Greenhouse crop transpiration calculation method based on improved Penman-Monteith model

Abstract

The invention relates to the technical field of crop transpiration calculation, and particularly discloses a greenhouse crop transpiration calculation method based on an improved Penman-Monteith model, which comprises the following steps of: researching convection types in a greenhouse under different ventilation by setting a ventilation mode of the greenhouse; an improved calculation method for an aerodynamic resistance parameter ra and a canopy resistance parameter rc is obtained according to a convection type in combination with meteorological data and plant growth data in a greenhouse, and the improved calculation method is combined with a Penman-Monteith model applied to greenhouse crop ET simulation to obtain an improved greenhouse crop transpiration calculation model. After verification, the model is proved to have relatively high simulation precision; the improved Penman-Monteih greenhouse crop transpiration calculation model is used for predicting the transpiration of the greenhouse tomatoes in different growth periods and comparing the transpiration with the measured value, the influence degree of ventilation on the water consumption of the greenhouse crops in different growth periods can be determined, and the method has practical significance in guiding natural ventilation management of the greenhouse tomatoes in different growth periods.

Description

Technical Field

[0001] The invention belongs to the technical field of crop transpiration calculation, and in particular relates to a method for calculating greenhouse crop transpiration based on an improved Penman-Monteith model. Background Art

[0002] Greenhouse cultivation is of great significance to improving agricultural production efficiency and quality, saving resources, and promoting the adjustment of agricultural industrial structure. At present, the production scale of solar greenhouses in my country is gradually expanding, but the semi-closed management of solar greenhouses has created a complex internal environment of the greenhouse. It is particularly important to clarify the mechanism of the influence of environmental regulation on the water demand of greenhouse crops.

[0003] Solar radiation, air humidity, air temperature and wind speed are the main meteorological factors that affect the transpiration rate of crops. When humidity increases, the water vapor pressure difference between leaves and air decreases, and transpiration weakens; when temperature rises, the water vapor pressure difference between leaves and air increases, and the transpiration rate increases, but transpiration weakens after exceeding the critical temperature; wind speed promotes the transpiration rate, but it also inhibits transpiration after exceeding the critical value. Different ventilation methods significantly change the effects of the above meteorological factors on the water consumption process of plants. Studies have found that poor airflow in greenhouses not only affects crop growth and development, but also changes its water consumption process, thereby changing the predetermined irrigation system. At present, most studies on greenhouse ventilation use CFD models to analyze the effects of different ventilation on the indoor environment. However, it is unclear how different ventilation modes affect the transpiration of greenhouse crops.

[0004] Obtaining the changing patterns of water consumption in different time periods through measurement requires the use of precision instruments, which is expensive and laborious, so building a water consumption-related model becomes the key to solving the problem. At present, the calculation methods of greenhouse crop water consumption include modern mathematical algorithms such as machine learning and traditional algorithms such as empirical formulas and theoretical models. Among them, although modern mathematical algorithms such as machine learning are not very sensitive to missing data and the algorithms are relatively simple, they require a large amount of data, cannot observe the learning process, and cannot reflect physical meaning; traditional algorithms are mostly based on crop physiological ecology and environmental changes to establish a relationship model between evaporation and transpiration and environmental factors. This method has a strong theoretical basis. The Penman-Monteith (PM) model is recognized as the model with the best accuracy. Improving PM by changing or introducing new model parameters for application in crop water consumption calculation is the main consideration at present. For example, Ma Zhao et al. improved the Penman-Monteith model based on radiation to estimate the reference crop evaporation in the main grain producing areas, and used the classic sunshine duration model combined with the PM model to calculate crop evaporation. However, for greenhouse crops, the conventional classic sunshine duration model is not fully applicable to the microclimate space of the greenhouse. Therefore, it is still necessary to study a new evaporation calculation model in combination with the actual situation of the greenhouse microclimate to characterize the evaporation of greenhouse crops. Summary of the invention

