Extending periodic eddy covariance latent heat fluxes through tree sapflow measurements to estimate long-term total evaporation in a peat swamp forest
Notice bibliographique
Résumé
Abstract. A combination of measurement and modelling was used to find a pragmatic solution to estimate the annual total evaporation (ET) from the rare and indigenous Nkazana Peat Swamp Forest (PSF) on the east coast of Southern Africa to improve the water balance estimates within the area. Total evaporation was measured during three window periods (between seven and nine days each) using an eddy covariance (EC) system on a telescopic mast above the forest canopy. Sapflow of an understory and an emergent tree was measured using a low maintenance heat pulse velocity system for an entire hydrological year (October 2009 to September 2010). An empirical model was derived, describing the relationship between the observed ET of the Nkazana PSF measured during two of the window periods (R2 = 0.92 and 0.90) which, overlapped with sapflow measurements, thereby providing hourly estimates of predicted ET of the Nkazana PSF for a year, totalling 1125 mm (while rainfall was 650 mm). In building the empirical model, it was found that including the understory tree sapflow provided no benefit to the model performance. In addition, the observed emergent tree sapflow relationship with observed ET between the two field campaigns was consistent and could be represented by a single empirical model (R2= 0.90; RMSE = 0.08 mm). During the window periods of EC measurement, no single meteorological variable was found to describe the Nkazana PSF ET satisfactorily. However, in terms of evaporation models, the hourly FAO56 Penman–Monteith equation best described the observed ET from EC during the August 2009 (R2 = 0.75), November 2009 (R2 = 0.85) and March 2010 (R2 = 0.76) field campaigns, compared to the Priestley–Taylor model (R2 = 0.54, 0.74 and 0.62 during the respective field campaigns). From the empirical model of ET and the FAO56 Penman–Monteith equation, a monthly crop factor (Kc) was derived for the Nkazana PSF providing a method of estimating long-term swamp forest ET from meteorological data. The monthly crop factor indicated two distinct periods. From February to May, it was between 1.2 and 1.4 compared with June to January, when the crop factor was 0.8 to 1.0. The derived monthly Kc values were verified as accurate (to one significant digit) using historical data measured at the same site, also using EC, from a~previous study. The measurements provided insights into the microclimate within a subtropical peat swamp forest and the contrasting sapflow of emergent and understory trees. They showed that expensive, high maintenance equipment can be used during manageable window periods in conjunction with low maintenance systems, dedicated to individual trees, to derive a model to estimate long-term ET over remote heterogeneous forests. In addition, the contrast in ET and rainfall emphasises the reliance of the Nkazana PSF on groundwater.
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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 | 0,000 | 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 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 ».