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Enregistrement W2002848833 · doi:10.1029/2011wr011393

Comment on “Evaporation from soils under thermal boundary conditions: Experimental and modeling investigation to compare equilibrium and nonequilibrium based approaches,” by Kathleen M. Smits, Abdullah Cihan, Toshihiro Sakaki, and Tissa H. Illangasekare

2012· article· en· W2002848833 sur OpenAlexaff
Michael D. Novak

Notice bibliographique

RevueWater Resources Research · 2012
Typearticle
Langueen
DomaineEngineering
ThématiqueSoil and Unsaturated Flow
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésNon-equilibrium thermodynamicsThermodynamicsEvaporationSoil waterBoundary (topology)ThermalMaterials scienceEnvironmental sciencePhysicsSoil scienceMathematics

Résumé

récupéré en direct d'OpenAlex

[1] Smits et al. [2011], hereafter referred to as S11, presented a study of the coupled vertical transfer of moisture and heat in a bare soil that included both laboratory measurements of transient flow and implementation of physically-based numerical models corresponding to these measurements. In the laboratory experiment a 1.1 m long vertical cylindrical column of uniformly packed medium-coarse textured sand was initially saturated at room temperature (23 ± 1°C) with the water table maintained at the top of the column and with a plastic sheet covering the upper surface to prevent evaporation. The bottom of the column was then sealed (preventing drainage) and the soil surface uncovered and exposed to infrared heating with a controller that kept the surface temperature nearly constant (56–60°C) for 32 day. Evaporation of moisture from the soil surface then occurred without forced convection due to an artificial wind source and was measured by monitoring column weight. Relative humidity of the air at the soil surface was measured by placing a sensor in “very good contact with the soil grains” at the top of the column. Soil temperature, volumetric water content, and matric potential were measured at 0.1 m intervals along the column starting at a depth of 0.1 m and down to 1 or 1.1 m. These measurements were used to test moisture and heat transfer theory that considers both liquid and vapor phases for water within the soil and associated mass flow of dry air. Two versions of the theory were considered, the first making the usual assumption that the vapor density in the soil pores is equal to the thermodynamic equilibrium value associated with the bound liquid phase and the second relaxing this assumption and providing an explicit expression for the local rate of evaporation. The authors claim that the theory with the nonequilibrium assumption fits the measurements better than the equilibrium case although their final conclusions are less definite, suggesting that “transport in the gas phase is better suited to be modeled with nonequilibrium liquid/gas phase change for highly transient field conditions where the thermal conditions at the land-atmosphere interface are constantly changing” (Abstract) and that the “nonequilibrium model provides an excellent alternative to the equilibrium approach when knowledge of the evaporation rate is not readily available” (Conclusions). Given that the validity of the equilibrium assumption has long been standard doctrine within soil physics (with some well-understood exceptions) and of particular importance for coupled heat and moisture flow the results claimed in this paper are unexpected and need careful examination. [5] Calculating the fractional degree of nonequilibrium with equation (6) is problematic mainly because Aep varies strongly with water content in a complex manner [Costanza-Robinson and Brusseau, 2002; Culligan et al., 2004] and, for a soil drying by evaporation, Seis significantly nonzero only in a narrow zone (the “drying front,” typically less than 2 mm wide) whose location varies dynamically near the soil surface and which separates the nearly air-dry surface layer and the wetter underlying soil [Fuchs and Tanner, 1967; van de Griend and Owe, 1994; Yamanaka et al., 1998; Novak, 2010]. This behavior is not discussed explicitly by S11 but the nonequilibrium vapor density curves in their Figures 3b, 3d, and 12 are consistent with it. The drying front apparently penetrates nearly 30 cm by the end of the experiment which perhaps is consistent with the artificially high evaporation rates (1.7 mm h−1 initially), initial saturation of the soil, prevention of drainage, and high saturated hydraulic conductivity (3744 mm h−1). According to equation (6), equilibrium is expected below the drying front (for ) because is nearly zero or even negative (condensation). Similar reasoning does not apply for the dry layer above the drying front because Aep also approaches zero at low water contents [Costanza-Robinson and Brusseau, 2002; Culligan et al., 2004]. Nonequilibrium in that layer though has little effect on overall evaporation since evaporation within it is small, the dominant process being diffusion of water vapor from the underlying evaporation zone to the atmosphere. The moderate sensitivity of evaporation to parameter b shown in Figure 3c of S11 is expected since the vapor density at the drying front partly controls the gradient driving water vapor through the dry layer (Figure 3d). [6] S11 infers nonequilibrium by comparing theory and measurements. To do so accurately requires isolating a measurement that is strongly dependent on the degree of nonequilibrium. S11 used the cumulative evaporation curve. This curve also depends critically on soil hydraulic properties and imposed boundary conditions and to a lesser extent on the soil thermal regime. S11 independently measured the soil water retention curve, saturated hydraulic conductivity, and soil thermal conductivity and fitted these to well-known empirical expressions but how well these represented the measurements and how well the samples used for these measurements were representative of the soil in the column is not discussed. The dependence of hydraulic conductivity on was not measured, therefore the accuracy of the van Genuchten-Mualem relative permeability model they used is not known.Hanks and Gardner [1965] showed conclusively that the dependence of the wet end of the hydraulic diffusivity curve strongly determines cumulative evaporation in a drying soil (and not the dry surface “mulch” layer usually considered limiting). Furthermore, according to S11 cumulative evaporation is more sensitive to the parameter