Landslide

Susceptibility

The methodology involves integrating landslide susceptibility and earthquake characteristics or rainfall data to determine, on a global scale, the probability of earthquake- and precipitation-induced landslides. The latter is assessed for both present and future climate conditions. The susceptibility map categorizes different terrains into five susceptibility classes, considering factors such as slope, vegetation (land use), lithology, and soil moisture, using global datasets.

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Flowchart of the landslide hazard model and risk assessment for critical infrastructure.

To evaluate the potential for rainfall-triggered landslides, 24-hour rainfall intensities are utilized to classify areas into five rainfall hazard classes. The potential for earthquake-induced landslides is assessed based on the peak ground acceleration (PGA) of the earthquake event (scenario) at a given location and the susceptibility index of the terrain at that location. The landslide susceptibility map(s) and rainfall data or earthquake PGA are combined to produce a hazard matrix. The result is a probabilistic hazard map that can be used for scenario-based assessment of global landslide risk to critical infrastructure, with a resolution of three arc seconds (approximately 90 meters at the equator) for the whole globe.

More detailed information: 

A new model for global landslide susceptibility assessment and scenario-based hazard assessment (2023)

Rosa M. Palau, Farrokh Nadim, Eivind Paulsen, Erlend Storrøsten

Global Infrastructure Resilience 2023 Position Paper available here

Risk

The proposed fully probabilistic risk assessment considers multiple events of multiple hazards, which implies the simulation of thousands of possibilities in which those hazards may manifest, under future changing climates. For each simulated event, the damage to the infrastructure system is quantified through the vulnerability functions. Repeating this process for different hazard events results in different damages simulated for the same infrastructure, each rendering some economic loss with a probability of occurrence. Typically, low damage events have a higher probability of occurrence, which means they are more frequent, and high damage events have lower probabilities or are less frequent (see Figure below). This collection of loss amounts and probabilities makes up a truly probabilistic and multi-hazard risk assessment of any infrastructure system. This process will be applied to all infrastructure sectors country-by-country

 

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Illustration of the calculation of loss in an event-based probabilistic risk assessment

Although disaster risk is fully quantified by the set of losses, it is more practical to express it as condensed metrics that summarize the results into curves or point estimates. Two of the most widely used metrics are the Probable Maximum Loss (PML) curve and the Average Annual Loss (AAL). 

The PML curve describes the variation of losses to the return period. It fully integrates all the consequences, even of different hazards, to define the feasibility that large loss amounts occur sometime in the future. 

On the other hand, the AAL is a multi-annual loss average, like an insurance premium, i.e., it quantifies an annual loss that, in the long term, accumulates to the total amount of losses that will be caused by disasters to the infrastructure. It is a multi-hazard metric as well.