiel BV: GEO0200.TXT, created on 1st February 2000. The number of high-rise residents in the Standard Method 2004 has been filtered out of Geo-Marktprofiel’s file of people.



When determining the number of casualties, it is assumed that residents of high-rise dwellings are not likely to be flood victims. Residents of high-rise dwellings can find safety in upper floors in the event of a flood. High-rise is defined in this case as buildings with more than three floors above ground. The relations between data from the Geo-Marktprofiel file and the damage categories is as follows. Damage category type casualties npers vehicles nautos Table 4-5: Relation data Geo-Marktprofiel people file – damage categories

The number of vehicles is 0.38 multiplied by the number of residents per postcode, including high-rise residents.

4.2.5 Companies

The company file Dunn & Bradstreet (version no 2002/1) is used to calculate damage to businesses. The company type and number of employees is derived from this file. SIC-codes (Standard Industrial Classification) are used to distinguish between company types in the Dunn & Bradstreet file. Table 4-6 shows the relation between the SIC-code and the classification employed within the Standard Method. The number of employees is included per company in the Dunn & Bradstreet file. Damage to companies is calculated on the basis of this number of employees. NB Companies with 5000 or more employees at one location have been removed from the Dun & Bradstreet file. This relates mainly to holding companies; employees at other (often foreign) locations are included.

NEI’s report [Briene et al, 2002] gives damage amounts per job; in D&B, on the other hand, the number of employees is counted. It has been assumed in the Standard Method that employees and jobs can be connected one on one. The number of jobs is, in reality, slightly less (approx. factor 0.9) compared to the number of employees per company. However, this factor differs per company.



Damage category Description SIC- code SIC- code mineral extraction Extraction 1000-1400 industry Manufacturing 2000-3900 utilities Energy 4900 building trade Contracting 1500-1700

Wholesale and Retail Trade 5000-5900 Hotels, guesthouses etc. 7000 Services 7200-7400 Recovery services 7500-7600 Film 7800

trade, catering

Entertainment 7900 transport and communication Transport Communication 4000-4800

Banks and insurance 6000-6400 Real estate 6500-6600

banks and insurance

Holdings 6700 care provision, other Medical care 8000-8100

Educational institutions 8200 Social services 8300 Museums 8400

government

Other government services 8600 - 9900 Table 4-6: Relation between data from D&B file and damage categories

4.2.6 Other

To be able to link postcode related area data to geographical locations, the 6 position postcode file from Kadata (April 2002 version) is used. The location of pumping stations and purification plants is taken from the Waterstaatkundig Informatie Systeem WIS (Hydraulic Information System) chart. The WIS file used was created on 7 February 1997. The following data from the Kunstwerk coverage are used in the Standard Method. Damage category WIS

code WIS type KuWerk (WIS type Structures)

purification plants 4 sewage treatment plant pumping stations 15 Pumping station 15 cap <> -6 Table 4-7: Relation between data from WIS file and damage categories

‘Cap <> -6’ are pumping stations with a capacity greater than 6 m3/s or an unknown capacity.

Before using the purification plant file in the Standard Method, the line geometry of purification plants from the WIS must be converted to point-geometry (1 point per purification plant). Besides pumping stations and purification plants, other objects can stand in an area which, in the event of a flood, can make up a sizeable portion of damage volume but which are not included in



the basic files of the Standard Method. Examples include: (nuclear) power stations, large chemical plants, windmills, castles and mains. To be able to include exceptional objects in the damage calculation, a new dataset must be created by the user; refer for this to the HIS- Damage and Casualty Module Version 2.1 Users Manual.

4.3 Evacuation data

To be able to calculate then number of expected casualties, a scenario should be compiled containing, besides hydraulic data (see section 4), the evacuation factor. The evacuation factor is a value between 0 and 1 and gives the fraction of the number of people that can be preventively evacuated from the area. The group of people preventively evacuated derives from the results of a calculation with the EvacuatieCalculator [University of Twente, 2004] and the Evacuatie PreProcessor from HIS (HIS-EPP). A description of HIS-EPP is included in Appendix F of the Users Manual [2004].



5 Determining flood damage

5.1 Damage in low-frequency flooded areas

5.1.1 Damage calculation

There are different ways to determine flood damage. A formula generally used to calculate flood damage is:

S n Sii

n

i i==∑α

1

with αi = damage factor category i ni = number of units in category i

Si = maximum damage per unit in category i

Damage factor αi is derived from a damage function. There is one damage function per category. This factor shows the influence of hydraulic conditions, such as flood depth. The following parameters influence the damage factor: • flood depth (m) • flow rate (m/s) • critical flow rate (m/s) • rise rate (m/hr) (important for determining the number of casualties) • material factor (building material for dwellings: bricks or concrete) • shelter factor • presence of storm (waves)

The total damage in an area is the sum of direct damage caused by interruption of operations and indirect damage in all categories found in that area. Examples of categories are: agriculture, dwellings, vehicles, infrastructure etc. Each category has units in the form of the number of m2, objects, metres or jobs. Damage resulting from interruption of operations is understood to mean damage to suppliers and customers outside the diked area due to (partial) reduction in turnover. This damage is calculated by means of multiplying the added value per place of work or hectare using a sector specific multiplier. Calculated at national level, the multiplier takes into account both substitution effects outside the diked area and suppliers within the diked area (these are already processed in the direct damage of the diked area). This means that application of the multiplier can create an overestimation of the actual damage. The larger the flooded area, the greater the overestimation will be. The Standard Method can, therefore, be provided with a reduction factor. A reduction factor of 0.25 should be used as standard for indirect damage.

Damage factors in the Standard Method are derived from the ‘Tweede Waterkeringen Hoeksche Waard‘ study [Vrouwenvelder, 1997]. The TAW model was used in this study with the exception of dwellings and companies categories which are established using the Boertien1-model.

5.1.2 Damage factors

The damage factors shown below are applied to define the damage in low-frequency flooded areas.



