Development and evaluation of RZWQM2-P: A model for phosphorus management in tile-drained agricultural fields
Notice bibliographique
Résumé
A rising environmental concern, phosphorus (P) loss from agricultural fields via surface runoff or sub-surface drainage ends up in freshwater bodies (river, lakes), where it causes widespread algal blooms and water quality degradation. Recent studies suggest that agricultural fields fitted with artificial tile drainage system contribute heavily to these P losses. Simulation models could help to measure and manage the agricultural P losses and inform prudent management decisions to mitigate this problem in a time saving and cost-effective way. Computer simulation models for this purpose are presently lacking, particularly for tile drained agricultural fields. Accordingly, the present study was undertaken to develop a computer simulation model to simulate P loss from a tile drained agricultural field through different hydrological pathways. A state-of-the-art algorithm to simulate the fate and transport of P in tile-drained agricultural systems is proposed, tested and incorporated into the RZWQM2 model, to take advantage of its hydrologic and agricultural management subroutines — thereby yielding the RZWQM2-P model. Structured according to Jones et al., (1984) with updates and modifications prescribed by Vadas, (2014), the RZWQM2-P model features dedicated manure and fertilizer P pools to simulate P dynamics arising from their application. To simulate daily P absorption/desorption among the P pools, a dynamically changing rate factor is applied rather than a constant rate factor. Tile drainage dissolved reactive P (DRP) and particulate bound P (PP) loss are estimated according to Francesconi et al., (2016) and Jarvis et al., (1999), respectively. Losses of DRP and PP through surface runoff are simulated according to Neitsch et al., (2011) and McElroy et al., (1976), respectively. The RZWQM2-P model’s capacity to simulate the DRP and PP loss from an agricultural field through surface runoff and tile drainage was evaluated using two sets of observed P loss and water flow data collected from subsurface-drained fields under a corn-soybean rotation on a clay loam soil in southwestern Ontario, Canada. For both cases, the RZWQM2-P model performed satisfactorily (NSE > 0.50, PBAIS within ±30%, IoA >0.75). A sensitivity analysis of the RZWQM2-P’s input parameters was conducted to facilitate the application of the model by users like agricultural managers and environmental stakeholders. The sensitivity analysis found the simulation of RZWQM2-P’s P loss depends on many parameters; however, macroporosity was the preeminent parameter in simulation of all form of P losses. The DRP loss through surface runoff was most sensitive to the P extraction coefficient, and PP loss through surface runoff was mainly governed by the parameters of the Universal Soil Loss Equation. Tile flow DRP and PP losses were most sensitive to the plant P uptake distribution parameter and the soil detachability coefficient. The newly developed RZWQM2-P model is a capable tool for the simulation of P losses from an agricultural field, particularly for the tile-drained fields, however, it requires skilled and computationally demanding modelling
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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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 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 ».