An analysis method for spatiotemporal variation characteristics of urban green space ecosystem evapotranspiration

Abstract

The present application relates to the field of ecological hydrology, and particularly relates to a kind of urban green space ecosystem evapotranspiration spatiotemporal variation characteristic analysis method, according to different vegetation, different community and different regional scale, adopt field survey, positioning observation, mobile observation and model simulation method, carry out the ecological hydrological process analysis of urban green space ecosystem atmosphere-vegetation-soil.The present application reveals the dominant factor that influences the evapotranspiration and ecological process of green water ecological system in the region by analyzing the spatiotemporal variation characteristic of evapotranspiration and ecological process of green space ecosystem in different spatiotemporal scale in city, clarifies the response mechanism of evapotranspiration and ecological process of urban green space ecosystem by coupling each factor of evapotranspiration and ecological process of urban green space ecosystem, so as to provide data reference for urban green space management planning and sponge city construction.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of ecological hydrology, in particular to a method for analyzing spatiotemporal variation characteristics of evapotranspiration of urban green space ecological system. BACKGROUND

[0002] Urban green space ecological system is an organic component of overall urban planning, reflecting the natural properties of the city, which includes artificial vegetation, semi-natural vegetation and natural vegetation. Urban green space vegetation community is an important factor for regulating urban waterlogging and reducing flood occurrence. In the city, urban green space is the most important biological barrier for maintaining and improving the ecological environment of the city, which can regulate temperature and improve the ecological environment of the city, and maintain the benign circulation of the urban ecological system. Therefore, it is of great significance to carry out research on the evapotranspiration of urban green space ecological system. Especially the ecological system of super large city green space, on the one hand, it is strongly disturbed by human activities, on the other hand, it is an important system for environmental beautification and rainstorm waterlogging regulation. Therefore, the green space ecological system of super large city is the main control system of the interaction evolution process of its ecological process and hydrological process, but the corresponding mechanism of ecological hydrology is still relatively weak. Therefore, experimental observation and model simulation should be combined to comprehensively study the influence mechanism of urban green space ecological system structure and ecological process on the regulation function of urban ecological hydrology from the aspects of "multi-factor, multi-scale and multi-angle", and explore the dominant factors affecting the realization of hydrological regulation function. Evapotranspiration is an important part of the interaction mechanism of hydrological process and ecological process of urban green space ecological system, is an important link between ecological process and hydrological process, and is the most important index for studying the interaction mechanism of ecological process and hydrological process. Due to the highly nonlinear characteristics of ecological process and hydrological process, there is currently a lack of theory and method for the interaction mechanism of ecological process and hydrological process of vegetation ecological system, especially for urban green space ecological system, which needs to be further explored and studied. SUMMARY

[0003] In view of the above deficiencies in the prior art, the present application aims to provide a method for analyzing spatiotemporal variation characteristics of evapotranspiration of urban green space ecological system.

[0004] In order to achieve the above-mentioned application purposes, the technical scheme adopted by the present application is as follows:

[0005] A method for analyzing spatiotemporal variation characteristics of evapotranspiration of urban green space ecological system is provided, which adopts field sample plot investigation, positioning observation, flow observation and model simulation methods according to different vegetation, different communities and different regional scales to carry out ecological hydrological process analysis of atmosphere-vegetation-soil of urban green space ecological system; specifically including the following steps:

[0006] S1, on the scale of single tree, through the observation of tree phenological growth changes, leaf area index changes and photosynthetic physiological changes, the ecological process of the tree is analyzed; through the observation of tree sap flow instrument, tree canopy interception, tree stem flow and through rain sensor, the hydrological cycle process of single tree is observed;

[0007] S2, on the scale of community, through sample plot investigation and regular artificial observation, the ecological characteristics of dominant vegetation community are analyzed, and through water balance field and flux observation tower, the evapotranspiration characteristics of vegetation community are studied;

[0008] S3, on the regional scale, through the establishment of SWH model database, the evapotranspiration of urban green space ecological system is simulated and analyzed; the urban surface vegetation coverage, NDVI and leaf area index are interpreted from TM image, and the characteristics of the change of urban vegetation ecological process are analyzed; based on the influence of urban surface vegetation change and growth on hydrological process, the spatio-temporal variation characteristics of urban green space ecological system ecological hydrological process are analyzed;

[0009] S4, using the research results of ecological process and evapotranspiration of urban green space ecological system at different scales, combining with the simulation results of SWH model under different vegetation coverage scenarios, through mathematical statistical analysis and model simulation method, the mutual relationship between evapotranspiration and ecological process of urban green space ecological system is clarified, and the response mechanism of evapotranspiration of urban green space ecological system to its ecological process is coupled.