Parameters used in the functions are: - d = flood depth (m) - u = flow rate (m/s) - ukr = critical flow rate (m/s) - w = rise rate (m/hour) - β = material factor - r = shelter factor - s = presence of storm (waves)

Agriculture, recreation and airports The damage factor for agriculture, recreation parks and airports is:

Figure 5-1: Agriculture and recreation damage factor



Pumping stations The damage factor for pumping stations is:

Figure 5-2: Pumping stations damage factor

Vehicles The damage factor for vehicles is:

Figure 5-3: Vehicles damage factor



Roads and railways

The damage factor for roads and railways is:

Figure 5-4: Roads and railways damage factor

Gas and water mains The damage factor for gas and water mains is:

Figure 5-5: Gas and water mains damage factor



Electricity and communication (systems) The damage factor for electricity and communication systems is:

Figure 5-6: Electricity and communication systems damage factor

Companies The damage factor for companies is:

Figure 5-7: Companies damage factor



5.1.3 Dwellings damage factor

The damage factors for single-family dwellings, farms, and low-rise, intermediate and high-rise dwellings are used to calculate damage to both buildings and contents. Apart from water levels, the influence of waves (in case of storms) and flow rate are important in the damage factors for the different dwelling types. These two factors can cause a dwelling to collapse, representing maximum damage.

Water depth and flow rate When calculating damage it must first be defined which dwellings have collapsed due to high flow rates and which dwellings have a damage factor of 1 due to water having reached the greater part of the dwelling. To determine if dwellings will collapse due to high flow rates1, a critical flow rate must be included in the damage module. The value per flood scenario should be entered by the user. If the flow rate according to the hydraulic model is higher than the critical flow rate in the calculation, the damage factor equals 1. The critical flow rate to be included in the damage module concerns all (intermediate and) high-rise dwellings in the flooded area; the critical flow rate for other dwelling types is derived from the entered value. The flow rate at which buildings can collapse lies between 1 and 8 m/s. The Standard Method should always be calculated using a critical flow rate of 8 m/s.

The critical flow rate for single-family dwellings, farms and low-rise dwellings is a ¼ of the critical flow rate indicated in the damage module. This value is lower because the walls of these dwelling types are resistant to flow rates of just 1 or 2 m/s, while cast concrete is resistant to flow rates of 8 m/s maximum. Damage category Materials Critical flow rates to be used in the

damage module Single-family dwellings and farms Brickwork 4 – 8 m/s (*¼ =1 – 2) Low-rise dwellings Brickwork 4 – 8 m/s (*¼ =1 – 2) Intermediate dwellings Cast concrete 6 – 8 m/s High-rise dwellings Cast concrete 6 – 8 m/s Table 5-1: Relation between damage category, materials and critical flow rate

Storm After having established the damage factor caused by water depth and (too high) flow rates, the probability of buildings collapsing as a result of waves in the event of a storm can be determined. This probability is included in the final damage factor.. (N.B. if u>ukr (or u> ¼ ukr) then α(d) =1) The probability of a dwelling collapsing due to waves during a storm is calculated as follows:

It has been assumed in the Standard Method that the material factor for single-family dwellings, farms and low-rise dwellings is 0.8, and 0.4 for (intermediate and) high-rise dwellings.

1 It is not clear from the literature which high flow rates cause a risk to dwellings. When compiling hydraulic data for a

calculation, the flow rate may only need be included, for example, if the maximum water level is at least half a metre.



The shelter factor has to be estimated per scenario and can be entered either as a fixed value or as a grid. The shelter factor is a reciprocal value of between 0 and 1; an exposure factor, to be exact. There is no shelter at value 1, and value 0 indicates maximum shelter. It has to be noted that the influence of waves on damage to dwellings in a flooded area is limited (max. 1%) and only counts for larger flood depths. Total damage factor The total damage factor for dwellings (on the basis of flood depth, flow rates and the probability of collapsing due to storm) is calculated as follows:

Single-family dwellings and farms The damage factor for single-family dwellings and farms concerns both damage to dwellings (buildings) and contents damage. The damage function is a weighed summation of the Boertien functions for contents and buildings damage. If necessary, the maximum damage amount or the damage function can be adjusted, but the ratio between the two damage amounts must be taken into account. The damage function was originally based on a median damage amount for contents of NLG100,000 and for buildings damage to single-family dwellings and farms of NLG 215,500. The ratio is 0.46. The damage amounts for single-family dwellings in the Standard Method are EUR 70,000 and EUR 171,000 respectively. The new ratio is 0.41. The difference between the two ratios is so small that it is not necessary to adjust the damage function. The possibility was considered of remove the function in the Standard Method for farms somewhat from the function of single-family dwellings. The damage amounts are EUR 70,000 and EUR 332,000 respectively, which gives a ratio of 0.22. This function has not been changed for practical reasons. The damage function is quite complicated; implementation of the damage function in Delphi source code is included in Appendix D. The damage function for contents, buildings and total damage is shown in the following graph.



Figure 5-8: Single-family dwellings and farms damage factor (without storm or current)

Low-rise dwellings The damage factor for low-rise dwellings concerns both dwellings (buildings) damage and contents damage. It has been assumed that, when calculating damage to low-rise dwellings, low-rise consists of 2 storeys. The concave form of the functions for multi-storey buildings shows that the lower layers often contain services essential to all the other floors. Basement garages, for example, or central installations and communal spaces on the ground floor. Damage to the ground floor also has consequences for the floors above. Damage function implementation in Delphi source-code is included in Appendix D. The following graph shows the damage function.

Figure 5-9: Low-rise dwellings damage factor (without storm or flow)



Intermediate dwellings The damage factor for intermediate dwellings concerns both dwellings (buildings) damage and contents damage. It has been assumed that, when calculating damage to intermediate dwellings, intermediate consists of 4 floors. Damage function implementation in Delphi source-code is included in Appendix D. The following graph shows the damage function.

Figure 5-10: Intermediate dwellings damage factor (without storm or current)

High-rise dwellings The damage factor for high-rise dwellings concerns both dwellings (buildings) damage and contents damage. It has been assumed that, when calculating damage to high-rise dwellings, high-rise consists of 6 floors. Damage function implementation in Delphi source-code is included in Appendix D. The following graph shows the damage function.

