The 2014 flood event in the Assiniboine River Basin: Causes, assessment and damage
Notice bibliographique
Résumé
The 2014 Assiniboine River flood caused millions of dollars in damage to southern Manitoba and Saskatchewan. Heavy precipitation in late June and early July resulted in states of emergency being declared in both provinces as water levels reached record levels in the Upper Assiniboine Watershed, and near record levels downstream of the City of Brandon. In spite of the significant measures both provinces took to protect their citizens, the flood washed out roads and bridges and caused severe damage to properties, riverbanks and dikes. Some communities became isolated due to the flood damage to roads. Several hundred people were evacuated from homes and communities in Manitoba and Saskatchewan. The other major impact was on the farming community. The timing of this flood made it more costly than the 2011 flood from the farming perspective since most farmers had already planted their crops. The origin of the 2014 flood was different from any other major flood of the Assiniboine River since records have been kept; this was a true summer flood in that the spring freshet had already passed and flows had receded to a baseflow condition. The event was entirely due to rainfall on a basin where conditions were extremely wet and had been since before the 2011 flood. This resulted in record flows being recorded on many tributaries, and flows nearly equal to those of the 2011 event along the Assiniboine River. It should be noted that the 2011 event was initially a snowmelt event due to greater-than-normal accumulation of winter snowpack. The 2014 summer flood was “unprecedented” in the previous 130 years of observations of the Assiniboine River flows and follows only three years after the 2011 event that was described with the same adjective. The influence of anthropogenic activities, both in changing the land use and extending the drainage network, undoubtedly has played a significant role in altering prairie hydrology and potentially increasing the magnitude of flood events.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».