An empirical method to forecast the effect of storm intensity on shallow landslide abundance

We hypothesize that the number of shallow landslides a storm triggers in a landscape increases with rainfall intensity, duration and the number of unstable model cells for a given shallow landslide susceptibility model of that landscape. For selected areas in California, USA, we use digital maps of historic shallow landslides with adjacent rainfall records to construct a relation between rainfall intensity and the fraction of unstable model cells that actually failed in historic storms. We find that this fraction increases as a power law with the 6-hour rainfall intensity for sites in southern California. We use this relation to forecast shallow landslide abundance for a dynamic numerical simulation storm for California, representing the most extreme historic storms known to have impacted the state.