Suggesting a scheme to construct an integrated assessment system of flood control measures

Establishment of a scheme to select optimum economic flood control measures

Construction of an assessment system applicable for members of the typhoon committee

Constructing reasonable and integrated assessment system of flood control measures

Investigation of domestic and foreign flood control assessment system and establishment of plans

D/B, module, andSystem, Damage Estimation and Economic moduleconstruction

Flood control assessment

system

2008

2009

2010

2011Module design of the system andmodule D/B design

Present status analysisand establishment of plans

Requirements analysis of users and analysis

of structural measures

System, Inside module construction

Maintenance and utilization

Framing the plans for maintenance and utilization

1. Estimation flood discharge

2. Estimation flood stage at the watch point(channel routing)

3. Bank height > flood stage ?

7. Inundation

8. Estimation of the flood area & depth in the protected lowland

9. Estimation of the potential flood damage(Multi-dimensional flood damage analysis)

10. Repetition of the 1~9 procedures with each flood control measures

11. Selection of the optimal measure

4. No Inundation

5. Protected lowland flooding?

6. Potential flood damage=0

Yes

Yes

No

Classification for Local characteristicClassification for Local characteristic

Class Criterion of applicaton ApplicationBig city City over millions Seoul and 5 metropolitan

citiesMidium size city City under millions GyeongGi province etc

Small city Developed city from farming area Jeju province

Farming area

Area over 500 per/km^2 populaton density

Mountain area Other area except farming area

Human life damage in flood damage occurrenceHuman life damage in flood damage occurrence

Class(per/ha)

Big city Midium size city Small city Farming

areaMountain

areaDeath 0.004 0.004 0.001 0.002 0.002Injury 0.002 0.002 0.001 0.001 0.002

Economic index research by the administrative districtEconomic index research by the administrative district

Dist.(Million) 2005 2006 2007 2008

Seoul 20.87 21.97 23.59 24.48

Pusan 13.40 13.91 14.94 16.12

Daegu 11.47 12.18 13.06 13.59

Inchun 15.67 16.68 18.29 18.27

Gwangju 13.09 14.07 14.73 15.52

Daejun 13.64 14.09 14.92 15.81

Ulsan 38.97 40.22 44.51 48.62

Gyeonggi 15.95 16.71 17.54 17.76

Gangwon 15.46 16.31 17.67 18.10

Chungbuk 18.00 18.86 20.22 20.30

Chungnam 24.76 26.64 28.48 29.96

Joenbuk 13.88 14.74 16.14 16.88

Jeonnam 23.12 23.06 26.03 29.59

Gyeongbuk 23.29 23.66 24.28 26.16

Gyeongnam 18.74 19.81 22.13 23.93

Jeju 14.71 14.90 16.04 16.42

Local GDP research

- Analysis results are not correct to use only population for classification index

- Comprehensive indexes are population density and per GDP

Population density

Per GDP

The spread of population & life expectancy investigation by administrative districtThe spread of population & life expectancy investigation by administrative district Use for casualty loss amount estimation

Dist.Average age Population

Life exp.Man Woman Ave. Man Woman

Seoul 34.6 36.3 35.5 4,837,112 4,925,434 45.8

Pusan 35.5 38.0 36.7 1,735,860 1,776,687 42.1

Daegu 33.8 36.5 35.2 1,227,168 1,228,848 44.3

Inchun 33.4 35.1 34.2 1,262,612 1,255,068 45.3

Gwangju 32.3 34.3 33.3 701,265 712,379 46.5

Daejun 32.8 34.7 33.8 720,734 717,817 46.5

Ulsan 32.2 34.1 33.1 538,031 506,903 45.6

Gyeonggi 33.0 34.6 33.8 5,192,007 5,148,999 46.3

Gangwon 36.3 39.3 37.8 733,266 727,504 41.4

Chungbuk 35.2 38.2 36.7 730,084 723,788 42.5

Chungnam 36.3 39.4 37.8 945,540 933,877 41.8

Joenbuk 36.2 39.8 38.0 874,662 904,217 41.5

Jeonnam 37.8 42.3 40.1 889,805 925,369 39.4

Gyeongbuk 36.5 40.5 38.5 1,292,673 1,302,046 40.9

Gyeongnam 34.6 38.0 36.3 1,521,110 1,519,883 42.4

Jeju 33.5 37.1 35.3 263,721 266,965 45.1- - - 23,465,650 23,575,784

The spread of population & life expectancy investigation by administrative districtThe spread of population & life expectancy investigation by administrative district

Dist.(Million)

Death loss

Injury loss

Victim loss

Pop. density (per/㎢ )

