Vulnerability Analysis in the Körös-corner flood area along the Middle-Tisza River

(1)

Integrated Flood Risk Analysis

and Management Methodologies

Vulnerability Analysis in the Körös-corner

flood area along the Middle-Tisza River

PILOT STUDY APPLICATION OF GENERAL VULNERABILITY

ANALYSIS TECHNIQUES

Date June

2008

Report Number

T22-08-03

Revision Number 1_5_P01

Deliverable Number: D22.3 Due date for deliverable: June 2008 Actual submission date: July 2008

Task Leader VITUKI / HEURAqua

FLOODsite is co-funded by the European Community

Sixth Framework Programme for European Research and Technological Development (2002-2006) FLOODsite is an Integrated Project in the Global Change and Eco-systems Sub-Priority

Start date March 2004, duration 5 Years Document Dissemination Level

PU Public PU

PP Restricted to other programme participants (including the Commission Services) RE Restricted to a group specified by the consortium (including the Commission Services) CO Confidential, only for members of the consortium (including the Commission Services)

Co-ordinator: HR Wallingford, UK

Project Contract No: GOCE-CT-2004-505420 Project website: www.floodsite.net

(2)

D

OCUMENT

I

NFORMATION

Title

Vulnerability analysis in the Körös corner flood area along the Middle Tisza River – Pilot study application of general vulnerability analysis techniques

Lead Author Sándor Tóth (HEURAqua)

Contributors Dr. Sándor Kovács (Middle-Tisza DEWD, Szolnok, HU)

László Kummer (Middle-Tisza DEWD, Szolnok, HU) Distribution Public

Document Reference T22-08-03

D

OCUMENT

H

ISTORY

Date Revision Prepared by Organisation Approved by Notes

30/01/08 1.0 S. Toth HEURAqua

05/03/08 1.1 S. Kovacs M-T DEWD S. Toth

24/06/08 1.23 L. Kummer M-T DEWD S. Toth 27/06/08 1.24 L. Kummer M-T DEWD S. Toth 02/07/08 1.25 S. Kovacs M-T DEWD S. Toth

07/07/08 1.31 P. Bakonyi VITUKI 08/07/08 1.4 S. Toth HEURAqua P. Bakonyi 21/05/09 1_5_P01 J Rance HR

Wallingford

Formatting for publication

A

CKNOWLEDGEMENT

The work described in this publication was supported by the European Community’s Sixth Framework Programme through the grant to the budget of the Integrated Project FLOODsite, Contract GOCE-CT-2004-505420.

D

ISCLAIMER

This document reflects only the authors’ views and not those of the European Community. This work may rely on data from sources external to members of the FLOODsite project Consortium. Members of the Consortium do not accept liability for loss or damage suffered by any third party as a result of errors or inaccuracies in such data. The information in this document is provided “as is” and no guarantee or warranty is given that the information is fit for any particular purpose. The user thereof uses the information at its sole risk and neither the European Community nor any member of the FLOODsite Consortium is liable for any use that may be made of the information.

(3)

T22_08_03_Vulnerability_Analysis_PilotStudy _D22_3_V1_5_P01 21 May 2009

S

UMMARY

The objective of this report is a pilot study application of general vulnerability analysis techniques developed in FLOODsite sub-theme 1.3, in one of the flood cells to identify the effectiveness of flood management strategies.

Chapter 1 describes the preconditions of the work, Chapter 2, based on the results of the analysis of the preconditions justifies to perform an indicative vulnerability analysis (or, damage evaluation) in macro scale level for a flood area of limited extent only. The introduction and characterisation of the selected flood ara is given in Chapter 3.

Results of the work performed are demonstrated in Chapter 4 of this report,

− we developed the flood hazard map of the Körös corner flood area, indicating the distribution of flood depth,

− determined the extension of land use categories and the distribution of the value of assets at risk in the Körös corner flood area (mean estimation),

− developed relative damage functions,

− calculated and determined the distribution of flood event damages for three different scenarios, the floods of 200 year, 100 year and 50 year recurrence period (or 0.5% - 1.0% and 2.0% probability), − calculated the annual average damage

− documented the uncertainties.

