Mixed Hydrometeorological Processes Explain Regional Landslide Potential
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| Název: | Mixed Hydrometeorological Processes Explain Regional Landslide Potential |
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| Autoři: | Chuxuan Li, Alexander L. Handwerger, Daniel E. Horton |
| Zdroj: | Geophysical Research Letters, Vol 52, Iss 14, Pp n/a-n/a (2025) Geophysical Research Letters, vol 52, iss 14 |
| Informace o vydavateli: | American Geophysical Union (AGU), 2025. |
| Rok vydání: | 2025 |
| Témata: | 37 Earth Sciences (for-2020), QC801-809, hydrologic modeling, regional landslide potential, Geophysics. Cosmic physics, atmospheric rivers, 3701 Atmospheric Sciences (for-2020), Meteorology & Atmospheric Sciences (science-metrix), climate extremes |
| Popis: | During December 2022–January 2023, nine atmospheric rivers (ARs) struck California consecutively, causing catastrophic flooding and 600+ landslides. The extensive footprints of landslide‐triggering storms and their diverse hydrometeorological forcings highlight the urgent need to incorporate regional‐scale hydrometeorology into landslide research. Here, using a meteorologically‐informed hydrologic model, we simulate the time‐evolving water budget during the nine‐AR event and identify hydrometeorological conditions that contributed to widespread landslide occurrences across California. Our analysis reveals that 89% of observed landslides occurred under excessively wet conditions, driven by precipitation exceeding the capacities of infiltration, storage, evapotranspiration, and soil drainage. Using K‐means clustering, we identify three distinct hydrometeorological pathways that increased landslide potential: intense precipitation‐induced runoff (∼32% of reported landslides), rain on pre‐wetted soils (∼53%), and snowmelt and soil ice thawing (∼15%). Our findings highlight the importance of constraining the compounding factors that influence slope stability over spatial scales consistent with landslide‐triggering weather systems. |
| Druh dokumentu: | Article |
| Jazyk: | English |
| ISSN: | 1944-8007 0094-8276 |
| DOI: | 10.1029/2025gl115912 |
| Přístupová URL adresa: | https://doaj.org/article/f84553af14514caeb1da583295b10b3f https://escholarship.org/uc/item/5s31z847 |
| Rights: | CC BY NC |
| Přístupové číslo: | edsair.doi.dedup.....b163e90364aa13c0c43402adb8fb7238 |
| Databáze: | OpenAIRE |
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Nájsť tento článok vo Web of Science | Abstrakt: | During December 2022–January 2023, nine atmospheric rivers (ARs) struck California consecutively, causing catastrophic flooding and 600+ landslides. The extensive footprints of landslide‐triggering storms and their diverse hydrometeorological forcings highlight the urgent need to incorporate regional‐scale hydrometeorology into landslide research. Here, using a meteorologically‐informed hydrologic model, we simulate the time‐evolving water budget during the nine‐AR event and identify hydrometeorological conditions that contributed to widespread landslide occurrences across California. Our analysis reveals that 89% of observed landslides occurred under excessively wet conditions, driven by precipitation exceeding the capacities of infiltration, storage, evapotranspiration, and soil drainage. Using K‐means clustering, we identify three distinct hydrometeorological pathways that increased landslide potential: intense precipitation‐induced runoff (∼32% of reported landslides), rain on pre‐wetted soils (∼53%), and snowmelt and soil ice thawing (∼15%). Our findings highlight the importance of constraining the compounding factors that influence slope stability over spatial scales consistent with landslide‐triggering weather systems. |
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| ISSN: | 19448007 00948276 |
| DOI: | 10.1029/2025gl115912 |