Preferential Water Infiltration Path in a Slow-Moving Clayey Earthslide Evidenced by Cross-Correlation of Hydrometeorological Time Series (Charlaix Landslide, French Western Alps)

Abstract

Slow-moving clayey earthslides frequently exhibit seasonal activity suggesting that deformation processes do not only depend on slope and intrinsic geomechanical parameters. On the contrary, seasonal motion patterns are frequently observed with acceleration during the wet season and deceleration during the dry season. Within landslides, it is mainly the phreatic water table which is monitored. However, in the case of deep-seated landslides made of heterogeneous lithological units and with several slip surfaces, the characterization of the phreatic water table does not allow to relate satisfactorily the activity of the landslide with environmental parameters such as rainfall and subsequent water infiltration at depth. This paper presents a seasonal analysis of water infiltration within a slow-moving clayey landslide. Results of an extensive geotechnical and geophysical prospect are first exposed. Then, rainfall and water table level time series are analysed for two water tables using the cross-correlation technique: the phreatic water table located a few metres deep and a water table located above a shear surface located 12 m deep. Results show that water infiltrates faster down to the deepest water table. Then, time series were split between “dry” and “wet” seasons and the effective rainfall was computed from the original rainfall time series. Cross-correlation results show that the phreatic water table responds identically to rainfall in both seasons. On the contrary, the water table located above the shear surface has a very contrasting behaviour between summer (mainly drainage) and winter (behaviour similar to the phreatic water table with storage of water during a few weeks). This difference in behaviour is in agreement with the landslide kinematics.

Spatio‐temporal assessment of the hydrological drivers of an active deep‐seated gravitational slope deformation: The Vögelsberg landslide in Tyrol (Austria)

“…Assuming different response behaviours referring to different event characteristics, additional knowledge of the temporal boundaries of triggering events was considered for a catchment-wide response time estimation. We used a cross-correlation approach to estimate respective response times, as it is proven to be an appropriate way for an automated assessment of time lags between precipitation and landslide displacement rate time series of hydrologically driven landslides (Bievre et al, 2018;Lollino et al, 2002Lollino et al, , 2006. The cross-correlation function (R xy ) describing the correlation between the function of available water (x t ) and landslide displacement rate (y t ) under varying time lags (τ) is expressed as…”

“…Handwerger et al, (2013), for example, investigated the controls on seasonal deformation of multiple slowly moving landslides using satellite radar interferometry (InSAR) and precipitation data recorded at a rain gauge approximately 30 km away from the landslide area. Bievre et al (2018) combined extensive geophysical, geotechnical and hydrogeological investigations towards a better understanding of the causes of seasonal variations of displacement rates. They used cross-correlations between hydrometeorological and piezometer time series to prove a preferential water infiltration path in a slow-moving clayey earthslide.…”

Precursory Motion and Time‐Of‐Failure Prediction of the Achoma Landslide, Peru, From High Frequency PlanetScope Satellites

“…For that reason, and also due to its similarity with the Maca landslide, we can suspect the rain infiltration and/or the river erosion to be serious controlling factors of the Achoma landslide. Ground water storage might possibly play a role in the delayed acceleration of the landslide, as it is observed on many different slow‐moving landslides (e.g., Bièvre et al., 2018) and in particular on the nearby Maca landslide (Zerathe et al., 2016). However in Maca, despite the motion continues for weeks after the rainy season, the velocity decreases with time.…”

Electrical resistivity monitoring of an earthslide with electrodes located outside the unstable zone (Pont‐Bourquin landslide, Swiss Alps)

“…Daily rainfall was obtained from a weather station located in the village of Les Diablerets (∼1 km west of the landslide) and operated by the Federal Office of Meteorology and Climatology (Me-teoSwiss). Bièvre et al (2018b) showed that using effective rainfall improved hydrogeological interpretations compared to using total rainfall. In the same way, Uhlemann et al (2017) also used effective rainfall to interpret resistivity time series on the Hollin Hill landslide in England.…”

“…where K is the geometric factor (m), R is the electrical resistance ( ), V MN is the voltage (V) measured between electrodes M and N and I AB is the electric current (A) measured between electrodes A and B. When the method is appropriate for the site conditions, that is with a resistivity contrast sufficient enough between the landslide and the undisturbed ground, the interpretation of inverted resistivity data provides two-and three-dimensional (3D) images of the geological setting and of the landslide geometry (Chambers et al, 2011;Travelletti et al, 2012;Bièvre et al, 2018b;Crawford and Bryson, 2018). When measurements are repeated over time, the method allows the monitoring of changes in resistivity ( ρ) (Travelletti et al, 2012;Uhlemann et al, 2017) by measuring changes in the ground resistance R (c.f., equation ( 2)).…”