An urban green space surface evapotranspiration partitioning method and system based on impedance parameters

Abstract

The present application relates to the field of urban green space evapotranspiration zoning, and particularly relates to a kind of urban green space surface evapotranspiration zoning method and system based on impedance parameter, realize the distinction of tree, shrub and lawn transpiration in urban green space.The present application first collects and pre-processes vegetation morphological parameter, meteorological data, crown surface temperature, soil heat flux, vegetation transpiration and eddy correlation flux data;Using back-penman-monteith formula and surface energy balance equation, the leaf boundary layer impedance and crown stomatal impedance of each vegetation type are calculated;Through the flux footprint model, the proportion of each vegetation type in the flux contribution source area is determined, and the total aerodynamic impedance and total stomatal impedance of the ground surface are back-calculated;According to the surface energy balance equation, the aerodynamic impedance of each vegetation is solved and fitted and corrected;Finally, the corrected impedance parameter is substituted into the Penman-Monteith model to calculate the transpiration of each vegetation.The method effectively overcomes the mismatching problem of single scale and community scale data, and improves the calculation accuracy of evapotranspiration zoning.

Description

Technical Field

[0001] This invention relates to the field of monitoring and analysis technology of urban green space evapotranspiration, specifically to a method and system for zoning urban green space surface evapotranspiration based on impedance parameters. Background Technology

[0002] Urban green spaces play a vital role in regulating microclimate, purifying air, and moderating the water cycle. Accurate estimation of urban green space evapotranspiration (ET) is crucial for urban water resource management and ecological environment regulation. ET typically consists of two main components: vegetation transpiration and soil evaporation. However, due to differences in canopy structure, stomatal characteristics, and leaf boundary layer characteristics among different vegetation types (such as trees, shrubs, and lawns), their evapotranspiration processes exhibit significant spatiotemporal heterogeneity. Furthermore, different observation methods suffer from scale differences. For example, data obtained using stem flow meters or micro-lysimeters at the single-plant scale primarily reflect evapotranspiration information for individual or local areas, while eddy covariance flux observation systems provide information covering the entire urban green space community scale. This mismatch in data scale leads to lower accuracy in integrating multi-scale data using traditional ET zoning methods.

[0003] Currently, existing studies both domestically and internationally primarily employ energy balance methods, eddy covariance flux techniques, and other direct or indirect measurement methods to estimate evapotranspiration (ET) or distinguish its components. However, these methods often struggle to simultaneously address computational errors caused by scale differences and the complex coupling issues between different vegetation types. Therefore, overcoming the scale differences between single-plant and community-scale observation data, and achieving precise differentiation of evapotranspiration components among different vegetation types in urban green spaces, has become a pressing technical challenge for current urban ecohydrological research and urban water resource management. Summary of the Invention

[0004] To overcome the problem of low accuracy in zoning urban green space surface evapotranspiration components caused by mismatch in multi-scale observation data, the above-mentioned objective of this application is achieved through the following technical solution:

[0005] Firstly, this application provides a method for zoning urban green space surface evapotranspiration based on impedance parameters, including:

[0006] A method for zoning urban green space surface evapotranspiration based on impedance parameters, characterized in that the method includes the following steps:

[0007] S1. Collect and process vegetation morphology parameters, meteorological data, vegetation canopy surface temperature data, soil heat flux data, vegetation transpiration data, and eddy covariance flux data of urban green spaces.

[0008] S2. Based on meteorological data, vegetation canopy surface temperature data, soil heat flux data, and vegetation transpiration data, vegetation leaf boundary layer impedance data and vegetation canopy stomatal impedance data are calculated by back-deriving the Penman-Monteith formula and the surface energy balance equation.

[0009] S3. Based on vegetation morphology parameters, obtain flux contribution source area information of eddy covariance flux observation tower, determine the proportion of trees, shrubs and lawns in the source area, and calculate the total aerodynamic impedance and total stomatal impedance of urban green space based on eddy covariance flux observation data, vegetation leaf boundary layer impedance and canopy stomatal impedance data.

[0010] S4. Based on meteorological data, vegetation canopy surface temperature data, soil heat flux data, vegetation transpiration data, and vegetation canopy stomatal impedance data, calculate vegetation aerodynamic impedance, and correct vegetation canopy stomatal impedance and vegetation aerodynamic impedance according to total surface stomatal impedance and total surface aerodynamic impedance.

[0011] S5. Based on the corrected stomatal impedance and aerodynamic impedance data of vegetation canopy, the transpiration of trees, shrubs and lawns is calculated according to the Penman-Monteith model to distinguish the components of surface evapotranspiration in urban green spaces.

