JP2005052045A - System for quantitatively evaluating environmental influence of plant - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a system for quantitatively evaluating environmental influence of plants based on an exchange process of emission, energy, water and carbon dioxide in a soil-plant-air circulation system. <P>SOLUTION: This system for quantitatively evaluating the environmental influence of plants comprises the followings: a tree crown structure data acquisition means 10 observing a predetermined range of an evaluation area where plants grow by a laser beam cutting method to obtain a three-dimensional structure of a plant community in the evaluation area as unidimensional tree crown structure data; and an evaluation means 20 evaluating, in time series, environmental influences of plants at the evaluation area caused from physiological and biochemical activities based on the unidimensional tree crown structure data and geographic data obtained via a geographic information system. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

  The present invention relates to a quantitative evaluation system for the effects of plants on the environment.

  Temporal and spatial changes in plant communities in the evaluation area not only affect water and heat movements in the evaluation area, but also affect the weather and atmospheric environment in the surrounding area. Therefore, in order to evaluate the environmental changes in the evaluation area, a number of evaluation systems that take into account the plant communities in the evaluation area have been developed. Since such an evaluation system requires a large amount of information such as plant communities and weather data regarding the evaluation area, human and material investment is indispensable to collect the information. For example, in order to evaluate future changes in the environment due to changes in land use due to forest development or changes in water and heat transport processes due to forest management, it is necessary to collect observation data. It requires a great deal of time, labor, and physical investment and is inefficient. In light of this situation, various methods for measuring canopy and weather have been developed and used to satisfy information requirements.

  The canopy structure measurement method is a method of measuring the crown formed by leaves, branches, etc., and expressing the information as numerical data. Information on the surface crown structure includes a leaf area index (LAI), a cross-sectional area index (BAI), a leaf inclination angle, and vertical distribution of each. For example, LAI is a non-destructive measurement method using a canopy structure measuring device such as LAI-2000 (Canopy Analyzer (LI-cor)), a litter trap method for determining leaf area from litterfall, There is a method of cutting the area and measuring the area destructively. Further, the information on the inclination angle of the leaf can be obtained by measuring each leaf one by one using a clinometer.

  Numerous numerical models have been developed to evaluate the water and energy exchange processes that occur in plant communities, and studies on the relationship between these processes and the canopy structure are being conducted. Such numerical models are classified into two types depending on how the crown is handled. As shown in FIG. 1A, one numerical model is a big-leaf type model that handles a tree crown as one leaf. As another model, as shown in FIG. 1B, there is a multi-layer model that considers the difference in the spatial structure of the tree crown and evaluates the influence of the structure on various processes in detail.

  Even with these conventional evaluation methods, it is possible to evaluate the influence of the physiological and biochemical activities of plants on the environment of the evaluation area.

In addition, a thermal environment prediction method that can reproduce the design of a building, a tree, and the like and predict the surface temperature is also known (Patent Document 1). In this prediction method, spatial components are formed in a three-dimensional space, the spatial components are cut for heights at predetermined intervals, the coordinates of the generated plane graphic are obtained, and the plane graphic is converted into a predetermined mesh. In each of the meshes, site-specific information is given, a heat balance calculation is performed for each mesh, a surface temperature is calculated, and a thermal environment evaluation index is calculated based on the surface temperature. Even if this method is used, it is thought that the influence which the plant in the evaluation area of the fixed range where the plant has grown has on the environment can be evaluated.
JP 2003-99697 A

  However, when the litter trap method is used for measuring the canopy structure, the litterfall has a large spatiality, so that a large number of litter traps are installed and observation is required for a long time. Furthermore, this method has a big problem that information other than leaf quantity and area cannot be obtained. In addition, although a measuring apparatus such as LAI-2000 is simple, it cannot obtain tree crown distance information and is expensive, resulting in an increase in cost. The method of cutting leaves from the tree crown damages the environment and makes it impossible to continuously measure the same evaluation area. Since the measurement of the leaf inclination angle using the clinometer measures each leaf, there is a concern that it is not labor-saving and may cause individual differences depending on the measurer.

