An Integrated Study to Evaluate Debris Flow Hazard in Alpine Environment

Abstract

Debris flows are among the most dangerous natural processes affecting the alpine environment due to their magnitude (volume of transported material) and the long runout. The presence of structures and infrastructures on alluvial fans can lead to severe problems in terms of interactions between debris flows and human activities. Risk mitigation in these areas requires identifying the magnitude, triggers, and propagation of debris flows. Here, we propose an integrated methodology to characterize these phenomena. The methodology consists of three complementary procedures. Firstly, we adopt a classification method based on the propensity of the catchment bedrocks to produce clayey-grained material. The classification allows us to identify the most likely rheology of the process. Secondly, we calculate a sediment connectivity index to estimate the topographic control on the possible coupling between the sediment source areas and the catchment channel network. This step allows for the assessment of the debris supply, which is most likely available for the channelized processes. Finally, with the data obtained in the previous steps, we modeled the propagation and depositional pattern of debris flows with a 3D code based on Cellular Automata. The results of the numerical runs allow us to identify the depositional patterns and the areas potentially involved in the flow processes. This integrated methodology is applied to a test-bed catchment located in Northwestern Alps. The results indicate that this approach can be regarded as a useful tool to estimate debris flow related potential hazard scenarios in an alpine environment in an expeditious way without possessing an exhaustive knowledge of the investigated catchment, including data on historical debris flow events.

The Debris Flow Occurred at Ru Secco Creek, Venetian Dolomites, on 4 August 2015: Analysis of the Phenomenon, Its Characteristics and Reproduction by Models

“…The analysis of the pre-event morphology between '50s and nowadays also showed that slopes on the right side of Ru Secco Creek were routed by debris flows before their transformation in a ski resorting area while the left side was not subjected to debris flow phenomena (Figures S4, S5). In the present case study, the environmental changes due to man works can stop or reduce debris flow activity in areas prone to debris flow susceptibility, while those due to natural causes, as the formation of debris deposits caused by local terrain instabilities, if connected to the channel network (Cavalli et al, 2013;Tiranti et al, 2016Tiranti et al, , 2018, allow the conditions for debris flow occurrence, where it never did. Both the historical basins where debris flows formed until '50s and the new one of Ru Salvela are debris flow dominated according to the geomorphic indexes: the ruggedness number of Melton close or larger than 1 [0.75 is the inferior threshold value according to DeScally and Owens (2004)] and local slope larger than 0.6 m/m in the schematic diagram between local slope and drainage area proposed by Montgomery and Foufoula-Georgiou (1993) for the hillslope to valley transition also used by Tarolli and Dalla Fontana (2009).…”

Regional-scale inventory of periglacial moving landforms connected to the torrential network system

“…However, important limitations characterizing these methods can be pointed out and render them unsuitable for our research objectives. For instance, several authors have replicated the methodology developed by Cavalli et al (2013) and highlighted the indispensability of coupling such automatic approaches with geomorphological analysis based on aerial images and in situ field surveys, as relatively frequent discrepancies between computed connectivity index values and field observations were detected (e.g., Messenzehl et al, 2014;Micheletti and Lane, 2016;Tiranti et al, 2018). In addition, these different approaches for automatically inferring connectivity are generally developed at the catchment scale and aim at representing the spatial variability in sediment connectivity.…”

Linking the Random Forests Model and GIS to Assess Geo-Hazards Risk: A Case Study in Shifang County, China

“…For example, in terms of the slope index, because of the lack of a unified standard for the slope threshold, different scholars have reached very different results when determining the ranges of a slope, resulting in uncertainty in the assessment results. There are numerous risk assessment indices for geo-hazards, including hazard-forming environments, hazard factors, and hazard-bearing bodies [8]- [10].…”