EGU22-8407, updated on 29 Jan 2024
https://doi.org/10.5194/egusphere-egu22-8407
EGU General Assembly 2022
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Effect of temperature on post-earthquake landsliding near the epicentre of the 2008 Wenchuan earthquake

Marco Loche1, Gianvito Scaringi1, Ali P. Yunus2, Filippo Catani3, Hakan Tanyaş4, William Frodella5, Xuanmei Fan2, and Luigi Lombardo4
Marco Loche et al.
  • 1Institute of Hydrogeology, Engineering Geology and Applied Geophysics, Faculty of Science, Charles University, Czech Republic (marco.loche@natur.cuni.cz)
  • 2State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, China
  • 3Department of Geosciences, University of Padova, Padova, Italy
  • 4Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, Netherlands
  • 5Department of Earth Sciences, University of Florence, Florence, Italy

Geostatistical models of landslide susceptibility do not usually account for thermal data, although these data are widely available, and experiments demonstrate that temperature does influence the mechanical and hydraulic behaviours of soils and rocks via a variety of thermo-hydro-mechanically coupled processes.

We took the epicentral region of the 2008 Wenchuan earthquake in China as our study area, for which a rich multi-temporal inventory of landslides is available. We built a landslide susceptibility model using a generalised additive model with a slope-unit partitioning of the area (~500 km2, comprising 42 sub-catchments), and a minimal set of covariates, including the map of peak ground acceleration of the mainshock and Landsat 7 land surface temperature (LST) data retrieved from Google Earth Engine.

We demonstrated that the LST relates to the decay of post-earthquake landslide activity, and in particular that warmer slopes seems to be comparatively more affected by prolonged landsliding. We also verified that LST data provided different insight from that offered by the normalised difference vegetation index (NDVI), by running our model with NDVI maps instead of LST maps. The two input maps showed little collinearity, and the variable effects of the NDVI in the model output showed less complexity compared to those of the LST. This hints at the presence of thermo-mechanical effects in slopes in addition to the known hydrological effects, the latter being associated with changes in evapotranspiration and thus in principle capturable by the NDVI.

Even though studies in other regions, seismic and non-seismic, are necessary, we suggest that thermal data should be used in landslide susceptibility modelling more systematically because they could potentially improve the model results and suggest physically-based relationships influencing slope stability.

How to cite: Loche, M., Scaringi, G., Yunus, A. P., Catani, F., Tanyaş, H., Frodella, W., Fan, X., and Lombardo, L.: Effect of temperature on post-earthquake landsliding near the epicentre of the 2008 Wenchuan earthquake, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8407, https://doi.org/10.5194/egusphere-egu22-8407, 2022.