  Among the numerical models, the big-leaf type model is simple, but some of the parameters used in the model are simply linearized of complex non-linear natural phenomena, so it can be applied to various weather environments. There is a problem. In addition, this method has to acquire detailed micrometeorological data of the forest in the target area in time series, and for that purpose, a series of operations such as setting up observation towers and observation facilities is necessary. In addition, the multi-layer model has many parameters, although it fully considers non-linear natural phenomena. In particular, some parameters are given empirically.

  On the other hand, the method of Patent Document 1 does not consider the evapotranspiration process from the surface of the plant, and is not appropriate for evaluating the influence of the plant on the environment. That is, the thermal environment basically changes depending on temperature and humidity, and the influence of plants growing in the evaluation area cannot be ignored for accurate prediction of the thermal environment. In particular, transpiration from plants affects the temperature and humidity of the atmosphere, thereby changing the thermal environment. Since this method predicts the thermal environment with the main sleep being to reproduce the design of buildings and trees, it does not consider the physiological and biochemical activities of plants. Moreover, this method grasps the three-dimensional structure of the evaluation area, and is not suitable for future prediction.

  Therefore, the target area of the evaluation area where the forest is growing is targeted, and the actual condition of water and heat circulation in the evaluation area is clarified through long-term continuous monitoring. It is necessary to develop a system that detects changes in the hydrological environment accompanying changes in the individual environmental spaces that make up the environment, and evaluates the impact.

  An object of the present invention is to provide a system for evaluating the environmental impact of vegetation based on the exchange process of radiation, energy, water and carbon dioxide in the soil-plant-atmosphere circulation system.

The quantitative evaluation system of the influence of the plant on the environment of the present invention observes a certain range of evaluation area where the plant is growing by laser light cutting, and the three-dimensional structure of the plant community in the evaluation area is one-dimensional crown. Canopy structure data acquisition means obtained as structure data;
An evaluation means for evaluating, in a time series, the influence of the physiological and biochemical activities of plants on the environment of the evaluation area from the one-dimensional crown structure data and the environmental information of the evaluation area obtained by a geographic information system; It is characterized by having.

  The canopy structure data acquisition means observes a certain range of evaluation area where the plant is growing by laser beam cutting, and obtains a three-dimensional canopy structure of the evaluation area as one-dimensional canopy structure data. According to the laser beam cutting method, it is possible to measure the evaluation area in a non-destructive manner and acquire a large number of tree crown information (leaf area index, leaf inclination angle, leaf vertical distribution, etc.) in a short time. The inventors have previously proposed a laser beam cutting method for obtaining a three-dimensional structure of an evaluation area as one-dimensional crown structure data (Japanese Patent Application No. 2001-349857).

  As shown in FIG. 2, the canopy structure data acquisition means includes, for example, a laser unit capable of selectively emitting either a red laser beam having a wavelength of 685 nm or a near infrared laser beam having a wavelength of 830 nm, and a reflection from a measurement object. It consists of a CCD camera that can capture the image of the light (reflection brightness) and a control device such as a general-purpose personal computer that stores the image data captured by the CCD camera and controls the operation of the laser unit and the CCD camera. obtain.

  In addition, this evaluation system uses the one-dimensional canopy structure data obtained by such a canopy structure data acquisition means and the environmental information of the evaluation area obtained by the Geographic Information System (GIS) to obtain the physiological and biochemistry of the plant. The impact of social activities on the environment in the assessment area. The geographical information of the evaluation area obtained by GIS is based on what is marketed or maintained by the local government. As specific information to be databased, as shown in FIG. 3, land use information (for example, farmland, city, forest, etc.) indicating the surface condition of the evaluation area, soil type, geology, topography, etc. There are geographic information such as soil information and weather data such as rainfall, wind speed, temperature, humidity, and solar radiation.

