Impacts of Future Climate and Agricultural Land Use Changes on Groundwater Nitrate Concentrations in Southern Ontario
Notice bibliographique
Résumé
Contamination of groundwater by nitrate is a critical concern in agricultural subwatersheds in southern Ontario. Groundwater quality may further deteriorate due to socio-economic pressures and extreme future climate change conditions. The focus of this study was to assess the impacts of future climate changes and potential changes in agricultural land use on groundwater nitrate concentrations. Three research sites with contrasting hydrogeological settings, located in agricultural subwatersheds, were investigated: Norfolk County, Guelph, and Acton. The Norfolk (sandy aquifer) and Guelph (fractured bedrock aquifer) sites were examined in the most detail. Two different vadose zone models, DRAINMOD-NII and RZWQM2, were evaluated to select the most suitable model to represent the soil conditions encountered in southern Ontario. The selected vadose zone model, RZWQM2, was used to quantify the shallow nitrate concentrations and leaf area index (LAI) under different crop types. These data were used as input to fully integrated numerical models, developed using HydroGeoSphere software, for groundwater flow and contaminant transport for both sites. The HydroGeoSphere models were calibrated and validated for the 2014-2016 period using field data collected at both sites. Following calibration of the groundwater models, three different climate change models (2040-2059) and three different crop rotations (corn-soybean, continuous corn, corn-soybean-winter wheat-red clover) were applied (i.e., nine scenarios for each site) to evaluate the potential impact of future climate changes on groundwater quality. The selected climate change scenarios yielded less water availability for hydrologic processes. There was less impact on groundwater elevations at the Norfolk site compared to the Guelph site. The nitrate concentrations were lower significantly during the future period at both sites. However, the continuous corn land use scenario had much higher nitrate concentrations compared to base case scenario (corn-soybean rotation). Further, the best management practices (BMP) scenario (corn-soybeans-winter wheat-red clover rotation) produced significantly lower groundwater nitrate concentrations at both research sites. BMPs, such as the crop rotation tested herein, should be adopted to reduce the potential negative impacts of future climate change on groundwater quality, especially in vulnerable fractured bedrock aquifer settings and shallow sandy aquifers. These findings are important for water and land managers in agricultural settings, to mitigate future impacts of nutrient transport on groundwater quality under a changing climate.
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 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) | 0,000 | 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 ».