Method and device for determining evapotranspiration

Abstract

The application provides a method and device for determining the amount of surface evapotranspiration, wherein the method comprises: processing remote sensing monitoring data of a surface into remote sensing monitoring data of the surface with consistent spatial and temporal resolutions; calculating vegetation transpiration, soil evaporation, canopy interception evaporation, water body evaporation and ice and snow sublimation in a target region according to the remote sensing monitoring data of the surface with consistent spatial and temporal resolutions; and determining the total amount of surface evapotranspiration in the target region according to the vegetation transpiration, soil evaporation, canopy interception evaporation, water body evaporation and ice and snow sublimation in the target region. The above technical solution improves the accuracy of the determination of the amount of evapotranspiration and realizes continuous high-resolution estimation of evapotranspiration.

Description

Technical Field

[0001] This invention relates to the field of surface evapotranspiration technology, and in particular to a method and apparatus for determining surface evapotranspiration. Background Technology

[0002] Evapotranspiration (ET) encompasses both evaporation from soil and plant surfaces and sublimation from snow and ice, as well as transpiration through plant surfaces and cells. It is a continuous process occurring within a highly complex system. 70% of atmospheric precipitation falling to the Earth's surface returns to the atmosphere via evapotranspiration, reaching as high as 90% in arid regions, demonstrating that evapotranspiration is a crucial link in the water cycle. Furthermore, since water absorbs heat during vaporization (latent heat flux), evapotranspiration is also an important component of the Earth's surface energy balance. In addition, photosynthesis and transpiration are two of the most important physiological and ecological processes for energy flow and material cycling in ecosystems. Surface evapotranspiration is not only a vital ecological process coupled with the carbon cycle in terrestrial ecosystems but also a crucial link between ecological and hydrological processes. Therefore, research on surface evapotranspiration is of great significance for understanding regional energy balance, water cycling, and biogeochemical cycles.

[0003] In the field of remote sensing evapotranspiration monitoring, the academic community has developed dozens of remote sensing evapotranspiration estimation methods based on various remote sensing surface parameters, such as the traditional SEBAL and SEBS methods. Traditional energy balance-based remote sensing evapotranspiration is greatly affected by clouds, making it difficult to obtain continuous spatiotemporal evapotranspiration products. Currently, more and more studies are beginning to use mechanistic models based on quantitative remote sensing products to obtain actual surface evapotranspiration, such as the MOD16 algorithm developed by the University of Montana and the GLEAM algorithm developed by VU University Amsterdam. However, the accuracy of current algorithms still needs improvement, and they are unable to achieve continuous spatiotemporal high-resolution evapotranspiration estimation, thus failing to meet the major national needs for efficient water resource development and utilization.

[0004] It is evident that existing methods for determining evapotranspiration have low accuracy and are insufficient for achieving continuous, high-resolution evapotranspiration estimation in time and space. Summary of the Invention

[0005] This invention provides a method for determining surface evapotranspiration, thereby improving the accuracy of surface evapotranspiration determination and achieving spatiotemporally continuous high-resolution evapotranspiration estimation. The method includes:

[0006] Surface remote sensing monitoring data is processed into surface remote sensing monitoring data with consistent spatiotemporal resolution;

[0007] Based on surface remote sensing monitoring data with consistent spatiotemporal resolution, calculate vegetation transpiration, soil evaporation, canopy intercepted evaporation, water evaporation, and snow and ice sublimation within the target area;

[0008] The total surface evapotranspiration in the target area is determined based on vegetation evaporation, soil evaporation, canopy intercepted evaporation, water evaporation, and snow and ice sublimation.

[0009] In one embodiment, the surface remote sensing monitoring data includes: surface temperature, air pressure, wind speed, surface downwave radiation, surface longwave radiation, surface humidity, and vegetation index.

[0010] Processing surface remote sensing data into surface remote sensing data with consistent spatiotemporal resolution includes:

[0011] Using statistical downscaling methods, surface temperature, air pressure, wind speed, surface downwave radiation, and surface longwave radiation are processed into surface remote sensing monitoring data with consistent spatiotemporal resolution.

[0012] By using irregular triangle regression, brightness temperature scale, or spatial downscaling method based on thermal inertia, surface humidity is processed into surface remote sensing monitoring data with consistent spatiotemporal resolution.

[0013] Using the time series harmonic analysis method based on Fourier transform, vegetation indices are processed into spatiotemporally continuous surface remote sensing monitoring data.

[0014] Using the GDAL tool, the projections of surface temperature, air pressure, wind speed, surface downwave radiation, surface downwave radiation, surface humidity, and vegetation index are processed into a consistent projection.

[0015] In one embodiment, based on surface remote sensing monitoring data with consistent spatiotemporal resolution, the following calculations are made for vegetation transpiration, soil evaporation, canopy intercepted evaporation, water evaporation, and snow and ice sublimation within the target area:

[0016] Calculate the net surface radiation based on surface albedo, surface emissivity, surface downdraft shortwave radiation, surface downdraft longwave radiation, and surface temperature; calculate the net radiation consumed by vegetation transpiration and the net radiation consumed by soil evaporation based on the net surface radiation.