Figure 5-11: High-rise dwellings damage factor (without storm or current)



5.1.4 Maximum damage amounts

All categories shown in the following table have been included in the Standard Method, including the relevant functions, max. damage amounts and files used. The data concerning maximum damage amounts are taken from [Briene et al., 2002]. Maximum damage amounts are based on the 2000 price level. Damage category Unit Maximum

damage

amount ( €)

Damage

function

File

Agriculture direct m2 1.50 1 CBS land use

Agriculture indirect m2 1.60 1 CBS land use

Greenhouse horticulture direct m2 40.10 1 CBS land use

Greenhouse horticulture indirect m2 4.00 1 CBS land use

Urban area direct m2 48.60 1 CBS land use

Intensive recreation direct m2 10.90 1 CBS land use

Extensive recreation direct m2 8.90 1 CBS land use

Airports direct m2 1 197 1 CBS land use

Land use

Airports i.b. m2 36 1 CBS land use

National trunk roads direct m 1 450 4 NWB

National trunk roads indirect m 650 4 NWB

Motorways m 980 4 NWB

Other roads m 270 4 NWB

Railways direct m 25 150 4 Spoor_NS

Railways indirect m 86 4 Spoor_NS

Infrastructure

Railways i.b. m 151 4 Spoor_NS

Low-rise dwellings lot 172 000 9 Bridgis dwelling types

Intermediate dwellings lot 172 000 10 Bridgis dwelling types

High-rise dwellings lot 172 000 11 Bridgis dwelling types

Single-family dwelling lot 241 000 8 Bridgis dwelling types

Households

Farm lot

402 000 8 Bridgis dwelling types

Vehicles lot 1 070 3 revised Bridgis people file

Mineral extraction direct pw 1 820 000 7 D&B

Mineral extraction indirect pw 116 000 7 D&B

Mineral extraction i.b. pw 84 000 7 D&B

Industry direct pw 279 000 7 D&B

Industry indirect pw 70 000 7 D&B

Industry i.b. pw 62 000 7 D&B

Utilities direct pw 620 000 7 D&B

Utilities indirect pw 163 000 7 D&B

Utilities i.b. pw 112 000 7 D&B

Construction direct pw 10 000 7 D&B

Construction indirect pw 26 000 7 D&B

Construction i.b. pw 45 000 7 D&B

Trade, catering direct pw 20 000 7 D&B

Trade, catering indirect pw 3 500 7 D&B

Trade, catering i.b. pw 7 500 7 D&B

Companies

Banks, insurance direct pw 90 000 7 D&B



Damage category Unit Maximum

damage

amount ( €)

Damage

function

File

Banks, insurance indirect pw 7 000 7 D&B

Banks, insurance i.b. pw 14 000 7 D&B

Transport and communication

direct

pw 75 000 6 D&B


indirect

pw 6 400 6 D&B


i.b.

pw 11 200 6 D&B

Care provision, other direct pw 20 000 7 D&B

Care provision, other indirect pw 6 300 7 D&B

Care provision, other i.b. pw 3 400 7 D&B

Government direct pw 60 000 7 D&B

Government indirect pw 2 200 7 D&B

Government i.b. pw 9 200 7 D&B

Pumping stations lot 747 200 2 WIS Other

Purification plant lot 10 853 000 5 WIS

Table 5-2: Standard Method Damage in low- frequency flooded areas

The following abbreviations and codes apply to the above table: i.b.: interruption of operations j: job 1: Damage function ‘Agriculture, recreation and airports’ 2: Damage function ‘Pumping stations’ 3: Damage function ‘Vehicles’ 4: Damage function ‘Roads and railways’ 5: Damage function ‘Gas and water mains’ 6: Damage function ‘Electricity and communication systems’ 7: Damage function ‘Companies’ 8: Damage function ‘Single-family dwellings and farms’ 9: Damage function ‘Low-rise dwellings’ 10: Damage function ‘Intermediate dwellings’ 11: Damage function ‘High-rise dwellings’

Appendix C lists the files used.

5.2 Damage in high-frequency flooded areas

Further research is needed before completing the possible deviating damage functions and maximum damage amounts for high-frequency flooded areas; initially, damage functions and amounts can be used which relate to low-frequency flooded areas. A first suggestion is given below as to how the damage functions or the maximum damage amounts can be altered to calculate damage in high-frequency flooded areas. - Direct damage to arable farming, horticulture, greenhouse horticulture and cattle breeding will

be the same in both types of area. Areas that flood more frequently will be used less intensively, so cattle in areas unprotected by dikes will no longer be present during high water levels.



Therefore, maximum damage amounts and damage function are equal for both high- and low-frequency flooded areas.

- It is assumed that agricultural capital goods are less often present in high-frequency flooded areas; to this end, the maximum damage amount is adjusted.

- Urban areas that flood at least once every 25 years will be geared to inundation and (rapid) water drainage. Maximum damage will, therefore, be less.

- Damage to dumping and storage locations in high-frequency flooded areas will be comparable to such damage in low-frequency flooded areas. This also goes for damage to surface waters, extensive recreation and airports.

- Damage to intensive recreation will be less in high-frequency flooded areas, since building methods will be adapted to this.

- Maximum damage to national trunk roads, motorways and other roads, railways and airport runways will be less in high-frequency flooded areas, since flooding risks would have been taken account of during construction.

- Pumping stations, power stations and sewage purification plants stand pre-eminently in low-frequency flooded areas. This also applies to water storage facilities and main watercourses.

- Damage to dwellings will be less due to adapted construction methods; this can easily be shown by assuming the maximum damage amount to be lower than in low-frequency flooded areas.

- Contents damage will be less with flood depths up to 3 m because residents have moved contents to the first floor, for example, or because they are less likely to have parquet floors. However, with flood depths above 3 m, damage will be comparable to that in low-frequency flooded areas. This can be shown by adjusting the contents damage factor for flood depths of 3 m or less.

- Maximum damage (direct costs) to industry in high flood-frequency areas is less than in low flood-frequency areas, since flooding risks have been taken into account during construction.

- Vehicle damage in high flood-frequency areas will be significantly less than in low flood-frequency areas; residents are more likely to remove their vehicles prior to inundation. This can be included by reducing the damage factor.

- Damage caused by a breached dike, quay or dune is the same for both area types. - Reduced yield for arable farming, horticulture, greenhouse farming will be the same in both

types of area. - Companies in high flood-frequency areas are built and fitted with flooding in mind; these

companies will, therefore, resume their activities sooner. Maximum damage due to interruption of operations will, therefore, be less.

- Indirect damage amounts for companies will be the same for both area types.

Until further research has been carried out on the various damage types, it is suggested to (if necessary) reduce the maximum damage amount by 25% for high-frequency flooded areas compared to the maximum damage amount in low flood-frequency areas. The user can achieve this by manually reducing the calculated damage by 25%.

