Applications of a regional-scale integrated modelling platform towards watershed-level hydrologic insights
Notice bibliographique
Résumé
Persistent questions exist on how a regional scale model, such as the one developed for Southern Ontario, can be employed as a tool to address local level questions. While the spatial resolution of the regional model may be high enough for big-picture applications, it is arguably not high enough to provide useful insights on highly-dynamic small-scale hydrologic behavior or operational aspects of watershed management. In order to meet the needs of smaller scale applications, a set of HydroGeoSphere (HGS) fully-integrated groundwater - surface water models has been constructed for the 12 major watersheds that lie within the bounds of the regional model. These models have been constructed with a much higher level of spatial resolution than the regional model (i.e. with Strahler order 2 stream networks as opposed to Strahler order 3) and with full representation of the surface water features as channel elements within the model, which creates a more representative depiction of watershed and sub-watershed scale hydrologic behavior. As the underlying database upon which the watershed models are constructed is amalgamated across Southern Ontario, these models all share a consistent hydrostratigraphy, soil, and landcover representation, which in turn creates a uniform simulation framework that aligns with regional model behavior. However, in recognition of the fact that higher resolution model construction data may be available and/or required for smaller scale applications, the watershed models can be efficiently reconstructed using data in standard GIS formats. In addition to being able to use each of the 12 watershed models as a pre-built standalone fully-integrated model for individual watersheds, the full set of models is now running operationally as a surface water forecasting system for the whole of the Southern Ontario model domain. Using an ensemble set of weather forecasts and an advanced monitoring data assimilation scheme, surface water forecasts are being generated at daily frequency for a two week forecast interval for 100's of locations across Southern Ontario. Already, a demonstrated strength of the platform is that flows at ungauged locations (as well as known gauging locations) can be predicted with some certainty given that HGS employs a physics-based mass conservative approach for simulating water movement within the highly dynamic GW-SW system in Southern Ontario. In order to disseminate output from the hydrologic forecasting platform to watershed stakeholders, a cloud based portal has been developed with watershed-level dashboards and on-the-fly analytic functionality. While surface water flows are currently the only forecast endpoint, platform development is ongoing, with plans to release operational forecasts for other components of the hydrologic cycle in future releases.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».