Projects per year
Abstract
This work presents the results of the implementation of a probabilistic system to model the uncertainty associated to radar rainfall (RR) estimates and the way this uncertainty propagates through the sewer system of an urban area located in the North of England. The spatial and temporal correlations of the RR errors as well as the error covariance matrix were computed to build a RR error model able to generate RR ensembles that reproduce the uncertainty associated with the measured rainfall. The results showed that the RR ensembles provide important information about the uncertainty in the rainfall measurement that can be propagated in the urban sewer system. The results showed that the measured flow peaks and flow volumes are often bounded within the uncertainty area produced by the RR ensembles. In 55% of the simulated events, the uncertainties in RR measurements can explain the uncertainties observed in the simulated flow volumes. However, there are also some events where the RR uncertainty cannot explain the whole uncertainty observed in the simulated flow volumes indicating that there are additional sources of uncertainty that must be considered such as the uncertainty in the urban drainage model structure, the uncertainty in the urban drainage model calibrated parameters, and the uncertainty in the measured sewer flows.
Original language | English |
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Pages (from-to) | 17-28 |
Number of pages | 12 |
Journal | Journal of Hydrology |
Volume | 528 |
Early online date | 8 Jun 2015 |
DOIs | |
Publication status | Published - Sep 2015 |
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Projects
- 1 Finished
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Urban flood modelling using probabilistic radar rainfall ensembles
1/01/11 → 1/05/12
Project: Research
Equipment
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HPC (High Performance Computing) facility
Caroline E Gardiner (Manager)
IT ServicesFacility/equipment: Facility
Profiles
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Dr Miguel A Rico-Ramirez
- Department of Civil Engineering - Associate Professor of Radar Hydrology and Hydroinformatics
- Water and Environmental Engineering
- Cabot Institute for the Environment
Person: Academic , Member