5.3 Uncertainty in flood damage

A method has been developed in the [Egorova, 2004] study for estimating uncertainty about flood damage calculated according to the Standard Method with HIS-SSM. It has been assumed that the maximum damage amount and the damage function are the most important sources of uncertainty when determining flood damage. The method developed links up with the current version of the Standard Method. Uncertainty is presented in the form of probability distributions. Uncertainty is



presented in terms of probability distribution. An extensive description of this study is included in Appendix F. The models give relatively little uncertainty in the damage total. Deviation of the 5th and 95th percentile of the expected value is 15-20% on average. The variation coefficient is usually about 10%. This can be explained by the small uncertainty about the maximum damage amount per object unit per damage category (NEI). For example, the damage category of single-family dwellings has the most influence on the total damage and has a variation coefficient of about 15%. This uncertainty is of the same order as the uncertainty in the flood damage total.



6 Determining the number of casualties

6.1 General

Various types of casualties can be distinguished. Since there are only methods available for determining the number of fatal casualties, and as the emphasis of this study lies on applying existing information, the Standard Method only involves determining the number of fatal casualties. Methods for determining the number of wounded persons, dead cattle and effected cattle are not included in the Standard Method. The function for determining the number of casualties during floods has been adjusted in relation to the previous version of the Standard Method, with new insights on the basis of research by DWW [Jonkman et al, 2004]. Casualties can occur in the Standard Method through: 1. high flood depths, 2. high rise rates (critical rise rates: 0.5 m/hour), and 3. high flow rates, close to the breach (critical flow rate: 2 m/s).

Furthermore, the possibility of preventive evacuation of people from an area can be considered in the Standard Method.

6.2 Calculating casualty numbers

6.2.1 Casualty function

Casualty numbers in the Standard Method are calculated using the factor f . These are the people not saved during rapid flooding. This factor is dependent on (1) flood depth, (2) rise rate and (3) flow rate. There are three distinct situations to which a separate damage function applies. Damage function (1) applies to the areas with a high flow rate (critical flow rate is greater than 2 m/s). Casualties can occur due to collapsing buildings as a result of high flow rates. Damage function (2) applies to areas where the rise rate is greater than 0.5 m/hour. People are no longer able to flee to higher ground as a result of rapidly rising water. Damage function (3) applies to remaining areas. Remaining areas are areas where casualties are not caused by high rise rates or flow rates, but by hypothermia, exhaustion or getting trapped. There is just one damage function for each location (grid cell). With:

applies to casualties caused by high flow rates (mostly close to breach):



applies to casualties caused by high rise rate:

applies to casualties in remaining areas:

Account is taken of high-rise dwellings when determining the number of casualties. Residents of high-rise dwellings have a greater chance of surviving a flood event; after all, they can move to the safety of higher floors. High-rise is defined in this case as buildings with more than three floors above ground. It is assumed that people in high-rise dwellings are safe and can be considered as having been evacuated. That is why residents linked to high-rise dwellings no longer appear in the SSM100NL2004 dataset of Standard Method 2004. Damage function implementation in Delphi source-code is included in Appendix E. It is possible to create output files for both maximum water level per location and flow rate per location with the current flood calculation software. These two files can be read in as a grid in HIS-SSM. Users must work out for themselves whether maximum occurring rise rate should be used or a rise rate measured at an arbitrary moment during the (fictitious) flood calculation. In the latter case, the user must decide at which moment during flood calculation rise rates must be executed (and which ones serve as input for HIS- SSM casualty calculation).

6.2.2 Evacuation factor

The Standard Method allows to include the fraction of the total number of people that have been evacuated ( f e ). The number of people remaining behind can be calculated per postcode using the EvacuatieCalculator (EC) [University of Twente, 2004]. These figures can be converted to the fraction of the total number of people preventively evacuated using the EvacuatiePreProcessor of HIS’s (HIS-EPP) as described in the User Manual. It is also possible to enter a factor manually. Factor f e can equal 0 in a situation without warning time and, as a result, without evacuation. In a situation with warning time and organised evacuation, this factor might rise to 1. The number of casualties calculated is multiplied in the HIS-SSM by ‘1-fe’ to include the influence of the evacuation possibilities.



7 Determining flood risk

7.1 General

The total damage and number of casualties per flood scenario in a (diked) area follow from the damage and casualty calculations. This determines the risk in combination with the conditional probability per flood scenario. There are various definitions of risk. Risk in the Standard Method Damage and Casualties is the result of flooding defined as the product of the probability of flooding and economic damage, or the number of casualties (risk= probability x result). The expectancy value of the damage or number of casualties is determined with the risk calculation. The general formula for calculating the damage or casualty number expectancy value is given as:

with: S = damage or casualties x = vector with all stochastic functions f = probability density function of x

The stochastic functions are the loads on flood protection systems, strength parameters of flood protection systems, model uncertainties, situations within the diked area, etc

7.2 Example of river situation

This section gives an example of a river situation. It is assumed that there are n dike sections in the diked area. The following probabilities are the result of a calculation made using the PC-ring and damage calculation: probability P(Fi), probability P(Fi and Fj) and damage S. P(Fi) is the probability of dike section i failure and P(Fi and Fj) is the probability of sections i and j both failing. In case a diked area consists of 2 sections, the following is available: P(F1) and P(F2), P(F1 and F2) and S1 and S2.

Event Probability Damage 1 dike section 1 fails and 2

does not P(F1) - P(F1 and F2) S1

2 dike section 2 fails and 1 does not

P(F1) - P(F1 and F2) S2

3 both dike section 1 and 2 fail

P(F1 and F2) ??

Table 7-1: Probability of dike section 1and/or 2 failing

It currently seems a good idea to choose the most unfavourable damage:



Another possibility is to divide into proportionality:

7.3 Example of sea situation

Things are a little different for sea dikes since the discharge effect does not occur. Because of this, the probability of dike section 1 and/or 2 actually failing simply means failure of both of them.

There is, at the most, only a time difference between the various dike bursts. This time difference can probably be ignored. Similar variants are conceivable for n dike sections. Firstly, all dike sections with equal damage are classified as a ‘super dike section’. Then one must apply to the super dike sections either the variant of the maxima (together with the Ditlevsen-variant’s failure probability calculation regarding flood risk, refer to [Vrouwenvelder; 1999]) or the proportional division.



8 Reference Barendregt, A., J.M. van Noortwijk, M.F.A.M. van Maarseveen, S.I.A. Tutert, M.H.P. Zuidgeest,

K.M. van Zuilekom, 2002. Evacuatie bij dreigende overstromingen. HKV LIJN IN WATER and Universiteit Twente. September 2002.

