Application the SWAT model for Extreme Urban Flash Floods in Seoul

Transcription

1 Application the SWAT model for Extreme Urban Flash Floods in Seoul 18 July 2013 International SWAT Conference, Toulouse, France 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 URL : wise2020.org

2 Contents Background & Aim Modeling Strategy Study Area Model Evaluation (Daily Time Step) Model Evaluation (Hourly Time Step) Summary & Conclusion Forward

3 Natural Hazards in Seoul: Floods Seoul is km 2 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 4 August 1998 Flood: 384mm (8.2 midnight ~ pm) 28 July 2011: 587 mm (7.26 ~ 7.28) Rainfall distribution midnight ~ pm, 384mm Gangnam & Mt.Woomyun ( ): daily rainfall 171 mm (7.26), 301mm (7.27), 115 mm(7.28)

4 Weather Information Service Engine (WISE) Goal Better customized service Objective WISE Funded by KMA 8 Years (2012 ~ 2019) $100 million Strategy Micro scale observation, modeling and analysis Science Integration Information delivery Subjects 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 Execute Step Operation 2019

5 WISE & Applications Urban Flash Flood Response System User Focused Agri-meteorological System Road and Traffic Weather Information Service Urban Ecology Predicting & Forecasting System 1 st Phase: Build Micro-Scale Weather Observation Networks 2 nd Phase: Develop Models and Trial Services 3 rd Phase: Run WISE Platform WISE Platform Design Develop Services: UFF, UFAS, R-T WIS, UEP&FS Pilot Services of Applications Run WISE Platform Maintain WISE Platform WISE Platform WISE User Survey Design Architectu re of WISE Build WISE Platform Center Server Desktop Link to related institutes Mobile services Micro-Scale weather Observation Design Test-Bed Build Test-Bed Build Super-Site Contents & System Design Prototype Design Develop models Extend models Develop systems Integrate models and Systems

6 Study Aims 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.

7 Modeling Strategy A semi distributed model is built to evaluate sensitivity of intensive rainfall Multi-scale modelling is required to overcome limitations of ungauged catchment Catchment to Regional scale (2012 ~ 2015) Implement Database Classifying Flash Floods Type Model (I) Surface Runoff Model (II) Hydraulic Coupling Model (I) / (II) Weather Data Catchment Scale Floods: Flood plains.. Hydrological Surface-Runoff Model at catchment scale River channel flows Han River (1,150 km 2 ) Daily run time step Spatial Data Regional Scale Floods (up to 10 km 2 ) Delineating Urban/ungauged catchment & coupling with network analysis Drainage system & sewer network analysis Gangnam area (9 km 2 ) Hydrological Data Daily Hourly 0.25 Hour run time step Floods with geological hazards: mud flow, land slides.. Hydrological model combined with geological model Soil & Landslide analysis Mt. Woomyun

8 Study Area Outlet #1 Outlet #2 Seoul Han River Whole Outlet Outlet #3 Paldang - Dam Study Area Boundary Subbasin Ungauged Catchment Stream Water Level / Discharge Station Sewage Treatment Plant

9 Sites of Interest Outlet #1 Area Average Rainfall (Yearly) Average Discharge (Yearly) : km 2 : 1,573.2 mm : 3,037.3 m 3 Outlet #1 Outlet #2 Seoul Outlet #2 Area Average Rainfall (Yearly) Average Discharge (Yearly) Outlet #3 : km 2 : 1,564.6 mm : 3,262.0 m 3 Whole Outlet Outlet #3 Han River Paldang - Dam Area : km 2 Average Rainfall (Yearly) : 1,490.2 mm Average Discharge (Yearly) : 5,909.7 m 3

10 Modeling Scheme Meteorological Data Precipitation, Temperature, Wind Speed, Solar Radiation, Relative Humidity GIS Data DEM, DSM Land Use, Soil type HEC-GeoRas Module Hydrological Modeling (SWAT) Watershed Delineation, HRUs, Point Sources, and so on Hydraulic Modeling (HEC-RAS) XSCuts, Friction Value, Boundary Condition Discharge Estimation Surface Flow Analysis

11 Spatial Input Data Spatial Resolution : 30 m

12 Performance Indicators Coefficient of Determination Root Mean Square Error Nash-Sutcliffe Model Efficiency Where, b x y O P N : : : : : : Estimated Regression Coefficient Variable Variable Observed Value Predicted Value Number of Data

13 Evaluation Results (I) Cal. 2010~2011 Daily Outlet #1 Val. 2008~2009 Paldang - Dam R 2 NS RMSE Cal Val

14 Evaluation Results (II) Cal. 2010~2011 Daily Outlet #2 Val. 2008~2009 Paldang - Dam R 2 NS RMSE Cal Val

15 Evaluation Results (III) Cal. 2010~2011 Daily Val. 2008~2009 Outlet #3 Paldang - Dam Cal. Val. R 2 NS RMSE

16 Evaluation Results (Whole) Cal. 2010~2011 Daily Val. 2008~2009 Whole Outlet Paldang - Dam R 2 NS RMSE Cal Val

17 Hourly Simulation ~ 8.5. Hourly Outlet #1 Outlet # ~ 8.5. Outlet # ~ 8.5. #1 #2 #3 R 2 NS RMSE

18 Small Ungauged Urban Catchment: Gangnam 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 A B

19 Surface Flow Analysis Flood Risk Map A B Subway Station Inundation Depth (m)

20 Summary & Conclusions 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 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.

21 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)

22 18 July 2013 Thank You for Listening Weather Information Service Engine Division, CATER Hyung Kyung Joh Sun Jung Jong-Sook Park / / / whgudrud@gmail.com alwayshappy.sun@gmail.com jspark9957@gmail.com