Sunlit Fractions Research Articles

A novel approach to account for shape-morphing and kinetic shading systems in building energy performance simulations

This paper proposes an innovative approach to analyse the energy behaviour of complex kinetic shading systems. Although several studies have analysed this topic, many are focused only on certain aspects or on simple shading systems due to a lack of tools for running reliable energy simulations on complex systems. This study aims to develop and validate a tool based on Python and EnergyPlus that can consider the continuous nature of the energy simulation and analyse complex kinetic systems. Simply providing an EnergyPlus model and a model of the shading configurations, the algorithm provides as output a comparison sheet to evaluate the performance of the system. The paper provides a description of the tools and studies focused on this topic; subsequently, a methodological insight is presented to explain the workflow, its validation, and the algorithm developed. Finally, the algorithm is tested on a case study to analyse a kinetic shading system. Abbreviations: DSF: Dynamic Shading File; EDSM: Equivalent Dynamic Shading Model; EMS: Energy Management System; ESSM: Equivalent Static Shading Model; Gf: Incident irradiance; Gf max: Incident irradiance threshold; PV: Photovoltaic; ST1/2/3: State 1/2/3; SSM: Static Shading Model; SF: Sunlit Fraction; SSF: Static Shading File; To: Outdoor temperature; To max 1/2: Outdoor temperature threshold 1/2; Tsol: Solar transmittance

Use of 3D modeling to refine predictions of canopy light utilization: A comparative study on canopy photosynthesis models with different dimensions.

Canopy photosynthesis integrates leaf functional and structural traits in space and time and correlates positively with yield formation. Many models with different levels of architectural details ranging from zero-dimensional (0D) to three-dimensional (3D) have been developed to simulate canopy light interception and photosynthesis. Based on these models, a crop growth model can be used to assess crop yield in response to genetic improvement, optimized practices, and environmental change. However, to what extent do architectural details influence light interception, photosynthetic production, and grain yield remains unknown. Here, we show that a crop growth model with high-resolution upscaling approach in space reduces the departure of predicted yield from actual yield and refines the simulation of canopy photosynthetic production. We found crop yield predictions decreased by 12.0-48.5% with increasing the resolution of light simulation, suggesting that a crop growth model without architectural details may result in a considerable departure from the actual photosynthetic production. A dramatic difference in light interception and photosynthetic production of canopy between cultivars was captured by the proposed 3D model rather than the 0D, 1D, and 2D models. Furthermore, we found that the overestimation of crop yield by the 0D model is caused by the overestimation of canopy photosynthetically active radiation (PAR) interception and the RUE and that by the 1D and 2D model is caused by the overestimated canopy photosynthesis rate that is possibly related to higher predicted PAR and fraction of sunlit leaves. Overall, this study confirms the necessity of taking detailed architecture traits into consideration when evaluating the strategies of genetic improvement and canopy configuration in improving crop yield by crop modeling.

Spectral invariants in ultra-high spatial resolution hyperspectral images

Current operational optical satellite-based Earth observation methods targeting at vegetation are optimised for the high- and medium-resolution satellites with pixels sizes starting at ten meters. This resolution is coarser than the typical size of a vegetation structural element, such as a tree crown, and much coarser that of scattering elements, such as leaves. For this reason, vegetation can be treated as a continuous medium and the variation in the local illumination conditions on individual leaves or tree crowns can be ignored. This does not hold anymore for very and ultra-high resolution imagery, obtained from new satellite systems or unmanned aerial vehicles, where individual tree crowns or even leaves can be discerned. We tested the applicability of the spectral invariant theory to this type of imagery for characterising the local illumination conditions on plant leaves using Monte Carlo ray tracing simulations. The simulations corroborated the direct link between the spectral invariant parameter ρ and the sunlit fraction of visible leaves, earlier alleged for hyperspectral remote sensing data based on mathematical considerations. The approach allowed us to separate the direct beam and multiple scattering irradiance components and provided intuitive interpretations of the recollision probability and canopy scattering coefficient computed for each image pixel.