[0005] In view of the defects and problems existing in the current crop evapotranspiration calculation based on the Penman-Monteith model, the present invention provides a greenhouse crop evapotranspiration calculation method based on an improved Penman-Monteith model, comprising the following steps:

[0006] S1. Set the ventilation mode, collect the meteorological data, soil data and plant growth data in the greenhouse under different ventilation modes, determine the greenhouse convection type under the ventilation mode, and construct an aerodynamic resistance model and a canopy resistance model suitable for the greenhouse environment; calculate the aerodynamic resistance r according to the constructed aerodynamic resistance model and canopy resistance model. a and canopy resistance r c ;

[0007] S2, the aerodynamic resistance r a , canopy resistance r c Combined with the Penman-Monteith model, a greenhouse crop transpiration calculation model under different ventilation modes is obtained to calculate the greenhouse crop transpiration.

[0008] In the above-mentioned greenhouse crop transpiration calculation method based on the improved Penman-Monteith model, the meteorological data includes air density ρ a , temperature, total solar radiation R s , net radiation above the canopy Rn , saturated water vapor pressure difference VPD, wind speed V; the soil data include soil moisture content; the plant growth data include leaf length l, leaf width w, leaf characteristic length d, leaf area index LAI.

[0009] In the above-mentioned greenhouse crop transpiration calculation method based on the improved Penman-Monteith model, the aerodynamic resistance model construction in step S1 includes the following steps:

[0010] (1) Setting the greenhouse ventilation mode and determining the convection type in the greenhouse, which includes free convection, forced convection and mixed convection, and determining the heat transfer coefficient h of the greenhouse according to the convection type s ,

[0011]

[0012] Where: k c is the thermal conductivity of air, 0.0264W / (m·K); G r is the Grashof number, R e is the Reynolds number, where G r / R e 2 ≥10 is free convection; G r / R e 2 ≤0.1 is forced convection; 0.1 <G r / R e 2 <10 is mixed convection;

[0013] (2) Calculate the aerodynamic resistance r based on the determined heat transfer coefficient a ,

[0014]

[0015] Where: d is the characteristic length of the blade, unit: m; ρ a is the air density, 1.166kg / m 3 ;c p is the specific heat of air at constant pressure, 1013 J / (kg·K); LAI is the leaf area index.

[0016] In the above-mentioned greenhouse crop transpiration calculation method based on the improved Penman-Monteith model, the canopy resistance model construction in step S1 includes the following steps:

[0017] (1) Based on the total solar radiation R s Calculate the stomatal resistance r of the plant leaves s ,

[0018]

[0019] (2) According to the obtained pore resistance r s Calculating canopy resistance r for greenhouse crops c ,

[0020]

[0021] Where: r s is the pore resistance, unit is s / m; R s is the total solar radiation, in w / m 2 ;LAI e is the effective leaf area index.

[0022] In the above-mentioned method for calculating greenhouse crop transpiration based on the improved Penman-Monteith model, the Penman-Monteith model in step S2 is:

[0023]

[0024] R n =R n [1-exp(-kLAI)]

[0025] Where: λET is the latent heat flux, unit W / m 2 ; λ is the latent heat coefficient of vaporization, 2.45×10 6 J / kg; Δ is the slope of the saturated water vapor pressure-temperature curve, unit kpa / ℃; ρ a is the air density, 1.166kg / m 3 ;c p is the specific heat of air at constant pressure, 1013 J / (kg·K); VPD is the saturated vapor pressure difference, in kPa; r a is the aerodynamic resistance, unit is s / m; γ is the hygrometer constant, 0.065 kPa / K; r c is the canopy resistance, unit s / m; R n ' is the net radiation intercepted by the crop canopy, in W / m 2 ; R n is the net radiation above the canopy, in W / m 2 ; k is the crop canopy extinction coefficient.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] 1. This paper studies the convection type and pore resistance under different ventilation environments in greenhouses and finds that different ventilation methods have a great influence on the r a and r cThe results show that the calculation model of air resistance parameters and canopy resistance parameters is improved based on this, and it is combined with the Penman-Monteith model to obtain the improved Penman-Monteith model. The improved Penman-Monteith model is used to calculate the evapotranspiration of greenhouse crops, and the improved model is evaluated by mean square error, root mean square error, mean absolute error, consistency index, model efficiency index and determination coefficient, which proves that the model has high simulation accuracy.

