Modelling Crop Transpiration in Greenhouses: Different Models for Different Applications

Models for the evapotranspiration of greenhouse crops are needed both for accurate irrigation and for the simulation or management of the greenhouse climate. For this purpose, several evapotranspiration models have been developed and presented, all based on the Penman–Monteith approach, the “big-leaf” model. So, on the one hand, relatively simple models have been developed for irrigation scheduling purposes, and on the other, “knowledge–mechanistic” models have been developed for climate control purposes. These models differ in the amount of detail about variables, such as stomatal and aerodynamic conductance. The aim of this review paper is to present the variables and parameters affecting greenhouse crop transpiration, and to analyze and discuss the existing models for its simulation. The common sub-models used for the simulation of crop transpiration in greenhouses (aerodynamic and stomatal conductances, and intercepted radiation) are evaluated. The worth of the multilayer models for the simulation of the mass and energy exchanges between crops and air are also analyzed and discussed. Following the presentation of the different models and approaches, it is obvious that the different applications for which these models have been developed entail varying requirements to the models, so that they cannot always be compared. Models developed in different locations (high–low latitudes or for closed or highly ventilated greenhouses) are discussed, and their sensitivity to different parameters is presented.

Moderate forest disturbance as a stringent test for gap and big-leaf models

Disturbance-induced tree mortality is a key factor regulating the carbon balance of a forest, but tree mortality and its subsequent effects are poorly represented processes in terrestrial ecosystem models. In particular, it is unclear whether models can robustly simulate moderate (non-catastrophic) disturbances, which tend to increase biological and structural complexity and are increasingly common in aging US forests. We tested whether three forest ecosystem models – Biome-BGC, a classic big-leaf model, and the ED and ZELIG gap-oriented models – could reproduce the resilience to moderate disturbance observed in an experimentally manipulated forest (the Forest Accelerated Succession Experiment in northern Michigan, USA, in which 38% of canopy dominants were stem girdled and compared to control plots). Each model was parameterized, spun up, and disturbed following similar protocols, and run for 5 years post-disturbance. The models replicated observed declines in aboveground biomass well. Biome-BGC captured the timing and rebound of observed leaf area index (LAI), while ED and ZELIG correctly estimated the magnitude of LAI decline. None of the models fully captured the observed post-disturbance C fluxes. Biome-BGC net primary production (NPP) was correctly resilient, but for the wrong reasons, while ED and ZELIG exhibited large, unobserved drops in NPP and net ecosystem production. The biological mechanisms proposed to explain the observed rapid resilience of the C cycle are typically not incorporated by these or other models. As a result we expect that most ecosystem models, developed to simulate processes following stand-replacing disturbances, will not simulate well the gradual and less extensive tree mortality characteristic of moderate disturbances.

Dry deposition of nitrogen compounds (NO₂, HNO₃, NH₃), sulfur dioxide and ozone in west and central African ecosystems using the inferential method

This work is part of the IDAF program (IGAC-DEBITS-AFRICA) and is based on the long-term monitoring of gas concentrations (1998–2007) established at seven remote sites representative of major African ecosystems. Dry deposition fluxes were estimated by the inferential method using on the one hand surface measurements of gas concentrations (NO2, HNO3, NH3, SO2 and O3) and on the other hand modeled exchange rates. Dry deposition velocities (Vd) were calculated using the big-leaf model of Zhang et al. (2003b). The bidirectional approach is used for NH3 surface–atmosphere exchange (Zhang et al., 2010). Surface and meteorological conditions specific to IDAF sites have been used in the models of deposition. The seasonal and annual mean variations of gaseous dry deposition fluxes (NO2, HNO3, NH3, O3 and SO2) are analyzed. Along the latitudinal transect of ecosystems, the annual mean dry deposition fluxes of nitrogen compounds range from −0.4 to −0.8 kg N ha−1 yr−1 for NO2, from −0.7 to −1.0 kg N ha−1 yr−1 for HNO3 and from −0.7 to −8.3 kg N ha−1 yr−1 for NH3 over the study period (1998–2007). The total nitrogen dry deposition flux (NO2+HNO3+NH3) is more important in forests (−10 kg N ha−1 yr−1) than in wet and dry savannas (−1.6 to −3.9 kg N ha−1 yr−1). The annual mean dry deposition fluxes of ozone range between −11 and −19 kg ha−1 yr−1 in dry and wet savannas, and −11 and −13 kg ha−1 yr−1 in forests. Lowest O3 dry deposition fluxes in forests are correlated to low measured O3 concentrations, lower by a factor of 2–3, compared to other ecosystems. Along the ecosystem transect, the annual mean of SO2 dry deposition fluxes presents low values and a small variability (−0.5 to −1 kg S ha−1 yr−1). No specific trend in the interannual variability of these gaseous dry deposition fluxes is observed over the study period.

