4.7 Article

Combining spatial modelling and regionalization of rainfall thresholds for debris flows hazard mapping in the Emilia-Romagna Apennines (Italy)

Journal

LANDSLIDES
Volume 18, Issue 11, Pages 3513-3529

Publisher

SPRINGER HEIDELBERG
DOI: 10.1007/s10346-021-01739-w

Keywords

Debris flows; Spatial models; Rainfall thresholds; Hazard mapping; Apennines; Italy

Funding

  1. Agency for Civil Protection and Territorial Security of Emilia-Romagna Region

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The study combines spatial modeling and regionalization of debris rainfall thresholds to assess and map debris flow initiation hazard in the Emilia-Romagna Apennines, Italy. Different spatial statistical models were trained and compared, resulting in a hazard map that classifies areas into high, medium, low, or null hazard based on spatial and temporal probabilities. This map is considered reliable for integrating existing inventory maps in land-use regulation and emergency planning despite its limitations.
Landslides hazard assessment requires the combination of spatial and temporal probabilities. In this work, we combine spatial modelling and regionalization of debris rainfall thresholds for assessing both these probabilities and map debris flows initiation hazard over 15 x 10(3) km(2) of the Emilia-Romagna Apennines (Italy). In this area, debris flows are spatially and temporally less frequent than earth slides and earth flows. However, more than a hundred debris flows occurred in October 2014 and September 2015 during two large rainstorms clusters in Parma in Piacenza provinces; some tens of debris flows are reported to have occurred in the past and few others have occurred recently. Since landslides inventory maps used for land use planning only consider some large debris flows accumulation fans, and substantially no information is given on the slopes along which these phenomena might occur, this study aims to fill this gap by creating a hazard map using the evidences collected after the recent abovementioned multi-occurrence events. Different spatial statistical models (Frequency Ratio [FR], Weight of Evidence [WOE] and Logistic Regression [LR]), set up with various combinations of geo-environmental causal factors, have been trained using 60% of debris flow initiation points mapped after the 2014 and 2015 events. The predictive performances of the models have been compared by success rate curves using the remaining 40% of initiation points of the 2014 and 2015 events. The model with the best predictive capability (area under the curve > 0.96) has been further validated using the spatial distribution of other debris flows occurred in the period 1972-2016, and its outputs have been classified into spatial probability classes. Furthermore, the annual exceedance probability of recently published debris flows 3 h cumulated rainfall triggering thresholds has been calculated for in 185 rain gauges and regionalized by spatial interpolation. Finally, spatial and temporal probability maps ranked in a 0-1 range have been combined into a regional debris flows initiation hazard map that, on the basis of the return periods, is associated to different yearly probability values. The resulting hazard map classifies 0.87% of the area as high hazard, 2.83% as medium hazard, 0.5% as low hazard and the remaining 95.81% as null hazard. The spatial distribution of hazardous zones is quantitatively and qualitatively consistent with the spatial distribution of past debris flows. Furthermore, it is coherent with geomorphological common sense and it has proven sufficiently accurate in discriminating as hazardous the debris flows initiation zones of phenomena occurred after it was produced. On such a basis, despite its limitations, we consider the debris flows hazard map produced sufficiently reliable to integrate existing inventory maps in land-use regulation and emergency planning.

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