Seoul 955.8 477.9 0.5718 16231.7 Pusan 564.1 282.1 0.3671 4612.0 Daegu 508.1 254.1 0.3142 2787.9 Inchun 709.9 354.9 0.4293 2546.6

Gwangju 608.7 304.3 0.3586 2829.8 Daejun 634.3 317.1 0.3737 2672.0 Ulsan 1777.0 888.5 1.0677 992.6

Gyeonggi 738.5 369.2 0.4370 1028.1 Gangwon 640.0 320.0 0.4236 88.2 Chungbuk 765.0 382.5 0.4932 196.5 Chungnam 1035.0 517.5 0.6784 219.7

Joenbuk 576.0 288.0 0.3803 221.5 Jeonnam 910.9 455.5 0.6334 150.7

Gyeongbuk 952.6 476.3 0.6381 137.1 Gyeongna

m 794.6 397.3 0.5134 290.5

Jeju 663.4 331.7 0.4030 287.8

Estimation of Casualty loss amount

- Death + Injury+ Victim loss amount

- Death loss amount = Flooding area( ㏊ ) × Death rate of flooding area(per/ ㏊ ) × life expectancy(yr) × per GDP

- Injury loss amount = Flooding area( ㏊ ) × Injury rate of flooding area(per/ ㏊ ) × life expectancy(yr) × per GDP/ 2

- Victim loss amount = Flooding area( ㏊ ) × Victim rate of flooding area(per/ ㏊ ) × evacuation day(day) × per GDP / 365(day)

Constuction to use various digital map Constuction to use various digital map from GIS basisfrom GIS basis

Administrative district map DEM(1/5,000, 1/25,000) Land use map

- Use of satellite images- Use of satellite images

Computation through space Computation through space information compositioninformation composition

Administrative district

Space information composition

Land use×

Flooding area×

Flooding depth

Estimate probabilistic rainfall using established analysis results such as probable isohyetal charts

If it is not reliable or available, estimate the probabilistic distribution of rainfall

Rainfall estimation

To use as the input of hydrologic model to simulate flood aspects, the probabilistic rainfall needs to be timely distributed

The methods such as Huff and Yen and Chow could be applied

Time distribution

Various hydrologic models such as HEC-HMS, HEC-1, ILLUDAS, SWMM could be used to simulate streamflow using the timely distributed probabilistic rainfall

Hydrologic model should be carefully selected with the features of applied basins

Flood estimation

100-YEAR 1-HOUR RAINFALL

The procedure of estimating probabilistic precipitationThe procedure of estimating probabilistic precipitation

Meteorological data construction

Applying probabilistic distribution

Parameter estimation

Goodness of fit test

Selecting the optimum distribution

Estimating probabilistic precipitation

Normal, Lognormal, Gamma, Log-pearson type III, GEV, Gubel, Log-Gumbel, Weibull

Maximum likelihood, Method of moments

Colmogorov-Smirnov,Cramer-von-Mises,

PPCC, x2

Time distributionHuff,

Yen and Chow

Runoff simulation using hydrologic modelRunoff simulation using hydrologic modelUrban area Natural area

Effective rainfall

Initial loss Proper values according to pervious and impervious region

NRCS method

Infiltration Horton equation for the rate curve of infiltration capacity

Green-Ampt, NRCS

Horton equation for the rate curve of infiltration capacity

Green-Ampt, NRCSBasin data

Basin area Estimate with Topography(GIS), etc Estimate with Topography(GIS), etcImpervious area

Estimate separately Indirect application (When CN is estimated)

Surface runoff

Estimation method

Storage equation, Kinematic wave, etc

Clark, SCS, Snyder, Nakayasu, etc

Main parameter

Basin length and slopeSurface roughness coefficient

Arrival and delay timeStorage coefficient

Uniqueness Separating basins according to drainage system

Separating basins according to streams and main simulation points

Channel runoff

Estimation method

Kinematic waveDiffusive waveHydrodynamic method, etc

MuskingumMuskingum-CungeKinematic wave, etc

Main parameter

length and slope of Channel and sewer

Roughness coefficient, etc

Length and slope of channelRoughness coefficient Storage constant, etc

Uniqueness Pressured flow analysis for sewer full of water

Open channel analysis

Models ILLUDAS, SWMM, etc HEC-1, HEC-HMS, etc(Ref. A guideline for the flood estimation of urban area, 2008)

Initial setup Assets & maps Flood simulation Damage estimation Analysis

Currency unit(₩,$,.)Area unit(m2, km2,.) Load basin map

Set the range of asset classifications

according to map

Create the tables of assets

Input the tables or Use default values

Set a flood simulation method

Create cross

sections of floodplain

Generate floodplain and depth grid

Generate HEC-RAS

input

Run HEC-RAS

Import simulated inundation with each

flood control

measures

Set the range of assets to estimate

damage

Estimate the amount of loss for each flood control

measures

Set an analysis method

Analyze the socio-economic values of

flood control measures

Suggest the optimum measures

AB

A :Simulate flood inundation using HEC-RAS model

B : Import simulated inundation results from another model available for an applied basin