Barendregt, A. and J.M. van Noortwijk, 2004. Bepalen beschikbare en benodigde tijd voor evacuatie bij dreigende overstromingen. HKV LIJN IN WATER. June 2004.

Beijersbergen, J.A. and J.G. Westerhoven, 1991.Secundaire Waterkeringen, Inundatieberekeningen Hoeksche Waard, Resultaten; Province of South-Holland, Dienst Water en Milieu 26 January 1991.

Briene, M., Koppert, S., Koopman, A. and A.Verkennis, 2002. Financiele onderbouwing kengetallen hoogwaterschade; NEI B.V.; 2002.

Burrough P.A. and R.A. McDonell, 1998. Principles of Geographical Information Systems; Oxford University Press. 1998.

Central Bureau voor de Statistiek; Statistisch jaarboek 2000. January 2000.

CUR and TAW, 1990. Probabilistic design of flood defences, Report 141; CUR. June 1990

De Jonge, J.J., 1997. Tweede Waterkeringen Hoeksche Waard, Schademodellering, Bureaustudie; Waterloopkundig Laboratorium/WL. January 1997.

De Leeuw, A., F. den Heijer and J.J. de Jonge, 1998. Onafhankelijk onderzoek Markermeer, Technisch inhoudelijke en integrerende studie, deelrapport 4: schadebepaling bij inundatie; Waterloopkundig Laboratorium/WL. April 1998.

Dijkman, M., J. Huizinga, R. Waterman and A. Barendregt, 2004. HIS- Schade en Slachtoffer Module Versie 2.1, Systeemdocumentatie. HKV LIJN IN WATER and Geodan IT. November 2004.

Egorova, R., 2004. Uncertainty in flood damage estimation. HKV LIJN IN WATER and University of Delft. July 2004.

Huizinga, H.J., M. Dijkman, A. Barendregt and R. Waterman, 2004. HIS- Schade en Slachtoffer Module. Version 2.1. User manual. HKV LIJN IN WATER and Geodan. November 2004.

Jak, M., 1998. Projectplan Standaardmethodiek Schade- en slachtofferbepaling; Rijkswaterstaat, Dienst Weg- en Waterbouwkunde. August 1998.

Jonkman et al, 2004. Methode voor de bepaling van het aantal slachtoffers ten gevolge van een grootschalige overstroming - Onderbouwing van de slachtofferfuncties voor de Standaardmethode Schade en Slachtoffers als gevolg van overstromingen. Rijkswaterstaat, Dienst Weg- en Waterbouwkunde. May 2004.

Jongerius, F.N., 1997. Handleiding voor gebruik legenda’s bij topbestanden; Meetkundige Dienst, afdeling GAG. November 1997.

Kok, M. , 1997. Schadefuncties buitendijkse gebieden; HKV LIJN IN WATER. October 1997.

Maarseveen, M., M. Zuidgeest, K. van Zuilekom, 2004. De Evacuatie Calculator (EC), versie 1.0. Achtergronden, modelfilosofie en modellering. Universiteit Twente, Afdeling Verkeer, Vervoer en Ruimte. Enschede. April 2004.



Maarseveen, M., M. Zuidgeest, K. van Zuilekom, 2004. De Evacuatie Calculator (EC), versie 1.0. Technical Documentation. Universiteit Twente, Afdeling Verkeer, Vervoer en Ruimte. Enschede, April 2004.

Meetkundige Dienst, 1998. Atlas Basispakket Geo-Gegevens, Digitale geografische basisbestanden voor het Ministerie van Verkeer en Waterstaat. February 1998.

Rand European-American Center for Policy Analysis, 1993. Investigating Basic Principles of River Dike Improvement; Safety Analysis, Cost Estimation and Impact Assessment. 1993.

Snuverink, M.A.M. et.al., 1998. Schade bij inundatie van buitendijkse industrie. Tebodin. December 1998.

TNO Bouw, 1989. Bijlage I van rapport IBBC BI-89-224. December 1989.

Vrisou van Eck, N., Kok, M. and A.C.W.M. Vrouwenvelder, 1999a. Standaardmethode Schade en Slachtoffers als gevolg van overstromingen, deel 1: Standaardmethode. December 1999.

Vrisou van Eck, N., Kok, M. and A.C.W.M. Vrouwenvelder, 1999b. Standaardmethode Schade en Slachtoffers als gevolg van overstromingen, deel 2: Achtergronden. December 1999.

Vrouwenvelder, A.C.W.M., 1997a. Tweede Waterkeringen Hoeksche Waard, Voorbereiding TAW-advies, Evaluatie schade/slachtofferberekening; TNO. February 1997.

Vrouwenvelder, A.C.W.M., 1997b. Case Study Kabeljauwsche Waard. Risico-analytische benadering.; TNO. March 1997.

Vrouwenvelder, A.C.W.M., 1999. Theoriehandleiding PC-Ring, Deel C: Rekentechnieken, 3e concept; TNO Bouw. January 1999.

Vrouwenvelder, A.C.W.M. and C.M. Steenhuis, 1997. Tweede Waterkeringen Hoeksche Waard. Berekening van het aantal slachtoffers bij verschillende inundatiescenario’s. TNO. February 1997.

Vrouwenvelder, A.C.W.M. and P.H. Waarts, 1994. TAW-E Rapport Risico-Analyse. TNO. January 1994

Waarts, P.H., 1992. Methode voor de bepaling van het aantal doden als gevolg van inundatie; TNO. September 1992.

Waterloopkundig Laboratorium and RAND European-American Center for Policy Analysis, 1993. Toetsing uitgangspunten rivierdijkversterkingen, deelrapport 1: Veiligheid tegen overstromingen. 1993.

Waterloopkundig Laboratorium\WL, Bouwdienst Rijkswaterstaat and Dienst Weg en Waterbouwkunde Rijkswaterstaat, 1994. Onderzoek Watersnood Maas, Deelrapport 9, Schademodellering. December 1994.

Wit, A.J.W. de, Th.G.C. van der Heijden and H.A.M. Thunnissen, 1999. Vervaardiging en nauwkeurigheid van het LGN3-grondgebruiksbestand. SC-DLO. 1999.

