A computer analysis of the flow of water and nutrients in agricultural soils as affected by subsurface drainage
Notice bibliographique
Résumé
A computer model was developed in order to determine the effects of drainage practices on nutrient losses from level agricultural soils. The model performs a daily simulation of the vertical flow of water, nitrogen, phosphorus, and heat, and of the growth of crops. A water flow submodel calculates the depth of the water table based on daily predictions of evaporation, transpiration, flow to drains and ditches, and deep percolation. An original saturated-unsaturated flow algorithm is used to determine moisture infiltration, redistribution, and upward flow in the soil matrix, as well as bypassing flow in the soil macropores and horizontal flux between the soil matrix and the macropores, and surface runoff. Nutrient movement occurs by mass flow. Heat flow, nutrient biochemical transformations, and crop growth are determined by using well established relations. Field tests were carried out for a period of two years on an experimental site in the Lower Fraser Valley of British Columbia. The water table depth was measured on a continuous basis. Grab samples of drainwater and observation wells were obtained periodically and analyzed for nitrogen (N0₃-N, NH₄-N, and TKN) and phosphorus (P0₄-P and TP). The field results show a decrease in the concentration of all nutrients over the sampling period, and provide evidence that denitrification and bypassing flow are important mechanisms affecting the nutrient balance of this soil. These results were used to calibrate the model. An excellent fit of the observed water table profile and an adequate fit of the observed drain concentration of nitrate were obtained. The simulation revealed that bypassing flow is a very important transfer mechanism in this soil and must be included in order to obtain a satisfactory fit of the experimental data. A sensitivity analysis of the model showed that the patterns of moisture flow have a predominant influence on the rate of nutrient leaching. In particular, it was found that the nutrient concentration in drain water is a strong function of the hydraulic conductivity of the soil matrix and of the horizontal distance between the soil macropores, which control the ratio of moisture flow in the soil matrix to the macropore flow and the lateral diffusion of nutrients between the soil matrix and the macropores. The effects of four different drainage designs on nutrient losses were simulated over a period of two years for three different soils and two different nutrient distributions in the soil. It was found that there is a large difference between the amount of nutrients leached from drainage systems using different drainage coefficients. There was also a large difference in the response of two drainage designs based on the same drainage coefficient but using different depth and spacing of drains. Transient effects, as determined by the initial vertical distribution of the nutrients, were seen to remain dominant over the two year duration of the simulation. The model was found to be useful in explaining the apparent contradictions found in the literature assessing the effects of subsurface drainage on nutrient losses. The results from the model show these effects to be strongly site and condition specific. Furthermore, the model shows that soils and drainage designs that produce similar volumes of drain flow may exhibit very different leaching responses, and that drainage designs equivalent from a hydraulic standpoint can be very dissimilar in their potential for leaching nutrients. The model provides a tool which can be used to determine the appropriateness of different drainage designs in soils where minimizing nutrient losses is critical.
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 | 0,001 |
| 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 ».