Effect of Forest Canopy Structure on Wintertime Land Surface Albedo: Evaluating CLM5 Simulations With In‐Situ Measurements

AbstractLand Surface Albedo (LSA) of forested environments continues to be a source of uncertainty in land surface modeling, especially across seasonally snow covered domains. Assessment and improvement of global scale model performance has been hampered by the contrasting spatial scales of model resolution and in‐situ LSA measurements. In this study, point‐scale simulations of the Community Land Model 5.0 (CLM5) were evaluated across a large range of forest structures and solar angles at two climatically different locations. LSA measurements, using an uncrewed aerial vehicle with up and down‐looking shortwave radiation sensors, showed canopy structural shading of the snow surface exerted a primary control on LSA. Diurnal patterns of measured LSA revealed strong effects of both azimuth and zenith angles, neither of which were adequately represented in simulations. In sparse forest environments, LSA were overestimated by up to 66%. Further analysis revealed a lack of correlation between Plant Area Index (PAI), the primary canopy descriptor in CLM5, and measured LSA. Instead, measured LSA showed considerable correlation with the fraction of snow visible in the sensor's field of view, a correlation which increased further when only considering the sunlit fraction of visible snow. The use of effective PAI values as a simple first‐order correction for the discrepancy between measured and simulated LSA in sparse forest environments substantially improved model results (64%–76% RMSE reduction). However, the large biases suggest the need for a more generic solution, for example, by introducing a canopy metric that represents canopy gap fraction rather than assuming a spatially homogeneous canopy.

Correction of Canopy Shadow Effects on Reflectance in an Evergreen Conifer Forest Using a 3D Point Cloud

Correction of spectral reflectance for shadow and topography in optical remote sensing data is challenging. Here, we corrected for canopy self-shadowing in an evergreen conifer forest in mountainous terrain using a three-dimensional (3D) point cloud. In our approach, the surface was modeled from structure-from-motion processed images provided by an unmanned aerial vehicle; then, the relationship between the observed spectral reflectance of the Sentinel-2A/B multispectral instrument, and the simulated sunlit fraction (the percentage of the solar-illuminated area within a Sentinel-2 pixel) was determined based on a ray-tracing scheme using a 3D point cloud. Scene-based and pixel-based linear regressions were applied to remove canopy-shadow and topographic effects from satellite-observed reflectance. Scene-based regression resulted in large seasonal changes that caused overcorrection in winter. Pixel-based regression generated stable seasonal profiles in both the red and near-infrared reflectance values over the conifer canopy; however, excessively smoothed seasonal changes were implemented over deciduous vegetation. In both correction methods, the reflection of incident light by the canopy likely improved the correction accuracy by decreasing the contrast between illuminated and shaded pixels in summer and increasing it in winter. The results were also visually compared with those from the Sun-Canopy-Sensor with C (SCS+C) method and the Sentinel-2 Level-2A product. This research demonstrates the effectiveness of using a 3D point cloud to correct for self-shadowing and topographic effects on remotely sensed reflectance.

Evaluation of Different Methods for Estimating the Fraction of Sunlit Leaves and Its Contribution for Photochemical Reflectance Index Utilization in a Coniferous Forest