(4)

(5)

C

ONTENTS Document Information ii Document History ii Acknowledgement ii Disclaimer ii Summary iii Contents v 1. Introduction ... 1

1.1. Data on inundation characteristics... 1

1.2. Land use data ... 1

1.3. Value of assets at risk ... 1

1.4. Flood damage data... 1

2. Selection of an appropriate approach ... 2

3. Brief description of the selected flood area... 3

3.1. Topography of the Körös corner flood area... 4

3.2. Land use characteristics... 4

4. Risk assessment and mapping ... 6

4.1. Modelling the inundation... 6

4.1.1. Digital elevation model ... 6

4.1.2. Hydraulic input... 6

4.1.3. Inundation modelling ... 8

4.2. Determination of economic risk ... 9

4.2.1. Value of assets at risk... 9

4.2.2. Relative damage functions ... 11

4.2.3. Damage calculation... 12

4.2.4. Documentation of uncertainties ... 17

4.2.5. Calculation of Annual Average Damage (AAD) ... 18

5. Conclusion... 18

6. References ... 20

Tables

Table 1. Extension of land use categories and value of assets in risk in the Körös corner flood

area (mean estimation) 10

Table 2. Damages for the 200-year flood event in the Körös corner flood area (mean estimation) 13 Table 3. Damages for the 100-year flood event in the Körös corner flood area (mean estimation) 13 Table 4. Differences between the results of 200-years and 100-years flood scenarios: 15 Table 5. Damages for the 50-year flood event in the Körös corner flood area (mean estimation) 15

Figures

Fig. 1. Location of the 2.86 Körös corner flood area 3 Fig. 2. Topographical map of the 2.86 Körös corner flood area 4 Fig. 3. Land use map of the 2.86 Körös corner flood area based on CLC 50 images 5 Fig. 4. Flood hydrograph of the 200-year (p=0,5 %) flood of River Tisza 6

(6)

at the confluence of River Körös 6 Fig. 5. Filling curve in the Körös flood area, p=0.5% 7 Fig. 6. Flood hydrograph of the 100-year (p=1.0 %) flood of River Tisza at the confluence of River

Körös 7 Fig. 7. Filling curve in the Körös flood area, p=1.0% 7 Fig. 8. Flood hazard map of the Körös corner flood area in case of p=0,5% flood (86.20

m flood level) 8

Fig. 9. Distribution of the value of assets at risk in the Körös corner flood area (mean estimation) 11 Fig. 10. Relative damage functions for residential buildings 12 Fig. 11. Relative damage functions, industrial, commercial and agricultural units 12 Fig. 12. Damages for the 200-year flood event in the Körös corner flood area (mean estimation) 14 Fig. 13. Damages for the 100-year flood event in the Körös corner flood area (mean estimation) 16 Fig. 14. Uncertainties in the relative damage functions 17 Photos

(7)

1. Introduction

The objective of this report is a pilot study application of general vulnerability analysis techniques developed in FLOODsite sub-theme 1.3, in one of the flood cells to identify the effectiveness of flood management strategies.

During the preparation for this analysis, to enable a realistic objective setting, first we had to review and evaluate data availability along the Tisza pilot site from Szolnok to Csongrád. The floodplain of this 88.4 km long river section consist of 6 separate flood area (floodplain basin) with a total extension of 563.42 km2_{s accommodating some 110 thousand inhabitants in 15 settlements, including Szolnok}

itself, an industrialised town.

1.1. Data on inundation characteristics

In Hungary there are flood plain maps available produced in 1976-77 in scales of 1:50 000 and 1:100 000. (later in 1:500 000 as well) showing the extent of inundation of 1 in 100 as well as 1 in 1000 year floods. The maps also show the major transportation infrastructures, contours of settlements. However, these flood plain maps do not provide any information on elements of hazard like flood depth, duration or velocity (the latter is less important being our river valleys and floodplains rather flat). The maps are available in paper format only.

Furthermore, in Hungary no accurate digital elevation model is available yet for the protected flood areas. Ortophotos were produced only for the flood bed in the recent past and for the territories of the selected flood detention basins along the River Tisza. DEMs for these limited areas were made to support the 1D modelling of the river and the detention basins. An accurate survey of the Hungarian floodplains, combining ortophotos produced for the whole country by FÖMI1_{with new LiDAR}

measurements, as a result of which digital maps and DEMs of the required accuracy will be available, will start next year only.

Lack of data related to flood depth prevents us from undertaking the whole pilot area, therefore a smaller separate flood basin must be selected within it, for which DEM can be produced within the timeframe and budget conditions of this project.

1.2. Land use data

In Hungary the CORINE Land Cover CLC 100 and CLC 50 is available, the scale of the latter corresponds to that of the existing floodplain maps. No other, more detailed land use products were produced in the geographical area. of interest, therefore detailed investigation and analysis is not possible.

1.3. Value of assets at risk

Data related to the value of assets are available in statistical annuals, compiled by the Hungarian Central Statistical Office, like the Hungarian Statistical Yearbook, Regional and County Statistical Yearbooks, etc. The basis of these datasets is collected and reported on settlement level, no address-point data or other detailed investigations are available for the pilot site.