[0012] By adopting the above technical solution, this application provides a method for urban green space surface evapotranspiration zoning based on impedance parameters. Traditional methods suffer from scale mismatch when processing single-plant-scale observation data such as stem flowmeters and community-scale flux data such as eddy covariance, and are difficult to effectively characterize the complex coupling relationships between different vegetation types, resulting in low accuracy of evapotranspiration zoning results. This application first collects and preprocesses vegetation morphology parameters, meteorological data, vegetation canopy surface temperature data, soil heat flux data, vegetation transpiration data, and eddy covariance flux observation data. Secondly, it uses the Penman-Monteith formula and the surface energy balance equation to calculate the evapotranspiration zoning results for different vegetation types. The process begins by determining the leaf boundary layer impedance and canopy stomatal impedance of different vegetation types (trees, shrubs, and lawns). Then, using a flux footprint model, the flux contribution source region at each time point is identified, and the area proportion of each vegetation type within the flux contribution source region is calculated. From this, the total surface aerodynamic impedance and total surface stomatal impedance of urban green spaces are derived. Furthermore, the aerodynamic impedance of each vegetation type is solved using the surface energy balance equation, and then fitted and corrected using the total surface aerodynamic impedance and total surface stomatal impedance of urban green spaces. Finally, the corrected impedance parameters are substituted into the Penman-Monteith model to calculate the transpiration of each vegetation type, thus achieving the zoning of surface evapotranspiration components in urban green spaces.

[0013] Optionally, S1 specifically includes:

[0014] Acquire vegetation morphology parameters in urban green spaces, including vegetation height, leaf area index, and vegetation canopy coverage.

[0015] Net radiation meters and temperature and humidity sensors were installed above the tree canopy, shrub canopy, and lawn to obtain net radiation data and temperature and humidity data for each vegetation type.

[0016] Infrared thermometers were installed above the tree canopy, shrub canopy, and lawn to obtain canopy surface temperature data for each vegetation type.

[0017] Soil heat flux plates were installed at soil depths below the tree canopy, shrub canopy, and lawn to obtain soil heat flux data below each vegetation type.

[0018] Representative trees, shrubs and lawns were selected, and vegetation transpiration data were obtained using stem flow meters and miniature lysimeters;

[0019] The overall water vapor flux data of urban green space, as well as the overall net radiation, temperature, humidity and wind speed data at the height of the observation tower, were collected using an eddy covariance flux monitoring system.

[0020] The measurement data were processed to determine the proportion of each vegetation type in the source area of ​​footprint flux contribution.

[0021] By adopting the above technical solution, this application discloses a method for multi-source data acquisition. Due to the significant spatial heterogeneity and vertical stratification of trees, shrubs, and lawns in urban green spaces, monitoring their water flux is quite difficult. This application first establishes a basic database by acquiring vegetation morphology parameters, then deploys instruments such as net radiation meters, temperature and humidity sensors, and infrared thermometers in various vegetation areas to acquire local-scale data. At the same time, stem flow meters and micro lysimeters are used to directly monitor the vegetation transpiration process. Finally, an eddy covariance system is used to acquire flux data at the overall scale. This achieves data connectivity from the individual tree to the community scale, and effectively solves the scale conversion problem caused by spatial heterogeneity through footprint analysis technology, providing reliable data support for improving the accuracy of urban green space evapotranspiration estimation.

[0022] Optionally, in S2, the boundary layer impedance of vegetation leaves is calculated as follows:

[0023]

[0024] In the formula, r b,t r b,sh and r b,g These are the leaf boundary layer impedances of trees, shrubs, and lawns, respectively; ρ is the air density; c p It is the specific heat capacity of air; T s,t T s,sh and T s,gThese are the canopy surface temperatures of trees, shrubs, and lawns, respectively; T a,t T a,sh and T a,g These are the air temperatures near the tree canopy, shrub canopy, and lawn, respectively; R n,t R n,sh and R n,g These are the net radiation of tree canopy, shrub canopy, and lawn, respectively; LE t LE sh and LE g These are the latent heat fluxes of tree canopy, shrub canopy, and lawn transpiration, respectively; G t G sh and G g These are the soil heat fluxes beneath trees, shrubs, and lawns, respectively.

[0025] The stomatal impedance of the vegetation canopy is calculated as follows:

[0026]

[0027] In the formula, r c,t r c,sh and r c,g These are the stomatal resistances of tree canopies, shrub canopies, and lawns, respectively; VPD t VPD sh and VPD g These represent the air saturated water vapor pressure difference near trees, shrubs, and lawns, respectively; Δ is the slope of the saturated water vapor pressure-temperature curve; and γ is the hygrometer constant.

[0028] By adopting the above technical solutions, this application improves the accuracy of calculating urban green space vegetation evapotranspiration and stomatal impedance of different vegetation types in urban green spaces. Since there are significant differences in the spatial distribution and structural characteristics of trees, shrubs, and lawns in urban green spaces, the physiological characteristics and environmental responses of different vegetation types also differ significantly. Traditional single empirical formulas often produce calculation errors. This application introduces heat transfer characteristic parameters such as air density (ρ) and specific heat capacity (cp), combined with the difference between the surface temperature of the vegetation canopy and the air temperature gradient, as well as energy balance components, to calculate the leaf boundary layer impedance of different vegetation types. Simultaneously, by establishing a stomatal impedance calculation framework based on water vapor pressure difference, and considering the physiological characteristics of trees (rc,t), shrubs (rc,sh), and lawns (rc,g), dynamic and accurate calculation of stomatal impedance is achieved, providing a scientific basis for accurately assessing the evapotranspiration process of urban green space vegetation.