a in the expression for , the vapor enhancement factor, than the nonequilibrium parameter b. As recognized by S11 the enhancement factor is controversial and according to their Figures 3a and 3d a lower value would require a lower value of b which reduces nonequilibrium. Therefore, the case for nonequilibrium presented by S11 is not proved unambiguously. [7] S11's description of surface boundary conditions for moisture transport and some of their theoretical results can be questioned, as follows: [8] 1. The nonequilibrium theory requires their transport equations (1) and (6), or alternately (1) and (10) or (6) and (10), and therefore correspondingly two upper boundary conditions for moisture flow, but only one was discussed. [9] 2. For the equilibrium/nonequilibrium comparison a surface resistance boundary condition, equation (11), was assumed. The surface resistance in large part represents the resistance to the diffusion of water vapor from the evaporation zone through the dry surface layer to the atmosphere [Fuchs and Tanner, 1967; van de Griend and Owe, 1994]. This resistance is already accounted for implicitly in the moisture flow equations and imposing such a resistance in the boundary condition amounts to “double counting”. Indeed the theory can be used to calculate the surface resistance at any time during the experiment. This is especially evident in S11 since the van de Griend and Owe [1994] expression they used was developed from typical field situations for which the depth of the drying layer is cm whereas apparently it was as much as 30 cm in the S11 experiment. Furthermore, the description of equation (11) is vague, referring to vapor concentrations immediately above (measured time-dependent relative humidity/temperature supposedly at the soil surface) and below (calculation depth unspecified) the soil surface. The best way to compare cumulative evaporation rate between equilibrium and nonequilibrium models would have been to impose the measured time-dependent vapor concentration as a Dirichlet boundary condition (as done for the heat equation with measured surface temperature). [10] 3. According to section 3.2, the surface resistance boundary condition, equation (11), was only used for the equilibrium/nonequilibrium comparison discussed in section 4.2. According to section 3.3, for the comparison of the nonequilibrium model with experimental data (section 4.1) either time-dependent vapor flux or concentration may be used, both apparently from measurements. The authors indicate that both boundary conditions yielded identical results. But if measured (evaporative) flux (from column weight) was imposed as a boundary condition then why do Figures 3a, 3c, and 6 show differences between calculated and measured cumulative evaporation? Indeed it was by minimizing these differences that parametersa and b were determined. Furthermore, it is difficult to comprehend the statements that the results were unchanged for vapor flux and vapor concentration boundary conditions. [11] 4. In section 4.3 and the Conclusions the authors indicate strongly that choosing whether to use an equilibrium or nonequilibrium model depends on which type of boundary condition is to be used and that the nonequilibrium model is more suited to transient field conditions. This is incorrect both mathematically and physically. Concentration, flux, or mixed boundary conditions (linear or nonlinear) may be applied to either model (e.g., Novak [2010], which utilizes an equilibrium model similar to S11's but with strongly nonlinear energy balance/aerodynamic transfer boundary conditions to simulate field measurements). It is not true that the equilibrium model cannot be driven with a surface vapor concentration or any other type of boundary condition. Furthermore, the equilibrium assumption is either valid or not valid in a soil and there is not any question of choice although, as discussed above, the author expects that if and when nonequilibrium occurs in the dry surface layer the consequences for evaporation are likely small. [12] 5. S11 neglected gas phase resistance in the equilibrium model for the equilibrium/nonequilibrium comparison. As it turns out advective vapor flux was 5 orders of magnitude smaller than diffusive flux in the nonequilibrium model (Figure 8) and so the assumption had little effect. Physically, advective gas fluxes must have been similar for both models because cumulative evaporation was similar and soil temperatures were likely similar for both models. The advection of air in the theory was due to expansion associated with heating and the replacement of evaporated water. [13] In conclusion, the authors of S11 have not shown beyond a doubt that nonequilibrium occurred in their laboratory column experiment. In this paper, the author argued above that the nonequilibrium term in their theory, equation (9), is unphysical and incomplete. The description of how the surface boundary condition for moisture was implemented in their models is often unclear. Interested readers would benefit greatly if in their reply to this comment all boundary conditions and input parameters used in the models and not described fully in Sll would be reported in a table (moisture b.c.’s, expressions for soil thermal properties, water retention curve, water and gas permeabilities, radial heat loss) and graphically (measured surface temperature). Explicit presentation of all model variables that would allow readers to repeat the calculations should be standard for theoretical studies of coupled moisture and heat transfer but unfortunately this has been overlooked in a number of such recent publications.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,009
score de la tête « metaresearch » (Gemma)0,026
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,029
Score d'incertitude au seuil0,046

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0090,026
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0020,002
Bibliométrie0,0010,001
Études des sciences et des technologies0,0040,006
Communication savante0,0040,005
Science ouverte0,0070,003
Intégrité de la recherche0,0290,029
Charge utile insuffisante (le modèle a refusé de juger)0,0040,006

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.

Tête enseignante Opus0,093
Tête enseignante GPT0,293
Écart entre enseignants0,200 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations10
Publié2012
Routes d'admission1
Résumé présentoui

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