Physical processes driving 'switching events'
Notice bibliographique
Résumé
Commonly, the parts of the glacier bed that are hydraulically connected to the surface experience significant diurnal variations in water pressure, in response to cycles of surface melting. Closely spaced points on the bed often exhibit nearly identical temporal variations in water pressure, suggesting that they are connected not only to the surface but to each other through conduits along the bed. This behaviour is typically observed directly through instrumented boreholes drilled to the glacier bed. A ‘switching event’ occurs when one of a pair of boreholes abruptly changes from being connected, in the sense of exhibiting the same diurnal oscillations as the other borehole, to being disconnected, or vice versa. A switching event is indicative of a connection through a subglacial conduit being closed, or opened, and therefore provides a limited but highly specific window into the evolution of subglacial conduits and permeability.However, in most subglacial drainage models, conduits are not represented individually but averaged over a small area of the bed to produce a macroporous continuum representation as a ‘water sheet’, quantified by a mean conduit depth h. The most common assumption is that the water sheet consists of linked cavities and that these open due to basal sliding over bed roughness, and close due to viscous creep (e.g. Hewitt, 2011). Within that framework, the simplest mechanism for a switching event is that a connection is established or closed when the sheet thickness h passes through some percolation threshold hc (Rada and Schoof, 2018).We want to test whether the observed switching events can be explained by that mechanism, which in turn implies that two conditions must be met: water sheet depth indeed evolves according to a competition between opening due to basal sliding and creep closure, and that a simple threshold in h suffices to capture the geometric complexity involved in creating or closing connections at the bed.In a large dataset of borehole water-pressure time series, we identify borehole pairs that exhibit strong evidence of switching behaviour. We assume that switching events can be described by the evolution of a water sheet, with connections between boreholes being opened and closed as sheet thickness passes through a threshold value as described above. We use the switching event catalogue we have created to invert for parameters in the sheet evolution model using a binary indicator function for connectedness to compute the model data mismatch in the absence of any other direct measures of sheet thickness.This procedure allows us to capture the majority of observed switching events with plausible parameter values. The exception is a set of short-lived periods of connectedness characterized by switching events that are clustered in space and time. In a complementary study (Racz et al, 2023 in prep.), we, therefore, investigate if this class of switching events can instead be explained by an alternative mechanism in which the sudden resumption of surface water supply, following a period of snow cover, drives the propagation of a hydrofracture (e.g. Tsai and Rice 2010, 2012).
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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 ».