Proper determinations of light use efficiency (LUE) and absorbed photosynthetically active radiation (APAR) are essential for LUE models to simulate gross primary productivity (GPP). This study intended to apply the photochemical reflectance index (PRI) to track LUE or APAR variations in a subtropical coniferous forest using tower-based PRI and GPP measurements. To improve the ability of using PRI to track LUE or APAR, a two-leaf approach differentiating sunlit and shaded leaves was used to process the remote sensing and flux data. However, penumbra region, the ‘grey region’ between sunlit and shaded leaves, increases the difficulty for quantifying the fractions of sunlit and shaded leaves. Firstly, three methods with different ways on treating the penumbra region were investigated for estimating the fraction of sunlit leaves (PT). After evaluating the correlations between observed PRI (PRIobs) and inversely retrieved PRI (PRIinv) from estimated PT using the three methods, we found that treating a substantial portion of penumbra region as sunlit leaves was reasonable and using the ratio of canopy reflectance to leaf reflectance as PT was accurate and efficient. Based on this, we used the two-leaf approach to estimate the canopy-level PRI, aiming to evaluate the ability of using PRI as a proxy for LUE or APAR. Results showed that PRI was able to capture half-hourly and daily changes in LUE and APAR, and the two-leaf approach could enhance the correlations between PRI and both LUE and APAR at both half-hourly and daily time steps. Strong diurnal correlations (averaged R = 0.82 from 173 days) between two-leaf PRI and APAR were found on more than 80% days and the relationship between them over the whole study period was also very significant (R2>0.5, p<0.0001) regardless of different climate conditions, suggesting that the two-leaf PRI was probably a better proxy for APAR than for LUE at short-term scale as PRI mainly represented the absorbed energy allocated to photoprotection at short time scale and was a direct outcome driven by APAR. However, the scattered relationships of PRI with LUE and APAR indicated there were still many limitations in usage of PRI to accurately estimate physiological parameters affected by changing weather conditions, pigment pool size, etc., which needed further exploration.

Spectral Similarity and PRI Variations for a Boreal Forest Stand Using Multi-angular Airborne Imagery

The photochemical reflectance index (PRI) is a proxy for light use efficiency (LUE), and is used in remote sensing to measure plant stress and photosynthetic downregulation in plant canopies. It is known to depend on local light conditions within a canopy indicating non-photosynthetic quenching of incident radiation. Additionally, when measured from a distance, canopy PRI depends on shadow fraction—the fraction of shaded foliage in the instantaneous field of view of the sensor—due to observation geometry. Our aim is to quantify the extent to which sunlit fraction alone can describe variations in PRI so that it would be possible to correct for its variation and identify other possible factors affecting the PRI–sunlit fraction relationship. We used a high spatial and spectral resolution Aisa Eagle airborne imaging spectrometer above a boreal Scots pine site in Finland (Hyytiälä forest research station, 61°50′N, 24°17′E), with the sensor looking in nadir and tilted (off-nadir) directions. The spectral resolution of the data was 4.6 nm, and the spatial resolution was 0.6 m. We compared the PRI for three different scatter angles ( β = 19 ° , 55 ° and 76 °, defined as the angle between sensor and solar directions) at the forest stand level, and observed a small (0.006) but statistically significant (p < 0.01) difference in stand PRI. We found that stand mean PRI was not a direct function of sunlit fraction. However, for each scatter angle separately, we found a clear non-linear relationship between PRI and sunlit fraction. The relationship was systematic and had a similar shape for all of the scatter angles. As the PRI–sunlit fraction curves for the different scatter angles were shifted with respect to each other, no universal curve could be found causing the observed independence of canopy PRI from the average sunlit fraction of each view direction. We found the shifts of the curves to be related to a leaf structural effect on canopy scattering: the ratio of needle spectral reflectance to transmittance. We demonstrate that modeling PRI–sunlit fraction relationships using high spatial resolution imaging spectroscopy data is suitable and needed in order to quantify PRI variations over forest canopies.

Estimating structural parameters of agricultural crops from ground-based multi-angular digital images with a fractional model of sun and shade components

