On the possibility of calibrating urban storm-water drainage models using gauge-based adjusted radar rainfall estimates
File(s)Susana_Ochoa_Calibration_merged_rainfall.pdf (372.2 KB)
Accepted version
Author(s)
Ochoa-Rodriguez, S
Wang, L
Simoes, N
Onof, C
Maksimović, Č
Type
Conference Paper
Abstract
Traditionally, urban storm water drainage models have been calibrated using only raingauge data, which may result in overly conservative models due to the lack of spatial description of rainfall. With the advent of weather radars, radar rainfall estimates with higher temporal and spatial resolution have become increasingly available and have started to be used operationally for urban storm water model calibration and real time operation. Nonetheless, the insufficient accuracy of radar rainfall estimates has proven problematic and has hindered its widespread practical use. This work explores 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. Four different types of rainfall estimates were used as input to the recently verified urban storm water drainage models of the Beddington catchment in South London; these included: raingauge, block-kriged raingauge, radar (UK Met Office Nimrod) and the adjusted (or merged) radar rainfall estimates. The performance of the simulated flow and water depths was assessed using measurements from 78 gauges. Results suggest that a better calibration could be achieved by using the block-kriged raingauge and the adjusted radar estimates as input, as compared to using only radar or raingauge estimates.
Date Issued
2013
Citation
2013
Copyright Statement
© The Authors.
Description
24/07/14 meb. Authors did not sign CTA.
Identifier
internal-pdf://susana_ochoa_calibration_merged_rainfall-3377264736/Susana_Ochoa_Calibration_merged_rainfall.pdf
Source
7th International Conference on Sewer Processes & Networks
Place of Publication
Sheffield, UK
Start Date
27 Aug 2013
Finish Date
30 Aug 2013