[0017] The vegetation transpiration rate in the target area is calculated based on net radiation consumed by vegetation transpiration, aerodynamic impedance of the vegetation canopy, vegetation canopy resistance, and surface temperature. The soil evaporation rate in the target area is calculated based on net radiation consumed by soil evaporation, surface heat flux, soil aerodynamic impedance, and soil surface resistance. The canopy interception evaporation rate in the target area is calculated based on rainfall and rainfall frequency. The water evaporation rate in the target area is calculated based on net surface radiation and surface heat flux. The snow and ice sublimation rate in the target area is calculated based on wind speed.

[0018] In one embodiment, the net surface radiation is calculated based on surface albedo, surface emissivity, downward shortwave radiation, downward longwave radiation, and surface temperature, including: calculating the net surface radiation according to the following formula:

[0019] Rn=(1-α)Rs ↓ +εR L↓ -σεT s 4 ;

[0020] Where Rn is the net surface radiation, α is the surface albedo, ε is the surface emissivity, and Rs is the surface emissivity. ↓ For surface downwave shortwave radiation, R L↓ For downward longwave radiation from the Earth's surface, σ is the Stefan-Boltzmann constant, and T s This refers to the Earth's surface temperature.

[0021] In one embodiment, calculating the net radiation loss due to vegetation transpiration and the net radiation loss due to soil evaporation based on the net surface radiation includes: calculating the net radiation loss due to vegetation transpiration according to the following formula:

[0022] Rn c =Fc(Rn-Rn) i );

[0023] Based on the net surface radiation, calculate the net radiation loss due to vegetation transpiration and the net radiation loss due to soil evaporation, including calculating the net radiation loss due to soil evaporation using the following formula:

[0024] Rn s =(1-Fc)(Rn-Rn) i );

[0025] Where Rn is the net radiation at the Earth's surface, Rn = Rn i +Rn c +Rn s , Rn i To retain net radiation from evaporative emissions in the canopy, Rn c For the net radiation consumed by vegetation transpiration, Rn s Fc represents the net radiation consumed by soil evaporation, and Fc is the vegetation cover index.

[0026] In one embodiment, the vegetation transpiration rate within a target area is calculated based on net radiation consumed by vegetation transpiration, aerodynamic impedance of the vegetation canopy, canopy resistance, and surface temperature, including: vegetation transpiration rate within the target area according to the following formula:

[0027] T r =C c PM c / λ;

[0028]

[0029] C c ={1+R c R a / [R s (R c +R a )]} -1 ;

[0030] R a =(Δ+γ)r a,a ;

[0031] R s =(Δ+γ)r a,s +γr s,s ;

[0032] R c =(Δ+γ)r a,c +γr s,c ;

[0033] Among them, T r G is the vegetation transpiration rate, G is the surface heat flux, Δ is the slope of the tangent line to the temperature-saturated vapor pressure curve at temperature T (K), ρ is the air density, and c is the density of the air. p Let λ be the isothermal specific heat of air, γ be the latent heat of vaporization, γ be the wet / dry surface constant, D be the vapor pressure deficit at the height of the vegetation canopy, and r be the pressure of vaporization. s,s r s,c r a,c r a,s and r a,a These are, respectively, soil surface impedance, canopy surface impedance, canopy boundary layer aerodynamic impedance, aerodynamic impedance between soil surface and canopy source-sink height, and aerodynamic impedance between the canopy source-sink height and a reference height, PM. c C represents the potential transpiration of vegetation. c R is the vegetation transpiration resistance coefficient. n For net surface radiation, R n,s R represents the net radiation flux of the soil. a R c and R s To calculate the impedance coefficient (C c Intermediate variables in the process.

[0034] In one embodiment, calculating soil evaporation within a target area based on net radiation consumed by soil evaporation, surface heat flux, soil aerodynamic impedance, and soil surface impedance includes: calculating soil evaporation within the target area according to the following formula:

[0035] E s =C sPM s / λ;

[0036]

[0037] C s ={1+R s R a / [R c (R s +R a )]} -1 ;

[0038] R a =(Δ+γ)r a,a ;

[0039] R s =(Δ+γ)r a,s +γr s,s ;

[0040] R c =(Δ+γ)r a,c +γr s,c ;

[0041] Among them, E s Let G be the soil evaporation, G be the surface heat flux, Δ be the slope of the tangent line to the temperature-saturated vapor pressure curve at temperature T (K), ρ be the air density, and c be the density of the air. p The isothermal specific heat of air, λ is the latent heat of vaporization, γ is the wet / dry surface constant, D is the vapor pressure deficit at the height of the vegetation canopy, and r s,s r s,c r a,c r a,s and r a,a (sm -1 These represent the soil surface impedance, canopy surface impedance, canopy boundary layer aerodynamic impedance, aerodynamic impedance between the soil surface and the canopy source-sink height, and aerodynamic impedance between the canopy source-sink height and the reference height, respectively. s C represents the potential evaporation of the soil. s R is the soil evaporation resistance coefficient. n For net surface radiation, R n,c R is the net radiation flux of the canopy. a R c and R s To calculate the impedance coefficient (C s Intermediate variables in the process.

