Modelling soil water dynamics of an intensively cultivated histosol
Notice bibliographique
Résumé
Understanding the soil water dynamics in cultivated organic soils is crucial for achieving sustainable agriculture on histosols, preserving ecosystem health, and mitigating the impacts of climate change. There has been extensive research on the soil-hydraulic properties of mineral soils, yet there is a limited understanding of such characteristics in cultivated organic soils. This limitation arises because of the high organic matter content, significant porosity, high compressibility, high tortuosity, low shear strength, and the tendency of organic soils to undergo shrinkage and swelling. To bridge this knowledge gap, in this dissertation, a laboratory column experiment was designed, and a computer model was employed to analyze soil water retention curves (SWRCs) of organic soils. Intact soil columns (length: 60 cm, diameter: 20 cm) were collected from intensively cultivated organic soil in the Napierville region of Quebec, Canada. These soil columns were subjected to wetting and drying cycles for 112 days, and the effect on soil water status was monitored by measuring matric potential at different depths (10 cm, 26 cm, and 48 cm) using automated matric potential sensors. Based on the lab data, the Hydrus 1D model was then used to simulate SWRCs at the three soil depths. Initial hydraulic parameters, as found in the van Genuchten-Mualem model (pore size distribution index, and bubbling pressure), were drawn from the literature on similar soil types. An inverse modelling approach within Hydrus 1D was executed to optimize the hydraulic parameters by comparing the model’s output with observed matric potential data. In the laboratory experiment, the matric potential gradually decreased from saturation to 277.52 kPa, -181.2 kPa, and -89.93 kPa at depths 10 cm, 26 cm, and 48 cm, respectively, during the first drying period (52 days), indicating a larger decrease at lesser depths. The soil columns were then subjected to a second drying period (19 days), and the matric potential decreased from -50.01 kPa, -60.02 kPa, and -44.1 kPa to -263.89 kPa, -172.61 kPa, and -109.76 kPa at the same depths. The results were similar to those reported in other studies conducted on peat soil at corresponding depths. The Hydrus 1D inverse modelling showed that simulated matric potential steadily decreased from saturation to -267.92 kPa, -189.95 kPa, and -85.31 kPa at depths of 10 cm, 26 cm, and 48 cm, respectively, during the first drying period. Likewise, during the second drying period, the simulated matric potential decreased from -85 kPa, -68.1 kPa, and -65.6 kPa to -222.12 kPa, -162.3 kPa, and -90.81 kPa at the same depths. Model accuracy was validated for the second drying period with a coefficient of determination and Nash-Sutcliffe Efficiency: 0.971 and 0.915, 0.928 and 0.879, and 0.69 and -0.365 at depths of 10 cm, 26 cm, and 48 cm, respectively. The optimized soil hydraulic parameters for SWRC in Hydrus 1D inverse modelling were suitable for accurately describing the behaviour of peat soils in the study area. Based on the simulated SWRCs, the moisture contents at field capacity were 0.6 cm³/cm³, 0.696 cm³/cm³, and 0.49 cm³/cm³, while the wilting points were 0.165 cm³/cm³, 0.107 cm³/cm³, and 0.14 cm³/cm³ for soil depths of 10 cm, 26 cm, and 48 cm, respectively. The weighted available water content was 264 mm for a soil depth of 60 cm, which is the typical root zone depth for crops such as carrots, lettuce, celery, and onions. This amount is lower than the crop water requirement of 375-525 mm per year for organic soil in Quebec. Therefore, additional irrigation water is necessary for these organic soils. The present results can assist researchers, land managers, and agricultural practitioners in deciding water management practices for the intensive cultivation of histosols
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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 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».