Ten Years of Coupled Hydrology and Hydraulic Modelling Supporting Storm Water Management: Some examples, lessons learnt and a look forward - Ole Larsen, APAC Research Director, DHI Singapore

1. Ten Years of Coupled Hydrology Hydraulic Modelling
supporting Storm Water Management
– some examples, Lessons Learnt and a look forward
Ole Larsen, APAC Research Director, DHI Singapore
Stephen J Flood, Senior Engineer, DHI UK
Nick Elderfield, MD DHI UK
© DHI

2. Urban Hydrology
Describes the complex hydrology as a
series of individual processes in the
urban environment

3. But is a reductionist
approach valid?

4. Early steps of urban overland flow models

5. The workhorse of the 90’s
© DHI
• Interpreta-tion
of
results!

6. Creating flood maps using GIS
• Lumped conceptual rainfall-runoff
models translate rainfall to pipe nodes
• Surcharge would be storred in ”artificial”
basins that represented flood areas
• Interpolation of waterlevels in GIS was
used to map flood events

7. Soon smarter solutions were made – 2D models
• Faster 2D solvers
• Availability of Lidar (an other) data
• Rainfall stations
• Data driven models

8. Structures
Structures (weirs, pumps
gates etc) cannot be
simulated in 2D.
Structures are added as 1 D
elements in the 2D models
Depending on structure also
transfer of momentum

9. Example of 1D pipe and 2D flood model coupling
© DHI

10. Coupling of river and pipeflow models
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11. First coupling interface from early 2000’s (Mouse – M21)
© DHI

12. Current interface – Pipe flow, River, and 2D - HD and AD
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13. Realistic view of urban flooding

14. Detailed models with long run time
© DHI
Slight change in work
– are the data
correct?
In this case missing
inlets lead to
misleading results

15. MIKE 21 FM Christchurch Supermodel
© DHI
Catchment area approx. 420 km2
including three river systems in
the model domain:
 Avon River
 Styx River
 Heathcote River
2D model domain:
 4.2 million elements
 10 m x 10 m resolution flexible
mesh (rectangular elements)
 Distributed rainfall-runoff, with
no losses (rain-on-grid)
Design rainfall event:
 100 year ARI rainfall
 single peak storm
 21 hour duration

16. MIKE 21 FM Christchurch Supermodel
© DHI
Run time on desktop PC with
GPU is 3.5 hours approx.
compared to weeks on desktop
CPU only hardware
16 core Dell workstation with:
 2 x Intel® Xeon® CPU ES-
2687W v2 (8 core, 3.40 GHZ)
 32 GB of RAM
 ONE GeForce GTX TITAN
GPU card
 Windows 7 operating system
Tests with TWO GPU cards show
a run time of 1.75 hours approx.

17. Desktop
CPU
user
Desktop
CPU+GPU
user

18. Can we now handle the uncertainty?
© DHI

19. • Precipitation
and snowmelt
• Vegetation
based
evapotrans-piration
and
infiltration
• Un- and
saturated
groundwater
flow
• Channel
flow in
rivers
and lakes
• Overland
surface
flow and
flooding
• Demand
driven
irrigation
• Solute
Transport
Distributed hydrology

20. SHE
• Promotion from the 80’s

21. © DHI
drainflow
leakage
rain
infiltration
runoff
evaporation
MOUSE
infiltration
MOUSE
MIKE SHE
MIKE SHE

22. Groundwater and sewer
© DHI

23. Detailed hydrological modelling
© DHI

24. © DHI

25. New standards for sewer rehabilization
© DHI

26. Distributed physically based hydrology vs RR
MIKE SHE was set up
using global coverage
spatial data sets…
Nash-Sutcliffe (R2)
1.00
0.90
0.80
0.70
0.60
0.50
0.40
0.30
0.20
0.10
0.00
Osobloga
Olza
Klodnica
Mala panew
Olawa
Nysa Klodska
Kaczawa
Sleza
Bystrzyca
Barycz
Czerna
Bobr
Average
SHE R2 NAM R2
Topography
Land use
Soil map
GW zones
..and was found to
perform better than
traditional RR
models

28. Local Area Weather Radar aka Hydrology Radar
18. August 2010 - Billund airport closed 45 minutes due to heavy rain
30
Circle diameter: 120 km
Pixel size: 500x500
Image frequency: 5 minute
Data from Vejle LAWR, DK

29. 31
LAWR – brief history
• Developed as part of EU ESPRIT
project in 1997
• First installation in 1998 – now
40+ worldwide
− One nationwide network in El Salvador
• Designed for high resolution
precipitation measurement over
small areas

30. • Range
− 60 km for forecast
− 20 km for Quantitative Precipitation Est.
• Spatial resolution (Cartesian)
− 500x500
− 250x250v
− 100x100
• Image frequency
− 1 or 5 minute
• Single layer
32

31. Example from Singapore LAWR – MSHE – Mike Urban Flood
© DHI
• Heavy event
• No attenuation

32. Example of forecasts
© DHI
Best model results for hindcast and
forecast are achieved with distributed
rainfall and hydrology
Now possible to significantly expand
urban flood forecast lead time

33. Integrated Real Time Control System
© DHI
SCADA
Models
Rainfall
forecast
• Automated operation of:
− Data collection
− Data processing
− Model execution
− Finding the optimal solution
− Control of structures
− Issue warnings
#35

34. Integrated real-time control of urban waters
© DHI
Sewer
#36

35. Trends
• Sensor technology changes from analogue to
© DHI
digital
• Crowd sourcing of data
• Apps for direct communication
• Availability of global data
• Easy distribution of results (databases, portals,
web...)
• Enough challenges for the future – but different
from the past

36. Take home messages
• Urban drainage storm water models typically need high degree of detail to
resolve the flooding – it’s important, but data are available today
• Detailed models are slow, too slow – GPU and HPC technology is a game
changer
• With all this speed provided by GPU and HPC, the uncertainty in model set-up
and parameters can be assessed => use speed advantages from GPU
for uncertainty assessment
• Physically based, distributed hydrological modelling and distributed rainfall
can be used in coupled modelling to great effect

37. Thank you for your attention
(please visit our booth to see more!)
Ole Larsen;
Stephen J Flood; and
Nick Elderfield
© DHI

38. The expert in WATER ENVIRONMENTS