1.4. Flood damage data

It is important to note that 97% of the floodplains are protected by dikes in Hungary and the emergency operation even against extreme floods is successful in the vast majority of the cases. Despite this, quite a number of dike failures have been recorded even in the past 50 years (L. Nagy – S. Tóth (2004), however, also as a result of the developed confinement plans and perfectly organized implementation of those, inundation of settlements rather rarely occurred. (1956, 1965, 1970, 2001). From the historical databases and archives data on inundated area and settlements, sometimes also the number of damaged and destroyed houses, number of evacuated, total sum of losses can be extracted

(8)

but no details on the damages caused in individual properties. Additionally it is important to note that in the socialist era, before changing the political regime, rules of statistical data collection was also different, and the shift for the market oriented economics in 1989 brought significant changes in property conditions including the owners. These circumstances made the majority of previous data void.

No valid conclusion can be drawn for future measures from the existing unreliable and contradictory historical damage data. There was no organised systematic collection of flood damage data from which relations between flood depth and damages for different properties, land use categories could be derived.

2. Selection of an appropriate approach

Based on the information on pre-existing data related to inundation characteristics, land use patterns, value of assets at risk and availability of damage functions, and taking also into consideration the guidance for selection of an appropriate approach illustrated in Fig. 3.4 of the T9_06_01 Flood damage guideline. The followings can be undertaken in case of this pilot study

Spatial scale: is limited by the need to produce a DEM within the timeframe and budget of the project and should not exceed 100-130 km2_{flood area.}

Objective and accuracy: based on the availability of resources and data, despite the smaller extension of the selected flood area, we can undertake to perform an indicative vulnerability analysis (or damage evaluation) with relatively low level of accuracy only.

Concerning the pre-existing data, we have approximate values and land use categories (CLC-50), enabling us to select the macro 1 approach.

During selection of the flood area to be investigated, experiences of the extreme flood of 2006 were also taken into consideration. In this respect we remind the reader on the characterisation of that flood given in our report T-22-07-01 on River capacity improvement and partial floodplain reactivation along the Middle-Tisza.

(9)

At the confluence of the Tisza and Körös rivers flood stages of 1 in 200 year developed with an extreme duration, threatening the Körös corner flood area with dike breach at 7 different locations.

3. Brief description of the selected flood area

The selected flood area (Fig. 1. and 2) is situated in a rural environment at the confluence of Tisza and Hármas-Körös rivers. It covers the inner area of four settlements (Tiszaug, Tiszasas, Csépa and Szelevény) and the outer area of Tiszainoka, Tiszakürt and Kunszentmárton. Population of the flood area is in the range of 5,000 capita while the endangered assets in the settlements are in the magnitude of 100 million Euros, in the agriculture 20 million Euros.

(10)

3.1. Topography of the Körös corner flood area

The rather triangle shaped flood area is fully protected by the left bank flood embankments of the River Tisza from West-South-West and the right bank dikes of the River Körös from the East. The southern part of the flood area is characterised by very low, 80-82 m a.s.l. elevations while the majority of northern edge of the flood area forms high ground (85-87-88 m.a.s.l.) accommodating the majority of the inner area of 3 settlements, namely that of Tiszaug, Tiszasas and Csépa. The last settlement to the East, Szelevény is situated at somewhat lower ground, 83-84 m.a.s.l., with some smaller parts over 85-86 m.a.s.l. The inner area of Kunszentmárton is over the Hármas-Körös River. From the North the flood area is bordered by the Kecskemét-Kunszentmárton railway and the road No. 44.

Fig. 2. Topographical map of the 2.86 Körös corner flood area

3.2. Land use characteristics

Land use patterns based on Corine Land Cover 1:50,000 (CLC 50) are shown in Fig. 3. Prevailing land use category or type of activity at the lower elevations is agricultural, mainly arable land but there are also some complex cultivation patterns, orchards and pastures as well. Forests are rather rare in the

(11)

protected flood area but are dominant in the floodway of the rivers. These forests are composed of broad-leaved trees with rather dense under vegetation. There are also some wetlands and lakes, mainly the oxbows of the River Tisza and Körös.

Industrial activity is restricted to the eastern edge of the flood area and is situated on rather higher elevation in the periphery of Kunszentmárton but still in the risk zone of potential inundation in case of failure of the defences.

Commercial (retail, catering and hotel trade) units are placed on higher ground mainly in the inner area of the settlements. Hotel trade is developing in the area, mainly in Tiszaug, where not only guest houses but a three-star hotel with broad selection of leisure facilities and services are available.