[0010] Further, in step S2, the ecological characteristics of vegetation community include species composition, coverage, biomass, abundance, structure and phenological characteristics.

[0011] Further, in step S2, the determination of the hydrological process of vegetation community includes the following sub-steps:

[0012] The determination of hydrological process follows the principle of water balance, and the water balance equation is:

[0013] P=S+I s +E w +△w (1)

[0014] In formula 1, P is the rainfall, S is the transpiration, I s is the canopy interception, E w is the understory evapotranspiration (litter evaporation + understory vegetation transpiration + soil evaporation), and△w is the change amount of soil water storage;

[0015] S2-1, determination of single plant transpiration

[0016] According to the general Granier sap flow formula, the sap flow density (V s ) and sap flow flux (F) of the determination point are calculated and determined:

[0017] V s= 0.0119K 1.231 x 3600 (2)

[0018] In formula 2: V s is the sap flow density (g-cm -2 h -1 ); K = (dT m -dT) / dT, where dT m is the maximum temperature difference between the heating probe and the reference probe without sap flow, and dT is the instantaneous temperature difference;

[0019] The sap flux (F) is calculated by the following formula:

[0020]

[0021] In formula 3: F is the sap flux (g); n is the number of sampling times; V i is the sap flow density (g-cm -2 h -1 ) at the i-th sampling time; A s is the bark area (cm 2 ); and Δt is the sampling interval (h);

[0022] Bark area calculation: the bark and heartwood are distinguished according to color; the wood core is drilled at the breast height of the trunk with a growth cone, and the bark thickness is measured with a ruler; based on the investigation data of each wood, the bark area of the sample wood and the total bark area per unit area of the sample plot are calculated based on the determined diameter at breast height-bark area quantity relationship; the 24h sap flow density is summed to obtain the sap flux per unit bark area; and the 24h sap flow velocity is summed to obtain the daily transpiration of a single plant;

[0023] S2-2, determination of canopy interception

[0024] The canopy interception is calculated by measuring the rainfall outside the forest, the rainfall inside the forest, and the trunk runoff;

[0025] The calculation formula of the canopy interception is:

[0026] Is = P lw -P ln -P jl (4)

[0027] In formula 4: I s s the canopy interception, P lw is the rainfall outside the forest, P ln is the rainfall inside the forest, and P jl is the trunk runoff;

[0028] S2-3, determination of change in soil water storage

[0029] The soil water content is determined by using the drying method, and the soil water storage capacity can be calculated by the following formula:

[0030] W=∑w i =0.1ω i γ di h i (5)

[0031] In formula 5, W is the soil water storage capacity (mm);ω i is the water content of the i-th layer of soil (%);γ di is the dry bulk density of the i-th layer of soil (g / cm 3 );h i is the thickness of the i-th layer of soil (cm);

[0032] S2-4, calculation of the evapotranspiration under forest

[0033] The rainfall, the canopy interception, the artificial vegetation transpiration and the change of the soil water storage capacity can be determined, and the evapotranspiration under forest can be derived according to formula 1.

[0034] E w =P-I s -S-△W (6)

[0035] The evapotranspiration of the artificial vegetation can be obtained by summing up the transpiration of the trees and the evapotranspiration under forest.

[0036] Further, in step S2, the calculation formula of the evapotranspiration characteristics of the vegetation community observed by the flux observation tower is as follows:

[0037]

[0038] In the formula, λ is the latent heat of water vaporization, H is the sensible heat flux, ET is the latent heat flux, ρ a is the air density, C p is the specific heat of air at constant pressure, T', w' and q' are the vertical temperature, wind speed and humidity fluctuation values respectively.

[0039] Further, in step S4, by analyzing the correlation characteristics and interaction relationship between the evapotranspiration of the urban green space ecological system and various factors of the ecological process in different time and space scales, the factor coupling of the interaction mechanism of the evapotranspiration and the ecological process of the urban green space ecological system is coupled through a multivariate nonlinear regression model.