[0028] 2. The method of the present invention is used to estimate T r The corresponding heat transfer coefficient is selected according to the daily convection conditions to calculate the daily r a , the calculation results are closer to the true value, with high accuracy and precision.

[0029] 3. The present invention uses the improved Penman-Monteith greenhouse crop transpiration calculation model to predict the transpiration of greenhouse tomatoes in different growth stages and compares it with the measured value, proving the influence of ventilation on the water consumption of greenhouse crops in different growth stages, which has practical significance for guiding the natural ventilation management of greenhouse tomatoes in different growth stages. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 Schematic diagram of greenhouse structure and ventilation holes.

[0031] Figure 2 Canopy resistance of greenhouse tomatoes under different ventilation treatments in 2020 and 2021 c And changes in leaf area LAI.

[0032] Figure 3 For the 2020 and 2021 greenhouses, the r / R e 2 Classification of convection conditions.

[0033] Figure 4 The aerodynamic resistance r in the greenhouse under different treatments in 2020 and 2021 a and the changes in wind speed V throughout the growing period.

[0034] Figure 5 The transpiration of greenhouse tomatoes was calculated based on the improved PM model in 2020 and 2021.

[0035] Figure 6 The comprehensive situation of greenhouse tomato transpiration was calculated based on the improved PM model for different treatments in 2020 and 2021. DETAILED DESCRIPTION

[0036] Since the currently improved PM model cannot be fully applied to the microclimate space of a greenhouse, it is necessary to provide a high-precision evapotranspiration calculation model to characterize the evapotranspiration of greenhouse crops in combination with the actual situation of the greenhouse microclimate. The present invention is further described below in combination with the accompanying drawings and specific embodiments.

[0037] Example 1: This example provides a method for calculating greenhouse crop transpiration based on an improved PM model. The method first calculates two important parameters in the PM model, the aerodynamic resistance parameter r, according to the ventilation mode in the greenhouse. a and canopy resistance parameter r c The corrected aerodynamic drag parameter r a and canopy resistance parameter r c Combined with the PM model, an improved PM calculation model is obtained, the main contents of which are as follows.

[0038] (1) Construct the aerodynamic resistance r of the greenhouse under different ventilation modes a Computational model

[0039] Set the ventilation mode and collect the meteorological data, soil data and plant growth data in the greenhouse under different ventilation modes. The meteorological data includes the air density ρ a , temperature, total solar radiation R s , net radiation above the canopy R n , saturated water vapor pressure difference VPD, wind speed V; soil data include soil moisture content; the plant growth data include leaf length l, leaf width w, leaf characteristic length d, leaf area index LAI.

[0040] According to the ventilation conditions, the greenhouse convection type under the ventilation mode is determined. In the greenhouse tomato greenhouse, under the ventilation mode, affected by the gaseous liquid flow and wind speed, different convection types are presented in the greenhouse, namely free convection, forced convection and mixed convection. If the upper and lower surface temperatures of the leaves are the same, it is free convection (G r / R e 2 ≥10); if the flowing air contacts with the object with high temperature, it is forced convection (G r / R e 2 ≤0.1); when both free convection and forced convection exist, it is mixed convection (0.1 <G r / R e 2 <10).