[0029] Optional, in S3,

[0030] The total surface aerodynamic impedance of urban green spaces is determined as follows:

[0031]

[0032] In the formula, r a It is the total aerodynamic impedance of urban green space; T s It is the weighted average surface temperature of urban green spaces, T s =f t ×T s,t +f sh ×T s,sh +f g ×T s,g ;f t f sh and f g These represent the proportions of trees, shrubs, and lawns within the source area contributing to the footprint flux; G is the weighted average soil heat flux of urban green space, G = f t ×G t +f sh ×G sh +f g ×G g ;T atm It is an eddy covariance flux observation tower, used to measure air temperature at a certain altitude; R n 1 is the net radiation of urban green space measured by the net radiometer of the eddy covariance flux observation tower; LE is the latent heat flux measured by the eddy covariance flux observation tower.

[0033] The total surface stomatal impedance of urban green spaces is determined as follows:

[0034]

[0035] In the formula, r c It is the total surface porosity of urban green space; VPD is the air saturated water vapor pressure difference at the height of the eddy covariance flux observation instrument.

[0036] By adopting the above technical solution, this application achieves an accurate characterization of the overall transmission characteristics of complex green space systems. Since urban green spaces often contain multiple vegetation types such as trees, shrubs, and lawns, their contributions to the observed flux vary significantly. This application introduces the source region weights (ft, fsh, fg) of footprint flux contribution, and combines them with the weighted average surface temperature (Ts) and soil heat flux (G) to establish a calculation framework for the total aerodynamic impedance (ra) and total stomatal impedance (rc) of the surface at the eddy covariance observation scale, realizing an effective conversion from the single-plant scale to the community scale. This not only solves the problem of scale mismatch in observation data, but also accurately reflects the coupling effect of different vegetation types under complex underlying surface conditions.

[0037] Optionally, in S4, the aerodynamic impedance of vegetation is calculated as follows:

[0038] r c,t rc,sh and r c,g Substituting into the following formula, solve the following equations to obtain r. a,t r a,sh and r a,g :

[0039]

[0040] In the formula: r a,t r a,sh and r a,g These are the aerodynamic impedances of trees, shrubs, and lawns, respectively.

[0041] The stomatal impedance and aerodynamic impedance of vegetation canopy are corrected based on the total surface stomatal impedance and the total surface aerodynamic impedance, specifically as follows:

[0042]

[0043] In the formula, α1, α2, α3, β1, β2 and β3 are fitting parameters. The values ​​of fitting parameters α1, α2, α3, β1, β2 and β3 can be determined based on the total aerodynamic impedance and total stomatal impedance of urban green space, as well as the aerodynamic impedance and canopy stomatal impedance of trees, shrubs and lawns.

[0044] By adopting the above technical solution, this application establishes a multi-scale impedance correction method based on fitting parameters. Since trees, shrubs, and lawns in urban green spaces have different canopy heights and structural characteristics, and there are complex vegetation coupling effects in urban green spaces, directly extrapolating the impedance parameters at the single-tree scale to the community scale will produce large errors. This application solves for the aerodynamic impedance of trees (ra,t), shrubs (ra,sh), and lawns (ra,g) by coupling vegetation stomatal impedance (rc) and energy balance components, respectively, achieving independent characterization of the aerodynamic characteristics of different vegetation types. By establishing the fitting relationship between the total surface impedance and the impedance of various vegetation types, scale transformation and parameter optimization from local to global are achieved. This not only improves the accuracy of impedance parameters but also effectively coordinates data obtained from different observation methods, ensuring the reliability of the final evapotranspiration zoning results.

[0045] Optionally, in S5, the transpiration rates of trees, shrubs, and lawns are calculated based on the Penman-Monteith model, specifically as follows:

[0046]

[0047] In the formula, ET t It is the transpiration of trees, ET sh It's shrub transpiration, ET g It's the grass evaporating.

[0048] By adopting the above technical solution, this application achieves precise quantification of the transpiration process of different vegetation types in urban green spaces. Due to the significant differences in water transport characteristics among trees (ETt), shrubs (ETsh), and lawns (ETg) in urban green spaces, and the complex coupling relationships between them, traditional simplified calculation methods often fail to accurately reflect these differences. This application establishes a complete vegetation transpiration calculation system by integrating net radiation, saturated vapor pressure difference, meteorological parameters, and corrected impedance parameters, achieving precise zoning of urban green space evapotranspiration. This not only improves calculation accuracy but also dynamically reflects the response characteristics of different vegetation types to environmental changes, providing a scientific basis for refined management and water-saving irrigation of urban green spaces.

[0049] Secondly, this application provides an urban green space surface evapotranspiration zoning system based on impedance parameters, comprising:

[0050] The data acquisition module is used to collect and process vegetation morphology parameters, meteorological data, vegetation canopy surface temperature data, soil heat flux data, vegetation transpiration data, and eddy covariance flux data of urban green spaces.

[0051] The impedance calculation module is used to calculate the boundary layer impedance data of vegetation leaves and the stomatal impedance data of vegetation canopy based on meteorological data, vegetation canopy surface temperature data, soil heat flux data, and vegetation transpiration data, by back-deriving the Penman-Monteith formula and the surface energy balance equation.

[0052] The source region analysis module is used to obtain flux contribution source region information of eddy covariance flux observation tower based on vegetation morphology parameters, determine the proportion of trees, shrubs and lawns in the source region, and calculate the total aerodynamic impedance and total stomatal impedance of urban green space based on eddy covariance flux observation data, vegetation leaf boundary layer impedance and canopy stomatal impedance data.