[0040] The present application has the following advantages:

[0041] The application discloses a method for analyzing the temporal and spatial variation characteristics of the evapotranspiration and ecological process of the green land ecosystem in different time and space scales of a city, revealing the dominant factors affecting the evapotranspiration and ecological process of the green water ecosystem in the region, coupling the evapotranspiration and ecological process factors of the urban green land ecosystem, and clarifying the response mechanism of the evapotranspiration and ecological process of the urban green land ecosystem, so as to provide data reference for the urban green land management planning and the sponge city construction. BRIEF DESCRIPTION OF DRAWINGS

[0042] Figure 1 A method flowchart of the application is shown in the figure.

[0043] Figure 2 A coupling framework schematic diagram of the evapotranspiration and ecological process factors is shown in the figure. DETAILED DESCRIPTION

[0044] The specific embodiment of the application is described below, so that the person skilled in the art can understand the application, but it should be clear that the application is not limited to the scope of the specific embodiment, and for the person skilled in the art, as long as various changes are within the spirit and scope of the application defined and determined by the appended claims, the changes are obvious, and all the application and creation using the concept of the application are within the scope of protection.

[0045] EMBODIMENT

[0046] REFERENCE Figure 1The present embodiment selects the green space ecosystem of city A as the research object. In view of the key water transfer process and regulation mechanism and scale effect of the water balance relationship of the atmosphere-vegetation-soil system in the region, and other problems, field plot investigation, positioning observation, flow observation and model simulation methods are adopted to carry out the ecological hydrological process research of the atmosphere-vegetation-soil of the green space ecosystem of city A according to different vegetation, different communities and different scales. On the single tree scale, the ecological process of the tree is analyzed by observing the phenological growth change, leaf area index change and photosynthetic physiological change of the tree. The hydrological cycle process of the single tree is observed by using the tree sap flow instrument, tree crown interception, tree stem flow and through rain sensor. On the community scale, the ecological characteristics (species composition, coverage, biomass, abundance, structure, phenological characteristics, etc.) of the dominant vegetation community are analyzed by plot investigation and regular manual observation. The evapotranspiration characteristics of the vegetation community are researched by the water balance field and flux observation tower. On the regional scale, the evapotranspiration of the green space ecosystem of A region is simulated and analyzed by establishing the SWH model database. The characteristics of the change of the vegetation ecological process of A city are analyzed by interpreting the surface vegetation coverage, NDVI and leaf area index, etc. of A city in the past 20 years by using the TM image. The influence of the surface vegetation change and growth of A city on the hydrological process is analyzed. The spatio-temporal variation characteristics of the ecological hydrological process of the green space ecosystem of A city are analyzed. By using the research results of the ecological process and evapotranspiration of the green space ecosystem of city A at different scales, combining with the simulation results of the SWH model under different vegetation coverage scenarios, the mutual relationship between the evapotranspiration and ecological process of the green space ecosystem of A city is clarified by mathematical statistical analysis and model simulation methods. The response mechanism of the evapotranspiration of the green space ecosystem of A city to the ecological process is coupled.

[0047] The specific implementation method is as follows:

[0048] (1) Ecological structure survey of green space ecosystem

[0049] The phenological observation and photosynthetic physiological observation are carried out by the observation facilities of the ecological station of A city. The sample plot is completed with the assistance of A station. The experimental design of the sample plot is as follows: first, a sample plot (50x50m, 9 sample circles are set in each sample plot) is set up without boundary sample circle method: a temporary sample plot is selected in the observation point, a center point is determined, and then a cross-shaped sample rope with a length of 25m is scattered from the center point in the south, north, east and west directions, and 5 sample circles (R=4m) are set on each sample rope, and the distance between the centers of the sample circles is 12.5m.

[0050] Each wood check ruler:

[0051] The growth potential, diameter at breast height, tree height, branch height and crown width of each tree (live standing wood, dead standing wood) are respectively investigated and measured.

[0052] 1) Crown width, the south-north and east-west crown width of each tree is respectively measured by using a tape measure, and the average value (unit: centimeter, retaining 1 decimal place) is obtained.