The urban fabric of the settlements shows discontinuous rural character and is composed by detached houses with gardens. The average plot size is 655 m2. Along the banks of the larger two oxbows recreation houses have been erected. These are also detached houses, sometimes bungalows. Several farm houses can also be found in the agricultural land.

(12)

4. Risk assessment and mapping

4.1. Modelling the inundation

4.1.1. Digital elevation model

With due regard to the timeframe and budget conditions of this project, we decided to apply ELK-DDM-5 product of FŐMI, our National Institute for Land Survey and Remote Sensing. ELK-ELK-DDM-5 is based on the digital database of the 1:10,000 scaled digital topographical maps. This database contains TIN and GRID format elevation models derived from vectorised contour lines. The DEM is improved by stereographic evaluation. Grid size is 5m * 5m, horizontal accuracy mx =0,6-0,7 m; my = 0,6-0,7 m, vertical accuracy mz= ±0,70 m. In order to improve vertical accuracy, the DEM was improved by additional GPS survey at sensitive and critical parts of the flood area, where the more valuable assets are accumulated.

4.1.2. Hydraulic input

We decided to assess flood hazards and risks for three alternatives. One of the cases was the actual spring flood of 2006, height and duration of which proved to be a 200-year event (p=0.5%). Although the integrity of the defences during that flood could be defended by extraordinary emergency interventions, for the sake of this analysis we assumed a breach near the confluence. The flood hydrograph and the effect of the breach on the river flood is shown in Fig.4.

Fig. 4. Flood hydrograph of the 200-year (p=0,5 %) flood of River Tisza at the confluence of River Körös

Filling the flood basin is illustrated in Fig. 5., the highest level of inundation in the flood area is 86.20 m.a.s.l.

Flood hydrograph and filling curve for the 100 year case are given in Fig.6 and Fig. 7, the highest level of inundation in the flood area in this case is 85.85 m.a.s.l. Third alternative is the 1:50 yrs flood.

(13)

Fig. 5. Filling curve in the Körös flood area, p=0.5%

Fig. 6. Flood hydrograph of the 100-year (p=1.0 %) flood of River Tisza at the confluence of River

Körös

Fig. 7. Filling curve in the Körös flood area, p=1.0%

(14)

4.1.3. Inundation modelling

Inundation modelling has been performed by using the HEC-RAS model. Flood extent and distribution of flood depth is illustrated in Fig. 8. It is clearly seen that properties in the fringes of municipalities Tiszaug, Tiszasas and Csépa will be covered in the range of <1m to max. 1-2 m, while Szelevény, which is intersected by the depressions of an ancient, silted up oxbow will suffer more serious inundation both in the share of inundated area and in flood depth. Industrial plant in the outer area of Kunszentmárton will be affected by ~1m flood depth.

Fig. 8. Flood hazard map of the Körös corner flood area in case of p=0,5% flood (86.20 m flood level)

The agricultural lands at the lower elevations will suffer 3-6 m inundation, duration of which exceeds 15 days, therefore the flood damage can be considered as the total annual production. Recreation areas along the banks of the oxbows as well as farm houses will also suffer from similar flood depth and duration.

(15)

4.2. Determination of economic risk

Data collection, analysis and evaluation was restricted to the determination of direct tangible damages to different land use categories, especially to the most sensitive ones like the residential buildings and the household goods in the settlements, similar components in the recreation zones at the banks of the oxbows, industrial and commercial units and agricultural buildings and their stocks. Damage to streets, roads and railways as well as to cars is not taken into account. Indirect damage, like losses due to business interruption, traffic disruption and emergency costs were also not involved.

For the evaluation of the economic risk a macro.scale approach was used since neither the available DEM, nor the rather coarse land use information and the level of economic data enabled us to apply a meso-scale method resulting in more detailed analysis.

4.2.1. Value of assets at risk

Data related to the value of assets were collected from statistical annuals, compiled by the Hungarian Central Statistical Office and its regional branch offices. In this respect the County Statistical Yearbook was used where the datasets are collected and published on settlement level. This enabled us to handle and analyse municipal statistical data.

The net value of fixed assets (depreciated value) is taken from official County Statistical Yearbook at the settlement level for different economic sectors.

Concerning the housing estates we crosschecked and corrected the data using additional information gained from real estate agencies based on actual real estate sales of typical housing estate types and categories; therefore the final asset value data also reflect the appraisal of the market. These “improved” data were recognised as gross values of assets. The net (depreciated) value was calculated applying the net/gross value proportions of the official statistics.