  As shown in FIG. 4, the numerical model is a one-dimensional multilayer model that evaluates heat, water vapor, and carbon dioxide exchange between soil, vegetation, and air. Each process can be evaluated by combining the micrometeorology module with the physiological / biochemical module. Specifically, the micrometeorology module is composed of a model relating to energy balance on the leaf surface and soil surface, microclimate change based on turbulent diffusion and radiation balance. The physiological / biochemical module is composed of a conductance model, a model related to transpiration and photosynthesis.

  The numerical model uses these one-dimensional crown structure data and GIS information to assess the impact of plants on the radiation, energy, water and carbon dioxide exchange processes in the soil-plant-atmosphere circulation. Details of the numerical model are described below.

"Micrometeorological model"
Momentum, heat, water vapor, carbon dioxide and the like exchanged between individual leaves and the atmosphere in the community are transported in the vertical direction by turbulent flow and exchanged with the atmosphere above the community. At this time, the average distribution of wind speed, temperature, etc. within the community is determined by the balance between the intensity of the sink / source by the leaves and the transport efficiency by the turbulent flow. When air masses in the forest directly enter the forest, the wind is weakened immediately in the leafy crown, but gradually decreases in the foliage. That is, the average wind speed in the community varies depending on the size of the leaf area density (A) and its distribution. This phenomenon can be expressed by the following second moment balance equation. When the field is steady and horizontally uniform, the equation of motion of the average wind speed (u (omitting overline)) can be written as:

Here, (omitted overline.) U'w' is flux momentum, c _d is the drag coefficient of the single leaf. The ground of the group fall becomes a sink (u′w ′ (overline is omitted) <0) that absorbs the momentum. Accordingly, momentum transport is downward (u′w ′ (overline omitted) <0) at any height within the community. The transport of momentum into and out of the community by turbulent flow determines the distribution of scalars (temperature, humidity, etc.) in combination with sensible heat and water vapor transport to the leaf surface. This process is expressed as Equation 2.

x is a scalar, and S _x is a scalar source (storage) caused by the gradient between the leaf surface and the atmosphere in the community.

  When the air mass on the community directly enters the community, the low-temperature and low-humidity air outside the community is carried into the community through the high-temperature and high-humidity canopy, contrary to the local gradient of average temperature and average humidity. Directional flux is generated. The flux (w′x ′ (overline is omitted)) is expressed as Equation 3.

  Here, the first term on the right side is a shear generation term, the second term is a diffusion term, the third term is a redistribution term due to pressure, and the fourth term is a sink / source term. In the contact boundary layer above the community, the shear stress does not change much in the height direction compared to the average wind speed. For this reason, the contribution of the diffusion term in the above equation is considered to be not large. However, in the community, the momentum of the wind is strongly absorbed in the upper part of the community, and the magnitude of the shear stress decreases rapidly with the depth from the upper part of the community. As a result of adding the effect of turbulent transport, shear stress is transported downward from the upper part of the community.

  Since Equation 3 expresses the effect of momentum transport by direct intrusion of an air mass, when Equation 1 and Equation 3 are combined, the average wind speed distribution is calculated. Similarly, by using Equations 2 and 3, a distribution of scalar components can be obtained. The third-order closure model is composed of 22 simultaneous equations, and 22 unknowns are approximated by the central difference method. For details on the third-order closure model, see Meyers and Paw (1986, 1987).

"Radiation transfer in the community"
The solar radiation energy incident on the upper end of the community is blocked by the leaves and branches in the community, and becomes weaker as it enters the lower layer through the processes of absorption, reflection, and transmission. Plant leaves do not absorb all the components of sunlight, but absorb well the wavelength (PAR) that is effective for photosynthesis, and hardly absorb the near-infrared region (NIR) of longer wavelengths. In the solar radiation that passes through the tree canopy, the transmission process differs depending on the scattered light and direct light. FIG. 5 is a schematic diagram of the process. The direct solar radiation amount (Q _b ) flowing into the height z from FIG. 5 and the scattered light (Q _d ) reflected from the height z + 1 are expressed by Equations 4 and 5.

