Articles | Volume 23, issue 2
Hydrol. Earth Syst. Sci., 23, 829–849, 2019
Hydrol. Earth Syst. Sci., 23, 829–849, 2019

Research article 13 Feb 2019

Research article | 13 Feb 2019

Mapping rainfall hazard based on rain gauge data: an objective cross-validation framework for model selection

Juliette Blanchet et al.

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A non-stationary extreme value approach for climate projection ensembles: application to snow loads in the French Alps
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Cited articles

Ahrens, B.: Distance in spatial interpolation of daily rain gauge data, Hydrol. Earth Syst. Sci., 10, 197–208,, 2006. a
Beguería, S. and Vicente-Serrano, S. M.: Mapping the Hazard of Extreme Rainfall by Peaks over Threshold Extreme Value Analysis and Spatial Regression Techniques, J. Appl. Meteorol. Clim., 45, 108–124,, 2006. a
Beguería, S., Vicente-Serrano, S. M., López-Moreno, J. I., and García-Ruiz, J. M.: Annual and seasonal mapping of peak intensity, magnitude and duration of extreme precipitation events across a climatic gradient, northeast Spain, Int. J. Climatol., 29, 1759–1779,, 2009. a, b
Blanchet, J. and Lehning, M.: Mapping snow depth return levels: smooth spatial modeling versus station interpolation, Hydrol. Earth Syst. Sci., 14, 2527–2544,, 2010. a
Blanchet, J., Touati, J., Lawrence, D., Garavaglia, F., and Paquet, E.: Evaluation of a compound distribution based on weather patterns subsampling for extreme rainfall in Norway, Nat. Hazards Earth Syst. Sci., 15, 2653–2667,, 2015. a, b, c, d, e
Short summary
We propose an objective framework for estimating rainfall cumulative distribution functions in a region when data are only available at rain gauges. Our methodology allows us to assess goodness-of-fit of the full distribution, but with a particular focus on its tail. It is applied to daily rainfall in the Ardèche catchment in the south of France. Results show a preference for a mixture of Gamma distribution over seasons and weather patterns, with parameters interpolated with a thin plate spline.