The value of stocks, which is not included in fixed assets, is estimated by assuming a typical relation between fixed assets and stocks for each economic sector, which is also derived from official statistics. Indications on the value of the machinery, equipments and stocks of the only significant industrial plant in the eastern corner of the flood area in the outer area of Kunszentmárton was derived from the emergency response plans (contingency plans) provided by the factory to mitigate consequences of accidental water pollution,.

The value of private household inventories, which is also not included in fixed assets, is estimated by an approximate value per square metre taken from insurance data.

In case of agricultural and forest land use types the value of assets as well as the data related to yearly and seasonal production was taken from the study produced by AKI (2006).

The determined net values of the assets were assigned to land use categories corresponding to the respective sectors. The applied land use data source, the CLC-50, due to its scale of 1:50,000 can not provide information on single buildings, or from blocks of houses or street network in the settlements. However, it shows aggregated areas with more or less the same use for the whole flood area in 11 different categories, differentiating residential and recreation areas, industrial and commercial facilities, agricultural facilities, farms, agricultural lands of different cultivation, etc. as seen in Fig. 3. By assigning the values to the corresponding areas the net values of assets in risk per land use categories and the total sum of the values can be calculated as shown in Table 1.

The table informs that the total value of assets in the Körös corner flood area exceeds € 184 million, 65% of which is at risk while the rest is situated on the floodplain islands, Over 153 M€ of the total values represents urban assets, 60% of which is at risk of inundation. The total agricultural assets sum up to 31.5 M€, almost 89% of which are at risk.

Performing the spatial modelling of the values on land use categories in a GIS results in a map of the spatial distribution of the net value of assets per square metre as shown in Fig. 9 ).

(16)

Table 1. Extension of land use categories and value of assets in risk in the Körös corner flood area (mean estimation)

Land use categories in the

Körös corner flood area

SUM_AREA

Weighted average value Total value of assets Weighted average value Depre-ciation Average net value Total net value of assets

m2 1000 HUF/ha 1000 HUF €/m2 €/m2 1000 EUR

Residential 2 055 500 130 000 26 721 498 52 0,40 31,2 64 132 Recreation area 294 425 100 000 2 944 246 40 0,30 28 8 244 Arable land _{72 765 064} ₃₄₈ _{2 532 224} _0,14 _0,14 _{10 129} Orchards _{366 992} ₆₀₀ _{22 020} _0,24 _0,24 ₈₈ Complex cultivation patterns _{538 156} ₈₆₆ _{46 604} _0,35 _0,35 ₁₈₆ Forest 2 604 155 213,36 55 562 0,09 0,09 222 Pastures _{9 008 205} _192,4 _{173 318} _0,08 _0,08 ₆₉₃ Industrial and commercial facilities 188 417 500 000 9 420 869 200 0,50 100 18 842 Agricultural facilities 530 516 150 000 7 957 743 60 0,50 30 15 915 Farms 749 846 3 500 262 446 1,40 0,60 0,56 420 Inundated b y 200-yea r flood even t

Water and wetland 3 157 158 218 68 826 0,09 275

92 258 434 50 205 356 119 147 Residential area 1 914 105 130000 24 883 362 31,2 59 720 Recreation area 936 100000 9 362 28 26 Arable land _{4 473 612} _351,14 _{157 086} _0,14 ₆₂₆ Pastures 147 980 192,4 2 847 0,08 12 Forest 93 816 213,36 2 002 0,09 8 Industrial and commercial facilities 22 112 500000 1 105 619 100 2 211

Flodplain islands

Agricultural facilities 96 965 75000 727 239 30 2 909

(17)

Fig. 9. Distribution of the value of assets at risk in the Körös corner flood area (mean estimation)

4.2.2. Relative damage functions

In order to estimate the damaged share of the asset values, depending on inundation depth, relative depth-damage functions have to be applied. Such damage functions show the average susceptibility of each sector against inundation depth.

Since there was no organised systematic collection of flood damage data in Hungary, from which relations between flood depth and damages for different properties, land use categories could be derived, consequently we do not possess any kind of damage functions. The time frame and budget conditions of this project did not enable to conduct a detailed survey resulting in the determination of reliable damage functions.

Different studies were therefore examined (Halcrow 1999, DHI Hydroinform, 2000; Drbal-Stepankova, 2007). Finalisation of the relative damage functions for residential and non-residential buildings and their inventories was made with the involvement of architect experts and real estate agents. Data and experience of insurance experts was also utilised.

