Landslip Model

Overview

Landslips are natural disasters where the ground moves downhill because of gravity, taking soil, rocks, or anything that comes along the way. Landslips are very destructive, causing loss of life and destruction of property and infrastructure resulting in significant financial damage amounting to billions of dollars each year. Landslips can happen for various reasons, including geological factors (like the type of soil or rocks), geomorphology (how the land is shaped), physical factors (such as tectonic activities), and even human activities (such as land clearing). However, all landslides have one thing in common: they need a trigger to occur. The trigger is an external event or forcing event that sets off the landslips. Some common triggers include heavy rainfall, earthquakes, volcanic eruptions, storm waves, or fast-flowing rivers that erode the slopes. Among these triggers, rainfall is responsible for about 90% of landslips. When it rains heavily for a period of time, the soil becomes soaked with water, making it unstable and more likely to collapse. Because of climate change, heavy rain events are expected to increase in frequency. This means that the risk of landslips may also increase. Here, the method used to predict the annual probability of landslips is driven by changes in extreme precipitation due to climate change.

Local Context Data Use

The likelihood of a slope failing at a particular spot depends on many factors, which can be divided into (1) static factors and (2) dynamic factors. 1. Static factors determine the vulnerability of an area to slope failure, rainfall acts as a trigger for landslips. 2. Dynamic factors are those that change over time and act as triggers for slope failure. Rainfall increases the pressure of water in the tiny spaces between soil particles, making the soil weaker and more likely to fail. Landslips depend on both recent rainfall and the moisture content of the soil. This is measured using the Antecedent Rainfall Index (ARfl) which considers the weighted rainfall over a period of seven days.

Baseline Hazard Data

The Climate Risk Engines calculate the annual probability of landslips at a specific location using three inputs: (1) susceptibility, (2) number of days exceeding the baseline threshold, and (3) an event trigger coefficient.

Climate Change Projections

Gridded projections for future epochs, based on CMIP6 GCMs, are used to project the changes in daily rainfall, which are then used to calculate ARfI. The landslip model looks at the probability of increased precipitation induced landslips. Not all precipitation will be sufficient to induce a landslip, so this model relies on the number of days exceeding a baseline threshold (within a given year), an event trigger coefficient and then calculates an annual probability.