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Susana Ochoa-Rodríguez SPN7 Conference – 30.08.2013
On the possibility of calibrating urban storm-water drainage models using gauge-based adjusted radar rainfall
estimates
Presenter: Susana Ochoa-Rodríguez
Authors: S. Ochoa-Rodriguez, L. Wang, N. Simões, C. Onof and C. Maksimovic
7th International Conference on Sewer Processes & Networks
Sheffield, UK, 30th August 2013
Susana Ochoa-Rodríguez SPN7 Conference – 30.08.2013
1. CONTEXT
Susana Ochoa-Rodríguez SPN7 Conference – 30.08.2013
Urban storm water drainage models
• These models are essential tools for:
• Urban planning
• Real time operation
• Urban flood forecasting and warning
Susana Ochoa-Rodríguez SPN7 Conference – 30.08.2013
“… Rainfall is the main input for urban pluvial flood models and the uncertainty
associated to it dominates the overall uncertainty in the modelling and
forecasting of these type of flooding… ’’ (Golding, 2009)
We really need to get the rainfall right!
Sensors commonly used for estimation of rainfall at catchment scales
RAINGAUGE RADAR
Accuracy
Coverage, spatial characterisation of rainfall field
Raingauge Weather Radar
Susana Ochoa-Rodríguez SPN7 Conference – 30.08.2013
Traditionally: calibration of models using only rain gauge data
May lead to overly conservative models due assumption of uniformly
distributed rain fields
In recent years: radar data increasingly available, have started to be used operationally (for calibration and RT applications)
Insufficient accuracy of radar rainfall estimates has proved problematic (e.g. it may result in physically
unfeasible parameters)
Susana Ochoa-Rodríguez SPN7 Conference – 30.08.2013
Dynamic local radar-raingauge merging or adjustment
Aim: To combine the advantages of radar and raingauge sensors to have a better spatial description and local accuracy of urban rainfall
Gauge-based adjusted radar rainfall estimates have not (are not normally) used for calibration of urban drainage
models
Susana Ochoa-Rodríguez SPN7 Conference – 30.08.2013
OBJECTIVE OF THIS WORK
To explore the possibility of improving the applicability of radar rainfall estimates to the calibration of urban storm-water drainage models by employing gauge-based radar
rainfall adjustment techniques
Susana Ochoa-Rodríguez SPN7 Conference – 30.08.2013
2. EXPERIMENTAL SITE AND DATASET
Susana Ochoa-Rodríguez SPN7 Conference – 30.08.2013
BEDDINGTON CATCHMENT, LONDON BOROUGH OF CROYDON
• Whole drainage area: 64 km2
• Highly urbanised
• Highly susceptible to surface water flooding
Sewer Network
Model of the sewer system of the Purley Area
• Number of nodes: 10,205
• Number of links: 10,500
• Pipe length: 708 km
• Semi-distributed model
• Number of subcatchments: 5,185
• Mean subcatchment area: 1.2 ha
• Verified in 2011 using predominantly radar data (but this was difficult!)
Rainfall and flow monitoring data for model calibration
• Medium term flow survey data:
– Carried out by TW between 28/01/11 and 13/07/11
– 79 flow gauges
– 18 rain gauges
– 2 min resolution
• Radar (Nimrod) data available at 1 km – 5 min
Susana Ochoa-Rodríguez SPN7 Conference – 30.08.2013
3. METHODOLOGY
Susana Ochoa-Rodríguez SPN7 Conference – 30.08.2013
Applied different rainfall inputs to the recently verified model of the catchment:
1. Original raingauge data, applied using Thiessen Polygons
2. Original radar (Nimrod) data
3. Merged rainfall data (using Bayesian methodology)
(3 storms were analysed – the same used for calibration)
Given the problems reported by the modeller when verifying the model using predominantly radar rainfall estimates, it was expected that a better goodness of fit could be achieved by simply inputting merged rainfall inputs
into the recently verified model of Beddington
Characteristics of rainfall events under consideration, as measured by raingauges and radar
MAX/MIN RAINFALL DEPTH AND INTENSITY AT INDIVIDUAL RG / RD GRID
Event Period
(length in hr)
RG Total
(mm)
RG Peak
(mm/hr)
RD Total
(mm)
RD Peak
(mm/hr)
Max/min Max/min Max/min Max/min
E1 05-07/05/11 (72 hrs) 43.8/23.8 10.8/3.6 87.5/7.2 40.2/1.2
E2 17-18/06/11 (48 hrs) 21.0/7.8 26.4/4.2 47.0/2.8 69.4/1.6
E3 05-07/07/11 (57 hrs) 10.8/4.8 16.8/2.9 18.7/1.5 31.2/0.7
AREAL AVERAGE RAINFALL DEPTH AND INTENSITY
Event Period
(length in hr)
RG Total
(mm)
RG Peak
(mm/hr)
RD Total
(mm)
RD Peak
(mm/hr)
Areal Areal Areal Areal
E1 05-07/05/11 (72 hrs) 34.5 8.0 36.4 7.1
E2 17-18/06/11 (48 hrs) 14.9 9.2 18.7 6.6
E3 05-07/07/11 (57 hrs) 7.4 4.4 7.9 2.5
Susana Ochoa-Rodríguez SPN7 Conference – 30.08.2013
4. RESULTS
Susana Ochoa-Rodríguez SPN7 Conference – 30.08.2013
Relative Error (RE) and R2 obtained for the different rainfall inputs (estimated based on
flow and depth measurements at 79 locations)
E1 E2 E3 E1 E2 E3
MEAN RE† – PEAK FLOW RATE MEAN RE† – PEAK FLOW DEPTH
RG 30.57% 40.56% 40.40% 90.96% 76.29% 20.79%
RD 28.27% 36.96% 53.59% 46.21% 24.76% 26.34%
MERGED 24.91% 29.75% 37.51% 32.34% 21.12% 18.93%
MEAN R2 – FLOW RATE MEAN R2 – FLOW DEPTH
RG 0.694 0.697 0.641 0.705 0.702 0.691
RD 0.666 0.667 0.575 0.703 0.656 0.664
MERGED 0.701 0.703 0.633 0.748 0.713 0.718 † MEAN RE%=OPeak-SpeakOPeak,
where Opeak and Speak represent the maximum observed and simulated flows
Susana Ochoa-Rodríguez SPN7 Conference – 30.08.2013
5. CONCLUSIONS AND FUTURE WORK
Susana Ochoa-Rodríguez SPN7 Conference – 30.08.2013
Conclusions & Future Work
• It is possible to calibrate storm-water drainage models using gauge-based adjusted rainfall inputs
• In fact, better results may be achieved when using gauge-based adjusted rainfall inputs, as these can better capture the spatial structure and accuracy of rainfall fields
• Future work: Uncertainty-based calibration of storm water drainage models considering rainfall uncertainty explicitly
Susana Ochoa-Rodríguez SPN7 Conference – 30.08.2013
THANK YOU
Susana Ochoa-Rodríguez