(18)

Relative damage functions for residential buildings 0 10 20 30 40 50 60 70 80 90 100 0 50 100 200 300 >300 Flood depth, cm Losses i n val ue pr opor ti on, %

House made of loam; cob Brick house, >35 yrs Brick house

Brick house, two-storey Inventory, 1 storey

Inventory, two-storey, warning Bungalow

Fig. 10. Relative damage functions for residential buildings

Relative damage functions, industrial, commercial and agricultural units

0 10 20 30 40 50 60 70 <50 50-100 100-200 200-300 >300 Flood depth, cm Losses i n val ue pr opor ti o n s, %

Industr. and comm. bldg. Stocks

Agricultural bldg. Machinery, equipment

Fig. 11. Relative damage functions, industrial, commercial and agricultural units

4.2.3. Damage calculation

Combination of the asset value map with the damage functions in the spatial model under ArcView/ArcInfo GIS platform results in the event damage map showing the distribution of damages of different magnitude for the analysed inundation events as can be seen in Fig. 12 and 13.

The flood event damages to be expected in the different land use categories in different flood depth classes are summarized in Tables 2 and 3.

(19)

Table 2. Damages for the 200-year flood event in the Körös corner flood area (mean estimation)

inundation depth 1 m inundation depth 2 m inundation depth 3 m inundation depth 4 m Land use categories A, ha €/m² 1 000 € A, ha €/m² 1 000 € A, ha €/m² 1 000 € A, ha €/m² 1 000 € Agricultural facilities 8,20 6,0 492 1,50 7,5 113 5,48 9,6 526 43,30 12,0 5 196 Forest 16,26 0,4 65 58,20 0,4 233 24,24 0,4 97 161,43 0,4 646 Orchard - - 0 - - 0 - - 0 36,70 0,5 183 Industrial and commercial facilities 18,50 35 6 474 0,26 40 106 - - 0 - - 0 Complex cultivation patterns - - 0 0,41 0,4 2 0,63 0,4 3 40,76 0,4 163 Pasture 20,00 0,1 20 88,50 0,1 89 150,79 0,1 151 641,28 0,1 641 Discontinuous rural fabric 81,36 7,8 6 346 65,57 12,5 8 196 31,87 15,6 4 971 41,75 18,7 7 806 Arable land 268,07 0,4 1 072 323,28 0,4 1 293 136,95 0,4 548 6 541,40 0,4 26 166

Farm - - 0 - - 0 - - 0 74,98 5,0 3 749

Recreation area (weekend houses) 0,72 9,8 71 0,44 12,6 55 1,55 15,4 239 26,73 20 5 346 Wetland 0,35 0,1 0 0,00 0,1 0 - - 0 315,70 0,1 316

Total 413,45 14 540 538,16 10 085 351,50 6 534 7 924,04 50 213

Sumtotal 9 227,14 81 372

inundation depth 1 m inundation depth 2 m inundation depth 3 m inundation depth 4 m Land use categories A, ha €/m² 1 000 € A, ha €/m² 1 000 € A, ha €/m² 1 000 € A, ha €/m² 1 000 € Agricultural facilities 1,60 6,0 96 4,23 7,5 317 4,73 9,6 454 41,22 12,0 4 947 Forest 50,12 0,4 200 35,71 0,4 143 19,37 0,4 77 151,11 0,4 604 Orchard - - 0 - - 0 - - 0 36,70 0,5 183 Industrial and commercial facilities 10,14 35,0 3 550 0,08 40,0 31 - - 0 - - 0 Complex cultivation patterns 0,18 0,4 1 0,54 0,4 2 1,18 0,4 5 39,90 0,4 160 Pasture 60 0,1 60 107,90 0,1 108 207,91 0,1 208 520,48 0,1 520 Discontinuous rural fabric 52,48 7,8 4 093 74,57 12,5 9 321 16,38 15,6 2 555 35,18 18,7 6 579 Arable land 303,47 0,4 1 214 196,85 0,4 787 156,52 0,4 626 6 460,57 0,4 25 842 Farm - - 0 - - 0 - - 0 74,98 5,0 3 749 Recreation area (weekend houses) 0,74 9,8 72 0,95 12,6 120 2,40 15,4 370 25,24 20,0 5 048 Wetland 0,01 0,1 0 - 315,70 0,1 316

Total 478,88 9 287 420,83 10 829 408,48 4 295 7 701,09 47 948

(20)

Fig. 12. Damages for the 200-year flood event in the Körös corner flood area

(21)

Table 4. Differences between the results of 200-years and 100-years flood scenarios:

200-year flood 100-year flood Difference (200-100) Inundation level peaks in the flood area, m.a.s.l. 86.20 85.85 35 cm

