An efficient workflow to accurately compute groundwater recharge for the study of rainfall-triggered deep-seated landslides, application to the Séchilienne unstable slope (western Alps)

Abstract

Abstract. Pore water pressure build-up by recharge of underground hydrosystems is one of the main triggering factors of deep-seated landslides. In most deep-seated landslides, pore water pressure data are not available since piezometers, if any, have a very short lifespan because of slope movements. As a consequence, indirect parameters, such as the calculated recharge, are the only data which enable understanding landslide hydrodynamic behaviour. However, in landslide studies, methods and recharge-area parameters used to determine the groundwater recharge are rarely detailed. In this study, the groundwater recharge is estimated with a soil-water balance based on characterisation of evapotranspiration and parameters characterising the recharge area (soil available water capacity, runoff and vegetation coefficient). A workflow to compute daily groundwater recharge is developed. This workflow requires the records of precipitation, air temperature, relative humidity, solar radiation and wind speed within or close to the landslide area. The determination of the parameters of the recharge area is based on a spatial analysis requiring field observations and spatial data sets (digital elevation models, aerial photographs and geological maps). This study demonstrates that the performance of the correlation with landslide displacement velocity data is significantly improved using the recharge estimated with the proposed workflow. The coefficient of determination obtained with the recharge estimated with the proposed workflow is 78 % higher on average than that obtained with precipitation, and is 38 % higher on average than that obtained with recharge computed with a commonly used simplification in landslide studies (recharge = precipitation minus non-calibrated evapotranspiration method).

Contribution of time-related environmental tracing combined with tracer tests for characterization of a groundwater conceptual model: a case study at the Séchilienne landslide, western Alps (France)

“…Helmstetter and Garambois (2010) showed a weak but significant correlation between rainfall signals and rockfall micro-seismicity. Vallet et al (2015) showed that the Séchilienne displacement rates are better correlated to the recharge than to the precipitation, reinforcing the significant role of groundwater flow in the Séchilienne destabilization. Because of the mountainous location of the studied landslide, precipitation consists of rain and snow.…”

“…To take into account the transit through the aquifer, the spring water δ 18 O signal was compared with the δ 18 O signal of a cumulated amount of precipitation that fell during the period between two consecutive spring sampling campaigns (about 3 months); thus, the isotopic signal of the rain collectors corresponds to the precipitation δ 18 O signal weighted by the 3-month rainfall amount. The 3-month period is based on the study of Vallet et al (2015) which shows that the best R 2 coefficient of determination between the cumulative groundwater recharge and the landslide velocity is obtained for periods from 68 to 132 days. As the landslide velocity is mainly controlled by the pore-water pressure, these periods can be considered as representative groundwater residence times.…”

“…The unstable slope boundary is defined according to the geophysical survey of Le Roux et al (2011). Recharge was computed according to the computation workflow of Vallet et al (2015) Groundwater conceptual model Stable zone: fractures vs. micro-fissured matrix Two main groundwater flow types are identified: (1) rapid and reactive water flow in fractures (S4, S13, S14, S15, S20, S21, S24 and S25; seasonal analysis, Fig. 5) which bypass the bulk of the less pervious and (2) inertial water flow from micro-fissured matrix, on which springs S9, S10 and S11 depend (seasonal analysis, Fig.…”

“…In addition, vertical gradients of the hydraulic conductivity can occur with values ranging from 10 −11 m/s at depth to 10 −5 m/s towards the decompressed surface areas (Maréchal and Etcheverry 2003). These permeability contrasts may be sufficient to support perched aquifers (Vengeon 1998;Tullen 2002;Cappa et al 2004;Binet 2006). Hydrogeological data strongly depend on the scale of observation (Clauser 1992), and local measurements are rarely representative of the overall behaviour of the aquifers.…”

Functioning and precipitation-displacement modelling of rainfall-induced deep-seated landslides subject to creep deformation

“…The soil reservoir is a soil-water balance model which simulates a diffuse groundwater recharge through soil cover according to the workflow calculation proposed by Vallet et al (2015a). This computation requires a precipitation dataset and the estimation of the evapotranspiration ET ([L] dimension) and of parameters characterising the recharge area.…”