A method and system for calculating forest surface resistance

Abstract

The present invention provides a method and system for calculating forest ground surface resistance, comprising the following steps: step 1, collecting and processing flux observation data, micro-meteorological observation data and leaf area index LAI data of flux stations; step 2, calibrating the minimum leaf resistance, the minimum soil surface resistance and the maximum litter surface resistance according to the latent heat flux data measured at the flux stations; step 3, calculating the ground surface resistance based on the minimum leaf resistance, the minimum soil surface resistance and the maximum litter surface resistance calibrated in step 2. The ground surface resistance estimated by the present invention can reflect the ground cover effect of litter on a large scale, thereby achieving a better estimation of ecosystem evapotranspiration.

Description

Technical Field

[0001] The invention relates to the field of forest ecohydrology, and in particular to a method and system for estimating the dynamic change of litter by using the leaf area index of the forest ecosystem so as to calculate the surface resistance. Background Art

[0002] Surface resistance controls the exchange of water, heat and gas between the surface and the atmosphere, and plays a key role in controlling soil evaporation. As a sensitive parameter in evapotranspiration models, accurate estimation of surface resistance helps to accurately simulate the evapotranspiration process. Since there is no direct observation method for surface resistance, the simulation of surface resistance is mostly reflected by the changes in soil water. However, this ignores the role of litter covering the soil surface.

[0003] Litter, as an important component of vegetation ecosystem, plays an important role in regulating the water, carbon and energy cycle of vegetation ecosystem. The eco-hydrological effect of litter on surface cover has been measured at many sites at home and abroad. However, due to the complexity of its influencing factors, it is difficult to describe this effect in a model. Therefore, it is difficult to consider the effect of litter in the surface resistance model, which leads to deviations in the simulation of litterfall periods in evapotranspiration models. Summary of the invention

[0004] The purpose of the present invention is to overcome the shortcomings of the prior art and to propose a method for calculating the surface resistance of a forest floor.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0006] A method for calculating surface resistance of a forest floor comprises the following steps:

[0007] Step 1: Collect and process flux observation data, micrometeorological observation data and leaf area index LAI data of flux stations;

[0008] Step 2: calibrate the minimum leaf resistance, the minimum soil surface resistance, and the maximum litter surface resistance based on the latent heat flux data measured at the flux site;

[0009] Step 3: Calculate the ground surface resistance based on the minimum leaf resistance, minimum soil surface resistance, and maximum litter surface resistance determined in step 2.

[0010] Furthermore, the flux observation data of the flux site in step 1 include: net radiation, soil heat flux, latent heat flux;

[0011] Micrometeorological observation data include: air temperature, air pressure, soil volume moisture content;

[0012] Leaf area index LAI data uses field continuous observation data or remote sensing product data:

[0013] Furthermore, in step 2, the minimum soil surface resistance and the maximum litter surface resistance are calibrated using a genetic algorithm. The calibration goal is to minimize the objective function. The objective function f is:

[0014] f=(R 2 -1) 2 +(k-1) 2

[0015] Among them, R 2 is the determination coefficient, and k is the slope of the fitting curve.

[0016] Further,

[0017]

[0018] Among them, λET sim，i is the ith simulated value of latent heat flux, λET obs，i is the ith observed value of latent heat flux, N is the number of samples, i is the ith sample number, is the average simulated value of the latent heat flux of N samples, is the average observed value of latent heat flux of N samples;

[0019] The simulated value of latent heat flux is calculated using the following formula:

[0020]

[0021] Among them, λET sim is the latent heat flux, Δ is the slope of the saturated water vapor pressure and temperature curve; R n is the net radiation; G is the soil heat flux; ρ a is the air density; C P is the specific heat of dry air; D is the saturated water vapor pressure difference VPD; is the effective aerodynamic drag; is the effective surface resistance; γ is the hygrometer constant.

[0022] Furthermore, the effective aerodynamic resistance for:

[0023]

[0024] Effective surface resistance for:

[0025]

[0026] in, is the canopy aerodynamic drag, is the soil aerodynamic resistance, is the atmospheric aerodynamic drag, is the canopy surface resistance, is the ground surface resistance.

