  A main objective in landslide research is to predict how far they will
travel. Landslides are complex, and a complete understanding in principle
requires accounting for numerous parameters. Here we engender a simplification
by investigating the maximum landslide runout using granular laboratory
experiments and a scaling analysis. We find that correctly accounting for the
fall height and grain size distribution not only yields an improved correlation
of normalized runout, but also quantitatively unites laboratory and field data.
In particular, we find that the mobility of landslides increases with the
square root of the fall height and with the skewness of the grain size
distribution.