[0042] In one embodiment, calculating the canopy evaporation interception rate within the target area based on the rainfall amount and rainfall frequency within the target area includes: calculating the canopy evaporation interception rate within the target area according to the following formula:

[0043]

[0044] Among them, E I P represents the amount of evaporation retained by the canopy. g,i Let P' be the rainfall amount of the i-th (1≤i≤n) rainfall event, n be the number of rainfall events, ER be the ratio of potential evaporation rate to precipitation rate during the rainfall period, and P' be the precipitation rate. g Fc is the vegetation cover index, representing the precipitation rate required to achieve canopy saturation.

[0045] In one embodiment, calculating the water evaporation rate within a target area based on net surface radiation and surface heat flux includes: calculating the water evaporation rate within the target area according to the following formula:

[0046] Ew=(Δ(Rn-G)+ρc p VPD / r a ) / (λΔ+λγ);

[0047] Where Ew is the water evaporation rate, Δ is the surface temperature, ρ is the air density, and c is the density of the air. p The isothermal specific heat of air, λ is the latent heat of vaporization, γ is the wet / dry surface constant, and r a Where is the atmospheric dynamic impedance, VPD is the saturated vapor pressure deficit, G is the surface heat flux, and Rn is the net surface radiation.

[0048] In one embodiment, calculating the amount of snow and ice sublimation in a target area based on wind speed includes: calculating the amount of snow and ice sublimation in the target area according to the following formula:

[0049] E snow =(0.18+0.098u) 10 VPD;

[0050] Among them, E snow For the amount of sublimation of ice and snow, u 10 The wind speed is at a height of 10m, and VPD represents the saturated vapor pressure deficit.

[0051] This invention also provides a device for determining surface evapotranspiration, to improve the accuracy of surface evapotranspiration determination and achieve spatiotemporal continuous high-resolution evapotranspiration estimation. The device includes:

[0052] The surface remote sensing monitoring data preprocessing module is used to process surface remote sensing monitoring data into surface remote sensing monitoring data with consistent spatiotemporal resolution;

[0053] Each evapotranspiration determination module is used to calculate vegetation evaporation, soil evaporation, canopy intercepted evaporation, water evaporation, and snow and ice sublimation within the target area based on surface remote sensing monitoring data with consistent spatiotemporal resolution.

[0054] The module for determining total surface evapotranspiration is used to determine the total surface evapotranspiration within a target area based on vegetation evaporation, soil evaporation, canopy intercepted evaporation, water evaporation, and snow and ice sublimation.

[0055] In one embodiment, the surface remote sensing monitoring data includes: surface temperature, air pressure, wind speed, surface downwave radiation, surface longwave radiation, surface humidity, and vegetation index.

[0056] The surface remote sensing monitoring data preprocessing module is specifically used for:

[0057] Processing surface remote sensing data into surface remote sensing data with consistent spatiotemporal resolution includes:

[0058] Using statistical downscaling methods, surface temperature, air pressure, wind speed, surface downwave radiation, and surface longwave radiation are processed into surface remote sensing monitoring data with consistent spatiotemporal resolution.

[0059] By using irregular triangle regression, brightness temperature scale, or spatial downscaling method based on thermal inertia, surface humidity is processed into surface remote sensing monitoring data with consistent spatiotemporal resolution.

[0060] Using the time series harmonic analysis method based on Fourier transform, vegetation indices are processed into spatiotemporally continuous surface remote sensing monitoring data.

[0061] Using the GDAL tool, the projections of surface temperature, air pressure, wind speed, surface downwave radiation, surface downwave radiation, surface humidity, and vegetation index are processed into a consistent projection.

[0062] In one embodiment, each evaporation rate determination module is specifically used for:

[0063] Calculate the net surface radiation based on surface albedo, surface emissivity, surface downdraft shortwave radiation, surface downdraft longwave radiation, and surface temperature; calculate the net radiation consumed by vegetation transpiration and the net radiation consumed by soil evaporation based on the net surface radiation.

[0064] The vegetation transpiration rate in the target area is calculated based on net radiation consumed by vegetation transpiration, aerodynamic impedance of the vegetation canopy, vegetation canopy resistance, and surface temperature. The soil evaporation rate in the target area is calculated based on net radiation consumed by soil evaporation, surface heat flux, soil aerodynamic impedance, and soil surface resistance. The canopy interception evaporation rate in the target area is calculated based on rainfall and rainfall frequency. The water evaporation rate in the target area is calculated based on net surface radiation and surface heat flux. The snow and ice sublimation rate in the target area is calculated based on wind speed.