[0027] Furthermore, canopy aerodynamic drag for:

[0028]

[0029] Soil aerodynamic resistance and atmospheric aerodynamic drag They are:

[0030]

[0031] Among them, r b is the average boundary layer resistance; L eff is the effective leaf area index, h c is the canopy height of the site, which is measured at the site; n is the eddy diffusion attenuation coefficient; K h is the turbulence attenuation coefficient at canopy height; z0 is the momentum roughness length; d is the zero plane displacement height, u * is the friction wind speed; k is the von Karman constant; z is the reference height, measured at the site;

[0032] Canopy surface resistance for:

[0033]

[0034] Among them, r smin is the minimum leaf resistance (sm -1 ), obtained by calibration; F1(S) represents the effect of photosynthetically active radiation S; F2(D) represents the effect of saturated vapor pressure difference VPD; F3(T a ) represents the air temperature T a effect.

[0035] Furthermore, the surface resistance in step 3 is calculated using the following formula:

[0036]

[0037] in, is the soil surface resistance; is the surface resistance of litter,

[0038]

[0039]

[0040]

[0041]

[0042] in, is the minimum soil surface resistance, obtained by calibration; f(θ) is the effect of soil water θ; θ f is the field water holding capacity, obtained by actual measurement; is the maximum litter surface resistance, obtained by calibration; C lit is litter cover; L max is the maximum leaf area index, and L is the ecosystem leaf area index LAI.

[0043] In another aspect, the present invention provides a forest floor surface resistance calculation system, comprising:

[0044] Data acquisition module: It is used to collect and process flux observation data, micro-meteorological observation data and leaf area index LAI data of flux stations;

[0045] Parameter calibration module, which is used to calibrate the minimum leaf resistance, the minimum soil surface resistance, and the maximum litter surface resistance according to the latent heat flux data measured at the flux site;

[0046] A ground surface resistance calculation module, which is used to calculate the ground surface resistance based on the calibrated minimum leaf resistance, minimum soil surface resistance, and maximum litter surface resistance;

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] (1) The present invention makes full use of the advantages of leaf area index in reflecting the changing characteristics of vegetation leaves. By establishing the relationship between leaf area index and litter coverage, it is able to reflect the coverage of litter on the ground surface on a large scale; (2) The present invention can adjust the size of the litter effect of different tree species on different underlying surfaces through the maximum surface resistance of litter, thereby achieving a better surface resistance estimation effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0050] Figure 1 It is a specific flow chart of the method of the present invention;

[0051] Figure 2 This is a schematic diagram of the change of litter coverage in this embodiment;

[0052] Figure 3 This is a schematic diagram of the change of the surface resistance of litter in this embodiment;

[0053] Figure 4 Schematic diagram of the change of ground surface resistance in this embodiment. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0055] Example 1

[0056] like Figure 1 As shown, this embodiment 1 provides a method for calculating forest floor surface resistance taking into account seasonal dynamic changes in litter, comprising the following steps:

[0057] Step 1: Collect and process flux observation data, micrometeorological observation data and leaf area index LAI data of flux stations;

[0058] Step 2: calibrate the minimum leaf resistance, the minimum soil surface resistance, and the maximum litter surface resistance based on the latent heat flux data measured at the flux site;

[0059] Step 3: Calculate the ground surface resistance based on the minimum leaf resistance, minimum soil surface resistance, and maximum litter surface resistance determined in step 2.

[0060] The flux observation data of the flux station in step 1 comes from all stations with deciduous broad-leaved forest as the underlying surface type in the FLXUNET2015 dataset, with a total of 212 station-years of data. The specific observation variables include: net radiation R n , soil heat flux G, latent heat flux λET; micro-meteorological observation data include: air temperature, air pressure P a , soil volume moisture content; LAI data can be obtained by continuous field observation data or remote sensing product data:

[0061] Furthermore, in step 2, when calibrating the relevant parameters according to the actual measured latent heat flux data of the site, the calibration method is a genetic algorithm, and the calibration goal is to minimize the objective function. The objective function f is:

[0062] f=(R 2 -1) 2+(k-1) 2 (1)

[0063] Among them, R 2 is the coefficient of determination, and k is the slope of the fitting curve.

[0064]

[0065]

[0066] Among them, λET sim，i is the ith simulated value of latent heat flux, λET obs，i is the ith observed value of latent heat flux, N is the number of samples, i is the ith sample, is the average simulated value of the latent heat flux of N samples, is the average observed value of the latent heat flux of N samples.

[0067] The latent heat flux is simulated using the following formula:

[0068]

[0069] Among them, λET sim is the latent heat flux (W m -2 ), Δ is the slope of the saturated water vapor pressure versus temperature curve (kPa K -1 );R n is the net radiation (W m -2 ); G is soil heat flux (W m -2 );ρ a is the air density, which is 1.03 kg m at room temperature. -3 ; C P is the specific heat of dry air, take 1013 J kg -1 K -1 ; D is the saturated vapor pressure difference VPD; is the effective aerodynamic drag (sm -1 ); is the effective surface resistance (sm -1 ); γ is the hygrometer constant (kPa K -1 );

[0070]

[0071] γ=0.665*10 -3 *P a (6)

[0072] Among them, T a is the air temperature (℃); P a is the atmospheric pressure (Pa).