Total area inundated, ha 9 227 9 009 218

Total event damage, 1000 € 81 372 72 360 9 012

- from wjich: discontinuous rural fabric 27 319 22 549 4 771

Industial and commercial units 6 580 3 581 2 999

Arable land 29 079 28470 609

Agricultural facilities 6 327 5 813 514

The flood crest of the 1:50 year flood (p=2%) at Csongrád gauge is 85.80 m.a.sl, max. level of inundation in the Körös corner flood area is 85.20 m.a.s.l.

inundation depth 1 m inundation depth 2 m inundation depth 3 m inundation depth 4 m Land use categories A, ha €/m² 1 000 € A, ha €/m² 1 000 € A, ha €/m² 1 000 € A, ha €/m² 1 000 € Agricultural facilities 1,50 6 90 5,48 7,5 411 43,30 9,6 4 157

Forest 58,20 0,4 233 24,24 0,4 97 161,43 0,4 646 Orchard 0,00 - 0 0 - 0 36,70 0,5 183 Industrial and commercial facilities 0,26 35 93 0 40,0 0 0 - 0 Complex cultivation patterns 0,41 0,4 2 0,63 0,4 3 40,76 0,4 163 Pasture 88,50 0,1 89 150,79 0,1 151 641,28 0,1 641 Discontinuous rural fabric 65,57 7,8 5 114 31,87 12,5 3 983 41,75 15,6 6 512 Arable land 323,28 0,4 1 293 136,95 0,4 548 6 541,40 0,4 26 166

Farm 0,00 - 0 0 - 0 74,98 5,0 3 749

Recreation area (weekend houses) 0,44 9,8 43 1,55 12,6 195 26,73 15,4 4 117 Wetland 0,00 0,1 0 0 - 0 315,70 0,1 316

Total 538,16 6 956 351,50 5 388 7 924,04 46 650

(22)

Fig. 13. Damages for the 100-year flood event in the Körös corner flood area

(23)

4.2.4. Documentation of uncertainties

Risk assessment and mapping has several potential sources of uncertainty. Over viewing the process of production, the following statements can be made:

Digital elevation model – although more and more precise and accurate technologies are available, DEM still remains one of the sources of uncertainty. However, while a DEM based on LiDAR surveys offer ±15 cm vertical accuracy, the ELK-DDM 5 we used for this analysis offers ±70 cm only, which could be improved with some additional GPS surveys at sensitive zones to ±50 cm.

Hydrological modelling – the confidence interval of the hydrographs of different probability is also in the range of ±70-80 cm.

Hydraulic modelling of inundation – the calibration and verification of the used HEC-RAS model resulted in an accuracy within ±10 cm, which is quite acceptable.

Statistical data – there are also doubts concerning the precision of the official statistical data provided on municipal level in the County Statistical Yearbooks. Crosschecking of the statistical data related to housing estates using additional information gained from real estate agencies based on actual real estate sales of typical housing estate types and categories showed significant alterations.2

Average deviations of the minimum and maximum values of assets from the mean values are as follows:

− buildings ±26-30%

− household equipments and goods ±38-40%

− Industry ±20-25%

The cumulative impact of the sources of uncertainties mentioned above, excluding the impact of the confidence interval of the flood hydrographs, is illustrated in Fig. 14.

Fig. 14. Uncertainties in the relative damage functions

2_{In fact, no databank is available on the value of private fixed assets including housing estates – this is one of}

(24)

The assessment of the susceptibility of the different assets to flood depth which is manifested in the applied depth/damage functions is also burdened with other significant deviations as illustrated in Figures 3.10 and 4.3 of the T9_06_01 Flood damage Guideline. With our rather poor, very general data we could unfortunately not make such analysis.

Since the scale of the applied land use map does not allow to demonstrate the above uncertainties of the most sensitive land use categories (residential, industrial and commercial), documentation of uncertainties in the maps will not be given.

4.2.5. Calculation of Annual Average Damage (AAD)

The basis for our AAD calculations is the inundation, asset value and event damage modelling introduced in the foregoing for events of different exceedance probability (1:50, 1:100, 1:200).

The formula (Meyer, 2007):

The calculation: D200+D100 D100+D50 D200 ₂ D100 ₂ D50 81 372 72 360 58 993 76 866 65 676 ΔP200-100 ΔP100-50 0,005 0,01 D200+D100 D100+D50 2 *ΔP200-100 2 *ΔP100-50 384 657 AAD EUR 1 041 thousand

The mean value of annual average damage in te Körös corner flood area is EUR 1,041,000

5. Conclusion

The original objective of this report as formulated in the DoW for months 49-60 was a pilot study application of general vulnerability analysis techniques developed in FLOODsite sub-theme 1.3, in one of the flood cells to identify the effectiveness of flood management strategies.