Here, τ is the transmittance, ρ is the reflectance, f _b is the rate of direct light, I _b is the probability of passing without being scattered, and I _d is the probability of passing the scattered light through the leaf layer. The subscripts d in Equations 4 and 5 represent scattered light, and b represents direct light. Also, ↓ indicates the downward direction of the solar radiation component, and ↑ indicates the upward direction.

  The probability that the direct solar radiation incident from the upper end of the community is not scattered and is transmitted is expressed by Equation 6, and the probability that the scattered component of solar radiation passes through the tree crown is expressed by Equation 7.

Here, H is the solar altitude, L is the leaf area index, G is the ratio of the leaf area in the leaf layer to the projected area on the plane perpendicular to the incident direction of sunlight, and Ω is the coefficient representing the leaf mass. . G is given by averaging the same function G _l (α, β, H) determined from the inclination angle α and azimuth angle β of the individual leaves over the entire community. If the distribution density function of the inclination angle of a single leaf is g ((α)), G is expressed by Equation 8. The single leaf function G ₁ is expressed by _Equation 9.

  The above equations hold for solar radiation over the entire short and long wave, but since PAR is easily absorbed by the leaves, the reflectance and transmittance values of the leaves need to be given separately for each wavelength.

Similarly, long wave radiation (Q _l ) is also approximated using Equations 10 and 11.

Here, T _s is the leaf surface temperature, ε _l is the injection rate, and σ is the Stefan-Boltzmann constant. For details of the radiation balance model, see Norman (1979).

"Single-leaf energy balance"
The radiant energy absorbed by individual leaves is distributed to sensible heat, latent heat of evapotranspiration, long-wave re-radiation, and tree heat storage. The ratio of energy distribution to each of these changes depending on the degree of opening and closing of the pores in addition to the weather conditions such as wind speed, temperature and humidity around the leaves. The energy balance of a single leaf is expressed by Equation 12.

In this equation, R _n is the net radiation amount, C _p is the constant pressure specific heat of air, ρ _a is the air density, T _a is the atmospheric temperature, L _v is the latent heat of water evaporation, and g _b and g _s are respectively The leaf boundary layer conductance and stomatal conductance, q _s (T _s ) and q _a are the specific humidity on the leaf surface and the specific humidity of the atmosphere, respectively. Here, R _n is given by the balance of short wave and long wave radiation calculated from the radiation balance model described above.

Each term on the right side of the above formula represents, in order, the long wave radiant energy, sensible heat and latent heat exchange emitted by the leaves. The meteorological data and conductance values are input to the equation to determine the leaf surface temperature, and the sensible heat and latent heat are calculated using the temperature. The leaf surface temperature T _s is given as a solution of a quadratic equation proposed by Paw (1987). This energy balance is interrelated with the photosynthesis model described later. Specifically, the leaf surface temperature obtained from the energy balance equation is input to the photosynthesis model, and photosynthesis, respiration rate, stomatal conductance, and the like are calculated. The calculated pore conductance is also used as input data in the energy balance equation. These processes can be solved numerically.

  The block evaporation process due to individual leaves during rainfall is calculated using Tanaka's (2002) model.

"Single leaf photosynthesis model"
The biochemical environmental reaction of photosynthesis in single leaves is calculated by Equation 13 using the model of Farquhar et al. (1980).

Here, _An is the carbon dioxide assimilation rate, V _c is the carboxylation reaction rate, V _o is the oxygen assimilation rate, and R _d is the respiration rate. In this model, the carbon dioxide assimilation rate per unit leaf area depends on Rubisco oxygen-limited assimilation rate (J _R ) and photochemical electron transfer activity-controlled assimilation rate (J _E ) according to the carbon dioxide partial pressure in the leaf. Given as a minimum.