Accurate and efficient in situ measurement methods of leaf area index (LAI) and leaf angle distribution (LAD) are needed to estimate the fluxes of water and energy in agricultural settings. However, available methods: to estimate these two parameters, especially LAD, are limited. In this study, we propose a field measurement method using multi-angular digital images to estimate LAI and LAD simultaneously from the area proportions of: (i) sunlit soil; (ii) sunlit leaves; (iii) shaded soil; and (iv) shaded leaves. A new expression of the fraction of sunlit leaves is developed based on the radiative transfer theory. Coupling the measured and modeled fractions with an optimization scheme, LAI and the LAD parameters are derived from inverting a fractional model of sunlit and shaded leaves and soil. Through four tests using simulated scenes and in situ measurements for row crops, it is determined that our method performs well. The absolute error of LAI estimation is less than 0.1 when LAI is low (i.e., <1.2), and the absolute deviations of LAI estimates are approximately 0.5 when the reference LAI is 3.5. The estimation errors of LAI and the G function (a representative of LAD which quantifies the projection of unit foliage area) for in situ measurements are respectively less than 0.2 and 0.06 in general. In addition, the accuracy of estimation is even higher when leaves are simulated as randomly distributed disks or observations from multiple azimuth planes are used. One of the most interesting features of this method is its ability to estimate reasonable LAD directly from the fractions of sunlit and shaded leaves, even when LAI is high (i.e., >3), so little background soil is seen. The sensitivity and uncertainty analysis is consistent with the estimation errors. Theoretically, the application of this method is not limited to row crops or to field measurement, as the derived formulae of sunlit and shaded components can be used for other types of vegetation by introducing the clumping index and can be used in the modeling of canopy vegetation parameters (e.g., canopy reflectance).

Improving the ability of the photochemical reflectance index to track canopy light use efficiency through differentiating sunlit and shaded leaves

Accurate estimation of light use efficiency (LUE) of plant canopies is essential for calculating gross primary productivity (GPP) using LUE models and is also useful for calibrating process-based models for regional and global applications. A promising method for estimating LUE is through remote sensing of the photochemical reflectance index (PRI). However, there are internal (e.g. pigment concentrations) and external factors (e.g. environmental conditions and sun-target-view geometry) that affect PRI signals. Considering the reflectance difference between sunlit and shaded leaves, the ratio of observed canopy reflectance to leaf reflectance is used to represent the observed fraction of sunlit leaves, and the observed fraction of shaded leaves is calculated with a geometrical optical model. Thus, a canopy-level PRI observation is separated into sunlit and shaded PRI values, and a two-leaf canopy PRI (PRIt) is calculated as sum of these two values weighted by their respective sunlit and shaded leaf area indices. The usefulness of PRIt in assessing the canopy-level LUE is evaluated with automated multi-angle PRI observations acquired on a flux tower from April to September 2013 over a sub-tropical coniferous forest in southern China. In each 15-minute observation cycle, PRI is observed at four view zenith angles fixed at (37°, 47°, 57°) or (42°, 52°, 62°) and the instantaneous solar zenith angle in the azimuth angle range from 45° to 325° (from the geodetic north). In both the half-hourly and daily time steps, PRIt can effectively improve (>50% and >35% increases in R2, respectively) the ability as a proxy of LUE derived from the tower flux measurements over the big-leaf PRI taken as the arithmetic average of the multi-angle measurements in a given time interval. In the dry season from July to September, correlations of PRI with LUE at daily time steps are much stronger in the two-leaf case than in the big-leaf case. The correlation between PRIt and LUE is the strongest (R2=0.785, p<0.001) in July. PRIt is very effective in detecting the light and low-moderate drought stress on LUE at half-hourly time steps, while ineffective in detecting severe atmospheric water and heat stress, which is probably due to alternative radiative energy sink, i.e. photorespiration. Overall, the two-leaf approach well overcomes some external effects (e.g. sun-target-view geometry) that interfere with PRI signals.

