A hydroclimatological approach to predicting regional landslide probability using Landlab

Strauch, Ronda; Istanbulluoglu, Erkan; Nudurupati, Sai Siddhartha; Bandaragoda, Christina; Gasparini, Nicole M.; Tucker, Gregory E.

doi:https://doi.org/10.5194/esurf-6-49-2018

Articles | Volume 6, issue 1

https://doi.org/10.5194/esurf-6-49-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/esurf-6-49-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 6, issue 1

Research article

|

07 Feb 2018

Research article |

| 07 Feb 2018

A hydroclimatological approach to predicting regional landslide probability using Landlab

Ronda Strauch, Erkan Istanbulluoglu, Sai Siddhartha Nudurupati, Christina Bandaragoda, Nicole M. Gasparini, and Gregory E. Tucker

Supplement

https://doi.org/10.5194/esurf-6-49-2018-supplement

Data sets

Regional landslide hazard using Landlab – NOCA Data R. Strauch, E. Istanbulluoglu, S. S. Nudurupati, and C. Bandaragoda https://doi.org/10.4211/hs.a5b52c0e1493401a815f4e77b09d352b

Model code and software

R. Strauch, E. Istanbulluoglu, S. S. Nudurupati, C. Bandaragoda, N. Gasparini, and G. Tucker A hydroclimatological approach to predicting regional landslide probability using Landlab: Model code and Users Manual https://doi.org/10.4211/hs.27d34fc967be4ee6bc1f1ae92657bf2b

Short summary

We develop a model of annual probability of shallow landslide initiation triggered by soil water from a hydrologic model. Our physically based model accommodates data uncertainty using a Monte Carlo approach. We found elevation-dependent patterns in probability related to the stabilizing effect of forests and soil and slope limitation at high elevations. We demonstrate our model in Washington, USA, but it is designed to run elsewhere with available data for risk planning using the Landlab.