WLlDelft hydraulics, TNO Bouw and Bouwdienst Rijkswaterstaat, 1999. Standaardmethode Schade- en Slachtofferbepaling, Definitiestudie. March 1999.



Other sources

Bridgis BV; CataloGIS

www.cbs.nl

www.ncgi.nl

www.geodan.nl

www.bridgis.nl

www.tdn.nl

www.esrinl.com

www.wldelft.nl



Appendices



Appendix A Definitions and abbreviations

General glossary New value The purchase value of an object Flood scenario The conditions under which a flood event occurs. Damage All financial and/or economic consequences of a flood. Casualties All fatal casualties resulting from drowning during a flood. Replacement value The amount needed to replace an object with a comparable object.



Appendix B Companies

A distinction is made in the Dunn & Bradstreet file between the following company types. Description SIC- Code

SIC-Code

min

eral

ext

ract

ion

indu

stry

utili

ties

Con

stru

ctio

n

trade

/cat

erin

g

trans

port

and

com

mun

icat

ion

bank

s an

d in

sura

nce

care

pro

visi

on, o

ther

gove

rnm

ent

Cultivation 100-900

Extraction 1000-1400 X

Contracting 1500-1700 X

Manufacturing 2000-3900 X

Transport Communication

4000-4800 X

Energy 4900 X

Wholesale and Retail Trade

5000-5900 X

Banks and insurance 6000-6400 X

Real estate 6500-6600 X

Holdings 6700 X

Hotels, guesthouses etc.

7000 X

Services 7200-7400 X

Recovery services 7500-7600 X

Film 7800 X

Entertainment 7900 X

Care provision, other 8000-8100 X

Educational institutions 8200 X Social services 8300 X Museums

8400

X

Other government services

8500-9900 X

Damage category and D&B file cross reference table



Appendix C Required files

Below follows an overview of the files needed for applying the Standard Method Damage and Casualties. Per file the location from which it is available is given. File Available 6 PPC file Basispakket Geogegevens

(Geo data standard package) CBS Bodemgebruik Basispakket Geogegevens

(Geo data standard package) Nationaal Wegen Bestand Basispakket Geogegevens

(Geo data standard package) NS-Spoor Basispakket Geogegevens

(Geo data standard package) Bridgis woontype aankoop (purchase) Geo-Marktprofiel personen aankoop (purchase) Dunn & Bradstreet bedrijven aankoop (purchase) WIS Basispakket Geogegevens

(Geo data standard package)



Appendix D Delphi implementation of dwelling damage functions

Single-family dwellings and farms //========================================= Function BOERTIEN_inboedels (d,u,w,r,s,ukr: Double):double; var p, rs, s1:Double; begin if d <= 0 then rs := 0 else if d>=5 then rs := 1 else if u > 0.25*ukr then rs := 1 else begin if (s<>0){storm} then p:= 0.8E-3 * power(d,1.8) * r else p:=0; if d<=1 then s1 := -0.470*sqr(d) + 0.940*d //0,1 else if d<=2 then s1 := 0.030*d + 0.44 //1,2 else if d<=4 then s1 := 0.005*sqr(d) + 0.135*d + 0.21 //2,4 else s1 := -0.170*sqr(d) + 1.700*d - 3.25; //4,5 rs := max(0,min(1,s1)); rs := p*1+(1-p)*rs; end; result := max(0,min(1,rs)); end; //========================================= Function BOERTIEN_opstal(d,u,w,r,s,ukr: Double):double; var p, rs, s1 :Double; begin if d <= 0 then rs := 0 else if d>=5 then rs := 1 else if u > 0.25*ukr then rs := 1 else begin if (s<>0){storm} then p:= 0.8E-3 * power(d,1.8) * r else p:=0;

if d<2 then s1 := 0.005*sqr(d) + 0.045*d //0,2 else if d<4 then s1 := 0.045*sqr(d) + 0.015*d - 0.1 //2,4 else s1 := -0.32 *sqr(d) + 3.2 *d - 7; //4,5 rs := max(0,min(1,s1));

rs := p*1+(1-p)*rs; end; result := max(0,min(1,rs)); end; //========================================= Function SSM_EengezinswoningenEnBoerderijen (d,u,w,r,s,ukr : Double):double;stdcall;



var f:double; begin //Boertien_woningen + Boertien_inboedels f:=215500/315500; result:=f*Boertien_opstal(d,u,w,r,s,ukr) +(1-f)*Boertien_inboedels(d,u,w,r,s,ukr); end; //=========================================

Low-rise dwellings //=========================================

begin if d <= 0 then α := 0 else if u > 0.25*ukr then α := 1 else if s <> 0 {ja} then begin P:=(0.8E-3 * power(d,1.8) * r) else P:= 0 begin s1 := P+(1-P)*(1 - sqr(sqr((1 - max(0,min(d,6))/6)))); α := max(0,min(1,s1)); End End; result:= α end

//========================================= Intermediate dwellings //=========================================

begin if d <= 0 then α := 0 if (u>ukr)) then α := 1 else if s <> 0 {ja} then begin P:=((0.8E-3 * power(d,1.8) * r > 0.5) else P:=0 begin s1 := P+(1-P)*(1 - sqr(sqr((1 - max(0,min(d,12)/12)))); α := max(0,min(1,s1)); End End; result:= α end



//========================================= High-rise dwellings //=========================================

begin if d <= 0 then α := 0 else if u > ukr then α := 1 else if s<>0 {ja} then begin P:=((0.4E-3 * power(d,1.8) * r) else P:=0 begin s1 := P+(1-P)*(1 - sqr(sqr((1 - max(0,min(d,18))/18)))); α := max(0,min(1,s1)) End End; result:=α;

end //=========================================



Appendix E Delphi implementation of casualty function

//========================================= The functions are implemented in the DLL of HIS-SSM version 2.1 (SSMFUNC.dll) in addition to the existing casualty function. Coding of the DLL functions is as follows: Function SSM_Slachtoffers_DWW2004(d,u,w,r,s,ukr: Double):double;

{d = waterdiepte

u = stroomsnelheid

w = stijgsnelheid}

var

rs :double;

begin

If ((d * u) >= 7) And (u >= 2) Then

rs := 1

Else If (w < 0.5) And (d > 0) Then

begin

rs := 1.34E-3*EXP(0.59*d);

rs :=min(max(rs,0),1);

end

Else If (w >= 0.5) And (d > 0) And (d < 1.5) Then

begin

rs := 1.34E-3*EXP(0.59*d);


end

Else If (w >= 0.5) And (d >= 1.5) And (d <= 4.7) Then

begin

rs := 1.45E-3*EXP(1.39*d);


end

Else If (w >= 0.5) And (d > 4.7) Then

rs := 1

Else

rs := 0;

result := rs;

end;

Supplementary to the published casualty function, the casualty factor is limited to the field [0.1] by the addition of extra code. //=========================================



Appendix F Uncertainty in flood damage estimation

This appendix contains an extensive summary of the Regina Egorova study ‘Uncertainty in flood damage estimation’ [Egorova, 2004].