Sunlit fractions on urban facets – Impact of spatial resolution and approach

The extent of the surface area sunlit is critical for radiative energy exchanges and therefore for a wide range of applications that require urban land surface models (ULSM), ranging from human comfort to weather forecasting. Here a computationally demanding shadow casting algorithm is used to assess the capability of a simple single-layer urban canopy model, which assumes an infinitely long rotating canyon (ILC), to reproduce sunlit areas on roofs, walls and roads over central London. Results indicate that the sunlit road areas are well-represented but somewhat smaller using an ILC, while sunlit roofs areas are consistently larger, especially for dense urban areas. The largest deviations from real world sunlit areas are for roofs during mornings and evenings. Sunlit fractions on walls are overestimated using an ILC during mornings and evenings are found. The implications of these errors are dependent on the application targeted. For example, (independent of albedo) ULSMs used in numerical weather prediction applying ILC representation of the urban form will overestimate outgoing shortwave radiation from roofs due to the overestimation of sunlit fraction of the roofs. Complications of deriving height to width ratios from real world data are also discussed.

High resolution imaging of maize (Zea mays) leaf temperature in the field: the key role of the regions of interest.

The use of remote sensors (thermometers and cameras) to analyse crop water status in field conditions is fraught with several difficulties. In particular, average canopy temperature measurements are affected by the mixture of soil and green regions, the mutual shading of leaves and the variability of absorbed radiation. The aim of the study was to analyse how the selection of different 'regions of interest' (ROI) in canopy images affect the variability of the resulting temperature averages. Using automated image segmentation techniques we computed the average temperature in four nested ROI of decreasing size, from the whole image down to the sunlit fraction of a leaf located in the upper part of the canopy. The study was conducted on maize (Zea mays L.) at the flowering stage, for its large leaves and well structured canopy. Our results suggest that, under these conditions, the ROI comprising the sunlit fraction of a leaf located in the upper part of the canopy should be analogous to the single leaf approach (in controlled conditions) that allows the estimation of stomatal conductance or plant water potential.

도시 차원의 건물 음영을 고려한 일사량 계산 모듈 개발에 관한 연구

Recently, development of detailed urban energy consumption prediction tools becomes a rising issue as it can provide more quantitative and qualitative information for planning a sustainable city. One of the target physical phenomena related to the urban case is to correctly calculate the solar irradiance on building envelops with taking into account the shading and mask effects. The sunlit fraction(SF) is commonly used to calculate the effective beam solar irradiance, and the sky-view factor(SVF) is used for the precise diffuse irradiance in the urban context. Both indicators are also employed in this work, and they are calculated using the polygon clipping method. The proposed solar insolation calculation module is implemented in Python, and results from the module are compared with existing SketchUp Plug-in tools. Results show that SF and SVF obtained from the module are almost the same as the existing tools, giving only less than 2% errors over the year. A case study is also carried out for comparison between the urban case and the single building case. As expected, total monthly insolation in the single building case is overestimated with a mean difference of about 20%.

A 3D Canopy Radiative Transfer Model for Global Climate Modeling: Description, Validation, and Application

Abstract The process of solar radiative transfer at the land surface is important to energy, water, and carbon balance, especially for vegetated areas. Currently the most commonly used two-stream model considers the plant functional types (PFTs) within a grid to be independent of each other and their leaves to be horizontally homogeneous. This assumption is unrealistic in most cases. To consider canopy three-dimensional (3D) structural effects, a new framework of 3D canopy radiative transfer model was developed and validated by numerical simulations and shows a good agreement. A comparison with the two-stream model in the offline Community Land Model (CLM4.0) shows that an increase of canopy absorption mainly happens with sparse vegetation or with multilayer canopies with a large sun zenith angle θsun and is due to increases of the ground and sky shadows and of the optical pathlength because of the shadow overlapping between bushes and canopy layers. A decrease of canopy absorption occurs in densely vegetated areas with small θsun. For a one-layer canopy, these decreases are due to crown shape effects that enhance the transmission through the canopy edge. For a multilayer canopy, aside from these shape effects, transmission is also increased by the decreased ground shadow due to the shadow overlapping between layers. Ground absorption usually changes with opposite sign as that of the canopy absorption. Somewhat lower albedos are found over most vegetated areas throughout the year. The 3D model also affects the calculation of the fraction of sunlit leaves and their corresponding absorption.