  When the assimilation rate by the Rubisco oxygen rate control becomes the minimum value, it is given by equation (14).

Where V _cmax is the maximum rate of carboxylation reaction, C _i is the carbon dioxide concentration in the leaf, O _i is the O ₂ concentration in the leaf, Γ is the compensation point for the carbon dioxide concentration in the leaf, and K _c and _Ko are respectively Michaelis constant for carbon dioxide and oxygen.

  When the minimum value is the photochemical electron transfer activity-controlled assimilation rate indicating the dependence of photosynthesis on PAR, it is given by Equation 15.

  Here, J is the saturation rate of electron transfer, and is given as a solution of a quadratic equation.

Plants exchange not only the surrounding atmosphere and carbon dioxide but also H ₂ O through the pores. The relationship between the carbon dioxide assimilation rate in the leaves and stomatal conductance (g _s ) is expressed by Equation 16 (Collatz et. Al, 1991).

Partial pressure of carbon dioxide where C _s is the leaf surface, rh is the relative humidity, m and g _o is a coefficient. If the model is known for the PAR absorbed by the leaves, atmospheric and leaf temperature, atmospheric carbon dioxide partial pressure, water vapor pressure, and leaf boundary layer conductance, then A _n , g _s , Variables of carbon dioxide partial pressure, water vapor pressure, and carbon dioxide partial pressure in leaves are given by simultaneous equations. Since all these variables have a non-linear relationship with each other, the solution cannot be obtained analytically, but is obtained by repeated numerical calculations.

"Soil temperature, moisture transfer"
The movement of heat in the soil is mainly carried out by conduction. In addition, it is transported with the movement of water and gas. Soil is composed of soil particles, water, and gas, and the heat transfer is greatly influenced by the mixed state of these three phases. The heat transfer is given by equation (17).

Here, C _s is the volumetric heat capacity of the soil, λ _s is the thermal conductivity, and Q _H is the heat storage amount. The temperature distribution in the soil changes over time, but it is driven by the energy given to the ground surface. Therefore, the balance of radiation, sensible heat, and latent heat flux on the ground surface is given as a boundary condition.

  The distribution of soil moisture whose movement is determined by the difference in water potential is given by Equation 18.

K _s is the saturated hydraulic conductivity, g is the acceleration of gravity, and U is the absorption from the root of the plant. Soil moisture varies with inflowing rainfall, evaporation from the ground, transpiration and runoff. Rainfall and ground evaporation are given as boundary conditions.

  Table 1 shows a comparison between this numerical model and other models. In Table 1, “HC” is Higher-Order Closure Model (Meyers and Paw U, 1986), “2nd-C” is Second-Order Closure Model (Wilson and Show, 1977), and “N” is Norman (1979). ) Model “single scale up” indicates scale up from single leaves to canopy, “gradient” moves due to gradient (potential) difference, “x” is not considered, and “◯” is considered.

"Effect of evaluation system"
The laser beam cutting method is environmentally friendly because it measures the canopy structure in a non-destructive manner, and the leaf area index, leaf area density, cross-sectional area, leaf / branch inclination angle and their distance information can be obtained in a short time. can get.

  By using existing geographic information and meteorological data (municipal agency, meteorological agency mesh data), observation work can be reduced, and high economic efficiency (reduction of observation facility costs and equipment purchase costs) is demonstrated.

  When the forest structure is changed by forest management such as logging, it is possible to predict how various processes such as water in the forest and heat transport will change by a numerical model. It is also possible to predict the effects of forest growth and changes in the atmospheric environment on various processes. Further, since the numerical model expresses in detail various processes that occur on the ground surface, it can be used as a surface process evaluation model (Land Surface Model) in GCM (Global Circulation Model) and the like.