[0053] 2) Canopy density, the canopy density of the stand is determined by statistical method, and the specific method is to mechanically set 50 sample points in the sample plot, to determine whether the sample point is covered by the vertical projection of the tree crown, to count the number n of covered sample points, and to calculate the canopy density of the stand by using the following formula:

[0054] PC = n / N

[0055] PC: canopy density

[0056] N: total number of sample points (generally at least 100 or more)

[0057] 3) Determine the tree height, and the specific method is as follows: a. The signal receiver has a small knife on the side, which is cut into the bark and fixed on the tree trunk 1.3 m high from the ground. b. Turn on the signal receiver. c. Hold the height meter, select an observation point that can see the top of the tree and the signal receiver, keep the red "OK" button of the height meter pressed all the time, aim the red dot in the sighting scope of the height meter at the signal receiver, until the red dot in the sighting scope disappears, then release the red "OK" button, the distance, angle and horizontal distance from the observation point to the signal receiver will be displayed on the display screen of the height meter. d. Aim the red dot in the sighting scope at the top of the tree, at this time the red cross line flashes, press the red "NO" button until the red cross line disappears, then release the red "NO" button, at this time the height of the tree (assuming the fixed height of the receiver is 1.3 m) can be displayed on the display screen of the height meter; repeat the above steps to continuously measure the height of different parts of the tree trunk.

[0058] 4) Use a steel tape to measure the diameter at breast height of each tree.

[0059] 5) Use a box ruler or a marker to measure the height under the branches.

[0060] 6) Use the sample method to investigate the composition structure of herbs, shrubs and trees in each sample plot.

[0061] (2) Measurement of hydrological process of vegetation community

[0062] The measurement of hydrological process in this example follows the principle of water balance. Based on the research at home and abroad, the water balance equation selected in this example is:

[0063] P = S + I s +E w +△w (1)

[0064] In formula 1, P is the rainfall, S is the transpiration, I s is the canopy interception, E wEvapotranspiration = Evaporation from litter + Transpiration from vegetation + Soil evaporation, and Δw is the change of soil water storage. The precipitation was observed by automatic and manual weather stations.

[0065] (a) Transpiration of single vegetation

[0066] First, we set observation points to observe the transpiration of artificial vegetation in a year. The transpiration of artificial vegetation was observed by FLGS-TDP plant sap flow meter (Dynamax, U.S.A) to convert the sap flow. More than 99.8% of the sap flow flux of artificial vegetation is used for transpiration water consumption, which can be calculated according to the sap flow flux formula. In addition to environmental factors (such as precipitation, temperature, solar radiation, etc.), the transpiration of artificial vegetation is also related to its own physiological characteristics. Therefore, in order to avoid the influence of physiological characteristics on transpiration, we selected artificial vegetation with the same tree species, age, diameter at breast height, height, crown width and growth potential as the observation object in three observation plots.

[0067] Sap flow density observation: TDP probe was installed at 130 cm from the ground of the tree. The dead skin on the surface of the tree trunk was scraped with a knife; the drill module was placed in the prepared measurement position, and then a 1.32 mm diameter drill was used to drill two 30 mm long holes. The two holes were kept vertical as much as possible. After drilling, the holes were cleaned with a needle tube to suck hydrogen peroxide (double oxygen water). Then the heating probe of TDP-30 was inserted into the upper hole, and the reference probe was inserted into the lower hole. The needle was inserted slowly and gradually, 10 mm each time, and alternately inserted. A 2-3 mm needle tube was left outside, and the other end of the probe was connected with the data collector. The average value of sap flow data was recorded automatically by Campbell's data collector every 30 minutes. Eight probes were inserted in the east of sample trees 1 and 2, the south of sample trees 3 and 4, the west of sample trees 5 and 6, and the north of sample trees 7 and 8. A 1 / 4 foam ball was placed around the probe, wrapped with aluminum film (reflective film) to prevent solar radiation, and sealed with tape to prevent rainwater from entering.

[0068] According to the general Granier sap flow formula, the sap flow density (V s ) and sap flow flux (F) of the measurement point were calculated:

[0069] V s = 0.0119K 1.231 ×3600 (2)

[0070] In formula 2, V s is the sap flow density (g·cm -2 h -1 ); K = (dT m -dT) / dT, where dT mdT represents the maximum temperature difference between the heating probe and the reference probe when there is no liquid flow, and dT represents the instantaneous temperature difference.

[0071] The formula for calculating the fluid flow rate (F) is:

[0072]

[0073] In Formula 3: F is the liquid flow rate (g); n is the number of samplings; V i The fluid flow density (g·cm³) at the i-th sampling point -2 h -1 A s Sapwood area (cm²) 2 ); △t is the sampling interval (h). The average sap flow density of the 8 sample trees at various times within the month is taken as the daily sap flow density V within the month. i The calculation period is uniformly set from January 1st to December 31st.