[0053] The impedance correction module is used to calculate the vegetation aerodynamic impedance based on meteorological data, vegetation canopy surface temperature data, soil heat flux data, vegetation transpiration data, and vegetation canopy stomatal impedance data, and to correct the vegetation canopy stomatal impedance and vegetation aerodynamic impedance according to the total surface stomatal impedance and the total surface aerodynamic impedance.

[0054] The evapotranspiration calculation module is used to calculate the transpiration of trees, shrubs and lawns based on the corrected stomatal impedance and aerodynamic impedance data of the vegetation canopy, according to the Penman-Monteith model, so as to distinguish the components of evapotranspiration from the surface of urban green spaces.

[0055] Thirdly, this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described method for zoning urban green space surface evapotranspiration based on impedance parameters.

[0056] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method for zoning urban green space surface evapotranspiration based on impedance parameters.

[0057] In summary, this application includes at least one of the following beneficial technical effects:

[0058] 1. This application utilizes multi-scale evapotranspiration observation data (including stem flow meter or micro lysimeter data at the individual plant scale and eddy covariance flux data at the community scale), which can adapt to the unevenness of meteorological conditions and vegetation distribution in the complex environment of urban green spaces. By combining the energy balance principle with the correction fitting method, it helps to more accurately infer the impedance parameters of each vegetation type, overcomes the calculation deviation of each component of evapotranspiration caused by the mismatch of data spatial scale in traditional methods, and thus improves the accuracy of surface evapotranspiration zoning in urban green spaces.

[0059] 2. This application fully considers the differences between single-tree scale and community scale data, and adopts the impedance parameter back-inference method based on physical processes and footprint partitioning technology to achieve the organic integration of data at different scales. It can finely distinguish the evapotranspiration components of different vegetation types such as trees, shrubs and lawns in urban green spaces, and realize the accurate decomposition of the overall evapotranspiration process, effectively reflecting the differences in the role of different vegetation in the surface water cycle of urban green spaces. Attached Figure Description

[0060] Figure 1 This is a flowchart illustrating the implementation of a method for zoning urban green space surface evapotranspiration based on impedance parameters.

[0061] Figure 2 This is a schematic diagram of an instrument setup for a method of zoning urban green space surface evapotranspiration based on impedance parameters.

[0062] Figure 3 This is a schematic diagram of a module for an urban green space surface evapotranspiration zoning system based on impedance parameters.

[0063] Figure 4 This is an internal structural diagram of an electronic device according to this application. Detailed Implementation

[0064] The present application will be further described in detail below with reference to the accompanying drawings.

[0065] In one embodiment, this application discloses a method for zoning urban green space surface evapotranspiration based on impedance parameters, the implementation flowchart of which is shown below. Figure 1 As shown, the specific steps include the following:

[0066] S1: Collect and process vegetation morphology parameters, meteorological data, vegetation canopy surface temperature data, soil heat flux data, vegetation transpiration data, and eddy covariance flux observation data for selected urban green spaces.

[0067] Specifically, step S1 includes the following steps:

[0068] S101: Morphological parameters of vegetation in selected urban green spaces were measured using on-site measurement methods. Specifically, a laser rangefinder was used to measure tree height, and a height measuring rod was used to measure shrub and lawn height; the leaf area index of trees and shrubs was measured using a LAI-2200C, and the leaf area index of lawns was measured using a direct sampling method; and orthophotos and multispectral images were acquired using drones to extract vegetation cover information in urban green spaces.

[0069] S102: Select representative vegetation canopy areas, avoiding human interference and building obstruction, and ensuring the selected vegetation is healthy. Install net radiation meters 0.5m–1m above the tree canopy, shrub canopy, and lawn to acquire net radiation data for each vegetation type; install temperature and humidity sensors near the tree canopy, shrub canopy, and lawn to acquire temperature and humidity data for the vicinity of each vegetation type. A schematic diagram of the instrument layout is shown below. Figure 2 As shown. It is necessary to ensure the instrument mounting bracket is stable to prevent wind or other environmental factors from affecting measurement stability; and the instrument needs regular maintenance to check for dust, rainwater deposits, or other contaminants that may affect measurements.

[0070] S103: Infrared thermometers should be installed 0.5m to 1m above the canopy of trees, shrubs, and lawns to obtain canopy surface temperature data for each vegetation type. For lawns and low shrubs, the infrared thermometer can be used vertically to avoid angular errors; for large trees, the infrared thermometer can be used at an angle, and radiation errors caused by the measurement angle should be corrected. Care should be taken to avoid affecting the net radiometer measurement when setting up the infrared thermometer.

[0071] S104: Install soil heat flux plates at a depth of 0.08m below the tree canopy, shrub canopy, and lawn to obtain soil heat flux data below each vegetation type.

[0072] S105: Tree transpiration was measured using a TDP pin-type stem flow meter. The sensor was mounted on the trunk 1.3m above the ground to avoid the heat gradient generated by the cold sap flowing from the soil and was wrapped with reflective aluminum foil to minimize the thermal effect caused by solar radiation. Tree sap flux density was calculated using Granier's empirical equation.

[0073]

[0074] In the formula: F d,t It is the sap flux density; ρ w ΔT is the density of water; ΔT is the temperature difference between the heated probe and the unheated probe; ΔT m It is the maximum temperature difference between the two probes when the sap flux density is zero.

