Impact of Ephemeral Gully Erosion and Economics in Agricultural Fields of Ontario, Canada
Notice bibliographique
Résumé
Abstract Agricultural soils in Ontario, Canada have greater erosion potential where 54% of cropland has a risk of erosion above the annual rate of soil regeneration. The estimated annual soil erosion cost to Ontario farmers is over $150 million including crop yield reductions, nutrient losses, pesticide losses, etc. (OMAFRA, 2016). Over the last few decades, overland erosion processes in agricultural fields have been studied extensively. However, Ephemeral Gully (EG) erosion due to concentrated flow that erodes topsoil and associated economic losses remains largely unstudied. In this study, the objectives were to: (1) evaluate the soil loss and corresponding topsoil depth reduction due to EG erosion; and (2) estimate the economic loss associated with crop production due to EG erosion. Three fields in southern Ontario were selected, and identified at 15178 Imperial Road (15.60 ha), 46844 Lyon Line (2.78 ha) and 46383 Wilson Line (15.58 ha) (Figure 1). In each field, EGs were visible from aerial images and also during field visits. Typical soil textures in these fields were mainly silty clay loams. The average annual precipitation in the area is about 850 mm. An Unmanned Aerial Vehicle (UAV) equipped with a high-resolution camera was used to obtain the Digital Elevation Model (DEM) of the agricultural fields and the DEM was used to identify potential ephemeral gullies (PEGs) of agricultural fields. Daily climate data was obtained from nearby weather stations, soil characteristics were developed from the Soil Landscapes of Canada (SLC) database and field management information was taken upon consultation with the farmers who own the fields. The selected fields were simulated with the AnnAGNPS model which calculates overland erosion using the Revised Universal Soil Loss Equation (RUSLE) and EG erosion using the Revised Ephemeral Gully Erosion Model (REGEM), respectively. The sediment yield generated by sheet and rill and EG were calibrated and validated with available measured data and or literature values so that the model simulated the sediment yield reasonably well. The economic impact of EG erosion was calculated based on the relationship between topsoil depth and corn yield developed by Fenton et al. (2005), and the reduction of topsoil depth driven by EG erosion. Results showed that soil losses from EG erosion were significant and were 6-10 times greater than sheet and rill erosion. The EGs developed not only due to rainfall but also due to snowmelt. The annual topsoil loss from EG erosion ranged from 1.00 to 2.53 cm in the studied fields and the annual topsoil loss from sheet and rill erosion was minimal (0.01 cm). The corresponding economic loss due to topsoil loss was calculated in terms of crop yield reduction by annually filling the EG using adjacent topsoil by tillage operation. Economic loss caused by EG erosion varied from $5.46 ha-1 to $12.66 ha-1. The results also indicate that EG erosion reduces annual farm income in the long term.
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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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 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 ».