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by Marra, F., Nikolopoulos, E.I., Creutin, J.-D. and Borga, M.
Abstract:
Summary Debris flow occurrence is generally forecasted by means of empirical rainfall depth–duration thresholds based on raingauge observations. Rainfall estimation errors related to the sparse nature of raingauge data are enhanced in case of convective rainfall events characterized by limited spatial extent. Such errors have been shown to cause underestimation of the rainfall thresholds and, thus, less efficient forecasts of debris flows occurrence. This work examines the spatial organization of debris flows-triggering rainfall around the debris flow initiation points using high-resolution, carefully corrected radar data for a set of short duration (<30 h) storm events occurred in the eastern Italian Alps. On average, triggering rainfall presents a local peak corresponding to the debris flow initiation point, with rain depth at 5 km (10 km) distance being on average around 70% (40%) of rain depth observed at the debris flow initiation points. The peak is consistently enhanced for events characterized by short durations and causes a systematic underestimation of the rainfall depth–duration thresholds when rainfall is measured away from the debris flow initiation points. We develop an analytical framework that exploits the general characteristics of the spatial rainfall organization to predict the systematic underestimation of the depth–duration thresholds when rainfall is sampled away from the initiation points. Predictions obtained based on this analytical framework are assessed using a Monte Carlo sampling technique.
Reference:
Marra, F., Nikolopoulos, E.I., Creutin, J.-D. and Borga, M., 2016: Space-time organization of debris flows-triggering rainfall and its effect on the identification of the rainfall threshold relationshipJournal of Hydrology, 541, 246-255.
Bibtex Entry:
@Article{Marra2016,
  Title                    = {Space-time organization of debris flows-triggering rainfall and its effect on the identification of the rainfall threshold relationship},
  Author                   = {Marra, F. and Nikolopoulos, E.I. and Creutin, J.-D. and Borga, M.},
  Journal                  = {Journal of Hydrology},
  Year                     = {2016},

  Month                    = {October},
  Number                   = {Part A},
  Pages                    = {246-255},
  Volume                   = {541},

  __markedentry            = {[hymexw:]},
  Abstract                 = {Summary Debris flow occurrence is generally forecasted by means of empirical rainfall depth–duration thresholds based on raingauge observations. Rainfall estimation errors related to the sparse nature of raingauge data are enhanced in case of convective rainfall events characterized by limited spatial extent. Such errors have been shown to cause underestimation of the rainfall thresholds and, thus, less efficient forecasts of debris flows occurrence. This work examines the spatial organization of debris flows-triggering rainfall around the debris flow initiation points using high-resolution, carefully corrected radar data for a set of short duration (<30 h) storm events occurred in the eastern Italian Alps. On average, triggering rainfall presents a local peak corresponding to the debris flow initiation point, with rain depth at 5 km (10 km) distance being on average around 70% (40%) of rain depth observed at the debris flow initiation points. The peak is consistently enhanced for events characterized by short durations and causes a systematic underestimation of the rainfall depth–duration thresholds when rainfall is measured away from the debris flow initiation points. We develop an analytical framework that exploits the general characteristics of the spatial rainfall organization to predict the systematic underestimation of the depth–duration thresholds when rainfall is sampled away from the initiation points. Predictions obtained based on this analytical framework are assessed using a Monte Carlo sampling technique.},
  Copublication            = {4: 1 Is, 2 It, 1 Fr},
  Doi                      = {10.1016/j.jhydrol.2015.10.010},
  ISSN                     = {0022-1694},
  Keywords                 = {Debris flows; landslides; rainfall estimation; rainfall threshold; weather radar;},
  Owner                    = {hymexw},
  Timestamp                = {2018.08.27},
  Url                      = {http://www.sciencedirect.com/science/article/pii/S0022169415007696}
}