[0075] The transpiration rate of trees is calculated as follows:

[0076]

[0077] In the formula: L v It is the latent heat of water vaporization; A c,t It is the projected area of ​​the tree canopy; A s,t This is the sapwood area of ​​the tree. The sapwood area is calculated by drilling the core of the tree using Haglof.

[0078] Shrub transpiration was measured using a wrap-around stem flow meter. The sensor was installed at the base 1 / 3 of the length, avoiding forks and wounds to ensure the water flow channel was undisturbed. The sensor was wrapped with insulating and heat-retaining material to minimize environmental temperature interference. A waterproof tarpaulin was used as the outer layer to prevent rainwater or dew from affecting the measurement results. The stem sap flux density was calculated using the Dynamax built-in program. The shrub transpiration was calculated as follows:

[0079]

[0080] In the formula: F d,t It is the sap flux density of shrub stems; A c,sh It is the projected area of ​​the shrub canopy; A s,sh It is the cross-sectional area of ​​the shrub's stem.

[0081] To measure lawn transpiration using a miniature lysimeter, select a sampler that matches the inner diameter of the lysimeter. Vertically cut the lawn soil (including intact turf and roots), preserving the original soil structure to avoid disturbance. Place the soil column into the lysimeter container and backfill to its original position, ensuring the container edge is flush with the surrounding soil to avoid the "edge effect" that could cause water seepage. Calculate the lawn transpiration based on weight changes during the measurement period.

[0082] S106: Use an open-circuit eddy covariance flux monitoring system to collect surface water vapor flux data of urban green spaces. A net radiation meter, temperature and humidity sensors, and an anemometer will collect net radiation data of the urban green space surface, as well as temperature, humidity, and wind speed data at the instrument's installation height. The instrument's installation height should be at least twice the height of the tree canopy, and the installation location should take into account the influence of the local prevailing wind direction, meeting the requirements for flux source areas on the urban green space ground surface.

[0083] S107: Time synchronization and data alignment are performed on various measured data. EddyPro software is used to process the raw eddy covariance flux data, performing coordinate rotation, time delay correction, spectral correction, and quality control. Based on urban green space vegetation morphology parameters, the flux contribution source areas at each time point are determined using a flux footprint model. Based on urban green space vegetation distribution information, the proportion of each vegetation type within each footprint flux contribution source area is determined.

[0084] S2: Based on meteorological data, vegetation canopy surface temperature data, soil heat flux data, and vegetation transpiration data, the boundary layer impedance of vegetation leaves and the stomatal impedance of vegetation canopy are calculated by back-deriving the Penman-Monteith formula and the surface energy balance equation.

[0085] Specifically, step S2 includes the following steps:

[0086] S201: Based on meteorological data, vegetation canopy surface temperature data, soil heat flux data, and vegetation transpiration data, the boundary layer impedance of vegetation leaves is calculated by inversely reconstructing the surface energy balance equation.

[0087]

[0088] In the formula, r b,t r b,sh and r b,g These are the leaf boundary layer impedances of trees, shrubs, and lawns, respectively; ρ is the air density; c p It is the specific heat capacity of air; T s,t T s,sh and T s,g These are the canopy surface temperatures of trees, shrubs, and lawns, respectively; T a,t T a,sh and T a,g These are the air temperatures near the tree canopy, shrub canopy, and lawn, respectively; R n,t R n,sh and R n,g These are the net radiation of tree canopy, shrub canopy, and lawn, respectively; LE t LE sh and LE g These are the latent heat fluxes of tree canopy, shrub canopy, and lawn transpiration, respectively; G t Gsh and G g These are the soil heat fluxes beneath trees, shrubs, and lawns, respectively.

[0089] S202: Based on meteorological data, soil heat flux data, and vegetation transpiration data, and inputting the vegetation leaf boundary layer impedance calculated in S201, the stomatal impedance of the vegetation canopy is calculated by inversely applying the Penman-Monteith formula.

[0090]

[0091] In the formula, r c,t r c,sh and r c,g These are the stomatal resistances of tree canopies, shrub canopies, and lawns, respectively; VPD t VPD sh and VPD g These represent the air saturated water vapor pressure difference near trees, shrubs, and lawns, respectively; Δ is the slope of the saturated water vapor pressure-temperature curve; and γ is the hygrometer constant.

[0092] S3: Based on vegetation morphology parameters, obtain flux contribution source area information from the eddy covariance flux observation tower, determine the proportion of trees, shrubs and lawns in the source area, and calculate the total aerodynamic impedance and total stomatal impedance of urban green space based on eddy covariance flux observation data, vegetation leaf boundary layer impedance and canopy stomatal impedance data.

[0093] Specifically, step S3 includes the following steps:

[0094] S301: Based on the proportion data of each vegetation type in the flux contribution source area, meteorological data, vegetation canopy surface temperature data, soil heat flux data, and eddy covariance flux observation data, the total surface aerodynamic impedance of urban green space is calculated by inversely proposing the surface energy balance equation.