On the nature of canopy illumination due to differences in elemental orientation and aggregation for radiative transfer

The nature of canopy radiative transfer mechanism (CRTM) describes the amount of beam penetration through a canopy and governs the nature of canopy illumination, i.e. the abundance of sunlit and shaded portions. Realistic representation of canopy illumination is critical for simulating various canopy biophysical processes associated with vegetated land surfaces. The adequate representation of CRTM can be attributed to the parameterizations of the two main canopy characteristics: the foliage projection (G-function) and the clumping effect (Ω function). Herein, using various types of G and Ω functions developed in a previous study, I tested 15 CRTM scenarios that combine different types of G and Ω functions to predict the dynamics of sunlit fraction (ε) of canopies having a wide range of plant area index (Ptotal) at various solar zenith angles (SZAs). It was observed that, for a given Ptotal, ε decreases as the SZA increases. However, ε significantly changed in accordance with the type of G and Ω functions used. Scenarios that employed random distribution of elements in space (S-4, S-9, and S-14) consistently returned larger ε values even at lower SZAs. This means that ignoring the clumping behavior of canopies could result in greater proportion of sunlit elements thereby reducing the beam penetration deeper into the canopy as opposed to those canopies where the elements are more aggregated. Beyond 70° SZA, almost all the scenarios returned similar ε values for a given Ptotal, which implied that the methods used is less sensitive at higher SZAs. The values of ε calculated by all the scenarios were significantly different from the S-6 (the ideal case). This observation highlights the importance of explicitly describing the G and Ω functions to adequately depict canopy illumination conditions.

Incorporating diffuse photosynthetically active radiation in a single-leaf model of canopy photosynthesis for a 56-year-old Douglas-fir forest

A simple top-down model of canopy photosynthesis (P) was developed and tested in this study. The model (referred to as the Q(e)-MM model) is P = alphaQ (e) P (max)/(alphaQ ( e ) + P (max)), alpha and P (max) are quantum-use efficiency and potential P, respectively. Q (e) is given by Q (d) (0) + kQ (b) (0), where Q (d) (0) and Q (b) (0) are the diffuse and direct photosynthetically active radiation (PAR) incident on the canopy, respectively. Q (e) can be considered to be the effective incident PAR contributing to P and k is a measure of the contribution of Q (b) (0) to Q (e). When k = 1, the Q(e)-MM model becomes the regular Michaelis-Menten type model of P (referred to as the MM model). A major objective of this study was to determine how well the Q(e)-MM model could estimate P of a 56-year-old coastal Douglas-fir stand. To this end, we parameterized the Q(e)-MM model using five and half years of eddy-covariance measurements of CO(2) flux above the Douglas-fir stand. The Q(e)-MM model, with the incorporation of a function of air temperature, accounted for 74% of the variance in over 34,000 half-hourly P measurements. P estimated using the Q(e)-MM model had no systematic errors with respect to Q (d) (0). Although the Q(e)-MM model has only one more parameter than the MM model, it accounted for 30% more variance in P than the latter when total incident PAR exceeded 900 micromol m(-2) s(-1). On average, k was found to be 0.22. We show that this small value of k reflects the significant effect of the scattering of the solar beam and the fraction of light-limited sunlit leaves. We also show that the success of the Q(e)-MM model was due to the fact that a large fraction of the sunlit leaves were light-limited as a result of their orientation to the solar beam.