Improved light and temperature responses for light use efficiency based GPP models

Gross primary production (GPP) is the process by which carbon enters ecosystems. Diagnostic models, based on the theory of light use efficiency (LUE) have emerged as one method to estimate ecosystem GPP. However, problems have been noted particularly when applying global results at regional levels. We hypothesize that accounting for non-linear light response and temperature acclimation of daily GPP in boreal regions will improve model performance. To test this hypothesis, we have chosen four diagnostic models for comparison, namely: an LUE model (linear in its light response) both with and without temperature acclimation and an LUE model and a big leaf model both with temperature acclimation and non-linear in their light response. All models include environmental modifiers for temperature and vapour pressure deficit (VPD). Initially, all models were calibrated against four eddy covariance sites within Russia for the years 2002–2004, for a total of 10 site years. Model evaluation was performed via 10-out cross-validation. This study presents a methodology for comparing diagnostic modeling approaches. Cross validation clearly demonstrates the improvement in model performance that temperature acclimation makes in modeling GPP at strongly temperature controlled sites in Russia. Additionally, the inclusion of a non-linear light response function is shown to further improve performance. Furthermore we demonstrate the parameterization of the big leaf model, incorporating environmental modifiers for temperature and VPD.

Dry deposition of nitrogen compounds (NO₂, HNO₃, NH₃), sulfur dioxide and ozone in West and Central African ecosystems using the inferential method

This work is part of the IDAF program (IGAC-DEBITS-AFRICA) and is based on the long term monitoring of gas concentrations (1998–2007) established on seven remote sites representative of major African ecosystems. Dry deposition fluxes were estimated by the inferential method using on one hand surface measurements of gas concentrations (NO2, HNO3, NH3, SO2, and O3) and on the other hand simulated dry deposition velocities (Vd). Vd were calculated using the big-leaf model of Zhang et al. (2003b). In the model of deposition, surface and meteorological conditions specific to IDAF sites have been adapted in order to simulate Vd representative of major African ecosystems. The monthly, seasonal and annual mean variations of gaseous dry deposition fluxes (NO2, HNO3, NH3, O3, and SO2) are analyzed. Along the latitudinal transect of ecosystems, the annual mean dry deposition fluxes of nitrogen compounds range from 0.4 ± 0.0 to 0.8 ± 0.2 kg N ha−1 yr−1 for NO2, from 0.7 ± 0.1 to 1.0 ± 0.3 kg N ha−1 yr−1 for HNO3, and from 2.3 ± 0.8 to 10.5 ± 5.0 kg N ha−1 yr−1 for NH3 over the study period (1998–2007). The total nitrogen dry deposition flux (NO2+HNO3+NH3) is more important in forests (11.2–11.8 kg N ha−1 yr−1) than in wet and dry savannas (3.4–5.3 kg N ha−1 yr−1). NH3 dominated nitrogen dry deposition, representing 67–80% of the total. The annual mean dry deposition fluxes of ozone range between 11.3 ± 4.7 and 17.5 ± 3.0 kg ha−1 yr−1 in dry savannas, 17.5 ± 3.0 and 19.2 ± 2.9 kg ha−1 yr−1 in wet savannas, and 10.6 ± 2.0 and 13.2 ± 3.6 kg ha−1 yr−1 in forests. Lowest O3 dry deposition fluxes in forests are correlated to low measured O3 concentrations, lower of a factor of 2–3, compared to others ecosystems. Along the ecosystem transect, annual mean of SO2 dry deposition fluxes present low values and a small variability (0.5 to 1 kg S ha−1 yr−1). No specific trend in the interannual variability of these gaseous dry deposition fluxes is observed over the study period.

Soil moisture variability on a steep slope near a ridge in a forested mountain range, Shikoku, Japan: a model study

Variability in soil moisture on a steep slope near a ridge in a forested mountain range, Shikoku, Japan, was studied observationally and numerically. Vertically integrated soil moisture, from a depth of −60 cm to the surface, W, was introduced as a key indicator, and its seasonal variation was analysed on a daily basis from August 2011 to August 2012. The “bucket with a bottom hole” (BBH) model of Teshima et al. (2006) was improved to consider the forest environment in simulating the variation in W. A “big-leaf” model was incorporated into the modified BBH model to estimate transpiration and interception by trees. The simulated soil moisture agreed reasonably with observed values on a daily to inter-seasonal timescale.

Modelling Amazonian forest eddy covariance data: a comparison of big leaf versus sun/shade models for the C-14 tower at Manaus I. Canopy photosynthesis

In this study, we concentrate on modelling gross primary productivity using two simple approaches to simulate canopy photosynthesis: "big leaf" and "sun/shade" models. Two approaches for calibration are used: scaling up of canopy photosynthetic parameters from the leaf to the canopy level and fitting canopy biochemistry to eddy covariance fluxes. Validation of the models is achieved by using eddy covariance data from the LBA site C14. Comparing the performance of both models we conclude that numerically (in terms of goodness of fit) and qualitatively, (in terms of residual response to different environmental variables) sun/shade does a better job. Compared to the sun/shade model, the big leaf model shows a lower goodness of fit and fails to respond to variations in the diffuse fraction, also having skewed responses to temperature and VPD. The separate treatment of sun and shade leaves in combination with the separation of the incoming light into direct beam and diffuse make sun/shade a strong modelling tool that catches more of the observed variability in canopy fluxes as measured by eddy covariance. In conclusion, the sun/shade approach is a relatively simple and effective tool for modelling photosynthetic carbon uptake that could be easily included in many terrestrial carbon models.