[0095]

[0096] In the formula, r a It is the total aerodynamic impedance of urban green space; T s It is the weighted average surface temperature of urban green spaces, T s =f t ×T s,t +f sh ×T s,sh +f g ×T s,g ;f t f sh and f gThese represent the proportions of trees, shrubs, and lawns within the source area contributing to the footprint flux; G is the weighted average soil heat flux of urban green space, G = f t ×G t +f sh ×G sh +f g ×G g ;T atm It is an eddy covariance flux observation tower, used to measure air temperature at a certain altitude; R n 1 is the net radiation of urban green space measured by the net radiometer of the eddy covariance flux observation tower; LE is the latent heat flux measured by the eddy covariance flux observation tower.

[0097] S302: Based on the proportion data of each vegetation type in the flux contribution source area, meteorological data, soil heat flux data, and eddy covariance flux observation data, and inputting the total surface aerodynamic impedance of urban green space calculated in S301, the total surface aerodynamic impedance of urban green space is calculated by inversely applying the Penman-Monteith formula.

[0098]

[0099] In the formula, r c It is the total pore impedance of urban green space; VPD is the air saturated water vapor pressure difference at the height of the eddy covariance flux observation instrument.

[0100] S4: Based on meteorological data, vegetation canopy surface temperature data, soil heat flux data, vegetation transpiration data, and vegetation canopy stomatal impedance data, calculate vegetation aerodynamic impedance, and correct vegetation canopy stomatal impedance and vegetation aerodynamic impedance according to total surface stomatal impedance and total surface aerodynamic impedance.

[0101] Specifically, step S4 includes the following steps:

[0102] S401: Based on meteorological data, vegetation canopy surface temperature data, soil heat flux data, vegetation transpiration data, and vegetation canopy stomatal impedance data calculated in S202, the vegetation aerodynamic impedance is calculated by solving the surface energy balance equation.

[0103]

[0104]

[0105] In the formula: r a,t r a,sh and r a,g These are the aerodynamic impedances of trees, shrubs, and lawns, respectively.

[0106] S402: Based on the total surface aerodynamic impedance of urban green space calculated in S301 and the total surface stomatal impedance of urban green space calculated in S302, the vegetation canopy stomatal impedance calculated in S202 and the vegetation aerodynamic impedance calculated in S401 are corrected:

[0107]

[0108] In the formula, α1, α2, α3, β1, β2 and β3 are fitting parameters. The values ​​of fitting parameters α1, α2, α3, β1, β2 and β3 can be determined based on the total aerodynamic impedance and total stomatal impedance of urban green space, as well as the aerodynamic impedance and canopy stomatal impedance of trees, shrubs and lawns.

[0109] S5: Based on the corrected stomatal impedance and aerodynamic impedance data of vegetation canopy, the transpiration of trees, shrubs and lawns is calculated according to the Penman-Monteith model to distinguish the components of surface evapotranspiration in urban green spaces.

[0110] Specifically, step S5 includes the following steps:

[0111] S501: Based on meteorological and soil heat flux data, using vegetation aerodynamic impedance data and vegetation canopy stomatal impedance data corrected by S402, the transpiration rates of trees, shrubs, and lawns are calculated according to the Penman-Monteith model.

[0112]

[0113]

[0114] In the formula, ET t It is the transpiration rate of trees; ET sh It is the transpiration rate of shrubs; ET g It is the transpiration rate of the lawn.

[0115] In one embodiment, this application provides an urban green space surface evapotranspiration zoning system based on impedance parameters. The urban green space surface evapotranspiration zoning system based on impedance parameters of this application will be described below in conjunction with the above-mentioned urban green space surface evapotranspiration zoning method based on impedance parameters.

[0116] Reference Figure 3 A zoning system for urban green space surface evapotranspiration based on impedance parameters, comprising:

[0117] The data acquisition module is used to collect and process vegetation morphology parameters, meteorological data, vegetation canopy surface temperature data, soil heat flux data, vegetation transpiration data, and eddy covariance flux data of urban green spaces.

[0118] The impedance calculation module is used to calculate the boundary layer impedance data of vegetation leaves and the stomatal impedance data of vegetation canopy based on meteorological data, vegetation canopy surface temperature data, soil heat flux data, and vegetation transpiration data, by back-deriving the Penman-Monteith formula and the surface energy balance equation.

[0119] The source region analysis module is used to obtain flux contribution source region information of eddy covariance flux observation tower based on vegetation morphology parameters, determine the proportion of trees, shrubs and lawns in the source region, and calculate the total aerodynamic impedance and total stomatal impedance of urban green space based on eddy covariance flux observation data, vegetation leaf boundary layer impedance and canopy stomatal impedance data.

[0120] The impedance correction module is used to calculate the vegetation aerodynamic impedance based on meteorological data, vegetation canopy surface temperature data, soil heat flux data, vegetation transpiration data, and vegetation canopy stomatal impedance data, and to correct the vegetation canopy stomatal impedance and vegetation aerodynamic impedance according to the total surface stomatal impedance and the total surface aerodynamic impedance.

[0121] The evapotranspiration calculation module is used to calculate the transpiration of trees, shrubs and lawns based on the corrected stomatal impedance and aerodynamic impedance data of the vegetation canopy, according to the Penman-Monteith model, so as to distinguish the components of evapotranspiration from the surface of urban green spaces.

[0122] In one embodiment, this application provides an electronic device, which may be a server, and its internal structure diagram may be as follows: Figure 4 As shown, the electronic device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database stores data. The network interface communicates with external terminals via a network connection. When executed by the processor, the computer program implements a method for zoning urban green space surface evapotranspiration based on impedance parameters.