[0041] Among them, the Grashof number (G r ), reflects the free convection air flow in the form of laminar or turbulent flow, and can be expressed by the equation of the temperature difference between the blade and the air,

[0042]

[0043] Where: β is the thermal expansion coefficient of air, 3.315×10 -3 1 / K; g is the acceleration due to gravity, 9.8m / s 2 ; T c is the canopy temperature, unit: °C; T a is the air temperature, unit is °C; v is the air dynamic viscosity, 1.64×10 -5 m 2 / s;

[0044] Reynolds number (R e ) reflects the effect of an imposed air flow on convection and can be expressed as a function of wind speed,

[0045]

[0046] Determine the heat transfer coefficient h based on the determined convection type s , calculate the aerodynamic drag r a ,

[0047]

[0048] Where: k c is the thermal conductivity of air, 0.0264W / (m·K); d is the characteristic length of the blade, in m; G r is the Grashof number; R e is the Reynolds number; ρ a is the air density, 1.166kg / m 3 ;c p is the specific heat of air at constant pressure, 1013 J / (kg·K); LAI is the leaf area index.

[0049] (2) Constructing canopy resistance r c Model

[0050] Leaf pore resistance r s is used to calculate the canopy resistance r in the PM model c An important parameter of c ; r s The decisive factor of is the degree of stomatal opening and closing of the plant leaves. Under sufficient irrigation conditions, the degree of stomatal opening and closing is mainly affected by meteorological factors. s Determined to affect the leaf pore resistance r s Greenhouse climate factors,

[0051]

[0052] Where: r s is the pore resistance, unit is s / m; R s is the total solar radiation, in w / m 2 ;LAI e is the effective leaf area index.

[0053] (3) The aerodynamic drag model and canopy drag model are combined with the PM model to obtain the greenhouse crop transpiration calculation model under different ventilation modes. The Penman-Monteith model can be expressed as follows when applied to the simulation of greenhouse crop ET:

[0054]

[0055] Where: λET is the latent heat flux, unit W / m 2 ; λ is the latent heat coefficient of vaporization, 2.45×10 6 J / kg; Δ is the slope of the saturated water vapor pressure-temperature curve, unit kpa / ℃; R n ' is the net radiation intercepted by the crop canopy, in W / m 2 ρ a is the air density, 1.166kg / m 3 ;c p is the specific heat of air at constant pressure, 1013 J / (kg·K); VPD is the saturated vapor pressure difference, in kPa; r a is the aerodynamic resistance, unit is s / m; γ is the hygrometer constant, 0.065 kPa / K; r c is the canopy resistance, unit is s / m.

[0056] R n ' is the difference between the net radiation above the canopy and the net radiation reaching the soil surface through the canopy

[0057] R n =R n [1-exp(-kLAI)]

[0058] Where: R n is the net radiation above the canopy, in W / m 2 ; k is the crop canopy extinction coefficient.

[0059] Experimental example: This experiment was conducted in March-July 2020 and 2021 in a solar greenhouse at the Xinxiang Comprehensive Experimental Base of the Chinese Academy of Agricultural Sciences (35°9′N, 113°5′E).

[0060] The average annual rainfall in the test area is 573 mm, the average annual temperature is 14.2 ° C, the average annual evapotranspiration is 1908.7 mm, the average annual sunshine hours are 2398.8 h, and the average annual wind speed is 2.3 m / s. It belongs to the warm temperate continental monsoon climate. The 0-100 cm soil layer is silt loam (16.9% clay, 76.7% silt, 6.4% sand), with a bulk density of 1.49 g / cm 3 . Field water holding capacity (θ f ) is 0.32cm 3 / cm 3 , wilting coefficient (θ w ) is 0.09cm 3 / cm 3 , the groundwater depth is below 5m.

[0061] The solar greenhouse used in this experiment faces south and has an area of ​​170m 2 (20m×8.5m). The greenhouse eaves are 3.9m high, the walls are made of bricks, and insulation materials are embedded inside the walls on the north, east and west sides. The roof is made of steel frame structure and covered with polyethylene plastic film. A 5cm thick quilt is laid on the surface of the plastic film to maintain a suitable temperature indoors. See the detailed cross-section of the solar greenhouse for details. Figure 1 .