[0074] Sapwood area calculation: First, distinguish the sapwood and heartwood by color. To avoid damaging the sample trees and affecting the measurement of sap flow, select 30 additional trees 5-20 meters around the sample plot. Drill core samples at breast height (DBH) using a growth cone and measure the sapwood thickness with a ruler. Based on the data from each tree, and establishing the relationship between DBH and sapwood area, calculate the sapwood area of ​​the sample trees and the total sapwood area per unit area of ​​the sample plot. Sum the sap flow density over 24 hours to obtain the sap flow rate per unit sapwood area; sum the sap flow velocity over 24 hours to obtain the daily transpiration rate per tree.

[0075] (b) Measurement of canopy interception

[0076] Canopy interception is calculated by measuring rainfall outside the forest, rainfall inside the forest, and trunk runoff. Rainfall inside the forest is measured by randomly placing five 20cm diameter automatic rain gauges within the sample plot to measure the amount of rain that passes through the forest. Trunk runoff is measured by attaching two self-made semi-circular metal canisters, 1.0m above the ground, to the sample trees. A small opening at the bottom of the canister connects to a hose, the other end of which is connected to an automatic rain gauge on the ground. The trunk runoff is measured by measuring the water level in the canister, and then the runoff per unit area is calculated based on the stand density. The formula for calculating canopy interception is as follows:

[0077] Is = P lw -P ln -P jl (4)

[0078] In Formula 4: I s P represents canopy interception. lw For rainfall outside the forest, P ln P represents rainfall within the forest. jlTrunk flow.

[0079] (c) Measurement of soil water storage change

[0080] Soil water content was measured by oven drying method. Soil samples were taken at 0-10 cm, 10-20 cm, 20-30 cm, 30-0 cm, 40-60 cm, and 60-80 cm, respectively, and measured in early January and late December. Soil bulk density was measured in late December by the cutting ring method. Soil water storage was calculated by the following formula:

[0081] W =∑w i = 0.1ω i γ di h i (5)

[0082] In formula 5, W is soil water storage (mm); ω i is the water content of the i-th layer of soil (%); γ di is the dry bulk density of the i-th layer of soil (g / cm 3 ); and h i is the thickness of the i-th layer of soil (cm).

[0083] Soil water storage in early January and late December was calculated by formula 5. The soil water storage change in a year was obtained by subtracting the soil water storage in early January from that in late December.

[0084] (d) Calculation of evapotranspiration of understory (litter + understory vegetation + soil)

[0085] Rainfall, canopy interception, artificial vegetation transpiration, and soil water storage change were all measured. The evapotranspiration of the understory was derived from formula 1.

[0086] E w = P - I s - S - ΔW (6)

[0087] Through the above experimental observations, the transpiration of trees and the evapotranspiration of the understory were summed up to obtain the evapotranspiration of artificial vegetation.

[0088] (3) Flux tower eddy correlation technique to observe community evapotranspiration

[0089] Eddy correlation method is based on the eddy correlation theory proposed by Australian micro-meteorologist Swinbank in 1951. It is a method of measuring and calculating the turbulent pulsation values of the sensible heat and latent heat of the underlying surface to obtain the plant evaporation and transpiration. The calculation formula is as follows:

[0090]

[0091] Where: λ is the latent heat of water vaporization; H is the sensible heat flux; ET is the latent heat flux; ρ a is the air density; C p is the specific heat at constant pressure of air; T', w', q' are the vertical temperature, wind speed and humidity fluctuation values, respectively.

[0092] (4) Evapotranspiration simulation using the SWH model

[0093] In this embodiment, the evapotranspiration of the green ecosystem in A City at the regional scale was simulated using the SWH model. Compared with other models, the SWH model combines an evapotranspiration process model with a remote sensing model, and has both mechanism and applicability in evapotranspiration simulation. The driving data required by the SWH model are only remote sensing data such as vegetation coverage index (NDVI) and leaf area index (LAI), and 8 meteorological factors such as precipitation, which are easy to obtain and facilitate the estimation of ET and GPP at large scale and regional scale. The SWH model can estimate plant transpiration and soil evaporation respectively, and also simulate total primary productivity, which is convenient for in-depth analysis of the mechanism of the evapotranspiration process and revealing the coupling relationship of the carbon and water cycles in the ecosystem.