  The data obtained by the evaluation system can be provided to the government and forest owners as forest management information by constructing a database in cooperation with GIS, etc., and contribute to the effective utilization of forest resources.

Evaluation process
As shown in FIG. 6, this evaluation system includes a crown structure data acquisition unit 10, a personal computer 20 as an evaluation unit that performs evaluation using a numerical model, and a geographic information system 30. The canopy structure data acquisition means 10 scans the laser unit 11 with red laser light having a wavelength of 685 nm and near-infrared laser light having a wavelength of 830 nm, and the CCD camera 12 captures the reflected luminance reflected from the measurement object. The image data is stored in the personal computer 20. The personal computer 20 analyzes the image data acquired by the CCD camera 12, and outputs tree structure data.

  The evaluation by the numerical model is performed according to the flowchart shown in FIG. First, in step S10, the analyzed one-dimensional crown structure data and the geographic information and weather data of the evaluation area constructed by the GIS are input. In step S20, the influence of the physiological / biochemical activity of the plant on the environment in the evaluation area is evaluated in time series from the one-dimensional crown structure data, geographic information, and meteorological data. At this time, first, in step S21, the radiation balance, surface temperature, photosynthesis, energy balance, soil surface energy balance, soil temperature and moisture movement are calculated. In step S22, profiles such as wind speed, temperature, humidity, and carbon dioxide are calculated. In step S23, energy and momentum flux profiles are calculated. Since these steps S21 to S23 are related to each other, calculation is repeated until a certain condition is satisfied. In step S30, the calculation result is output.

To explain the calculation process more specifically,
(1) Read weather data (temperature, humidity, wind speed, solar radiation, PAR, precipitation, carbon dioxide concentration) and geographic information. (2) Calculate LAI vertical distribution.
(3) Calculate solar altitude and radiation (PAR, NIR) profiles at the canopy.
(4) The initial value wind speed component profile is calculated.
(5) Estimate stomatal conductance.
(6) Estimate the long wave profile.
(7) After calculating the surface temperature, calculate photosynthesis, respiration rate, and stomatal conductance.
(8) Calculate the energy balance and surface temperature, soil moisture and temperature distribution, and soil respiration on the soil surface.
(9) Calculate the momentum, wind speed component, and scalar component profiles.
(10) The steps (7) to (9) are repeated until the convergence condition is satisfied. As a convergence condition, the energy flux in the uppermost layer of the tree crown was set to 0.5 Wm ⁻² or less.
(11) Returning to the process of (1) again, the next time step is calculated.

  We applied this evaluation system to a small watershed in Toyota Foresta Hills, a satoyama forest dominated by deciduous broad-leaved trees, and verified the usefulness of this evaluation system. The inventors have established a test basin in Toyota Foresta Hills and have conducted meteorological and hydrological observations since 2000. Specifically, a micrometeorological observation tower was constructed in this evaluation area, and meteorological instruments were installed at multiple altitudes to conduct micrometeorological observations inside and outside the forest. The amount of fluctuation in wind, moisture, heat and carbon dioxide is measured using an ultrasonic wind speed thermometer (DAT-600, Kaijo) and an open-perspective water / carbon dioxide variometer (LI-7500, Li-Cor). Variation was measured at 20 Hz. In this example, analysis was performed using data from May 2003.

  The above-ground part, which is the exchange for various processes, was divided into 20 layers and the calculation was performed. Furthermore, in order to consider the influence of the exchange process performed at the tree crown on the atmospheric boundary layer, the atmospheric layer was set to twice the tree height (12 m), and all 60 layers (36 m) were targeted for calculation. The number of layers can be freely changed according to the purpose. The parameters used for the calculation are shown in Table 2.

"Calculation result"
FIG. 8 shows the crown structure of Toyota Foresta Hills obtained by the laser beam cutting method. Leaves, branches, trunks, etc. are concentrated between 5 m and 10 m from the ground, suggesting that the height is an exchange place for water, heat and CO ₂ .