[0065] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-described method for determining surface evapotranspiration.

[0066] This invention also provides a computer-readable storage medium storing a computer program that performs the above-described method for determining surface evapotranspiration.

[0067] Compared with existing methods for determining surface evapotranspiration, firstly, the technical solution provided in this invention preprocesses surface remote sensing monitoring data into surface remote sensing monitoring data with consistent spatiotemporal resolution, laying the foundation for determining spatiotemporally continuous high-resolution evapotranspiration; secondly, the technical solution provided in this invention considers the detailed components of evapotranspiration, and calculates vegetation transpiration, soil evaporation, canopy intercepted evaporation, water evaporation, and snow and ice sublimation based on surface remote sensing monitoring data with consistent spatiotemporal resolution, providing more detailed and comprehensive evapotranspiration estimation results, improving the accuracy of evapotranspiration determination, and realizing spatiotemporally continuous high-resolution evapotranspiration estimation. Attached Figure Description

[0068] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, are not intended to limit the scope of the invention. In the drawings:

[0069] Figure 1 This is a flowchart illustrating the method for determining surface evapotranspiration in an embodiment of the present invention;

[0070] Figure 2 This is a flowchart illustrating a method for determining surface evapotranspiration in another embodiment of the present invention;

[0071] Figure 3 This is a ground verification of the method for determining surface evapotranspiration in Yingke, Heihe River Basin, my country, in this embodiment of the invention, and a comparison diagram with the MOD16 estimation results in the prior art.

[0072] Figure 4 This is a ground verification of the method for determining surface evapotranspiration in Arou, Heihe River Basin, my country, in this embodiment of the invention, and a comparison diagram with the MOD16 estimation results in the prior art.

[0073] Figure 5 This is a ground verification of the method for determining surface evapotranspiration in Guantan, Heihe River Basin, my country, in this embodiment of the invention, and a comparison diagram with the MOD16 estimation results in the prior art.

[0074] Figure 6 This is a schematic diagram of the structure of the device for determining surface evapotranspiration in an embodiment of the present invention. Detailed Implementation

[0075] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the embodiments and accompanying drawings. Here, the illustrative embodiments and descriptions of this invention are used to explain the invention, but are not intended to limit the invention.

[0076] This invention provides an evapotranspiration estimation scheme based on multi-source remote sensing data. It can consider surface processes based on large amounts of remote sensing data, providing spatiotemporally continuous high-resolution evapotranspiration estimation capabilities for regions and even globally. The scheme is described below.

[0077] Figure 1 This is a flowchart illustrating the method for determining surface evapotranspiration in an embodiment of the present invention; as shown below. Figure 1 As shown, the method includes the following steps:

[0078] Step 101: Process the surface remote sensing monitoring data into surface remote sensing monitoring data with consistent spatiotemporal resolution;

[0079] Step 102: Based on the surface remote sensing monitoring data with consistent spatiotemporal resolution, calculate the vegetation evaporation, soil evaporation, canopy intercepted evaporation, water evaporation, and snow and ice sublimation in the target area;

[0080] Step 103: Determine the total surface evapotranspiration in the target area based on vegetation evaporation, soil evaporation, canopy intercepted evaporation, water evaporation, and snow and ice sublimation.

[0081] Compared with existing methods for determining surface evapotranspiration, firstly, the technical solution provided in this invention preprocesses surface remote sensing monitoring data into surface remote sensing monitoring data with consistent spatiotemporal resolution, laying the foundation for determining spatiotemporally continuous high-resolution evapotranspiration; secondly, the technical solution provided in this invention considers the detailed components of evapotranspiration, and calculates vegetation transpiration, soil evaporation, canopy intercepted evaporation, water evaporation, and snow and ice sublimation based on surface remote sensing monitoring data with consistent spatiotemporal resolution, providing more detailed and comprehensive evapotranspiration estimation results, improving the accuracy of evapotranspiration determination, and achieving spatiotemporally continuous high-resolution evapotranspiration estimation.

[0082] (I) Step 101 above is the step of preprocessing the surface remote sensing monitoring data. The following is a description of step 101.

[0083] The aforementioned preprocessing steps primarily involve using methods such as downscaling, time-series reconstruction, and spatial projection transformation to generate input data with consistent spatiotemporal resolution from input data with different spatiotemporal resolutions. This output data serves as the driving data for the method used to determine surface evapotranspiration. This input data is the surface remote sensing monitoring data, which forms the basis of the method for determining surface evapotranspiration.

[0084] In one embodiment, surface remote sensing monitoring data may include: surface temperature, air pressure, wind speed, surface downwave radiation, surface downwave radiation, surface humidity, and vegetation index.

