dsd-int 2014 - symposium next generation hydro software (nghs) - 2d hydrodynamics of pearl river...
TRANSCRIPT
2D hydrodynamics of Pearl
River Estuary using
Delft3D Flexible Mesh
Li Li University of Hamburg
Qinghua Ye Deltares
Arthur van Dam Deltares
Delft Software Days 2014
Content of Presentation
•Significance
•Objectives
•Approach
•Model setup
• Future work
Significance
Threaten from the sea, e.g. storm
surge and typhoon
Threaten from the river, extreme
rainfall flooding risk caused by
storm surge becomes the major risk
along the coastal area in the world.
These two threatens happen
nearly every year in Pearl River
Delta after 2000.
Huge loss every year(half billion
dollars last year)
Fig. 1: Location of research area, Pearl
River Delta
Objectives
• To understand the interaction between marine system and river system during the
typhoon period.
•
• To model the flooding inundation caused by typhoons
•To use the economic losses as quantified index .
•Uncertainty analysis (typhoons from different direction and intensity, etc)
• Inundation simulation along coastline area is highly depend on the accurate
coastline definition, Delft3D Flexible Mesh model can properly resolve the
complicated coastline area with various topography and forcing using
unstructured mesh.
Approach
Risk Assessment &
Climate Adaptation
and Mitigation
Strategies
Delft3D Flexible Mesh including
D-Flow Flexible Mesh + WES
GIS-based topological analyses
Flooding Inundation
Inland flooding
(heavy rains and peak flows)
Coastal flooding
(storm surges and tide)
Topographic Exposition
Main Threats
Final Mesh
Bathymetry
Fig. 3 Combine bathymetry with patches
(HK model ,Detalres,1980-2014)
(Geerstmaar, 2013)
Boundary Conditions
• Sea side , 10 astronomic
tidal components are
used.
• River side, pearl river
average discharge every
year in wet and dry
seasons.
Input Parameters
• Timestep: 60 s
• Roughness: Manning 0.023 (constant), future using spatial varying
value
• Running time: one month in wet season and dry season separately
• Cell size: from ~100 m to ~1000 m
• Domain area: 33,000 km2
• Number of cells: 48640 cells, 56092 nodes
Calibration
4 points for the
calibration is selected
for water level and
discharge in wet and
dry seasons. They are,
Gaoyao(river side)
Shijiao (river side)
Makou(river side)
Kat o(sea side)
Gaoyao
Makou
Shijiao
Kat O
Makou Wet Season Measured Discharge
(1999.07)
0
0,5
1
1,5
2
2,5
3
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29
Dis
ch
arg
e()
m3/s
Makou Wet Season DailyDischarge(m3/s)
10 4
Makou Dry Season Measured Daily Discharge
(1999.12)
0
500
1000
1500
2000
2500
3000
3500
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31
Dis
ch
arg
e (
m3/s
)
Makou Dry SeasonDailyDischarge(m3/s)
Kat O Station Tidal Level
(2002.10.18-2002.10.23, hourly)
-0,8
-0,6
-0,4
-0,2
0
0,2
0,4
0,6
0,8
1
15:00 21:00 03:00 09:00 15:00 21:00
Wate
r le
vel (m
C.D
.)
Kat O tidal level Measurement Modelingl
Future Work
• Add the land mesh part for the inundation simulation
• 3 typical typhoon cases in different route and intensity
• Validate the inundation area using satellite image
• Applications
The Digital Elevation Model -> mesh on land
Future Work
• Add the land mesh part for the inundation simulation
• 3 typhoon cases in different route and intensity
• Validate the inundation area using satellite image
• Applications
Typhoon Dujuan in 2003(Middle route)
Track of Dujuan:29 August – 3 September 2003
Typhoon Koppu in 2009(west route)
Track of Koppu:11 September – 16 September 2009
Future Work
• Add the land mesh part for the inundation simulation
• 3 typhoon cases in different route and intensity
• Validate the inundation area using satellite image
• Applications
Inundation Area from Satellite Image
Applications
• Operational appliaction
• Hindcast application
• Forecast application
Requirement
• Meteorology data
• Typhoon data
• Satellite image
• Bathymetry
Model system
• Inundation area
• Water level
Application
• Urban planning
• Emergency management
• Economic lost evaluation
Reference
• Ying LI, Lianshou Chen, Shengjun Zhang. STATISTICAL CHARACTERISTICS OF TROPICAL
CYCLONE MAKING LANDFALLS ON CHINA. JOURNAL OF TROPICAL METEOROLOGY,2009,
20(1): 14-23.
• YUAN Jin nan, ZHEN Bin.Yearly variation features of tropical cyclone and its precipitation in
Guangdong Province of China. JOURNAL OF NATURAL DISASTERS, 2008,17(3):140-147.
• http://typhoon.weather.com.cn/hist/2013.shtml
• TROPICAL CYCLONES from 2000 to 2011. Hong Kong Observatory.
• http://gdem.ersdac.jspacesystems.or.jp/ gdem.ersdac.jspacesystems.or.jp
• http://www.noaa.gov/
Thank you for your attention!
Welcome suggestions!
Delft Software days 2014
Li Li
University of Hamburg