However, in Chapter 1 and 2 we clearly demonstrated that the quality of the available data, the absence of digital elevation model, the rather poor resolution and accuracy of the land use map available, etc. limit both the scale and accuracy of our pilot study in the application of the vulnerability

(25)

analysis methodologies developed. As a result of these conditions, we could undertake to perform an indicative vulnerability analysis (or damage evaluation) with relatively low level of accuracy for a flood area of limited extent only.

Results of the work performed are demonstrated in Chapter 4 of this report,

− we developed the flood hazard map of the Körös corner flood area, indicating the distribution of flood depth,

− determined the extension of land use categories and the distribution of the value of assets in risk in the Körös corner flood area (mean estimation),

− developed relative damage functions,

− calculated and determined the distribution of flood event damages for three different scenarios, the floods of 200 year, 100 year and 50 year recurrence period (or 0.5% - 1.0% and 2.0% probability), − calculated the annual average damage

− documented the uncertainties.

Unfortunately the scale of these results does not enable us to evaluate the effectiveness of the flood management strategy of the Tisza Valley (known as Update of the Vásárhelyi Plan) in economic terms. It is because both the interventions and the effects of this plan spread to the total length of the River Tisza in Hungary including the improvement of the flood conveyance capacity of the flood bed and the construction of 14-15 flood detention basins in a total capacity of 1.5 billion m3_{. Costs of this}

plan cover a roughly 600 km river section and even the assessment of their share in the reduction of the losses in the Körös corner flood area is beyond our possibilities.

The result of this plan as published in our report in 2007 (River capacity improvement and partial floodplain reactivation along the Middle-Tisza T-22-07-01) will be safety along the River Tisza against 1 in 1000-year floods. Definitely, in the river section affecting our selected flood area the implementation of the plan will result in a 75 cm depression of the flood crest of the 200-years flood. As a result of this lowered flood crest, failure probability of the flood embankments of the Körös corner flood area will almost be excluded. In other words, the Körös corner flood area will not suffer inundation after the implementation of the UVP project. Assuming a fatal case of failure, neither the residential nor the industrial and commercial land uses would be affected by flooding.

Despite this missing item we do believe that the report achieved its goal: we could demonstrate the applicability of the methodology of vulnerability analysis for an environment where flood risk assessment and mapping was not in the every day experience in the recent past but the introduction of such methods is just starting.

(26)

6. References

1. NAGY L. – TÓTH S. (2004): Detailed Technical Report on the collation and analysis of dike breach data with regards to formation process and location factors. IMPACT WP6. Contract No.: EVG1-CT-2001-00037

2. TÓTH S.– KOVÁCS S. (2007): River capacity improvement and partial floodplain reactivation along the Middle-Tisza T-22-07-01 FLOODsite

3. Central Statistical Office (2006): Statistical Yearbook of Hungary

4. Central Statistical Office (2006): Statistical Yearbook of Jász-Nagykun-Szolnok County 5. Central Statistical Office (2006): Statistical Yearbook of Bács-Kiskun County

6. AKI (2006): Táj- és földhasználat váltás a Tisza hullámterében (a a VTT I. ütemében tervezett beavatkozások).Changing of landscape and land use in the Tisza floodplain (as planned in the Phase I of the Upgrade of the Vásárhelyi Plan)

7. BIZA P, GIMUN V, KNAP R, AMENTHORP H C, SMITH G, IHLY T (2001), The use of a GIS based software tool for benefit-cost analysis of flood mitigation measures in the Czech Republic, DHI-Software Conference, June 2001

8. DRBAL K. - STEPANKOVA P. (2007) Methodology for Determination of Flood Risk and Potential Losses. ICPDR Flood Risk Mapping Workshop, Budapest

9. US Army Corps of Engineers (1996), Engineering Manual – EM 1110-2-1619. Engineering and Design – Risk based analysis for flood damage reduction studies

10. MESSNER F, PENNING-ROWSELL E, GREEN C, MEYER V, TUNSTALL S, VAN DER VEEN A (2007) Evaluating flood damages: guidance and recommendations on principles and methods. FLOODsite T9_06_01_Flood_damage_guidelines_D9_1_v2_2_p44

11. MEYER V, (2007) GIS-based Multicriteria Analysis as Decision Support in Flood Risk Management, FLOODsite Report_MCA_V1_4_P44