[0073] Furthermore, the effective aerodynamic drag is calculated using the following formula:

[0074]

[0075] in, is the canopy aerodynamic drag (sm -1 ); is the soil aerodynamic resistance (sm -1 ); is the atmospheric aerodynamic drag (sm -1 ).

[0076] Furthermore, the canopy aerodynamic drag is calculated using the following formula:

[0077]

[0078] Among them, r b is the average boundary layer resistance, 50 s m -1 ; L eff is the effective leaf area index (m 2 m -2 ), can be estimated by the following formula:

[0079]

[0080] Where L is the ecosystem leaf area index (m 2 m -2 ).

[0081] Furthermore, the soil aerodynamic resistance and the atmospheric aerodynamic resistance are calculated using the following formula:

[0082]

[0083]

[0084] Among them, h c is the canopy height of the site (m), which is measured at the site; n is the eddy diffusion attenuation coefficient; K h is the canopy height turbulence attenuation coefficient; z0 is the momentum roughness length (m); d is the zero plane displacement height (m). The above variables are calculated using the following formula:

[0085]

[0086] K h =ku * (h c -d) (12)

[0087]

[0088] z0=0.13h c (14)

[0089] d=2 / 3h c (15)

[0090] Among them, u * is the friction wind speed (ms -1 ); k is the von Karman constant, which is 0.41; z is the reference height, which is measured at the site (m).

[0091] Furthermore, the effective surface resistance is calculated using the following formula:

[0092]

[0093] in, is the canopy surface resistance (sm -1 ); is the surface resistance (sm -1 ).

[0094] Furthermore, the canopy surface resistance is calculated using the following formula:

[0095]

[0096] Among them, r smin is the minimum leaf resistance (sm -1 ), obtained by calibration; F1(S) represents the effect of photosynthetically active radiation S; F2(D) represents the effect of saturated vapor pressure difference VPD; F3(T a ) represents the air temperature T a The above variables are calculated using the following formula:

[0097]

[0098]

[0099] R nc =R n (1-exp(-kL))(20)

[0100] F2(D r ))=1-gD(21)

[0101] F3(T a )=1-0.0016(298-T a ) 2 (twenty two)

[0102] Among them, r smax is the maximum leaf resistance, which is 5000s m-1 ; R nc represents the net radiation received by the canopy (W m -2 ); k is the extinction coefficient, which is 0.7 for deciduous broad-leaved forest ecosystems; g is an empirical parameter, which is the reciprocal of the 99th percentile VPD.

[0103] Furthermore, the surface resistance of the ground is calculated using the following formula:

[0104]

[0105] in, is the soil surface resistance; The leaf area index is the surface resistance of litter. The leaf area index reflects the seasonal dynamic changes of vegetation leaves from growth and development to littering within a year, so that the accumulation of litter on the surface can be calculated, which is reflected as litter coverage. Since the accumulation of litter directly affects the water vapor transmission process between the surface and the atmosphere, the litter coverage can be used to reflect the degree of obstruction of litter to water vapor transport. Different maximum surface resistances of litter can reflect the maximum obstruction of litter of different tree species to water vapor transport. The combination of the two can reflect the obstruction of water vapor transport to the seasonal dynamic changes of litter of various tree species.

[0106] The above variables are calculated using the following formula:

[0107]

[0108]

[0109]

[0110]

[0111] in, is the minimum soil surface resistance (sm -1 ), obtained by calibration; f(θ) is the effect of soil water θ; θ f is the field water holding capacity, obtained by actual measurement; is the maximum litter surface resistance (sm -1 ), obtained by calibration; C lit is the litter cover, and its annual variation pattern is as follows Figure 2 As shown, it varies between 0 and 1; L max is the maximum leaf area index (m 2 m -2 ).

[0112] Furthermore, the surface resistance of the ground is calculated using the formula The minimum soil surface resistance and maximum litter surface resistance All are obtained by rate determination. 100s m -1 ; 500s m -1 . The annual change pattern is as follows Figure 3 As shown, in the range of 0 to 300 s m -1 Changes between. The annual change pattern is as follows Figure 4 As shown, in 0-600s m -1 Changes between.

[0113] It should be understood that parts not elaborated in detail in this specification belong to the prior art.