[0094] (5) Interpretation of remote sensing images

[0095] The spatial resolution of the remote sensing data was 30 m. Considering the image quality and the quality of the sensors of the Landsat series satellites, five remote sensing images covering A City in winter in 2000, 2005, 2010, 2015 and 2020 were finally selected for the inversion of the distribution of urban green space and the analysis of the spatiotemporal changes. In order to eliminate the distortion caused by atmospheric scattering, absorption and reflection in the remote sensing data, the FLASS module of ENVI5.1 was used to perform radiation calibration and atmospheric correction on the six image data obtained, so as to eliminate the error influence of the atmosphere on the data. The corrected data were spliced and cropped to obtain remote sensing image data of A City in different periods.

[0096] (6) Response mechanism and coupling of urban vegetation evapotranspiration and ecological process factors

[0097] Because of the highly nonlinear characteristics and scale effects of the eco-hydrological processes in urban green space ecosystems, the interaction mechanism between evapotranspiration and ecological process factors in urban green space ecosystems will be analyzed through nonlinear regression models. Nonlinear regression is a regression with nonlinear structure of unknown regression coefficients. Commonly used processing methods include linear iteration of regression function, piecewise regression, and iterative least squares. The main content of nonlinear regression analysis is similar to that of linear regression analysis. However, in many practical problems, the regression function is often a complex nonlinear function. The solution of nonlinear function can be divided into two categories: nonlinear transformation into linear and nonlinear transformation that cannot be transformed into linear. The basic method for processing nonlinear regression that can be linearized is to transform nonlinear regression into linear regression through variable transformation, and then use linear regression method for processing. It is assumed that the nonlinear expression between output variable and input variable has been obtained according to theory or experience, but the coefficients of the expression are unknown, and the values of the coefficients need to be determined according to n observations of input and output. According to the least squares method, the coefficient values are obtained, and the model obtained is a nonlinear regression model. For the nonlinear regression problems that cannot be linearly processed in actual scientific research, a least squares method based on regression problems is proposed. In the problem of minimizing the error square sum, a mathematical solution of the unconstrained extreme value problem in the optimization method, the simplex method, is applied. In the case of mastering the least squares method, the key to solving the above problem is to determine the curve type and how to convert it into a linear model. Determining the curve type generally considers two aspects: one is to derive or infer theoretically according to professional knowledge, and the other is to determine the general type of the curve by drawing and observing the scatter plot in the case of no professional knowledge. The specific process of the interaction mechanism between evapotranspiration and ecological process factors in urban green space ecosystems is coupled through a multivariate nonlinear regression model, as shown in Figure 2 .

[0098] In urban agglomeration, the spatial and temporal variation characteristics of ecological process and hydrological process of urban green space ecosystem at different time and space scales are not clear, especially for A as a representative of super large city, in the construction and planning of urban green space, the ecological process and evapotranspiration characteristics of specific green vegetation are lack of enough understanding. The invention comprehensively considers the response mechanism of evapotranspiration and ecological process of A city green space ecosystem, and plans to collect meteorological, hydrological, remote sensing and urban ecological station observation data from 1990 to 2020, and at the same time, build a SWH model database. Through the observation of urban ecological station, the spatial and temporal variation characteristics of super large urban green space ecosystem structure and ecological process in complex environment are analyzed, and the spatial and temporal variation characteristics of green space ecosystem evapotranspiration in super large urban community scale are explored. Through SWH model simulation, the spatial and temporal variation characteristics of A city green space ecosystem evapotranspiration are analyzed, and the action mechanism of urban green space ecosystem evapotranspiration and ecological process is clarified. Through the analysis of the correlation characteristics and interaction relationship between each factor of evapotranspiration and ecological process of urban green space ecosystem at different time and space scales, the coupling mechanism of evapotranspiration and ecological process of super large urban green space ecosystem is explored. In order to provide theoretical and data support for A city green space management and sponge city construction.

[0099] It is apparent to those skilled in the art that the application is not limited to the details of the foregoing exemplary embodiments and that the present application can be implemented in other particular forms without departing from the spirit or essential characteristics of the application. The presently disclosed embodiments are therefore considered in all respects to be illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalents of the claims are therefore intended to be embraced therein.

[0100] Furthermore, it should be understood that although the present specification is described in terms of embodiments, not every implementation embodies an independent technical solution, and the description of the specification is only for the sake of clarity, and those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can be combined appropriately to form other embodiments that those skilled in the art can understand.