Summary – ‘Uncertainty in flood damage estimation’

Floods cause much damage worldwide each year. Projects are implemented to increase safety from flooding along large rivers and to reduce the chances and consequences of flooding. Studies are being carried out to improve current operational methods for both the design of dams, dikes or weirs and flood risk estimation. Despite efforts to better predict and prevent floods and their consequences, absolute safety from high-water floods can never be guaranteed. The chances and consequences of flooding in a number of diked areas in the Netherlands are being studied in the research project ‘De Veiligheid van Nederland in Kaart’ (VNK). This research is part of the VNK project and examines the consequences of a flood and its associated uncertainties. The consequences of a flood (in this case damage and casualties) can be established using the Schade en Slachtoffermodule van het Hoogwater Informatie Systeem- HIS-SSM (Damage and Casualties module of the High-water Information System). Damage expectancy value is established using the method and data implemented in the HIS-SSM. This method, the so-called Standard Method Damage and Casualties, is a deterministic one for establishing the consequences (damage and casualties) of flooding in which uncertainty is not explicitly included. The Standard Method is based on national statistical databases, hydraulic information and damage functions (which are a function of water depth, flow rate and rise rate). These damage functions and associated maximum damage amounts are based on both expert assessment and available (statistical) information.

Objective The study’s objective is to quantify the uncertainty in flood damage, given a certain flood scenario. A method has been developed in this report for estimating the uncertainty in flood damage, the method then being applied to a diked area. This method links up to the current version of the Standard Method (version 2.0). The approach is based on the same principles (physical division) as the HIS-SSM. Uncertainty is presented in terms of probability distribution.

Standard Method Damage and Casualties The 'Standard Method Damage and Casualties’ consists of all the steps which need to be completed to establish flood risk per diked area with its corresponding flood probability. The total damage and casualty numbers per flood scenario in a diked area follow from the damage and casualty calculations. Monetary damage is divided into direct flood damage, direct damage resulting from interruption of operations and indirect damage in the area itself resulting from flooding. Flood damage is calculated for various types of land use (damage categories), i.e. agriculture, dwellings, vehicles, infrastructure etc. These damage categories are classified by the number of m2, objects, metres or jobs.



Damage in the Standard Method is calculated using the following formula .

m n

i ij iji j

S S nα= ∑ ∑

with αij = damage factor damage category i in cell j nij = number of units in damage category i in cell j Si = maximum damage per unit in damage category i n = number of grid cells m = number of damage categories

Damage factor is derived from a damage function. A damage function is defined per damage category. The damage category is defined as a fraction of the maximum potential damage as a function of hydraulic conditions, such as flood depth and flow rate. Maximum damage amounts included in the Standard Method per category are based on a study by the Nederlands Economisch Instituut (NEI). The total damage in a diked area is the sum of direct flood damage, direct damage as a result of interruption of operations and indirect damage in all common categories.

Approach and results Developing a method for establishing uncertainty in flood damage (distribution of uncertainty) is limited to the sources of uncertainty expected to contribute most to total uncertainty. Assuming that the flood scenario is given, the following are sources of uncertainty: • uncertainty in maximum damage • uncertainty in damage function

Firstly, insight was gained through literature search into methods for uncertainty estimation when establishing flood damage. A method is then developed to establish the uncertainty distribution of the flood damage. The method is then applied to case study dijkring 14 – Centraal Holland. This diked area was chosen because it has the largest population density and the highest economic value. The approach followed consists of the following steps: 1. Modelling of the uncertainty in the maximum damage amount 2. Modelling of the uncertainty in the damage function 3. Modelling of the spatial dependence of the damage 4. Performing a sensitivity analysis

1. Modelling of the uncertainty in the maximum damage amount Maximum damage, also called maximum damage amount, means the maximum potential damage per object unit (i.e. dwelling, section of road). The NEI report, in which damage amounts are underpinned, is used to model the maximum damage amount. Besides the average expected maximum damage amount for the various categories per unit, the lower limit (5th percentile) and upper limit (95th percentile) are also given in this report. The 5th and the 95th percentile have an underspending chance of 5% and an overspending chance of 5% respectively.

In order to represent the uncertainty, a certain chance distribution has been chosen and the distribution’s parameters estimated. Various probability distributions are analysed (gamma distribution, generalised gamma distribution, triangular distribution and beta distribution). To



describe the uncertainty in the maximum damage amount, the most suitable distribution has been chosen, i.e. the triangular distribution, given the percentiles and expected values. 2. Modelling of the uncertainty in the damage function The damage function gives the relation between damage and hydraulic characteristics of a flood (water depth, flow rate) as a fraction of the maximum damage amount per category. Beta distribution has been used to represent uncertainty in the damage function. The reason for this is that beta distribution is especially suitable for representing uncertainty in variables greater than 0 and less than 1 (such as chances and fractions). As far as the beta distribution is concerned, the expectation is equal to the HIS-SSM outcome, and the variance is proportional to a certain coefficient. The greater the coefficient, the greater the uncertainty in the damage function. The beta chosen for the probability distribution depends on this coefficient and has a value between 0 and 1.

3. Modelling of the spatial dependence of the damage To establish total damage in an area, damage amounts are summated in the Standard Method for the various cells per category. Flood damage is established per cell in HIS-SSM (100 meter*100 meter). Two sources of uncertainty are modelled in the previous steps: the maximum damage amount with triangular distribution and the damage function with beta distribution. The maximum damage amount does not differ per cell and is only dependent on the damage category. The damage function, on the other hand, varies for each category per cell. To summate the damage amounts for a diked area including the uncertainty per cell, it must be known to what degree the damage functions for the different cells are spatially dependent.

