EXCESS: the role of excess topography and peak ground acceleration on earthquake preconditioning of landslides

Collecting unprecedented data covering parts of the world susceptible to landslides
Landslide in Malaysia

EXCESS: the role of excess topography and peak ground acceleration on earthquake preconditioning of landslides

Collecting unprecedented data covering parts of the world susceptible to landslides
Title: EXCESS: the role of excess topography and peak ground acceleration on earthquake preconditioning of landslides
Funded by:
Funding amount: £778,813
Location: Â鶹´«Ã½, UK
Dates: 16 February 2024 – 15 February 2027
Project partners: University of Cardiff; University of Exeter, Vrije Universiteit Amsterdam, AECOM UK.
Â鶹´«Ã½ PI: Professor Sarah Boulton  
 

Global hazard

Many thousands of landslides occur globally each year, killing thousands of people (e.g., from 2004 and 2010; 32,322 people died in 2,620 separate landslide events) and significantly damaging infrastructure, disrupting economies and hindering international development. Despite extensive research, the ability to forecast when and where a landslide will occur remains a fundamental scientific challenge.
The aim of this project is to combine earthquake models to landscape evolution models, and in doing so create a new coupled physics-based model that can predict the locations of areas of high landslide susceptibility. 
This highly novel modelling approach will be developed and validated using data from recent earthquake-triggered landslides across a suite of diverse global locations.

Objectives

  1. Compile pre- and/or post-earthquake landslide event inventories for the selected study regions combining published datasets of earthquake-triggered landslides.
  2. Undertake statistical analysis of the datasets in comparison to a range of geological and geomorphological variables derived from digital elevation models, satellite data, and published information.
  3. Develop landscape susceptibility and hazard models for each area based on the landslide inventories.
  4. Undertake novel computer modelling to explore the underlying physical mechanisms for the observed landscape behaviours and downstream cascading hazards.
  5. Disseminate and publicise the methods and results of the research project to ensure the impact and uptake of the research.

Shallow landslide modelling

A significant output from objective 4 is the development of '', a physics-informed component within the open-source framework.  
This component forecasts where shallow landslides, typical of co-seismic failures will occur at a landscape scale. The model extends a classic physics-based sliding block approach to landslide analysis into three dimensions and uses a probabilistic selection scheme to represent natural variability in failure occurrence to generate a representative set of landslides for further analysis and comparison to observed failures after large earthquakes.
Seismograph graphic

Complex behaviour

Recent research shows that common assumptions about the behaviour of landslides are incorrect. For example, presumptions that the rate of landsliding in a certain area is constant from year to year, or that landslides occur in similar places in those landscapes. 
In fact, sudden extreme events, such as storms and earthquakes, change the rates and patterns of landsliding. Furthermore, earthquakes not only induce landslides because of ground deformation and shaking during the event but, after an earthquake, there are increased numbers of landslides over the next 1–10 years. This process has been termed 'earthquake preconditioning'. This phenomenon poses an additional hazard and risk that is largely unrecognised and unquantified. 
Our recent ground-breaking research in Nepal suggests that there is a link between the strength of an earthquake and excess topography (areas in the landscape that are above a stable threshold slope) and subsequent landsliding triggered by the earthquake. If this relationship is true in other parts of the world, we will have a highly innovative way of locating areas at higher risk.
Joshua Jones landslide research - Nov 2021 (1280x720)

How the project addresses the issue

This project will address this critical research frontier through the study of recent events and computer modelling. 
Firstly, we will create new landslide catalogues before, during and after recent large earthquakes for different regions, using high-resolution satellite imagery. These new landslide inventories will allow us to accurately determine the long-term average rate of landslide occurrence in each region and confidently identify the size and duration of periods of increased landsliding following an earthquake. 
The regions and earthquakes selected span a range of climates, tectonic settings, and earthquake sizes to enable us to investigate the influence, and determine the relative importance that different control factors (e.g., rainfall, slope, topography, earthquake size) have at a global level, ensuring that the research outputs have wide applicability. These datasets will then be used in landslide susceptibility models at regional level to form outputs that can be used in hazard and risk mitigation by national and regional governments and agencies.
Secondly, we will develop a new process-based computer model to investigate the mechanism of earthquake landscape damage. 
Unlike empirical statistical models, process-based models explicitly simulate the drivers of landslide occurrence and can consider the impact of sudden and rapid environmental changes. 
The results of the model will be validated by the susceptibility maps, and the ability to model multiple earthquakes over periods ranging from decades to thousands of years will lead to new insights into the role of earthquake-induced and earthquake-preconditioned landslides in long-term landscape evolution, ultimately increasing the ability to accurately forecast the location of landslides across earthquake cycles.
This project is led by Dr Sarah Boulton with colleagues from the Â鶹´«Ã½, Exeter (Dr Georgina Bennett), Cardiff (Professor TC Hales), Vrije Universiteit (Dr Benjamin Campforts) and industry experts from AECOM (Dr Michael Whitworth; Dr Joshua Jones).

Â鶹´«Ã½ project team

Related research

Landslide induced damage on the outskirts of the Nepal-China border town of Kodari (Credit: Joshua Jones)

Extreme weather and earthquakes need greater attention when examining Nepal’s landslides

A landslide triggered during the 2019 monsoon season near the village of Chakhu (Credit Josh Jones, Â鶹´«Ã½)

Earthquakes and extreme rainfall lead to a significant increase in the rates of landslides in Nepal

Landslide-earthquake damage to the Arniko Highway near the Nepal-China border (1280x720)

Predicting future landslides in the Himalayas

Funded by

Centre for Research in Natural Hazards and Risk Reduction (CHaRR)

Natural hazards cause billions of dollars of damage, significantly effect people's lives, and can have long-term negative environmental effects. Climate change, population growth and urbanisation exacerbate events, and increasingly devastating cascading and multihazard sequences result in unexpected chains of events. 
CHaRR brings together researchers from across the University to tackle outstanding questions in hazard science, risk and reduction, thus contributing to the targets of the Sendai Framework for Disaster Risk Reduction 2015–2030 as well as the UN Sustainable Development Goals.
 
Lava stream flowing into the sea