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Open AccessArticle

Optimal Temporal Resolution of Rainfall for Urban Applications and Uncertainty Propagation

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Department of Civil Engineering, University of Bristol, Bristol BS8 1US, UK
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Coasts, Rivers and Land Reclamation PMC, Witteveen + Bos, 7400 AE Deventer, The Netherlands
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School of GeoSciences, University of Edinburgh, King's Buildings, EH9 3JN Edinburgh, UK
*
Author to whom correspondence should be addressed.
Water 2017, 9(10), 762; https://doi.org/10.3390/w9100762
Received: 29 June 2017 / Revised: 20 September 2017 / Accepted: 22 September 2017 / Published: 4 October 2017
(This article belongs to the Special Issue Quantifying Uncertainty in Integrated Catchment Studies)
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. View Full-Text
Keywords: Kriging with External Drift; radar-rain gauge merging; rain gauge random error model; rainfall temporal downscaling; uncertainty propagation; rainfall ensembles Kriging with External Drift; radar-rain gauge merging; rain gauge random error model; rainfall temporal downscaling; uncertainty propagation; rainfall ensembles
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Cecinati, F.; De Niet, A.C.; Sawicka, K.; Rico-Ramirez, M.A. Optimal Temporal Resolution of Rainfall for Urban Applications and Uncertainty Propagation. Water 2017, 9, 762.

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