[0085] Processing surface remote sensing data into surface remote sensing data with consistent spatiotemporal resolution can include:

[0086] 1. Using statistical downscaling methods, surface air temperature, dew point temperature, air pressure, wind speed, surface downwave radiation, and surface longwave radiation are processed to achieve the same spatiotemporal resolution as other surface remote sensing monitoring data.

[0087] In practice, this downscaling method involves downscaling atmospheric driving data. Atmospheric driving data typically has a coarse spatial resolution. By using statistical downscaling, high spatial resolution atmospheric driving data can be obtained as input. The main variables include near-surface air temperature, dew point temperature, air pressure, wind speed, downward shortwave radiation, and downward longwave radiation. For example, for low-resolution air temperature, dew point temperature, and air pressure, since their values ​​exhibit a clear regularity with elevation, the data are first converted to sea-level air temperature, dew point temperature, and air pressure based on low-resolution elevation data. Then, bilinear interpolation is used to interpolate them from low resolution to high resolution. Finally, high-resolution elevation data is used to convert them to high-resolution air temperature, dew point temperature, and air pressure at the Earth's surface. For low-resolution downward longwave radiation, the low-resolution atmospheric emissivity is first calculated based on the low-resolution downward longwave radiation and air temperature data. Then, bilinear interpolation is used to interpolate it from low resolution to high resolution. Finally, high-resolution downward longwave radiation is calculated by combining it with high-resolution air temperature data. For low-resolution downward shortwave radiation, the low-resolution atmospheric transmittance is first calculated based on the low-resolution downward shortwave radiation. Then, bilinear interpolation is used to interpolate it from low resolution to high resolution. Finally, high-resolution downward shortwave radiation is calculated by combining it with high-resolution aspect and slope data.

[0088] 2. Using irregular triangle regression, brightness temperature scale, or thermal inertia-based spatial downscaling methods, surface humidity is processed into surface remote sensing monitoring data with consistent spatiotemporal resolution.

[0089] In practical implementation, this downscaling method is to downscale the coarse-resolution surface soil moisture (land surface humidity). The spatial resolution of surface soil moisture acquired by spaceborne microwave remote sensing is relatively coarse. Methods such as regression based on irregular triangles, brightness-temperature downscaling, and spatial downscaling based on thermal inertia can be used to obtain surface soil moisture with high spatial resolution. For example, in the regression based on irregular triangles, low-resolution surface humidity is used as the dependent variable, and low-resolution vegetation index, surface temperature, and albedo are used as independent variables. Each variable is normalized to eliminate the influence of dimensions. Then, a multiple regression equation is established and applied to the normalized high-resolution vegetation index, surface temperature, and albedo to obtain high-resolution surface humidity, making it consistent with the spatiotemporal resolution of other surface remote sensing monitoring data.

[0090] 3. Using the time series harmonic analysis method based on Fourier transform, vegetation indices are processed into spatiotemporally continuous surface remote sensing monitoring data.

[0091] For example, for a noisy long-term vegetation index dataset from satellite observations, the time series corresponding to each pixel is fitted using several cosine functions of different frequencies. The fitted sequence is then compared with the original sequence. If the difference exceeds a pre-set threshold, the corresponding observation in the original sequence is considered a noisy observation and is removed. The remaining observations are then fitted again, and the noisy observations are removed. This process is iterated until no new noisy observations appear or the number of remaining observations reaches the minimum limit for sequence fitting, at which point the iteration stops. The result of the final fitting step is the final continuously reconstructed time series.

[0092] In practice, this downscaling method is essentially the process of reconstructing the time series of remotely sensed vegetation indices. Vegetation indices acquired through optical remote sensing are subject to noise from clouds, necessitating the use of Fourier transform-based time series harmonic analysis to reconstruct and obtain spatiotemporally continuous vegetation indices. This step resolves the technical problem in existing energy balance-based remote sensing evapotranspiration methods, which are heavily influenced by clouds and struggle to obtain spatiotemporally continuous, high-resolution evapotranspiration estimates, thus achieving spatiotemporally continuous, high-resolution evapotranspiration estimation.

[0093] 4. Using the GDAL tool, the projections of surface temperature, air pressure, wind speed, surface downdraft shortwave radiation, surface downdraft longwave radiation, surface humidity, and vegetation index are processed into a consistent projection.

[0094] GDAL is a free and open-source geographic information processing toolkit with powerful functions such as raster image data format conversion, projection transformation, and resampling. This toolkit is available at http: / / www.gdal.org / . When performing projection transformation on a dataset, the `gdalwrap` command from the toolkit will be used to process each image individually. An example command line format is as follows:

[0095] gdalwrap-t_srs srs_def srcfile dstfile

[0096] Where srs_def is the target projection parameter, and all datasets will be unified to this type of projection method, srcfile is the file name of the projection to be processed, and dstfile is the file name of the result file after the projection.

