Four-dimensional surface motions of the Slumgullion landslide and quantification of hydrometeorological forcing

Landslides modify the natural landscape and cause fatalities and property damage worldwide.
Quantifying landslide dynamics is challenging due to the stochastic nature of the environment.
With its large area of ~1 km2 and perennial motions at ~10–20mm per day, the
Slumgullion landslide in Colorado, USA, represents an ideal natural laboratory to better
understand landslide behavior. Here, we use hybrid remote sensing data and methods to
recover the four-dimensional surface motions during 2011–2018. We refine the boundaries of
an area of ~0.35 km2 below the crest of the prehistoric landslide. We construct a mechanical
framework to quantify the rheology, subsurface channel geometry, mass flow rate, and
spatiotemporally dependent pore-water pressure feedback through a joint analysis of displacement
and hydrometeorological measurements from ground, air and space. Our study
demonstrates the importance of remotely characterizing often inaccessible, dangerous slopes
to better understand landslides and other quasi-static mass fluxes in natural and industrial
environments, which will ultimately help reduce associated hazards.