Forecasting landslides by taking their temperature: Combining mathematical and experimental modeling with field data on the case of the El Forn landslide (Andorra)

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Carolina Seguí , Manolis Veveakis


In this study we are suggesting a temperature-based modeling approach for deep-seated landslides, validated through combined field monitoring and experimental testing. The Silurian shales of the shear band of El Forn landslide (Andorra) have been characterized through thermal and rate controlled triaxial tests, thereby calibrating a mathematical model that is used to monitor the behavior of deep-seated landslides. We show that by measuring the temperature inside the shear band of the active landslide, we are able to quantify and reduce the uncertainty of the model's parameters, to adequately monitor and forecast the response of the selected deep-seated landslide. In particular, it is shown that by calibrating the model's parameters through the experimental and field data of a traditionally unobservable quantity, basal temperature, the model is able to reproduce the evolution of the observable displacement of the slide.





Basal temperature, Landslide monitoring, Experimental tests, Constitutive equations


Published: 2020-10-25 14:04

Last Updated: 2020-10-25 21:04


CC BY Attribution 4.0 International

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