[0097] In practice, this step involves projecting and transforming the input data. Since different input data have different projections, tools such as GDAL are needed to reproject the input data onto a unified standard.

[0098] (II) Step 102 above distinguishes the detailed components of evapotranspiration and calculates the evapotranspiration of each component based on the consistent spatiotemporal resolution surface remote sensing monitoring data obtained in step 101 above. The following section combines... Figure 2 Step 102 will be described below.

[0099] In one embodiment, calculating vegetation transpiration, soil evaporation, canopy intercepted evaporation, water evaporation, and snow sublimation within a target area based on surface remote sensing monitoring data with consistent spatiotemporal resolution may include:

[0100] Calculate the net surface radiation based on surface albedo, surface emissivity, surface downdraft shortwave radiation, surface downdraft longwave radiation, and surface temperature; calculate the net radiation consumed by vegetation transpiration and the net radiation consumed by soil evaporation based on the net surface radiation.

[0101] The vegetation transpiration rate in the target area is calculated based on net radiation consumed by vegetation transpiration, aerodynamic impedance of the vegetation canopy, vegetation canopy resistance, and surface temperature. The soil evaporation rate in the target area is calculated based on net radiation consumed by soil evaporation, surface heat flux, soil aerodynamic impedance, and soil surface resistance. The canopy interception evaporation rate in the target area is calculated based on rainfall and rainfall frequency. The water evaporation rate in the target area is calculated based on net surface radiation and surface heat flux. The snow and ice sublimation rate in the target area is calculated based on wind speed.

[0102] Since net radiation is the most important driving factor in the estimation of evapotranspiration, we first introduce the calculation and redistribution of total net radiation at the Earth's surface in order to determine the available energy for evapotranspiration of different surface elements.

[0103] (1) Calculation of total net surface radiation. Net surface radiation is the energy source of evapotranspiration, controlling the sensible heat flux, latent heat flux, and soil heat flux entering the atmosphere. Latent heat flux is the energy carried away by evapotranspiration. Net radiation is the difference between the surface radiation budget and radiation expenditure, including shortwave radiation and longwave radiation.

[0104] In one embodiment, the net surface radiation is calculated based on surface albedo, surface emissivity, downward shortwave radiation, downward longwave radiation, and surface temperature, including: calculating the net surface radiation according to the following formula:

[0105] Rn=(1-α)Rs ↓ +εR L↓ -σεT s 4 ;

[0106] Wherein, Rn is the net surface radiation (W / m). -2 ), where α is the surface albedo, ε is the surface emissivity, and Rs ↓ For surface downwave shortwave radiation, R L↓ Downward longwave radiation from the Earth's surface (W m) -2 ), where σ is the Stefan-Boltzmann constant (5.67 × 10⁻⁶). -8 W m -2 K -4 ), T s T represents the surface temperature (K). s On a daily scale, temperature can be used instead.

[0107] (2) Introduction to the distribution of total net surface radiation. The distribution of net radiation is the allocation of total net radiation to various evapotranspiration amounts. In a vegetation-soil system, the sum of the net radiation used for vegetation transpiration, soil evaporation, and canopy interception evaporation equals the total net radiation. In practice, the net radiation consumed by canopy interception evaporation can be calculated by reversing the canopy interception evaporation amount, and the remaining net radiation can be redistributed between vegetation and soil according to the vegetation index.

[0108] In one embodiment, the calculation of net radiation loss due to vegetation transpiration and net radiation loss due to soil evaporation based on net surface radiation includes calculating net radiation loss due to vegetation transpiration according to the following formula:

[0109] Rn c =Fc(Rn-Rn) i );

[0110] Based on the net radiation at the Earth's surface, calculate the net radiation consumed by vegetation transpiration and the net radiation consumed by soil evaporation, including calculating the net radiation consumed by soil evaporation according to the following formula;

[0111] Rns =(1-Fc)(Rn-Rn) i );

[0112] Where Rn is the net radiation at the Earth's surface, Rn = Rn i +Rn c +Rn s , Rn i Net radiation (W / m²) retained by the canopy for evaporation consumption -2 ), Rn c Net radiation consumed by vegetation transpiration (W m) -2 ), Rn s Net radiation consumed by soil evaporation (Wm) -2 ), where Fc is the vegetation cover index.

[0113] Secondly, the calculation of each evapotranspiration rate is introduced: Evapotranspiration estimation estimates vegetation transpiration, soil evaporation, canopy intercepted evaporation, water evaporation, and snow and ice surface sublimation within the target area (pixel) according to different parameterization schemes, and calculates the total evapotranspiration. A detailed introduction follows.

[0114] First, let's explain the meaning of the aforementioned pixel parameterization scheme. This scheme mainly uses IGBP land cover data to distinguish the land cover type of each pixel (in this embodiment, the target area can be a pixel). Each pixel contains one or more types of vegetation, soil, water, and snow / ice. Among them, vegetation is further subdivided according to different vegetation functional types, and different vegetation physiological and ecological parameter values ​​are determined in combination with the vegetation functional types. The reasons for choosing each parameterization scheme and its beneficial effects will be explained when we specifically introduce the estimation of evapotranspiration of each component.