[0062] Before transplanting, 112kg urea (containing 46% nitrogen), 150kg potassium sulfate (containing 50% K2O) and 120kg super phosphoric acid (containing 14% P2O5) were applied per hectare as basal fertilizer, and the land was plowed with a rotary tillage hoe to a depth of 16cm. When the first, second, third and fourth layers of fruits began to swell, topdressing was carried out with a differential pressure fertilizer box, with 18.8kg urea and 25kg potassium sulfate per hectare, and a total of 4 topdressings were applied during the entire growth period.

[0063] The tomato variety used in the experiment was "Jinpeng M6". Seedlings were raised in January and transplanted on March 5, 2020 and March 7, 2021, respectively. After transplanting, a 0.03mm black plastic film was covered on the soil surface and 30mm of irrigation was applied to ensure the survival of the seedlings. The area of ​​the seedling field is 17.6m 2 (8.8m long × 2m wide). When the seedlings grow to the 3-leaf 1-heart stage, they are planted in wide and narrow rows (65cm wide and 45cm narrow) in the greenhouse with a planting density of 5.7 plants / m 2 In this experiment, the growth period of greenhouse tomatoes was divided into four growth stages: seedling stage, flowering and fruiting stage, peak fruiting stage and picking stage.

[0064] The greenhouse used in the experiment is equipped with two ventilation openings, such as Figure 1As shown, they are located at the top of the greenhouse (42m×0.5m,) and the south side (42m×1.0m). The experiment set up two ventilation treatment modes, T1 (open only the top vents) and T2 (open the top and south vents at the same time). The two treatments were completed in two greenhouses respectively, and the time and frequency of ventilation management in each greenhouse were kept consistent. During the experiment, on sunny days, when the temperature in the greenhouse was close to 30℃ from 7:00 to 8:00 in the morning, the vents were fully opened for ventilation and dehumidification; on cloudy days, the vents were fully opened from 9:30 to 10:00 for ventilation and dehumidification; according to the temperature of the day, the vents were closed 1 to 2 hours before sunset in the afternoon, first of all, the temperature in the greenhouse was not lower than 15℃ at night and ventilation and dehumidification were ensured (if the temperature at night was lower than 15℃, the vents were completely closed; otherwise, some vents were closed to ensure the temperature and ventilation and dehumidification at the same time).

[0065] Canopy resistance r of greenhouse tomatoes at different developmental stages under different ventilation modes (T1 and T2) in 2020 and 2021 c The changing trend of LAI is as follows Figure 2 shown.

[0066] Depend on Figure 2 It can be seen that during the seedling stage, as the LAI increases, c It is showing a rapid downward trend. During the flowering and fruiting period and the peak fruiting period, r c As LAI increases, its downward trend slows down. This is because LAI and LAI in the late reproductive period e Slow growth leads to c When LAI is lower than 1.0, the average r c When LAI was higher than 1.0, it was 95.2s / m for T1 and 85.9s / m for T2. c It was 19.9% ​​higher than that of T2 treatment, indicating that better ventilation conditions would improve the canopy resistance of crops.

[0067] At the same time, it can be seen from the above results that canopy resistance is mainly related to surface resistance and crop leaf area index. Wind speed has a certain influence on crop leaf area during the entire growth period, especially in the early growth stage when LAI is small and is greatly affected by different ventilation conditions.

[0068] During the entire crop growth period, the average net radiation in the greenhouse in 2020 and 2021 was 98.80 and 102.22 W / m 2 The average characteristic lengths of tomato leaves were 7.4 and 6.3 cm respectively. The average wind speeds in the two years were 0.09 m / s for T1 and 0.15 m / s for T2. The temperature differences between the canopy and the air were -0.34 and -0.16 °C respectively.

[0069] By R in the greenhousen , V, T a , T c and growth characteristics, calculate G r / R e 2 The relative size of Figure 3 .

