Hyung Kyung Joh / Researcher / Weather Information Service Engine Division

Sun Jung / Researcher / Weather Information Service Engine Division

Jong-Sook Park / Senior Scientist / Weather Information Service Engine Division

Application the SWAT model for

Extreme Urban Flash Floods in Seoul

18 July 2013 International SWAT Conference, Toulouse, France

URL : wise2020.org

Contents

• Background & Aim

• Modeling Strategy

• Study Area

• Model Evaluation (Daily Time Step)

• Model Evaluation (Hourly Time Step)

• Summary & Conclusion

• Forward

Natural Hazards in Seoul: Floods

Seoul is 605.41 km2 with population of approximately 13 million

4 August 1998 Flood followed by floods in 2001, 2003, 2010, 2011 and 2012

However, No Information or Warnings from Government

Rainfall distribution - 1998.8.2 midnight ~ 1998. 8.4. 1 pm, 384mm

Gangnam & Mt.Woomyun

(2011.7.28):

daily rainfall 171 mm (7.26),

301mm (7.27), 115 mm(7.28)

4 August 1998 Flood: 384mm (8.2 midnight ~ 8.4. 1 pm)

28 July 2011: 587 mm (7.26 ~ 7.28)

Weather Information Service Engine (WISE)

Better customized service Goal

Objective

Strategy

Subjects

WISE

Micro scale observation, modeling and analysis

Science Integration Information delivery

Storm prediction system Boundary layer modeling

Multi-scale modeling Joint Numerical Test-bed

Observation

Urban applications Agriculture applications

Urban eco-systems Business applications

WISE platform Information contents

Graphic solution Technology transfer

Design

Plan

2013

Execute

Step 1

2015

Execute

Step 2

2017

Operation

2019

•Funded by KMA

•8 Years (2012 ~ 2019)

•$100 million

2012 2013 2017 2018 2019 2014 2016 2015

Contents &

System

Design

Micro-Scale

weather

Observation

Design

Test-Bed

Prototype

Design

Build

Test-Bed

Develop models

WISE Platform

Develop Services: UFF,

UFAS, R-T WIS,

UEP&FS

Pilot Services of

Applications

WISE Platform

Design

Maintain

WISE Platform

WISE

User Survey

Design Architectu

re of WISE

Extend models

Develop systems

Build WISE

Platform Center

Build

Super-Site

Integrate models and

Systems

Run WISE

Platform

Mobile services

Link to related

institutes

Desktop

Server

Road and Traffic Weather

Information Service

User Focused

Agri-meteorological System

Urban Ecology Predicting &

Forecasting System

Urban Flash Flood

Response System

1st Phase: Build Micro-Scale

Weather Observation

Networks

2nd Phase: Develop

Models and

Trial Services

3rd Phase:

Run WISE Platform

WISE & Applications

Difficult to measure intensive rainfall, as it lasts short and exits over

small areas and hard to estimate the inundation depth and other

hydrological features on site of urban flash floods

This study aims to provide a better understanding of urban flash

flood with improving estimation of the amount of excess water and

flood depth and to delineate flood vulnerable areas for Gangnam,

one of the site of suffering from remarkable urban flash floods in

Seoul.

Study Aims

A semi distributed model is built to evaluate sensitivity of intensive rainfall

Multi-scale modelling is required to overcome limitations of ungauged

catchment

Implement Database

Classifying

Flash Floods

Type

Model (I)

Surface

Runoff

Model (II)

Hydraulic

Coupling

Model (I) / (II)

Catchment Scale

Floods:

Flood plains..

Hydrological

Surface-Runoff

Model at

catchment scale

River channel

flows

Regional Scale

Floods

(up to 10 km2)

Floods with

geological hazards:

mud flow, land

slides..

Delineating

Urban/ungauged

catchment & coupling

with network analysis

Hydrological

model combined

with geological

model

Drainage system

& sewer network

analysis

Soil & Landslide

analysis Hydrological

Data

Han

River

(1,150 km2)

Gangnam

area

(9 km2)

Mt.

