To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure firstname.lastname@example.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Runout analysis is a key component of landslide risk assessment and management, and a range of empirical and numerical methods for analyzing runout are available. Significant advances have been made in the development of numerical runout models over the past decade, particularly with respect to three-dimensional modeling capabilities. As demonstrated in a recent model benchmarking workshop, most modern numerical models are able to simulate the bulk characteristics of typical real landslides. On the other hand, progress has been slower in developing suitable methodologies for selecting input parameter values for prediction. Ideally, these methods should fit within the probabilistic framework of quantitative landslide risk assessment, allowing users to estimate the spatial probability of impact and associated hazard intensity throughout the runout zone. Recent work on advanced model calibration techniques has attempted to address this need. Simple probabilistic empirical–statistical techniques can be extended to numerical modeling applications and provide a useful reference point for these discussions.