[0123] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the electronic device to which the present application is applied. The specific electronic device may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0124] In one embodiment, an electronic device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0125] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0126] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A method for zoning urban green space surface evapotranspiration based on impedance parameters, characterized in that, The method includes the following steps: S1. Collect and process vegetation morphology parameters, meteorological data, vegetation canopy surface temperature data, soil heat flux data, vegetation transpiration data, and eddy covariance flux data of urban green spaces. S2. Based on meteorological data, vegetation canopy surface temperature data, soil heat flux data, and vegetation transpiration data, vegetation leaf boundary layer impedance data and vegetation canopy stomatal impedance data are calculated by back-deriving the Penman-Monteith formula and the surface energy balance equation. S3. Based on vegetation morphology parameters, obtain flux contribution source area information of eddy covariance flux observation tower, determine the proportion of trees, shrubs and lawns in the source area, and calculate the total aerodynamic impedance and total stomatal impedance of urban green space based on eddy covariance flux observation data, vegetation leaf boundary layer impedance and canopy stomatal impedance data. S4. Based on meteorological data, vegetation canopy surface temperature data, soil heat flux data, vegetation transpiration data, and vegetation canopy stomatal impedance data, calculate vegetation aerodynamic impedance, and correct vegetation canopy stomatal impedance and vegetation aerodynamic impedance according to total surface stomatal impedance and total surface aerodynamic impedance. S5. Based on the corrected stomatal impedance and aerodynamic impedance data of vegetation canopy, calculate the transpiration of trees, shrubs and lawns according to the Penman-Monteith model to distinguish the components of surface evapotranspiration in urban green spaces. In S2, the boundary layer impedance of vegetation leaves is calculated as follows: In the formula, r b,t r b,sh and r b,g These are the leaf boundary layer impedances of trees, shrubs, and lawns, respectively; ρ is the air density; c p It is the specific heat capacity of air; T s,t T s,sh and T s,g These are the canopy surface temperatures of trees, shrubs, and lawns, respectively; T a,t T a,sh and T a,g These are the air temperatures near the tree canopy, shrub canopy, and lawn, respectively; R n,t R n,sh and R n,g These are the net radiation of tree canopy, shrub canopy, and lawn, respectively; LE t LE sh and LE g These are the latent heat fluxes of tree canopy, shrub canopy, and lawn transpiration, respectively; G t G sh and G g These are the soil heat fluxes beneath trees, shrubs, and lawns, respectively. The stomatal impedance of the vegetation canopy is calculated as follows: In the formula, r c,t r c,sh and r c,g These are the stomatal resistances of tree canopies, shrub canopies, and lawns, respectively; VPD t VPD sh and VPD g These represent the air saturated water vapor pressure difference near trees, shrubs, and lawns, respectively; Δ is the slope of the saturated water vapor pressure-temperature curve; γ is the hygrometer constant; and G is the weighted average soil heat flux of urban green space, G = f t ×G t +f sh ×G sh +f g ×G g ;f t f sh and f g These represent the proportions of trees, shrubs, and lawns within the source area of ​​the footprint flux contribution.

2. The method for zoning urban green space surface evapotranspiration based on impedance parameters as described in claim 1, characterized in that, S1 specifically includes: Acquire vegetation morphology parameters in urban green spaces, including vegetation height, leaf area index, and vegetation canopy coverage. Net radiation meters and temperature and humidity sensors were installed above the tree canopy, shrub canopy, and lawn to obtain net radiation data and temperature and humidity data for each vegetation type. Infrared thermometers were installed above the tree canopy, shrub canopy, and lawn to obtain canopy surface temperature data for each vegetation type. Soil heat flux plates were installed at soil depths below the tree canopy, shrub canopy, and lawn to obtain soil heat flux data below each vegetation type. Representative trees, shrubs and lawns were selected, and vegetation transpiration data were obtained using stem flow meters and miniature lysimeters; The overall water vapor flux data of urban green space, as well as the overall net radiation, temperature, humidity and wind speed data at the height of the observation tower, were collected using an eddy covariance flux monitoring system. The measurement data were processed to determine the proportion of each vegetation type in the footprint flux contribution source area.

3. The method for zoning urban green space surface evapotranspiration based on impedance parameters as described in claim 1, characterized in that, In S3 The total surface aerodynamic impedance of urban green spaces is determined as follows: In the formula, r a It is the total aerodynamic impedance of urban green space; T s It is the weighted average surface temperature of urban green spaces, T s =f t ×T s,t +f sh ×T s,sh +f g ×T s,g ;f t f sh and f g These represent the proportions of trees, shrubs, and lawns within the source area contributing to the footprint flux; G is the weighted average soil heat flux of urban green space, G = f t ×G t +f sh ×G sh +f g ×G g ;T atm It is the air temperature at the height measured by the eddy covariance flux observation tower; R n 1 is the net radiation of urban green space measured by the net radiometer of the eddy covariance flux observation tower; LE is the latent heat flux measured by the eddy covariance flux observation tower. The total surface porosity of urban green spaces is determined as follows: In the formula, r c It is the total surface porosity of urban green space; VPD is the air saturated water vapor pressure difference at the height of the eddy covariance flux observation instrument.

