Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/hess-2017-308
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
19 Jun 2017
Review status
This discussion paper is a preprint. A revision of this manuscript was accepted for the journal Hydrology and Earth System Sciences (HESS) and is expected to appear here in due course.
Impact of rainfall spatial aggregation on the identification of debris flow occurrence thresholds
Francesco Marra1, Elisa Destro2, Efthymios I. Nikolopoulos3, Davide Zoccatelli1,2, Jean Dominique Creutin4, Fausto Guzzetti5, and Marco Borga2 1Institute of Earth Sciences, Hebrew University of Jerusalem, Israel
2Department of Land, Environment, Agriculture and Forestry, University of Padova, Italy
3Department of Civil and Environmental Engineering, University of Connecticut, Storrs, USA
4Institut des Géosciences pour l’Environnement, Université de Grenoble Alpes/CNRS, France
5Instituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle Ricerche, Perugia, Italy
Abstract. The systematic underestimation observed in debris flows early warning thresholds has been associated to the use of sparse rain gauge networks to represent highly non-stationary rainfall fields. Remote sensing products permit concurrent estimates of debris flow-triggering rainfall for areas poorly covered by rain gauges, but the impact of using coarse spatial resolutions to represent such rainfall fields is still to be assessed. This study uses fine resolution radar data for ~ 100 debris flows in the eastern Italian Alps to (i) quantify the effect of spatial aggregation (1–20-km grid size) on the estimation of debris flow triggering rainfall and on the identification of early warning thresholds and (ii) compare thresholds derived from aggregated estimates and rain gauge networks of different densities. The impact of spatial aggregation is influenced by the spatial organization of rainfall and by its dependence on the severity of the triggering rainfall. Thresholds from aggregated estimates show up to 8 % and 21 % variations in the shape and scale parameters respectively. Thresholds from synthetic rain gauge networks show > 10 % variation in the shape and > 25 % systematic underestimation in the scale parameter, even for densities as high as 1/10 km−2.

Citation: Marra, F., Destro, E., Nikolopoulos, E. I., Zoccatelli, D., Creutin, J. D., Guzzetti, F., and Borga, M.: Impact of rainfall spatial aggregation on the identification of debris flow occurrence thresholds, Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-308, in review, 2017.
Francesco Marra et al.

Data sets

Radar rainfall estimation for the identification of debris-flow occurrence thresholds
F. Marra, E. I. Nikolopoulos, J. D. Creutin, and M. Borga
https://doi.org/10.1016/j.jhydrol.2014.09.039
Spatial estimation of debris flows-triggering rainfall and its dependence on rainfall return period
E. Destro, F. Marra, E. I. Nikolopoulos, D. Zoccatelli, J. D. Creutin, and M. Borga
https://doi.org/10.1016/j.geomorph.2016.11.019
Francesco Marra et al.

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Short summary
Previous studies reported a systematic underestimation of debris flows occurrence thresholds, due to the use of sparse networks in non-stationary rain fields. We analyzed high-resolution radar data to show that the spatially-aggregated estimates (e.g., satellite data) largely reduce this issue, in light of a reduced estimation variance. Our findings are transferable to other situations in which lower envelop curves are used to predict point-like events in presence of non-stationary fields.
Previous studies reported a systematic underestimation of debris flows occurrence thresholds,...
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