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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 19, issue 1
Hydrol. Earth Syst. Sci., 19, 427–449, 2015
https://doi.org/10.5194/hess-19-427-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Hydrol. Earth Syst. Sci., 19, 427–449, 2015
https://doi.org/10.5194/hess-19-427-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 22 Jan 2015

Research article | 22 Jan 2015

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)

A. Vallet, C. Bertrand, O. Fabbri, and J. Mudry A. Vallet et al.
  • UMR6249 – Chrono-Environnement, Université de Franche-Comté, 16 route de Gray, 25030 Besançon CEDEX, France

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).

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