Claims

1. A method for analyzing the spatiotemporal variation characteristics of evapotranspiration in urban green space ecosystems, characterized in that, Based on different vegetation types, communities, and regional scales, this study employs methods such as field plot surveys, fixed-point observations, mobile observations, and model simulations to analyze the eco-hydrological processes of urban green space ecosystems, encompassing the atmosphere, vegetation, and soil. The specific steps include: S1. At the individual tree scale, analyze the ecological processes of trees by observing changes in phenological growth, leaf area index, and photosynthetic physiology; observe the hydrological cycle process of individual trees using trunk sap flow meters, canopy interception, trunk stem flow, and penetrating rain sensors. S2. At the community scale, the ecological characteristics of dominant vegetation communities are analyzed through plot surveys and regular manual observations, and the evapotranspiration characteristics of vegetation communities are studied through water balance fields and flux observation towers. S3. At the regional scale, by establishing an SWH model database, the evapotranspiration of urban green space ecosystems is simulated and analyzed; TM imagery is used to interpret urban surface vegetation cover, NDVI, and leaf area index to analyze the characteristics of changes in urban vegetation ecological processes; based on the impact of urban surface vegetation changes and growth on hydrological processes, the spatiotemporal variation characteristics of eco-hydrological processes in urban green space ecosystems are analyzed. S4. Using the research results on ecological processes and evapotranspiration of urban green space ecosystems at different scales, combined with the simulation results of SWH model under different vegetation cover scenarios, through mathematical statistical analysis and model simulation methods, we will clarify the relationship between evapotranspiration and ecological processes of urban green space ecosystems, and couple the response mechanism of evapotranspiration of urban green space ecosystems to its ecological processes. Step S2, studying the evapotranspiration characteristics of vegetation communities through a water balance field, includes the following sub-steps: The measurement of hydrological processes follows the principle of water balance, and the water balance equation is: （1） In formula 1, P For rainfall, S Evapotranspiration I s For canopy interception, E w Forest evapotranspiration △w This refers to the change in soil water storage. S2-1. Measurement of transpiration of single vegetation plant Identify the sapwood and heartwood based on color; drill the core material at breast height (DBH) using a growth cone and measure the sapwood thickness with a ruler; based on the survey data for each tree, and after determining the quantitative relationship between DBH and sapwood area, calculate the sapwood area of ​​the sample tree and the total sapwood area per unit area of ​​the sample plot; sum the sap flow density of the trunk over 24 hours to obtain the sap flow rate per unit sapwood area; sum the sap flow velocity over 24 hours to obtain the transpiration rate of a single plant. S2-2, Measurement of Canopy Interception The canopy interception is calculated by measuring rainfall outside the forest, rainfall inside the forest, and trunk runoff. I s ; S2-3. Measurement of changes in soil water storage Soil moisture content was determined using the oven-drying method, and the change in soil water storage was calculated based on the soil moisture content. △w ; S2-4 Calculation of forest understory evapotranspiration Rainfall P Canopy interception I s Transpiration of artificial vegetation S Changes in soil water storage △w All can be measured, including forest understory evapotranspiration. E w It can be derived from Formula 1; （2） Transitivity of trees and evapotranspiration of the forest understory E w Summing these values ​​will give you the evapotranspiration of the artificial vegetation. In step S2, the calculation formula for the evapotranspiration characteristics of the vegetation community observed by the flux observation tower is as follows: （3） （4） In the formula: λ is the latent heat of water vaporization; H For sensible heat flux; ET Latent heat flux; ρ a air density; C p The specific heat at constant pressure of air; T ', w ', q ' represents the vertical temperature, wind speed, and humidity fluctuation values, respectively.

2. The method for analyzing the spatiotemporal variation characteristics of urban green space ecosystem evapotranspiration according to claim 1, characterized in that, In step S2, the ecological characteristics of the vegetation community include species composition, cover, biomass, abundance, structure, and phenological characteristics.

3. The method for analyzing the spatiotemporal variation characteristics of urban green space ecosystem evapotranspiration according to claim 1, characterized in that, In step S4, by analyzing the correlation characteristics and interaction relationships between various factors of evapotranspiration and ecological processes in urban green space ecosystems at different temporal and spatial scales, the factor coupling of the interaction mechanism between evapotranspiration and ecological processes in urban green space ecosystems is coupled through a multivariate nonlinear regression model.

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