www.floodrisk.or g.uk Funder: EPSRC Grant: EP/FP202511/1 Advances in Flood Risk Management Science - Improved short term rainfall and urban flood prediction Prof. Čedo Maksimović Nuno Simões, Li-Pen Wang, Susana Ochoa The Royal Society, London, 5 th September 2011
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Www.floodrisk.org.ukFunder:EPSRC Grant: EP/FP202511/1 Advances in Flood Risk Management Science - Improved short term rainfall and urban flood prediction.
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Integrate state-of-the-art rainfall forecasting and modelling techniques to produce reliable rainfall forecasts as inputs for urban pluvial flood modelling/forecasting
Radar-based integrated rainfall prediction
T = Future
T = Current
10 - 30 km
1 - 2 km
C-Band
X-Band1 km
100-500 m
Ground Raingauge Network
1 km
i
CALIBRATIONi
t
Numerical Weather Prediction: UM/MM5
Temporal
Spatial
Meteorological Radar
t
STATISTICALLYDOWNSCALING
Cranbrook catchment, London, UK
The drainage area of the Cranbrook catchment is approximately 910 hectares; the main water course is about 5.75 km long, of which 5.69 km are piped or culverted.
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1 -R
elati
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Lead Time (min)
Pipe 1455.1 (Upstream)
1 km - 5 min
1 km - 10 min
1 km - 15 min
2 km - 5 min
2 km - 10 min
2 km - 15 min
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Lead Time (min)
Pipe 463.1 (Mid-Catchment)
1 km - 5 min
1 km - 10 min
1 km - 15 min
2 km - 5 min
2 km - 10 min
2 km - 15 min
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Lead Time (min)
Pipe 307.1 (Downstream)
1 km - 5 min
1 km - 10 min
1 km - 15 min
2 km - 5 min
2 km - 10 min
2 km - 15 min
Nimrod
NimrodNowcast
Y
YYError Relative
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Uncertainties of using rainfall nowcasts over different spatial and temporal scales for event 2010/08/22-23.
Uncertainties of applying downscaled rainfall inputs to hydraulic modelling for event 2010/08/22-23.
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Flow
Dep
th (m
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Time (sec)
pipe 1455.1 (upstream)
1kmMax (500m)min (500m)Max (250m)min (250m)
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0.15
0.25
0.35
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Flow
Dep
th (m
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Time (sec)
pipe 463.1 (mid-catchment)
1kmMax (500m)min (500m)Max (250m)min (250m)
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Dep
th (m
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Time (sec)
pipe 307.1 (downstream)
1kmMax (500m)min (500m)Max (250m)min (250m)
lipen
The technique is not applied to the hydraulic model directly. This sentence could be confusing
Combine local point rainfall information with interpolation techniques to provide reliable rainfall forecasts as inputs for urban pluvial flood modelling/forecasting
Raingauge-only-based rainfall prediction= Time series prediction + interpolation techniques
Example in Coimbra, Portugal
Raingauges
Levelgauges
Time series prediction (in 5 minutes): ability to generate extreme values
• Radar-based integrated rainfall prediction can effectively reflect larger scale weather variation to local scales, but– Accuracy: Data combination techniques– Resolution: Super-resolution radar images / rainfall information
• Raingauge-only spatial-temporal rainfall prediction exhibits promising predictability, but– Lead time: Improved time series prediction models – Spatial variability: Interpolation techniques
• Hybrid dual-drainage modelling may be the solution to providing fast and reliable flood prediction, but– Flood prone areas: flood map generation– Calibration: Coupled with image processing techniques
Remaining issues Prospective work to address remaining issues