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Atmosphere 2018, 9(11), 446; https://doi.org/10.3390/atmos9110446

Considering Rain Gauge Uncertainty Using Kriging for Uncertain Data

1
Department of Civil Engineering, University of Bristol, Queen’s Building, University Walk, Bristol BS8 1TR, UK
2
Water Management Department, Technische Universiteit Delft, Building 23, Stevinweg 1, 2628 CN Delft, The Netherlands
A previous shorter version of the paper has been presented in the 10th World Congress of EWRA “Panta Rhei” Athens, Greece, 5–9 July 2017.
*
Author to whom correspondence should be addressed.
Received: 8 August 2018 / Revised: 1 November 2018 / Accepted: 7 November 2018 / Published: 14 November 2018
(This article belongs to the Special Issue Advances in Applications of Weather Radar Data)
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Abstract

In urban hydrological models, rainfall is the main input and one of the main sources of uncertainty. To reach sufficient spatial coverage and resolution, the integration of several rainfall data sources, including rain gauges and weather radars, is often necessary. The uncertainty associated with rain gauge measurements is dependent on rainfall intensity and on the characteristics of the devices. Common spatial interpolation methods do not account for rain gauge uncertainty variability. Kriging for Uncertain Data (KUD) allows the handling of the uncertainty of each rain gauge independently, modelling space- and time-variant errors. The applications of KUD to rain gauge interpolation and radar-gauge rainfall merging are studied and compared. First, the methodology is studied with synthetic experiments, to evaluate its performance varying rain gauge density, accuracy and rainfall field characteristics. Subsequently, the method is applied to a case study in the Dommel catchment, the Netherlands, where high-quality automatic gauges are complemented by lower-quality tipping-bucket gauges and radar composites. The case study and the synthetic experiments show that considering measurement uncertainty in rain gauge interpolation usually improves rainfall estimations, given a sufficient rain gauge density. Considering measurement uncertainty in radar-gauge merging consistently improved the estimates in the tested cases, thanks to the additional spatial information of radar rainfall data but should still be used cautiously for convective events and low-density rain gauge networks. View Full-Text
Keywords: rain gauge interpolation; radar-gauge merging; measurement uncertainty; Kriging for uncertain data; rain gauge uncertainty; rain gauge errors rain gauge interpolation; radar-gauge merging; measurement uncertainty; Kriging for uncertain data; rain gauge uncertainty; rain gauge errors
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Cecinati, F.; Moreno-Ródenas, A.M.; Rico-Ramirez, M.A.; ten Veldhuis, M.-C.; Langeveld, J.G. Considering Rain Gauge Uncertainty Using Kriging for Uncertain Data. Atmosphere 2018, 9, 446.

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