[0070] Depend on Figure 3 It can be seen that the days of mixed convection in the two-year T1 treatment accounted for an average of 20.2% of the growth period, and the average number of days in T2 was 10.3%. The rest were pure forced convection, and no period of pure free convection was observed. The pure forced convection in T2 was 10% higher than that in T1. This shows that different ventilation treatments have a certain impact on the convection of the greenhouse.

[0071] According to the determined convection type of the greenhouse, determine the heat transfer coefficient h s , given by the aerodynamic drag r a The calculation model calculates the aerodynamic drag r a .

[0072] Since pure free convection was not observed during the entire growth period, the heat transfer coefficient under pure free convection was not used in this example to calculate r a According to the daily convection conditions, the heat transfer coefficient under the corresponding convection conditions is used to calculate r a , so a comprehensive r is obtained during the entire reproductive period a The results are shown in Figure 4 .

[0073] Depend on Figure 4 It can be seen that in 2020 and 2021, under T1 and T2 treatments, r a With similar trend, as the tomato grows a Gradually decrease, r a Both showed maximum values ​​in the seedling stage. The average value of T1 treatment in the seedling stage was 212.9 s / m, 1.3 times higher than the average value of the entire growth period (93.2 s / m); the average value of T2 treatment in the seedling stage was 164.2 s / m, also 1.3 times higher than the average value of the entire growth period (72.4 s / m). Compared with the two ventilation treatments, T1 in the seedling stage was 29.7% higher than T2, while T1 in the entire growth period was 28.7% higher than T2. ​​It can be seen that r a Affected by wind speed, the r a The difference is obvious, a Overall performance is T2 <T1。

[0074] Since there was no pure free convection under the T1 and T2 ventilation treatments in 2020 and 2021, the aerodynamic drag model and the canopy drag model were combined with PM to calculate the daily transpiration. The aerodynamic drag model of forced convection and mixed convection was used for the aerodynamic drag model, and then compared with the measured value T r (stem flow rate) was fitted, and the results are shown in Figure 5 and Figure 6 .

[0075] IBM SPSS26 statistical software was used for data analysis, Microsoft Excel 2019 and Origin2020 were used for chart drawing, and mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), consistency index (d IA ), model efficiency index (EF) and determination coefficient (R 2 ) to evaluate the accuracy of the model. The smaller the MSE, MAE and RMSE, the higher the prediction accuracy of the model. 2 d IA EF reflects the degree of fit between the model prediction value and the measured value. The closer its value is to 1, the higher the degree of model fit. When EF is less than 0, the closer its value is to 0, the higher the degree of model fit. The results are shown in Table 1. The formula is as follows:

[0076]

[0077] Where: P i is the measured value, Q i is the model prediction value, is the average value of the measured values, is the average value of the model prediction, and N is the number of samples.

[0078] Table 1 Evaluation indexes of improved PM model fitting

[0079]

[0080]

[0081] Note: The whole growth period does not include the seedling stage

[0082] Depend on Figure 5 , Figure 6 As shown in Table 2, the slope of the fitting curve between the simulated value and the measured value of the T1 treatment during the entire growth period in 2020 is close to 1.0. r Underestimation 0.44%, R 2 , MAE, RMSE, MSE, d IAand EF were 0.87, 0.44 mm / d, 0.55 mm / d, 0.30 mm / d, 0.97 and 0.87, respectively; the slope of T2 treatment was 1.05, T r Overestimated by 6.14%, R 2 , MAE, RMSE, MSE, d IA and EF are 0.92, 0.41mm / d, 0.59mm / d, 0.35mm / d, 0.98 and 0.90 respectively.

[0083] The slope of the T1 treatment during the entire growth period in 2021 was 0.99, and the T r Underestimated by 0.6%, R 2 , MAE, RMSE, MSE, d IA and EF were 0.90, 0.42 mm / d, 0.58 mm / d, 0.33 mm / d, 0.97 and 0.90, respectively; the slope of T2 treatment was 1.08, T r Overestimated by 8.9%, R 2 , MAE, RMSE, MSE, d IA and EF are 0.87, 0.63mm / d, 0.88mm / d, 0.77mm / d, 0.95 and 0.79 respectively.