  Fig. 9 shows the measured values of the daily change in energy balance at Toyota Foresta Hills and the results calculated by this evaluation system. In FIG. 9, (A) is the amount of pure radiation, (B) is the latent heat, (C) is the sensible heat, and (D) is the flux of carbon dioxide. Here, the measured values of sensible heat, latent heat, and carbon dioxide flux are results obtained using the eddy correlation method. The negative flux of carbon dioxide means that trees absorb carbon dioxide. A positive value represents the release of carbon dioxide by respiration.

The spatial distribution of the energy flux over time is shown in FIG. (A) is the amount of pure radiation, (B) is the latent heat, and (C) is the sensible heat. All units are Wm- ² .

  In addition, FIG. 11 shows calculated values of the amount of moisture adhering to the canopy and the amount of blocked evaporation during rain.

FIG. 12 shows the time-space distribution of the amount of water adhering to the crown and the carbon dioxide flux during rainfall. (A) Rainfall (mm), (B) Water content on the crown (mm), (C) Drying rate on back of leaf, (D) Carbon dioxide flux (μmol m ^-2 s ^-1 ).

  FIG. 13 shows a comparison between the calculated value of the evaluation system on the soil surface and the actual measurement site. In FIG. 9 to FIG. 13, the solid line is the calculated value, and the round point is the measured value.

"Discussion"
Although the latent heat predicted by the evaluation system tended to be overestimated from the actual measurement value and the CO ₂ flux was underestimated, the calculated value showed a high correlation with the actual measurement value (FIG. 9). Many trees are mixed in the forest basin to which this evaluation system is applied, and the influence on various processes in the basin varies depending on the trees. However, the evaluation system calculated using parameters obtained from some dominant species in the test basin. That is, the parameter does not sufficiently consider the degree of influence of individual trees on various processes, and is a value averaged by some trees. The fact that the calculated values agree well with the actual measured values even though they were calculated using such parameters is undoubtedly the result of the evaluation system considering the spatial structure of the stand from the validity of parameterization. As shown in FIG. 8, in the test basin, leaves, branches and the like are concentrated at a height of 5 to 10 m. The evaluation system expressed that the absorption of radiant energy and the exchange of latent heat and sensible heat flux were mainly performed between 5 and 10 m due to the influence of such stand structure (FIG. 10). Furthermore, the height is also the main place for CO ₂ exchange between the atmosphere and the foliage (FIG. 12D). As the amount of leaves increases, the amount of energy absorbed is increased, but at the same time, the amount of rainfall that is cut off increases. Therefore, the cutoff evaporation amount increases and the microclimate environment of the tree crown changes. This change eventually affects the processes at the crown. For example, as the cutoff evaporation amount increases, the leaf surface temperature decreases. A decrease in temperature causes a decrease in respiration and a decrease in saturation between the air and the leaf surface, giving an environment suitable for opening of the pores. As a result, the amount of CO ₂ to be fixed increases. After the end of the rainfall, the amount of cut-off evaporation increases due to the increase of the inflowing energy, and the fluctuation amount of the main water vapor gradually becomes a pattern in which the amount of transpiration gradually dominates over time (FIG. 11). Thus, various processes in various climatic environments can be simulated well by the evaluation system.

Thus, the evaluation system was able to evaluate the environmental impact of the exchange process of radiation, energy, water and carbon dioxide in the soil-plant-atmosphere circulation. However, in the prediction of the evaluation system for some processes, there was a difference from the actual measurement location. One example is shown in FIG. Soil surface temperature is used as a boundary condition for various processes in soil and forest. Therefore, the error in the predicted value directly leads to errors in various processes. For example, a high soil surface temperature results in a high gradient with the soil temperature, causing high ground evaporation or sensible heat. Such energy distribution on the soil surface affects the energy balance of the entire basin. There are various causes for the error in the predicted value, but the influence of the parameters used in the evaluation system is particularly large. Therefore, sensitivity analysis of the calculated values and parameters by the evaluation system was performed. As a result, the resistance coefficient calculation Leaf evaluation system, it was revealed that relies heavily against C _d. The coefficient C _d represents the relationship between the amount of leaves and the microclimate environment in the stand. Changes in leaf mass affect stand microclimate environments, resulting in changes in processes. It is clear from the influence of the coefficient Cd on the processes that the processes in the basin largely depend on the stand structure. Therefore, it is suggested that when applying this evaluation system to other basins, information collection on the forest structure in the basin should be given the highest priority.

