The Impact of Spatial Decision Variables Influencing Crop Rotation on Phosphorus Load Reduction: A Hydrologic Modeling Approach
Notice bibliographique
Résumé
Non-point source anthropogenic nutrient loading through intensive farming practices is a global \nsource of water quality degradation by creating harmful algal blooms in aquatic ecosystems. \nPhosphorus, as the key nutrient in this process, has received much attention in different studies as \nwell as conservation programs aimed at mitigating the transfer of polluting nutrients to freshwater \nresources. Central to conservation initiatives developed to maintain and improve water quality is the \napplication of the Conservation Practices (CPs), introduced widely as practical, cost-effective \nmeasures with overall positive impacts on the rate of nutrient load reductions from farmlands to \nfreshwater resources. \nCrop rotation is one of the field-based BMPs applied to maintain the overall soil fertility and \npreventing the displacement of the topsoil layers by surface water runoff across the agricultural \nwatersheds. The underlying concept in the application of this particular BMP is a deviation from the \nmonoculture cropping system by integrating different crops into the farming process. This way, \ncultivated soils do not lose key nutrients, which are necessary for crop growth, and the overall crop \nproductivity remains unchanged in the landscape. The successful implementation of crop rotation \nhighly depends on planning the rotation process, which is influenced by a variety of environmental, \nstructural, and managerial factors, including the size of farmlands, climate variability, crop type, level \nof implementation, soil type, and market prices among other factors. Each of these decision \nvariables is subject to variation depending upon the variability of other factors, the complexity of \nwatersheds upon which this BMP is implemented, and the overall objectives of the BMP adoption. \nThis study aims to investigate two of these decision variables and their potential impacts on \nphosphorus load reductions through a scenario-based hydrologic modeling framework developed to \niv \nassess the post-crop rotation water quality improvements across the Medway Creek Watershed, \nsituated in the Lake Erie Basin in Ontario, Canada. These variables are the spatial pattern of crop \nrotation and its level of implementation, assessed at the watershed scale through the modifications \nmade to the delineation of the basic Hydrologic Response Units (HRUs) in the modeling process as \nwell as certain assumptions in the management schedules, and decision rules required for the \nintegration of crop rotation into the proposed modeling framework and optimal placement of this \nnon-structural BMP across the watershed. The main modeling package utilized in this study is the \nSoil and Water Assessment Tool (SWAT), used in conjunction with the ArcGIS and IBMSPSS tools \nto allow for spatial assessment and statistical analyses of the proposed hydrologic modeling results, \nrespectively. \nFollowing in-depth statistical analyses of the scenarios, the results of the study elicit the critical role \nof both factors by proposing optimal ranges of application on the watershed under study. \nAccordingly, to achieve optimal implementation results compared to the baseline scenario, which \nhas the zero rate of implementation, conservation initiatives in the watershed are encouraged to \nconsider the targeted placement of crop rotation on half of the lands under cultivation. Despite, \nhaving a statistically significant impact on water quality compared to the baseline scenario, the random \ndistribution scenario is less effective than the targeted scenario in mitigation of total phosphorus \nload. Similarly, compared to the medium rate of implementation the targeted placement in a higher \nproportion of the cultivated areas did not lead to statistically significant results but may be \nconsidered depending upon the purpose and scope of implementation.
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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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».