[0115] 1. Estimation of vegetation transpiration.

[0116] Vegetation transpiration is part of the soil-vegetation system. In this system, a multi-layered model scheme is employed. On sunny days, the Shuttleworth–Wallace dual-source model is used to estimate vegetation transpiration and soil evaporation separately. On rainy days, a precipitation interception evaporation estimation scheme is added. Therefore, the Shuttleworth–Wallace dual-source model is used for vegetation transpiration estimation.

[0117] In one embodiment, the vegetation transpiration rate within a target area is calculated based on net radiation consumed by vegetation transpiration, aerodynamic impedance of the vegetation canopy, canopy resistance, and surface temperature, including: vegetation transpiration rate within the target area according to the following formula:

[0118] T r =C c PM c / λ;

[0119]

[0120] C c ={1+R c R a / [R s (R c +R a )]} -1 ;

[0121] R a =(Δ+γ)r a,a ;

[0122] R s =(Δ+γ)r a,s +γr s,s ;

[0123] R c =(Δ+γ)r a,c +γr s,c ;

[0124] Among them, T r G is the vegetation transpiration rate, G is the surface heat flux, Δ is the slope of the tangent line to the temperature-saturated vapor pressure curve at temperature T (K), ρ is the air density, and c is the density of the air. p Let λ be the isothermal specific heat of air, γ be the latent heat of vaporization, γ be the wet / dry surface constant, D be the vapor pressure deficit at the height of the vegetation canopy, and r be the pressure of vaporization. s,s r s,c r a,c r a,s and r a,a These are, respectively, soil surface impedance, canopy surface impedance, canopy boundary layer aerodynamic impedance, aerodynamic impedance between soil surface and canopy source-sink height, and aerodynamic impedance between the canopy source-sink height and a reference height, PM. c C represents the potential transpiration of vegetation. c R is the vegetation transpiration resistance coefficient. n For net surface radiation, R n,s R represents the net radiation flux of the soil. a R c and R s To calculate the impedance coefficient (C c Intermediate variables in the process.

[0125] In practice, the aerodynamic impedance of the vegetation canopy is estimated based on the canopy height and wind speed; a Jarvis-type model is used to estimate the vegetation canopy resistance based on the surface downwave radiation, air temperature, water vapor pressure difference, and root zone soil moisture; Δ is the slope of the tangent line of the saturated water vapor pressure relationship curve at temperature T (K).

[0126] 2. Soil Evaporation Estimation. Soil evaporation in the soil-vegetation system is estimated using a multi-layer model. On sunny days, the Shuttleworth–Wallace dual-source model is used to estimate vegetation transpiration and soil evaporation separately. On rainy days, a precipitation interception evaporation estimation scheme is incorporated. Therefore, the Shuttleworth–Wallace dual-source model is used for soil evaporation estimation in the soil-vegetation system. (Compared to the soil-vegetation system, if the soil is bare, vegetation transpiration is ignored, and a single-layer model is used).

[0127] In one embodiment, the soil evaporation rate within a target area is calculated based on net radiation consumed by soil evaporation, surface heat flux, soil aerodynamic impedance, and soil surface impedance, including calculating the soil evaporation rate within the target area according to the following formula:

[0128] E s =C s PM s / λ;

[0129]

[0130] C s ={1+R s R a / [R c (R s +R a )]} -1 ;

[0131] R a =(Δ+γ)r a,a ;

[0132] R s =(Δ+γ)r a,s +γr s,s ;

[0133] R c =(Δ+γ)r a,c +γr s,c ;

[0134] Among them, E s Let G be the soil evaporation, G be the surface heat flux, Δ be the slope of the tangent line to the temperature-saturated vapor pressure curve at temperature T (K), ρ be the air density, and c be the density of the air. p The isothermal specific heat of air, λ is the latent heat of vaporization, γ is the wet / dry surface constant, D is the vapor pressure deficit at the height of the vegetation canopy, and r s,s r s,c r a,c r a,s and r a,a (sm -1These represent the soil surface impedance, canopy surface impedance, canopy boundary layer aerodynamic impedance, aerodynamic impedance between the soil surface and the canopy source-sink height, and aerodynamic impedance between the canopy source-sink height and the reference height, respectively. s C represents the potential evaporation of the soil. s R is the soil evaporation resistance coefficient. n For net surface radiation, R n,c R is the net radiation flux of the canopy. a R c and R s To calculate the impedance coefficient (C s Intermediate variables in the process.

[0135] 3. Canopy interception evaporation estimation. In practice, the RS-Gash model is used for estimation. The RS-Gash model is an improvement on the classic point-scale Gash precipitation interception model and can be used to calculate precipitation interception evaporation in regional-scale non-uniform vegetation.

