Optimal Temporal Resolution of Rainfall for Urban Applications and Uncertainty Propagation

The optimal temporal resolution for rainfall applications in urban hydrological models depends on different factors. Accumulations are often used to reduce uncertainty, while a sufficiently fine resolution is needed to capture the variability of the urban hydrological processes. Merging radar and ra...

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Bibliographic Details
Published in:Water (Basel) 2017-10, Vol.9 (10), p.762
Main Authors: Cecinati, Francesca, de Niet, Arie, Sawicka, Kasia, Rico-Ramirez, Miguel
Format: Article
Language:English
Subjects:
Case studies
Comparative analysis
Data processing
Hydrologic models
Hydrology
Position measurement
Radar
Rain
Rain and rainfall
Rainfall
Rainfall intensity
Technology application
Temporal resolution
Uncertainty
Urban areas
Urban drainage
Water levels
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Summary:The optimal temporal resolution for rainfall applications in urban hydrological models depends on different factors. Accumulations are often used to reduce uncertainty, while a sufficiently fine resolution is needed to capture the variability of the urban hydrological processes. Merging radar and rain gauge rainfall is recognized to improve the estimation accuracy. This work explores the possibility to merge radar and rain gauge rainfall at coarser temporal resolutions to reduce uncertainty, and to downscale the results. A case study in the UK is used to cross-validate the methodology. Rainfall estimates merged and downscaled at different resolutions are compared. As expected, coarser resolutions tend to reduce uncertainty in terms of rainfall estimation. Additionally, an example of urban application in Twenterand, the Netherlands, is presented. The rainfall data from four rain gauge networks are merged with radar composites and used in an InfoWorks model reproducing the urban drainage system of Vroomshoop, a village in Twenterand. Fourteen combinations of accumulation and downscaling resolutions are tested in the InfoWorks model and the optimal is selected comparing the results to water level observations. The uncertainty is propagated in the InfoWorks model with ensembles. The results show that the uncertainty estimated by the ensemble spread is proportional to the rainfall intensity and dependent on the relative position between rainfall cells and measurement points.
ISSN:2073-4441
2073-4441
DOI:10.3390/w9100762