Woomyun

Spatial

Data

Weather

Data

Daily run time step

Catchment to Regional scale (2012 ~ 2015)

Daily Hourly 0.25 Hour run time step

Modeling Strategy

Study Area

Study Area Boundary

Subbasin

Stream

Water Level / Discharge Station

Ungauged Catchment

Sewage Treatment Plant

Paldang -

Dam

Outlet #1

Outlet #2

Outlet #3

Whole

Outlet

Han River

Seoul

Sites of Interest

Outlet #1

Outlet #2

Outlet #3

Area

Average Rainfall (Yearly)

Average Discharge (Yearly)

: 199.1 km2

: 1,573.2 mm

: 3,037.3 m3

Area

Average Rainfall (Yearly)

Average Discharge (Yearly)

: 211.8 km2

: 1,564.6 mm

: 3,262.0 m3

Area

Average Rainfall (Yearly)

Average Discharge (Yearly)

: 201.6 km2

: 1,490.2 mm

: 5,909.7 m3

Paldang -

Dam

Outlet #1

Outlet #2

Outlet #3

Whole

Outlet

Han River

Seoul

Modeling Scheme

Meteorological Data GIS Data

Precipitation,

Temperature,

Wind Speed,

Solar Radiation,

Relative Humidity

DEM, DSM

Land Use,

Soil type

Hydrological

Modeling (SWAT)

Hydraulic

Modeling (HEC-RAS)

XSCuts,

Friction Value,

Boundary Condition

Watershed Delineation,

HRUs, Point Sources,

and so on…

Discharge

Estimation

Surface Flow

Analysis

HEC-GeoRas

Module

Spatial Input Data

Spatial Resolution : 30 m

Performance Indicators

Coefficient of Determination

Nash-Sutcliffe Model Efficiency

Root Mean Square Error

Where,

b

x

y

O

P

N

:

:

:

:

:

:

Estimated Regression Coefficient

Variable

Variable

Observed Value

Predicted Value

Number of Data

Daily

Evaluation Results (I)

R2

NS

RMSE

0.67

0.50

26.4

0.55

0.24

29.5

Cal. Val.

Val. 2008~2009

Outlet #1

Cal. 2010~2011

Paldang -

Dam

Daily

Evaluation Results (II)

R2

NS

RMSE

Cal. Val.

0.84

0.65

23.2

0.75

0.41

30.3

Cal. 2010~2011

Val. 2008~2009

Outlet #2

Paldang -

Dam

Daily

Evaluation Results (III)

R2

NS

RMSE

0.48

0.36

27.4

0.54

0.42

21.1

Cal. Val.

Cal. 2010~2011

Val. 2008~2009

Outlet #3

Paldang -

Dam

Daily

Evaluation Results (Whole)

R2

NS

RMSE

0.75

0.54

34.7

0.85

0.85

571.3

Cal. Val.

Cal. 2010~2011

Val. 2008~2009

Whole

Outlet Paldang -

Dam

Hourly

Hourly Simulation

Outlet #3

Outlet #2

Outlet #1

R2

NS

RMSE

0.42

0.36

177.9

0.62

0.41

198.6

#1 #2 #3

0.57

0.12

189.5

2011.7.26. ~ 8.5.

2011.7.26. ~ 8.5.

2011.7.26. ~ 8.5.

Small Ungauged Urban Catchment: Gangnam

A

B

Heavy Urbanization Since Late 1960s

Remained as Steep Slop Small Ungauged Urban Catchment

Ineffectively Designed Urban Drainage / Sewer Systems

Intensive Road Networks Accelerate Excess Water to Get Lower

Lying Areas

A B

Surface Flow Analysis

2.1

0.1

Subway Station

Inundation Depth (m)

Flood Risk Map

A

B

This preliminary study is an on-going work as a part of the WISE

(Weather Information Service Engine) project and purposes to

forecast and prevent weather disaster, especially is focused on

urban flash flood.

The practice target of urban flash flood was occurred on July 26th

2011.

This urban flash flood and flooding inundation at rainy season were

simulated with coupling hydrologic (SWAT) and hydraulic (HEC-

RAS) models.

Undoubtedly, the simulated flooding inundation results were over /

under estimated because of the lack of sewer network system

analysis.

Summary & Conclusions

Forward

Parameter Optimization for Urban Ungauged Catchment

Uncertainty Analysis

Sensitivity Analysis

Sewer Network Analysis

Predict Lag Time Delayed Under Various Range of Intensive

Rainfalls (What If)

Thank You for Listening

Weather Information Service Engine Division, CATER

18 July 2013

Hyung Kyung Joh

Sun Jung

Jong-Sook Park

/

/

/

whgudrud@gmail.com

alwayshappy.sun@gmail.com

jspark9957@gmail.com