Three different models are calculated for this. These models have a different approach to the dependence between damage in the grid cells. The first model assumes complete spatial dependence of the damage functions in the cells of the flooded area. The second model assumes independence between damage functions in the cells of the flooded area. The third model is based on a classification of water depths in different classes and complete dependence between the cells within a class and complete independence of the cells between the different classes. A comparison has been made of the three dependence models. The method developed for this, for obtaining probability distribution of flood damage, is programmed in MATLAB and applied to dijkring 14, Zuid–Holland. Monte-Carlo-simulation, with just 250 drawings due to the calculation duration, is applied to model the uncertainty of the maximum damages and damage functions. The result is expressed in a probability distribution of flood damage. A distinction is also made in three flood scenarios: a water level of 2m+NAP, 0m+NAP, 2m-NAP. The three models (complete dependence, independence and partial dependence) show the same tendency in the probability distribution of flood damage. There is a difference though in the size of the spread of potential damage amounts, that is the reliability. This effect is shown in the figures below (a,b,c). The results are shown for application of the three dependence models for estimating damage from a flood with a water level of 2m+NAP. The calculation of this flood scenario with HIS-SSM for dijkring 14 gives a total damage of € 283 billion. Figure (a) shows the probability distribution of flood damage in dijkring 14, calculated assuming complete dependence. Figure (b) shows the probability distribution of flood damage in dijkring 14, assuming independence. Figure (c) shows the results of the third model, in which damage amounts per cell are completely dependent for independent water depth classes. The figures show that the complete dependence model results in the largest spread of total damage amounts. The independence model has the smallest spread. The reason why the uncertainty is greater with complete dependence versus



independence is as follows: as far as complete dependence is concerned, extremely large damage in one grid cell is accompanied by extremely large damage in another grid cell. However, with independence, large and small damages alternate causing uncertainty to become more ‘averaged out’. Furthermore, the figures show that the deviation from the expected value in relation to damage established with HIS-SSM is below 2%. This is mainly caused by statistical fluctuation resulting from the Monte-Carlo method.



The results of the three flood scenarios are shown in the table below. The table gives the expected damage per combination of flood scenario and uncertainty model, the 5th and the 95th percentile, the standard deviation and the variation coefficient. The variation coefficient is defined as the ratio of the standard deviation and the expectation.

Damage (billion €) Water level (scenario)

Damage HIS (billion €)

Model* expectation 5% 95%

Standard dev. (billion €)

Variation coefficient

2 m+NAP 283

1

2

3

288

287

286

245

261

252

333

313

321

26.6

16.3

20.1

0.092

0.057

0.070

0 m NAP 141

1

2

3

152

151

146

127

137

128

181

166

167

16.1

8.8

12.2

0.105

0.058

0.084

2 m-NAP 57

1

2

3

61

61

61

46

55

52

78

66

71

9.9

3.3

5.9

0.163

0.055

0.097 *model 1 = complete dependence, model 2 = independence, model 3 = partial dependence

The table shows that, of all the models, the third scenario (2m-NAP) has the largest spread compared to the other two flood scenarios. This larger spread can be explained through the selected probability distribution of the damage functions. It has been assumed here that uncertainty is small for high and low water depths, but that it is large for average water depths (between 1 and 4 metres). A flood scenario with a water level of 2m-NAP fits a water depth of 1 to 4 metres. 4. Performing a sensitivity analysis The influence of the two uncertainty sources in damage estimation is examined in the first sensitivity analysis. In this context, the probability distribution of total damage for the following two situations was established: a. the damage function is given and the only source of uncertainty is the maximum damage

amount b. the maximum damage amount is given and the only source of uncertainty is the damage

function

On the basis of the probability distributions obtained, it is concluded that uncertainty in the damage function has no effect on the probability distribution of the total damage amount for the uncertainty model. Uncertainty is mainly established by the maximum damage amount. A second sensitivity analysis is performed in which the influence is examined of the degree of uncertainty in the damage function on the total damage amount. In the developed model in this study, it has been left to the user to indicate how uncertain the damage function is by specifying a certain coefficient. Various values are entered for this coefficient in the sensitivity analysis. It follows from this that the coefficient chosen influences the probability distribution of the flood damage to an important degree. A third sensitivity examined is the effect on the probability distribution of damage if the maximum damage amounts are spatially dependent for all damage categories, instead of independent. From the results, it can be concluded that, if both the maximum damage amount and the damage function are uncertain (model with complete dependence and model with partial dependence), the



differences with the original model, in which the damage amounts are independent, are not great. A difference can clearly be seen for the independent damage functions model. This can be explained as follows: the uncertainty of the damage function has no significant influence so that probability distribution of the total damage is established particularly by uncertainty in the maximum damage amount.

Conclusions and recommendations A method has been developed in this report for estimating uncertainties in flood damage. The method is applied to one diked area. It has been assumed that the maximum damage amount and the damage function are the most important sources of uncertainty when determining flood damage. The method developed links up with the current version of the Standard Method. Uncertainty is presented in the form of probability distributions. An important aspect in modelling probability distribution of damage, is the modelling of the spatial dependence of the damage. It can be concluded from the analysis’s results that the extremes for establishing flood damage are (with a certain degree of reliability) formed by the models with complete spatial dependence and independence. The model with spatial independence of the cells gives a too reliable estimate (a small spread) of flood damage and does not take sufficient account of uncertainty in the damage functions. Complete spatial dependence results in a large spread and an approach which is on the 'safe side'. It is therefore recommended to assume the model in which damage amounts per cell are completely dependent for independent water depth classes, as it gives more realistic results. The models give relatively little uncertainty in the damage total. Deviation of the 5th and 95th percentile of the expected value is 15-20% on average. The variation coefficient is usually about 10%. This can be explained by the small uncertainty about the maximum damage amount per object unit per damage category (NEI). For example, the damage category of single-family dwellings has the most influence on the total damage and has a variation coefficient of about 15%. This uncertainty is of the same order as the uncertainty in the flood damage total. Furthermore, the following recommendations are made for further research: • It is recommended that the number of drawings is increased to allow a more accurate

calculation for the probability distributions of the total damage. • It is recommended to obtain the opinion of experts for improving estimation of uncertainty in

damage functions. This is initially due to uncertainty being estimated by the project team and not on the basis of data.

• It is recommended to improve the current model by using information from the regional system and historical flood data.

• It is recommended to give more attention to modelling of the spatial dependence in damage. Assumption of dependence is definitely not appropriate in this situation.

DWW 2005 009 Standard method 2004 Damage and Casualties...

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