Initial setup and inputs Flood and damage estimation Socio-Economic analysis

Standards of damage loss

- Actual recovery costs- National

compensation costs

Simplicity of the model with the equivalent reliability

Familiarity with used technique

Running time Types of computers Availability of data Model support and

documentation

Model selection for the floodplain simulationModel selection for the floodplain simulation

River flood simulation using HEC-RASRiver flood simulation using HEC-RAS HEC-RAS is widely used and accepted in particular for floodplain

management and flood insurance studies (Karle, 2008) HEC-RAS in the simulation of extreme glacial outburst flood is

accurate enough for general flood protection purpose (Alho et al., 2008)

When more and more cross-sections were used, the simulation result of HEC-RAS was more similar to FESWMS 2D model (Cook et al, 2008)

The HEC-RAS and TELEMAC-2D models perform equally well in predicting the inundated area when calibrated, whereas the performance of the LISFLOOD-FP model is dependent on the calibration data used (Horritt et al., 2002)

To comprise a series of discrete areas acting as storage cells for floodplain

To Extend the cross-section across the full floodplain width

Floodplain treatment in HEC-RAS (Tayefi et al., 2007)Floodplain treatment in HEC-RAS (Tayefi et al., 2007)

Total damage Total damage from flood from flood The total amount of cost to be paid to recover the socio-economic

activities to the level possible if flood did not occur Consisted of direct and potential damage

Socio-Economic Activities

TimeFlood occurrence

Total Total damagedamage

Direct damage(Primary damage)

Potential damage(Secondary damage)

Direct damage Direct damage (primary damage)(primary damage) Destroyed constructions and agricultural area, damaged facilities and

products, and injured people Recoverable Damage (RD)

- The cases of Constructions, facilities, and products that can be reconstructed or produced through paying cost - The standard of damage estimation is the cost to reconstruct and replace the damaged stuffs

Non-Recoverable Damage (NRD)- The cases of People, livestock, agricultural products that can not be replaced by simply paying cost - The standard of damage estimation in this case is the amount of loss

Potential damage Potential damage (secondary damage)(secondary damage) Damage During a Recovery period (DDR)

- Costs engendered during a recovery from such cases as the interruption of production facilities, the inability of public facility, and the traffic jams caused by destroyed roads

Damage After a Recovery period (DAR)- As the example of a production facility deprived of buyers during a recovery, some facilities could have loss for their profit even though they have fully recovered for their facilities

Additional cases of damageAdditional cases of damage Intangible damage (Grigg, 1975)

- Some categories of intangible damage are: environmental quality, social well being, and aesthetic values

Uncertainty damage (Grigg, 1975)- The loss from uncertainty damage is from the stress of the occupants of a flood plain suffer because of the uncertainty with regard to when flood will occur and how serious it will be

Both intangible and uncertainty damage can be categorized as potential damage

The asset values and the ratio of each asset and inundated depth are used for estimating the amount of damage Damage items are categorized into structures and contents in a residential area, farmland and crops in an agricultural area, tangible assets and inventories in an industrial area, public facilities, and casualties

Procedure to estimate the flood damages by MD-FDAProcedure to estimate the flood damages by MD-FDA

CasualtiesCasualties To estimate the number of death and

injury, the concept of ratio from the number of death and injury per area is used

The socio-economical loss of death is the function of life expectancy and GDP

The loss of injury is 50 % of the death according to the domestic law of Korea. Thus the percent is flexible with the inherent standards of a applied basin for the severity ratio of injury to death

(Unit: n/ha)The number of death and injury per flooded area

(Ref. A study on the Economic Analysis in Flood Control Projects, 2004)

Structural and agricultural damageStructural and agricultural damage

Urban area Lower flood velocity could

be expected Historical record(2002/8) Complete destruction 12 Half destruction

14 No destruction

2,188

Mountainous area Higher flood velocity could

be expected Historical record(2002/8) Complete destruction 60 Half destruction

69 No destruction

0

Estimation of the destroyed buildingEstimation of the destroyed building Through considering the historical record which shows destruction

tendency of building for flood, the number of destroyed building for simulated flood can be estimated

There are similar flood velocity and depth if the flooded location and area are the same

The number of destroyed building has a linear correlation with the flooded area

Public facility damagePublic facility damage The damage ratio of public facilities to general assets is applied to

estimated the amount of public facility damage

The damage ratio of public facilities to general assets

(Ref. A study on the Economic Analysis in Flood Control Projects, 2004)