Improving rainfall nowcasting and urban runoff forecasting through dynamic radar-raingauge rainfall adjustment
File(s)Susana_Ochoa_Full_paper_merged_nowcasting.pdf (647.15 KB)
Accepted version
Author(s)
Type
Conference Paper
Abstract
The insufficient accuracy of radar rainfall estimates is a major source of uncertainty in short-term quantitative precipitation forecasts (QPFs) and associated urban flood forecasts. This study looks at the possibility of improving QPFs and urban runoff forecasts through the dynamic adjustment of radar rainfall estimates based on raingauge measurements. Two commonly used techniques (Kriging with External Drift (KED) and mean field bias correction) were used to adjust radar rainfall estimates for a large area of the UK (250,000 km2) based on raingauge data. QPFs were produced using original radar and adjusted rainfall estimates as input to a nowcasting algorithm. Runoff forecasts were generated by feeding the different QPFs into the storm water drainage model of an urban catchment in London. The performance of the adjusted precipitation estimates and the associated forecasts was tested using local rainfall and flow records. The results show that adjustments done at too large scales cannot provide tangible improvements in rainfall estimates and associated QPFs and runoff forecasts at small scales, such as those of urban catchments. Moreover, the results suggest that the KED adjusted rainfall estimates may be unsuitable for generating QPFs, as this method damages the continuity of spatial structures between consecutive rainfall fields.
Date Issued
2013
Citation
2013
Copyright Statement
© 2013 The Authors
Description
24.07.14.KB. Ok to add. Author says still has copyright, did not sign transfer. proceedings are freely available online.
Identifier
https://www.shef.ac.uk/spn7
Source
7th International Conference on Sewer Processes & Networks
Place of Publication
Sheffield, UK
Publisher URL
Start Date
28 Aug 2013
Finish Date
30 Aug 2013
Coverage Spatial
Sheffield, UK