Insights from the topographic characteristics of a large global catalog of rainfall-induced landslide event inventories

Abstract

Abstract. Landslides are a key hazard in high-relief areas around the world and pose a risk to population and infrastructure. It is important to understand where landslides are likely to occur in the landscape to inform local analyses of exposure and potential impacts. Large triggering events such as earthquakes or major rain storms often cause hundreds or thousands of landslides, and mapping the landslide populations generated by these events can provide extensive datasets of landslide locations. Previous work has explored the characteristic locations of landslides triggered by seismic shaking, but rainfall induced landslides are likely to occur in different parts of a given landscape when compared to seismically induced failures. Here we show measurements of a range of topographic parameters associated with rainfall-induced landslides inventories, including a number of previously unpublished inventories which we also present here. We find that average upstream angle and compound topographic index are strong predictors of landslide headscarp location, while local relief and topographic position index provide a stronger sense of where landslide material may end up (and thus where hazard may be highest). By providing a large compilation of inventory data for open use by the landslide community, we suggest that this work could be useful for other regional and global landslide modelling studies and local calibration of landslide susceptibility assessment, as well as hazard mitigation studies.

Estimating global landslide susceptibility and its uncertainty through ensemble modelling

“…CTI intrinsically contains information on the potential hydrological conditions of the site (through the catchment area) as well as its slope. In line with our study, Emberson et al (2021) found that the CTI is a strong predictor of rainfall-induced landslides for a number of inventories in the tropics and subtropics. Earlier global LSS maps by Nadim et al (2006), Hong et al (2007) 290 and Stanley and Kirschbaum (2017) primarily used slope information, while Lin et al (2017) use relative relief.…”

Retrieval of Monsoon Landslide Timings With Sentinel‐1 Reveals the Effects of Earthquakes and Extreme Rainfall

“…Instead, with ϕ = θ in the range 30°-50°, we obtain cohesions between 2 and 10 kPa, values that are typical for shallow landslides (Gabet et al, 2004;von Ruette et al, 2014;Wu & Sidle, 1995). This is consistent with recent studies where landslide susceptibility (whether triggered by rainfall or earthquakes) was found to scale with slope normalized by the landscape median rather than absolute slope, suggesting that mechanical strength (i.e., ϕ) is adjusted to the landscape (i.e., θ) (Emberson et al, 2021;Marc et al, 2018;Milledge et al, 2019). Furthermore, fixing C = 4,000 kPa in Equation 4and solving for ϕ yields a strong correlation between ϕ and θ and a reduced ϕ value in 2015 (Figures S4 and S5 in Supporting Information S1).…”

Observations and computational multi‐phase modelling in tropical river settings show complex channel changes downstream from rainfall‐triggered landslides

“…The effects of climate change are likely to increase the frequency of occurrence of landslides (Gariano & Guzzetti, 2016). Rivers in the Philippines are particularly dynamic, with fluctuating sediment supply from landslides (Abancó et al, 2021;Catane et al, 2012;Emberson et al, 2022), earthquakes (Atkinson, 1995), volcanoes (Gran et al, 2011) and anthropogenic activities such as dam construction for water supply, hydropower and mine tailings (Tabios III, 2020) contributing to globally high river migration rates (Dingle et al, 2019). Emblematic of this dynamism, high rates of river planform adjustment have been observed in the vicinity of bridge infrastructure (Boothroyd et al, 2021).…”