[0114] It should be understood that the above description of the preferred embodiment is relatively detailed, and it cannot be considered as limiting the scope of protection of the patent of the present invention. It is not necessary and impossible to list all the embodiments here. Under the enlightenment of the present invention, ordinary technicians in this field can also make substitutions or modifications without departing from the scope of protection of the claims of the present invention, which all fall within the scope of protection of the present invention. The scope of protection of the present invention shall be based on the attached claims.

Claims

1. A method for calculating forest surface resistance, characterized in that: The following steps are involved: Step 1: Collect and process flux observation data, micrometeorological observation data and leaf area index LAI data of flux stations; Step 2: calibrate the minimum leaf resistance, the minimum soil surface resistance, and the maximum litter surface resistance based on the latent heat flux data measured at the flux site; Step 3: Calculate the ground surface resistance based on the minimum leaf surface resistance, minimum soil surface resistance, and maximum litter surface resistance determined in step 2; The calculation of the ground surface resistance in step 3 is carried out using the following formula: in, is the soil surface resistance; is the surface resistance of litter, in, is the ground surface resistance, is the minimum soil surface resistance, obtained by calibration; f(θ) is the effect of soil water θ; θ f is the field water holding capacity, obtained by actual measurement; is the maximum litter surface resistance, obtained by calibration; C lit is litter cover; L max is the maximum leaf area index, and L is the ecosystem leaf area index LAI.

2. A method for calculating forest floor surface resistance according to claim 1, characterized in that: The flux observation data of the flux site in step 1 include: net radiation, soil heat flux, and latent heat flux; Micrometeorological observation data include: air temperature, air pressure, soil volume moisture content; Leaf area index LAI data uses field continuous observation data or remote sensing product data.

3. The method for calculating forest floor surface resistance according to claim 1, characterized in that: In step 2, the minimum soil surface resistance and the maximum litter surface resistance are obtained by using a genetic algorithm. The calibration goal is to minimize the objective function. The objective function f is: f=(R 2 -1) 2 +(k-1) 2 Among them, R 2 is the coefficient of determination, and k is the slope of the fitting curve.

4. A method for calculating forest floor surface resistance according to claim 3, characterized in that: Among them, λET sim，i is the ith simulated value of latent heat flux, λET obs，i is the ith observed value of latent heat flux, N is the number of samples, i is the ith sample number, is the average simulated value of the latent heat flux of N samples, is the average observed value of latent heat flux of N samples; The simulated value of latent heat flux is calculated using the following formula: Among them, λET sim is the latent heat flux, Δ is the slope of the saturated water vapor pressure and temperature curve; R n is the net radiation; G is the soil heat flux; ρ a is the air density; C P is the specific heat of dry air; D is the saturated water vapor pressure difference VPD; is the effective aerodynamic drag; is the effective surface resistance; γ is the hygrometer constant.

5. A method for calculating forest floor surface resistance according to claim 4, characterized in that: The effective aerodynamic drag for: Effective surface resistance for: in, is the canopy aerodynamic drag, is the soil aerodynamic resistance, is the atmospheric aerodynamic drag, is the canopy surface resistance, is the ground surface resistance.

6. A method for calculating forest floor surface resistance according to claim 5, characterized in that: Canopy aerodynamic drag for: Soil aerodynamic resistance and atmospheric aerodynamic drag They are: Among them, r b is the average boundary layer resistance; L eff is the effective leaf area index, h c is the canopy height of the site, which is measured at the site; n is the eddy diffusion attenuation coefficient; K h is the turbulence attenuation coefficient at canopy height; z0 is the momentum roughness length; d is the zero plane displacement height, u * is the friction wind speed; k is the von Karman constant; z is the reference height, measured at the site; Canopy surface resistance for: Among them, r smin is the minimum leaf resistance (sm -1 ), obtained by calibration; F1(S) represents the effect of photosynthetically active radiation S; F2(D) represents the effect of saturated vapor pressure difference VPD; F3(T a ) represents the air temperature T a effect.

7. A forest surface resistance calculation system, characterized in that: include: Data acquisition module: It is used to collect and process flux observation data, micro-meteorological observation data and leaf area index LAI data of flux stations; Parameter calibration module, which is used to calibrate the minimum leaf resistance, the minimum soil surface resistance, and the maximum litter surface resistance according to the latent heat flux data measured at the flux site; A ground surface resistance calculation module, which is used to calculate the ground surface resistance based on the calibrated minimum leaf resistance, minimum soil surface resistance, and maximum litter surface resistance; The forest floor surface resistance calculation system is used to execute the steps in the forest floor surface resistance calculation method described in any one of claims 1-6.

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