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An Improved Water-Driven Sediment Yield Model for Cold Agricultural Regions

2025· article· en· W7126515798 sur OpenAlexaboutno aff
Peter Lawford

Notice bibliographique

RevueUniversity Library (University of Saskatchewan) · 2025
Typearticle
Langueen
DomaineAgricultural and Biological Sciences
ThématiqueSoil erosion and sediment transport
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésSnowmeltHydrology (agriculture)ErosionSedimentSoil waterSedimentationSediment transportSurface runoffPonding
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Excessive transport of sediment in the world’s freshwater, typically from water-driven erosion occurring in agricultural regions, is a significant source of pollution and damage to the aquatic environment. Excess sediment erosion promotes the transport of phosphorus to lakes, which can increase cyanobacterial growth, cause sedimentation that limits the lifespan of wetlands, and increase turbidity, reducing sunlight access for aquatic life. ese conditions are influenced by, and potentially mitigated by, agricultural land management. Long-term observation and simulation help to understand and predict the effects of current and future sediment load risk. Due to the challenges in measuring sediment load and the need for evaluating future or potential loading conditions, in-situ observations need to be augmented by model outputs to inform policy development. Cold agricultural regions occupy large areas of North America, Europe, and Asia, and calculating sediment erosion here requires consideration of snow redistribution and melt, frozen soils, and ponding over grainfields and grasslands with well-developed soils. Soil erosion models typically target temperate climate hillslope-scale processes driven by rainfall-runoff during the growing season and fail to capture the critical dynamics of spring snowmelt over frozen or partially frozen soils and the “fill-and-spill” flow regimes characteristic of low-gradient, depressional areas of cold regions. is research addresses this critical knowledge gap by developing, evaluating, and applying a new soil erosion and sediment transport model specifically tailored to cold agricultural regions. e model captures overland flow and channelized flow using separate parameterisations, treats snowmelt with an energy-balance approach, calculates the impact of thawed and frozen soils on runoff, and explicitly accounts for fill-and-spill hydrology. e model was evaluated with observational data from three research basins across the Canadian Prairies, and a sensitivity analysis was performed to determine sensitivity to parameter and forcing variation. Model behaviour for sediment load was shown to have high sensitivity to surface slope, soil texture, and storage capacity of the soil as would be expected. Modelled results were generally in-line with observations. e model was then applied over more than 4000 small ~100 km² virtual basins across the Canadian Prairies to evaluate the spatial and temporal trends in in-stream sediment load from 1950 to 2020. e results suggest that basins in western Alberta and southern Manitoba have the highest trend of excessive sediment load, and that the trend of excess sediment load in southern Manitoba basins has increased significantly since 1950. is is primarily due to the increase in rainfall early in the growing season. Overall trends across the Prairies show a shi toward a larger role of rainstorms as a driver for sediment load in streams, and a reduced role of snowmelt, as the climate has warmed and the onset of spring freshet has advanced. In semi-arid regions, such as the Palliser triangle, where summer rainfall is low, there has been a net decrease in trend of excess in-stream sediment load. Separation of land-use and climate effects suggests that the introduction of continuous cropping has reduced sediment erosion by 14 to 30%. Modelling suggests that the loss of depressional storage across the Prairies has led sediment transport to increase by 15 to 29%, and climate change from the 1950-1980 epoch to the 1990-2020 epoch has caused changes in sediment load between -19% and +32%. e advantages of this model are due to the parameterisation of cold regions processes with a physically based approach, incorporation of a sub-daily timestep for modelling flashy streamflow in small basins, and erosion parameterisations for simulating overland flow and channel flow respectively. e outcome of this research is a more robust and reliable tool for predicting sediment load for changing climate and land-use regimes in cold agricultural regions, and a diagnosis of changing sediment erosion and transport regimes across the Canadian Prairies since the 1950s.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,093
Score d'incertitude au seuil0,185

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0020,001
Intégrité de la recherche0,0020,001
Charge utile insuffisante (le modèle a refusé de juger)0,0040,000

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.

Tête enseignante Opus0,013
Tête enseignante GPT0,168
Écart entre enseignants0,154 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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Même revueUniversity Library (University of Saskatchewan)Même sujetSoil erosion and sediment transportTravaux en français237 207