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Regional Debris-Flow Hazard Assessments

Horton, Pascal ; Lombardo, Luigi ; Mergili, Martin ; Wichmann, Volker ; Dahal, Ashok ; van den Bout, Bastian ; Guthrie, Richard ; Scheikl, Manfred ; Han, Zheng ; Sturzenegger, Matthieu

Advances in Debris-flow Science and Practice, 2024, p.383-432

Cham: Springer International Publishing

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  • Título:
    Regional Debris-Flow Hazard Assessments
  • Autor: Horton, Pascal ; Lombardo, Luigi ; Mergili, Martin ; Wichmann, Volker ; Dahal, Ashok ; van den Bout, Bastian ; Guthrie, Richard ; Scheikl, Manfred ; Han, Zheng ; Sturzenegger, Matthieu
  • É parte de: Advances in Debris-flow Science and Practice, 2024, p.383-432
  • Descrição: Regional debris-flow hazard assessments provide consistent information on potential hazards over large areas, often with limited available data. Different approaches to regional debris-flow hazard assessment include heuristic, empirical, statistical, or physically-based techniques. The resulting product is often a debris-flow susceptibility map that identifies locations where such events are more likely to occur. These locations can also be related to frequent events that have occurred in the past and are therefore more likely to occur in the future under similar conditions. This chapter provides an overview of these different approaches and a description of the models available at the time of writing. It details the assessment of the potential source areas and the runout, as well as how these two steps can be coupled. Some data-related issues and other challenges are then discussed. The first common problem is data scarcity, which impacts methods in different ways. Physically-based methods are demanding in terms of input data, while data-driven models require event inventories that should be as exhaustive as possible. Landslide inventories are important for every regional-scale approach, and compiling such an inventory is time-consuming and often biased due to mapping preferences. This raises questions about the impact of the completeness of these datasets and whether incomplete inventories still provide reliable predictive maps, mainly for data-driven models. As has been repeatedly demonstrated, the Digital Elevation Model (DEM) is an essential dataset for most methods, and its quality has an impact on the results of both the source areas assessment and the runout computation. In addition to the accuracy aspect, its resolution has a substantial impact on the calculated derivatives such as slope gradient or curvature, as well as on the modelled runout. Low-resolution datasets lack certain terrain features that may be relevant, but DEMs used at too high of a resolution are likely to add noise for regional-scale studies. These impacts may be overlooked by end-users. In light of these challenges, it is important to recognize that the data collected to run our models is a snapshot of the state of the environment at a given time. Yet we live in a changing environment, with, for example, changes in topography due to earthquakes, volcanic eruptions, avulsions, debris deposition, and human constructions. In addition, the climate is changing, affecting the frequency and intensity of extreme precipitation events, and consequently the frequency with which debris flows are triggered. As a result, new sites with little or no history of debris flows may be affected in the future. On the other hand, more frequent debris flows may reduce the volume of sediment transported in catchments with limited supply. A changing environment therefore brings uncertainties to the data used by our models, which may underestimate or overestimate potential susceptibility to debris flows in the future. With this in mind, we discuss the perspective of dynamic approaches. Finally, regional methods have several limitations. They rely on data available for large regions, but do not account for local watershed characteristics, such as sediment supply linked to specific geological processes. Site-specific conditions can also influence the runout computation, leading to atypical debris-flow trajectories. Additionally, regional models are not designed to provide reliable volume estimates or frequency-magnitude relationships, making them unsuitable for quantitative risk assessments, modelling specific events, or designing mitigation structures. Typically, the susceptibility map serves as the initial step in prioritizing areas requiring detailed debris-flow hazard mapping.
  • Títulos relacionados: Geoenvironmental Disaster Reduction
  • Editor: Cham: Springer International Publishing
  • Idioma: Inglês
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