Streamflow response to headwater reforestation in the Ganaraska River basin, southern Ontario, Canada
Notice bibliographique
Résumé
Abstract Increased attention is being paid to the role of reforestation in strategies for sustainable forest management, landscape restoration and carbon sequestration. Reforestation of drainage basins is generally assumed to reduce annual streamflow as well as peak and low flows. However, most studies of reforestation effects on streamflow have been conducted on small experimental basins, and the applicability of their results to larger basins is unclear. This study revisits an earlier examination of streamflow response to headwater reforestation in a 267 km 2 basin (Ganaraska River) in southern Ontario, Canada for 1945–2007. Forest cover in the basin headwaters increased from 13 km 2 in 1945 to 31 km 2 by 1990, with most of this change between 1950 and 1965. Streamflow metrics from the reforested basin and two headwater sub‐basins were compared to those from a nearby basin and sub‐basin of similar size and physiography to the Ganaraska basins but without extensive headwater reforestation. No temporal trends were found for inter‐basin differences in annual runoff or runoff ratios for the entire Ganaraska basin or its largest sub‐basin; however, reforestation appears to have reduced several metrics of peak streamflow at the basin and sub‐basin scale. Relationships between high flows classified according to generating event type and the associated precipitation depth suggest that expansion of forest cover in the Ganaraska River basin (GRB) and associated changes in microclimatic conditions have reduced the potential for frozen soil to generate surface runoff and high flows in response to rain‐on‐snow during spring snowmelt. This was accompanied by increased low flows from the GRB and its sub‐basins from 1960 to 2007 relative to the control basin, suggesting that the expanded forest cover has enhanced groundwater recharge by prolonging spring snowmelt and promoting infiltration of rainfall and snowmelt inputs relative to non‐forested areas. Some discrepancies between these results and those of other studies of streamflow response to reforestation may be attributed to the relatively large size of the GRB and the limited extent of reforestation. Nevertheless, the results highlight the importance of considering how reforestation may affect key hydrologic processes in a given landscape when predicting the resulting streamflow response. Copyright © 2011 John Wiley & Sons, Ltd.
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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 | 0,000 | 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 | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».