[0084] It can be seen that the PM model simulation results of T1 treatment underestimated the measured values ​​by 0.52% on average, and T2 overestimated the measured values ​​by 7.52%. The improved PM model can be used to estimate greenhouse tomato transpiration under two ventilation treatments.

[0085] The above description is only a preferred embodiment of the present invention and does not limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for calculating greenhouse crop transpiration based on an improved Penman-Monteith model, characterized in that: The following steps are involved: S1. Set the ventilation mode, collect the meteorological data, soil data and plant growth data in the greenhouse under different ventilation modes, determine the greenhouse convection type under the ventilation mode, and construct an aerodynamic resistance model and a canopy resistance model suitable for the greenhouse environment; calculate the aerodynamic resistance r according to the constructed aerodynamic resistance model and canopy resistance model. a and canopy resistance r c ; S2, the aerodynamic resistance r a , canopy resistance r c Combined with the Penman-Monteith model, a greenhouse crop transpiration calculation model under different ventilation modes is obtained to calculate the greenhouse crop transpiration.

2. The method for calculating greenhouse crop transpiration based on the improved Penman-Monteith model according to claim 1, characterized in that: The meteorological data includes air density ρ a , temperature, total solar radiation R s , net radiation above the canopy R n , saturated water vapor pressure difference VPD, wind speed V; the soil data include soil moisture content; the plant growth data include leaf length l, leaf width w, leaf characteristic length d, leaf area index LAI.

3. The method for calculating greenhouse crop transpiration based on the improved Penman-Monteith model according to claim 1, characterized in that: The aerodynamic drag model construction in step S1 includes the following steps: (1) Setting the greenhouse ventilation mode and determining the convection type in the greenhouse, which includes free convection, forced convection and mixed convection, and determining the heat transfer coefficient h of the greenhouse according to the convection type s , Where: k c is the thermal conductivity of air, 0.0264W / (m·K); G r is the Grashof number, R e is the Reynolds number, where G r / R e 2 ≥10 is free convection; G r / R e 2 ≤0.1 is forced convection; 0.1 <G r / R e 2 <10 is mixed convection; (2) Calculate the aerodynamic resistance r based on the determined heat transfer coefficient a , Where: d is the characteristic length of the blade, unit: m; ρ a is the air density, 1.166kg / m 3 ;c p is the specific heat of air at constant pressure, 1013 J / (kg·K); LAI is the leaf area index.

4. The method for calculating greenhouse crop transpiration based on the improved Penman-Monteith model according to claim 1, characterized in that: The construction of the canopy resistance model in step S1 includes the following steps: (1) Based on the total solar radiation R s Calculate the stomatal resistance r of the plant leaves s , (2) According to the obtained pore resistance r s Calculating canopy resistance r for greenhouse crops c , Where: r s is the pore resistance, unit is s / m; R s is the total solar radiation, in w / m 2 ;LAI e is the effective leaf area index.

5. The method for calculating greenhouse crop transpiration based on the improved Penman-Monteith model according to claim 1, characterized in that: The Penman-Monteith model in step S2 is: R' n =R n [1-exp(-kLAI)] Where: λET is the latent heat flux, unit W / m 2 ; λ is the latent heat coefficient of vaporization, 2.45×10 6 J / kg; Δ is the slope of the saturated water vapor pressure-temperature curve, unit kpa / ℃; ρ a is the air density, 1.166kg / m 3 ;c p is the specific heat of air at constant pressure, 1013 J / (kg·K); VPD is the saturated vapor pressure difference, in kPa; r a is the aerodynamic resistance, unit is s / m; γ is the hygrometer constant, 0.065 kPa / K; r c is the canopy resistance, unit s / m; R n ' is the net radiation intercepted by the crop canopy, in W / m 2 ; R n is the net radiation above the canopy, in W / m 2 ; k is the crop canopy extinction coefficient.

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