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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 21, issue 9
Hydrol. Earth Syst. Sci., 21, 4525-4532, 2017
https://doi.org/10.5194/hess-21-4525-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 21, 4525-4532, 2017
https://doi.org/10.5194/hess-21-4525-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 12 Sep 2017

Research article | 12 Sep 2017

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 Francesco Marra et al.
  • 1Institute of Earth Sciences, Hebrew University of Jerusalem, 91904, Jerusalem, Israel
  • 2Department of Land, Environment, Agriculture and Forestry, University of Padova, Padua, Italy
  • 3Department of Civil and Environmental Engineering, University of Connecticut, Storrs, CT, USA
  • 4Institut des Géosciences pour l'Environnement, Université de Grenoble Alpes/CNRS, Grenoble, France
  • 5Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle Ricerche, Perugia, Italy

Abstract. The systematic underestimation observed in debris flow early warning thresholds has been associated with 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 (1–20km 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 8–21% variation in the parameters whereas 10–25% systematic variation results from the use of rain gauge networks, even for densities as high as 1∕10km−2.

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Previous studies have reported a systematic underestimation of debris flow occurrence thresholds, due to the use of sparse networks in non-stationary rain fields. We analysed high-resolution radar data to show that 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 envelope curves are used to predict point-like events in the presence of non-stationary fields.
Previous studies have reported a systematic underestimation of debris flow occurrence...
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