4. The method for zoning urban green space surface evapotranspiration based on impedance parameters as described in claim 1, characterized in that, In S4, the aerodynamic impedance of vegetation is calculated as follows: r c,t r c,sh and r c,g Substituting into the following formula, solve the following equations to obtain r. a,t r a,sh and r a,g : In the formula: r a,t r a,sh and r a,g These are the aerodynamic impedances of trees, shrubs, and lawns, respectively; T atm VPD is the air temperature at the measurement height of the eddy covariance flux observation tower; VPD is the air saturation water vapor pressure difference at the installation height of the eddy covariance flux observation instrument. The stomatal impedance and aerodynamic impedance of vegetation canopy are corrected based on the total surface stomatal impedance and the total surface aerodynamic impedance, specifically as follows: In the formula, α1, α2, α3, β1, β2, and β3 are fitting parameters. The values ​​of these parameters can be determined based on the total aerodynamic impedance and total stomatal impedance of urban green spaces, as well as the aerodynamic impedance and canopy stomatal impedance of trees, shrubs, and lawns. a It is the total aerodynamic impedance of urban green space; r c It is the total surface porosity of urban green space.

5. The method for zoning urban green space surface evapotranspiration based on impedance parameters as described in claim 1, characterized in that, In S5, the transpiration rates of trees, shrubs, and lawns are calculated based on the Penman-Monteith model, specifically as follows: In the formula, ET t It is the transpiration of trees, ET sh It's shrub transpiration, ET g It's the lawn evaporating; r a,t r a,sh and r a,g These are the aerodynamic impedances of trees, shrubs, and lawns, respectively; VPD is the air saturation vapor pressure difference at the installation height of the eddy covariance flux observation instrument; f t f sh and f g These represent the proportions of trees, shrubs, and lawns within the footprint flux contribution source area; α1, α2, α3, β1, β2, and β3 are fitting parameters. The values ​​of fitting parameters α1, α2, α3, β1, β2, and β3 can be determined based on the total aerodynamic impedance and total stomatal impedance of urban green spaces, as well as the aerodynamic impedance and canopy stomatal impedance of trees, shrubs, and lawns.

6. A zoning system for urban green space surface evapotranspiration based on impedance parameters, characterized in that, include: The data acquisition module is used to collect and process vegetation morphology parameters, meteorological data, vegetation canopy surface temperature data, soil heat flux data, vegetation transpiration data, and eddy covariance flux data of urban green spaces. The impedance calculation module is used to calculate the boundary layer impedance data of vegetation leaves and the stomatal impedance data of vegetation canopy based on meteorological data, vegetation canopy surface temperature data, soil heat flux data, and vegetation transpiration data, by back-deriving the Penman-Monteith formula and the surface energy balance equation. The source region analysis module is used to obtain flux contribution source region information of eddy covariance flux observation tower based on vegetation morphology parameters, determine the proportion of trees, shrubs and lawns in the source region, and calculate the total aerodynamic impedance and total stomatal impedance of urban green space based on eddy covariance flux observation data, vegetation leaf boundary layer impedance and canopy stomatal impedance data. The impedance correction module is used to calculate the vegetation aerodynamic impedance based on meteorological data, vegetation canopy surface temperature data, soil heat flux data, vegetation transpiration data, and vegetation canopy stomatal impedance data, and to correct the vegetation canopy stomatal impedance and vegetation aerodynamic impedance according to the total surface stomatal impedance and the total surface aerodynamic impedance. The evapotranspiration calculation module is used to calculate the transpiration of trees, shrubs and lawns based on the corrected vegetation canopy stomatal impedance and vegetation aerodynamic impedance data, according to the Penman-Monteith model, so as to distinguish the components of evapotranspiration from the surface of urban green space. Specifically, the calculation of the boundary layer impedance of vegetation leaves is as follows: In the formula, r b,t r b,sh and r b,g These are the leaf boundary layer impedances of trees, shrubs, and lawns, respectively; ρ is the air density; c p It is the specific heat capacity of air; T s,t T s,sh and T s,g These are the canopy surface temperatures of trees, shrubs, and lawns, respectively; T a,t T a,sh and T a,g These are the air temperatures near the tree canopy, shrub canopy, and lawn, respectively; R n,t R n,sh and R n,g These are the net radiation of tree canopy, shrub canopy, and lawn, respectively; LE t LE sh and LE g These are the latent heat fluxes of tree canopy, shrub canopy, and lawn transpiration, respectively; G t G sh and G g These are the soil heat fluxes beneath trees, shrubs, and lawns, respectively. The stomatal impedance of the vegetation canopy is calculated as follows: In the formula, r c,t r c,sh and r c,g These are the stomatal resistances of tree canopies, shrub canopies, and lawns, respectively; VPD t VPD sh and VPD g These represent the air saturated water vapor pressure difference near trees, shrubs, and lawns, respectively; Δ is the slope of the saturated water vapor pressure-temperature curve; γ is the hygrometer constant; and G is the weighted average soil heat flux of urban green space, G = f t ×G t +f sh ×G sh +f g ×G g ;f t f sh and f g These represent the proportions of trees, shrubs, and lawns within the source area of ​​the footprint flux contribution.

7. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the urban green space surface evapotranspiration zoning method based on impedance parameters as described in any one of claims 1-5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the urban green space surface evapotranspiration zoning method based on impedance parameters as described in any one of claims 1-5.

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