The use of climatic data to estimate irrigation water requirements in the south central interior of British Columbia
Notice bibliographique
Résumé
Climatic data observed at six meteorological recording stations in the south central Interior of British Columbia were used to analyse the temporal and geographical variations in the frequency, intensity and duration of various climatic phenomena that affect the supply and demand of water by growing crops. Rather than using average values, the relative frequencies of occurrence of each element or combination of elements were examined, in order that a more objective picture of the range of conditions experienced within the region during the growing season might be obtained. An inspection of the moisture supply patterns indicated that greater amounts of precipitation tended to occur during the earlier half of the growing season at most stations, the month of June experiencing a definite maximum. However, natural precipitation would appear to be less effective for plant growth than its absolute totals suggest, due to its tendency to be concentrated into a few days per month. An analysis of the occurrence of wet and dry spells during the growing season using two probability models supported these facts, the highest frequency of wet spells occurring in June, while the lower probabilities of wet spells in July and August indicated an increase in the length of dry spells during the second half of the growing season. Although it is known that at least four weather elements affect water loss by crops (radiation, temperature, wind and water pressure deficit), daily data were only available for two of these elements, namely air temperature and relative humidity. An examination of the relative frequencies of their occurrence showed that the evaporative power of the air remained relatively low until the end of June, after which it increased sharply as these two elements combined in such a manner that they intensified evaporation loss. This fact was further illustrated when their joint daily observations were combined in a frequency table, both July and August experiencing the highest relative frequencies of torrid days (hot days with low relative humidities). The conclusions were further verified when the actual amounts of irrigation water were computed at selected stations by estimating potential evapotranspiration rates from Penman's empirical formula and using the soil budget technique. At all stations except Lytton, little irrigation was required in most years until the beginning of July, unless the soils had low moisture storage capacities, but from July to September the required irrigation amounts were considerably higher, a fact that was due to both the increased dryness of the atmosphere and to the previous depletion of the readily available soil moisture.
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 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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 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) | 0,001 | 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 ».