An evaluation and comparison of hydroclimatic data preceding extremely rapid glaciolacustrine landslides
Notice bibliographique
Résumé
Deep-seated landslides in overconsolidated glaciolacustrine materials typically cycle through episodic periods of gradual acceleration and deceleration. The 1973 Attachie landslide (BC, Canada) and 2014 Oso landslide (Washington, USA) are well-known examples of landslides that deviate from this trend, instead failing extremely rapidly, with considerable runout that dammed the Peace River (Attachie) and impacted a community nearly 1.5 km away, resulting in 43 fatalities (Oso). Given the velocity and runout distance of these two landslides, further characterization of the landslide, priming, and trigger mechanisms may help manage geohazard risk for other landslides in similar terrain.The landslide mechanisms and antecedent climatic conditions prior to failure have been relatively well studied for the Attachie and Oso landslides. As part of these studies, hydroclimatic re-analysis tools have been applied, correlating soil moisture data with precipitation records to understand the dominant timescale by which hydroclimatic conditions may have triggered activity within these landslides in the past.In spring 2022, another extremely rapid landslide derived from glaciolacustrine materials occurred on the Halfway River, less than 10 km away from and initiating within the same geological unit as the 1973 Attachie landslide. The objectives of this study are twofold: to apply the same hydroclimatic re-analysis and precipitation review methodology to the Halfway River landslide, and to compare hydroclimatic trends across all three landslides. Comparison of landslide morphology, mechanisms, and material properties between these landslides are left to future research.Soil moisture and precipitation data were obtained from the land component of the ERA5 climatological re-analysis data produced by Copernicus Climate Change Service of the European Union. At the Halfway River slide, soil moisture (1-3 m depth) was above the monthly average for 65% of the months since over the 8-year period prior to the failure, with above-average annual soil moisture in 5 of the 8 years. Soil moisture and precipitation at the time of failure were not exceptional, although the failure occurred during the first rain-on-snow event in above-zero °C conditions of the year, which may be the triggering event. Annual precipitation and soil moisture in the year prior to the April 2022 failure were below average, indicating that one year of drier-than-average conditions may be insufficient in arresting the deformation processes that are hypothesized to predicate these extremely rapid failures.No discrete trigger was identified for the Attachie landslide. The dominant theory is that a longer-term internal deformation and acceleration trend associated with a 10-to-15-year period of above-average soil moisture preceding the 1973 failure caused the event. At the Oso landslide, a possible triggering event was identified from a nearly one in 10-year soil moisture peak, resulting from both a longer-term elevated soil moisture trend and three weeks of intense rainfall. This occurred in the context of a 4-year period of above-average precipitation. While it is likely that a variety of processes contributed to the extremely rapid failures of these landslides, these examples support the current hypothesis that multi-year moisture trends drive gradual deformation, preconditioning these slopes for extremely rapid failures.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
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Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».