Canopy structure and photosynthesis modelling of grapevines (Vitis vinifera L. cv. Sultana) grown on an overhead (parronal) trellis system in Chile

Most table grapes in Chile are produced on an overhead (parronal) trellis system with typically high values for leaf area index (LAI). An apparent lack of sunlight inside such canopies often raises questions as to the photosynthetic effectiveness of shaded leaves, and the comparative importance of successive leaf layers (top to bottom) for the total canopy carbon balance. In particular, are some leaves parasitic with respect to daily carbon balance? Accordingly, we undertook a study of canopy architecture, light climate and photosynthetic physiology to address those issues. Canopy photosynthesis was inferred from a process-based model using measured values for: the vertical distribution of (1) leaf angle, (2) LAI, (3) the fraction of sunlit leaves and (4) single-leaf photosynthetic capacity. Photon flux densities (PFD) and measured values of CO2 assimilation by leaves located on different parts of the canopy were obtained at flowering (mid-October) and during active berry growth (mid-December). Results of leaf angle revealed that Sultana canopies on this system behave in an erectophile manner with an average leaf inclination of 60o above horizontal. Modelling the contribution made by different leaf layers to overall canopy photosynthesis demonstrated that leaf layers contributing most were those under a shade plus sunfleck regime. They were located between 20 and 40 cm above the horizontal trellis structure itself. Indeed, some photoinhibition was observed in leaves under continuous direct radiation towards the top of the canopy, and located above 40 cm layer. However, such leaves represented only a small proportion of total LAI, and thus compromised canopy photosynthesis to only a limited extent. Outcomes from our simulation studies imply that LAI values commonly reached by canopies managed according to the parronal system of grape trellising do not result in parasitic leaves.

Short-term environmental controls of heat and water vapour fluxes above a boreal coniferous forest: model computations compared with measurements by eddy correlation

Eddy correlation and stem flow measurements were coupled with detailed microclimate and soil measurements made in a boreal Scots pine forest in the late growing season of 1998 to determine sensible and latent heat fluxes from the soil and the canopy separately. A ‘resistance/energy’ model is constructed and parametrized in order to reproduce the dynamics of water and heat exchange between the soil, the canopy and the atmosphere as a part of a larger forest ecosystem model (FinnFor; Kellomäki and Väisänen, 1997). Unique features of the present model are that (1) energy flux equations are expressed in terms of conceptual resistances and their solutions are obtained by closing two surface energy budget equations defined separately for canopy and soil surface; (2) the forest canopy is divided into shaded and sunlit fractions in the radiation transfer submodel and the canopy resistance submodels; (3) a numerical integrating solutions are derived separately for net radiation absorption in the canopy, bulk canopy resistance and the bulk aerodynamic resistances of the forest; and (4) iterative determinations of canopy water potential based on a classical one-dimensional water flow model enable the model to represent explicitly the interaction between the above-ground and the below-ground water dynamics. The model is validated against 19-day flux measurements. In general, the total system sensible heat flux ( H), total system latent heat flux ( λE), canopy latent heat flux ( λE c), and soil surface heat flux ( G s) computed by the model matched well with the measured data. Based on 1/2 h flux measurements, daily λE varied from 0.50–7.38 MW m −2, H from 0.64–8.3 MW m −2, and λE c from 0.30–6.93 MW m −2. The Bowen ratio ( H/λE) ranged from−4.5 to 9.8, but 82% of the values for the Bowen ratio were within 0.5–2.5. The model computations showed that daily λE c and H c accounted for 21–64% and 43–66% of the daily total system flux, respectively. Daily soil latent heat ( λE s) and soil sensible heat ( H s) fluxes accounted for 0.02–4.5% and 0.05–7.6%, respectively, and the daily energy storage within the canopy ( S c) and G s accounted for 0.1–7.2% and 0.8–5.6%, respectively. Plotting of 1/2 h flux data against a single environmental factor indicated that a 68% change in λE c and a 72% change in H c can be explained by a change in canopy radiation absorption ( R nc ) at the 5% probability level. The high correlation between the canopy fluxes and R nc could be related to the moderate weather conditions and high soil water content during the selected days, whereas λE s, H s, S c and G s give no significant correlation with R n . As expected, λE c was strongly dependent on canopy resistance ( r cs), but less impact on aerodynamic resistances during most of the measuring time. The proportion of energy partitioning in H and λE exhibited a clear diurnal trend and was mainly controlled by the system total resistance and the vapour pressure deficit, but less related to changes in soil water content.