the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Characterizing the scale of regional landslide triggering from storm hydrometeorology
Abstract. Rainfall strongly affects landslide triggering; however, understanding how storm characteristics relate to the severity of landslides at the regional scale has thus far remained unclear, despite the societal benefits that would result from defining this relationship. As mapped landslide inventories typically cover a small region relative to a storm system, here we develop a proxy for landslide-inducing rainfall, A*, based on extremes of modelled soil water relative to its local climatology. We calibrate A* using four landslide inventories, comprising over 11,000 individual landslides over four unique storm events, and find that a common threshold can be applied to estimate regional shallow landslide triggering potential across diverse climatic regimes in California (USA). We then use the spatial distribution of A*, along with topography, to calculate the landslide potential area (LPA) for nine landslide-inducing storm events over the past twenty years, and test whether atmospheric metrics describing the strength of landfalling storms, such as integrated water vapor transport, correlate with the magnitude of hazardous landslide-inducing rainfall. We find that although the events with the largest LPA do occur during exceptional atmospheric river (AR) storms, the strength of landfalling atmospheric rivers does not scale neatly with landslide potential area, and even exceptionally strong ARs may yield minimal landslide impacts. Other factors, such as antecedent soil moisture driven by storm frequency, and mesoscale precipitation features within storms, are instead more likely to dictate the patterns of landslide-generating rainfall throughout the state.
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RC1: 'Review of “Characterizing the scale of regional landslide triggering from storm hydrometeorology” by Perkins et al.,', Odin Marc, 22 Apr 2024
The authors present an analysis of several storms induced landslide events, most relating to atmospheric rivers phenomena in California. They retrieve rainfall from a gridded gauge product (covering >10 years, 6hr resolution, 4km spatial resolution), and a leaky bucket model to constrain regolith moisture and derive a soil moisture anomaly, A*, relative to a 15 yr return event. They show that 15 yr return appear to be the minimal return time for causing extensive landsliding based on 4 well constrained cases and then show and discuss the advantage of using a soil moisture anomaly (rather than simple rainfall anomaly) to understand landsliding triggered by rainfall in California. The work is a nice progression from previous work arguing for the use of anomaly to study landslide event (Rainfall anomaly for Marc et al., 2019, or soil moisture anomaly for Saito and Matusyama 2012, but with a more complex methodology and rather preliminary data). Therefore the authors’ work goes provides first basis for simple, physically meainingful and regional scale indicators that could provide a basis for landslide hazard forecasting during storms. In terms of methodology and presentation, I had reviewed a previous version of this work and a lot of my previous concerns in terms of methodology and clarity have been addressed and this version of the draft appears very clear and well thought to me. I therefore congratulate the authors, as I think the work will be a very good contribution to Esurf !
I provide in the attached document a series of minor comments where I have identified potential improvements.
Sincerely, Odin Marc
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AC1: 'Reply on RC1', Jonathan Perkins, 17 Jul 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-873/egusphere-2024-873-AC1-supplement.pdf
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AC1: 'Reply on RC1', Jonathan Perkins, 17 Jul 2024
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RC2: 'Comment on egusphere-2024-873', Ben Mirus, 14 May 2024
This is a nice contribution to the literature in landslide science focused on spatiotemporal assessment of landslide potential using a simplified rainfall index approach. The concept is novel and the manuscript is well written, but some important details are missing related to the simplifying assumptions and methodology, as well as some critical discussion. These gaps can be addressed by addressing my comments in the attached document. Following these revisions the manuscript should ultimately be published as a final paper in NHESS.
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AC2: 'Reply on RC2', Jonathan Perkins, 18 Jul 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-873/egusphere-2024-873-AC2-supplement.pdf
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AC2: 'Reply on RC2', Jonathan Perkins, 18 Jul 2024
Status: closed
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RC1: 'Review of “Characterizing the scale of regional landslide triggering from storm hydrometeorology” by Perkins et al.,', Odin Marc, 22 Apr 2024
The authors present an analysis of several storms induced landslide events, most relating to atmospheric rivers phenomena in California. They retrieve rainfall from a gridded gauge product (covering >10 years, 6hr resolution, 4km spatial resolution), and a leaky bucket model to constrain regolith moisture and derive a soil moisture anomaly, A*, relative to a 15 yr return event. They show that 15 yr return appear to be the minimal return time for causing extensive landsliding based on 4 well constrained cases and then show and discuss the advantage of using a soil moisture anomaly (rather than simple rainfall anomaly) to understand landsliding triggered by rainfall in California. The work is a nice progression from previous work arguing for the use of anomaly to study landslide event (Rainfall anomaly for Marc et al., 2019, or soil moisture anomaly for Saito and Matusyama 2012, but with a more complex methodology and rather preliminary data). Therefore the authors’ work goes provides first basis for simple, physically meainingful and regional scale indicators that could provide a basis for landslide hazard forecasting during storms. In terms of methodology and presentation, I had reviewed a previous version of this work and a lot of my previous concerns in terms of methodology and clarity have been addressed and this version of the draft appears very clear and well thought to me. I therefore congratulate the authors, as I think the work will be a very good contribution to Esurf !
I provide in the attached document a series of minor comments where I have identified potential improvements.
Sincerely, Odin Marc
-
AC1: 'Reply on RC1', Jonathan Perkins, 17 Jul 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-873/egusphere-2024-873-AC1-supplement.pdf
-
AC1: 'Reply on RC1', Jonathan Perkins, 17 Jul 2024
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RC2: 'Comment on egusphere-2024-873', Ben Mirus, 14 May 2024
This is a nice contribution to the literature in landslide science focused on spatiotemporal assessment of landslide potential using a simplified rainfall index approach. The concept is novel and the manuscript is well written, but some important details are missing related to the simplifying assumptions and methodology, as well as some critical discussion. These gaps can be addressed by addressing my comments in the attached document. Following these revisions the manuscript should ultimately be published as a final paper in NHESS.
-
AC2: 'Reply on RC2', Jonathan Perkins, 18 Jul 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-873/egusphere-2024-873-AC2-supplement.pdf
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AC2: 'Reply on RC2', Jonathan Perkins, 18 Jul 2024
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