References
Collatz, GJ et al. (1991) Regulation of stomatal conductance and transpiration: a physiological model of canopy processes.Agri.For.Meteorol., 54, 107-136.
Farquhar, GD et al. (1980) A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species.Planta, 149, 78-90.
Meyers, TP and Paw U, KT (1987) Modeling the plant canopy micrometeorology with higher-order closure principles. Agr. For. Meteol., 41, 143-163.
Norman, JM (1979) Modeling the complete crop canopy. ASAE Mon. 249-277.
Paw U, KT (1987) Mathematical analysis of the operative temperature and energy budget.J. Therm. Biol., 12, 227-233.
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Pyles, RD, Weare, BC and Paw U, KT (2000) The UCD advanced canopy-atmosphere-soil algorithm: comparisons with observations from different climate and vegetation regimes.QJR Meteorol. Soc. 126, 2951-2980.
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In relation to a conventional numerical model, FIG. (A) is a schematic diagram of a single layer model method, and FIG. (B) is a schematic diagram of a multilayer model. It is a block diagram of the tree crown structure data acquisition means which concerns on this invention. It is a block diagram of the geographic information system which concerns on this invention. It is a schematic diagram of a numerical model. It is a schematic diagram of the radiation balance model which concerns on this invention. It is a block block diagram of this evaluation system. It is a process flowchart of the numerical model which is an evaluation means of this evaluation system. It is a computer screen figure which shows the crown structure of an evaluation area. It is a graph which shows the measured value of the daily change of the energy balance of an evaluation area, and the calculation result by this evaluation system. It is a screen figure of the computer which shows the spatial distribution of the energy flux by progress of time. It is a graph which shows the calculated value of the amount of adhesion | attachment water on a crown and the amount of interception evaporation at the time of rain. It is the screen figure of the computer which shows the time-space distribution of the moisture content on a crown and a carbon dioxide flux at the time of rainfall. It is a graph which shows the daily change of soil temperature.

Explanation of symbols

10 ... Tree crown structure data acquisition means 20 ... Evaluation means (personal computer)

Claims (6)

A canopy structure data acquisition means for observing an evaluation area of a certain range where a plant is growing by laser light cutting and obtaining a three-dimensional structure of a plant community in the evaluation area as one-dimensional canopy structure data;
An evaluation means for evaluating, in a time series, the influence of the physiological and biochemical activities of plants on the environment of the evaluation area from the one-dimensional crown structure data and the environmental information of the evaluation area obtained by a geographic information system; A system for quantitative evaluation of the effects of plants on the environment.   The quantitative evaluation system for the influence of a plant on the environment according to claim 1, wherein the one-dimensional tree crown structure data includes a leaf area index obtained for each layer divided in the height direction.   3. The quantitative evaluation system for the influence of plants on the environment according to claim 1, wherein the geographical information includes land use information and weather data.   4. The quantitative evaluation system for the influence of plants on the environment according to claim 3, wherein the geographical information includes soil information such as soil type, geology, and topography.   5. The quantitative evaluation system for the influence of plants on the environment according to claim 3, wherein the meteorological data comprises rainfall, wind speed, temperature, humidity and solar radiation in the evaluation area.   6. The quantitative evaluation system according to claim 1, wherein the evaluation means evaluates the fluctuation amount and balance of water, energy, and carbon dioxide.