[0136] In one embodiment, the canopy evaporation interception in the target area is calculated based on the rainfall amount and rainfall frequency within the target area, including calculating the canopy evaporation interception in the target area according to the following formula:

[0137]

[0138] Among them, E I Evaporation interception by the canopy (mm d) -1) P g,i Let be the rainfall amount (mmd) of the i-th (1≤i≤n) rainfall event. -1 ), where n is the number of rainfall events, ER is the ratio of potential evaporation rate to precipitation rate during rainfall, and P′ g Fc is the vegetation cover index, representing the precipitation rate required to achieve canopy saturation.

[0139] 4. Evaporation estimation. Water surface evaporation is a type of evaporation with a consistently sufficient water supply. Therefore, a single-layer model scheme is adopted, specifically using the single-layer Penman formula for calculation.

[0140] In one embodiment, the evaporation of water bodies within a target area is calculated based on net surface radiation and surface heat flux, including calculating the evaporation of water bodies within the target area according to the following formula:

[0141] Ew=(Δ(Rn-G)+ρc p VPD / r a ) / (λΔ+λγ);

[0142] Where Ew is the water evaporation rate, Δ is the surface temperature, ρ is the air density, and c is the density of the air. pThe isothermal specific heat of air, λ is the latent heat of vaporization, γ is the wet / dry surface constant, and r a Where is the atmospheric dynamic impedance, VPD is the saturated vapor pressure deficit, G is the surface heat flux, and Rn is the net surface radiation.

[0143] 5. Snow and Ice Sublimation Estimation. Snow and ice sublimation is a special case of water surface evaporation. Sublimation occurs when the water vapor pressure above the snow and ice is lower than the saturated water vapor pressure at the given temperature. Therefore, a single-layer model scheme is used. This invention provides two snow and ice sublimation estimation schemes. The first scheme is the same as the water evaporation estimation scheme, using the single-layer Penman formula for calculation; the second scheme uses the WMO recommended empirical equation for estimation.

[0144] In one embodiment, calculating the amount of snow and ice sublimation in a target area based on wind speed includes: calculating the amount of snow and ice sublimation in the target area according to the following formula:

[0145] E snow =(0.18+0.098u) 10 VPD;

[0146] Among them, E snow For the amount of sublimation of ice and snow, u 10 The wind speed is at a height of 10m, and VPD represents the saturated vapor pressure deficit.

[0147] (III) Step 103 is the process of determining the total evapotranspiration. The total evapotranspiration of a pixel (target area) is equal to the sum of vegetation transpiration, soil evaporation, canopy interception evaporation, water evaporation, and snow and ice surface sublimation within that pixel.

[0148] The following is in conjunction with the appendix Figures 3 to 5 This paper introduces the method for determining surface evapotranspiration provided in the embodiments of the present invention, and verifies the results of surface evapotranspiration estimation. Based on observations from surface flux stations, latent heat flux is converted into actual evapotranspiration, which verifies the accuracy of the evapotranspiration results of this algorithm. Based on the Yingke (…) method for determining surface evapotranspiration in the Heihe River Basin of my country… Figure 3 ), Arou Figure 4 ), Guantan ( Figure 5 The verification results at the station show that the algorithm's estimated evapotranspiration is highly comparable to that of surface observations, indicating that the proposed method has high accuracy in estimating evapotranspiration and can effectively capture the spatiotemporal variations of actual surface evapotranspiration. The root mean square error (RMSE) is between 0.38 and 0.59 mm / day, and the coefficient of determination (R²) is... 2 Its evaporation rate is between 0.87 and 0.96, which is superior to the internationally renowned MODIS official evaporation product (MOD16). As mentioned above and in the attached... Figures 3 to 5As can be seen (where hollow rhombuses represent the results of the implementation of this invention, black solid lines represent the fitting lines between the results of the implementation of this invention and surface observations, solid triangles represent the results of MOD16, the official evapotranspiration product of the internationally renowned MODIS, black dashed lines represent the fitting lines between MOD16 results and surface observations, and gray solid lines represent 1:1 lines), the technical solution provided by the embodiments of this invention improves the accuracy of evapotranspiration determination.

[0149] Based on the same inventive concept, this invention also provides a device for determining surface evapotranspiration, as described in the following embodiments. Since the principle underlying the surface evapotranspiration determination device is similar to the method for determining surface evapotranspiration, the implementation of the surface evapotranspiration determination device can refer to the implementation of the method for determining surface evapotranspiration, and repeated details will not be elaborated further. As used below, the terms "unit" or "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0150] Figure 6 This is a schematic diagram of the structure of the device for determining surface evapotranspiration in an embodiment of the present invention, as shown below. Figure 6 As shown, the device includes:

[0151] The surface remote sensing monitoring data preprocessing module 02 is used to process the surface remote sensing monitoring data into surface remote sensing monitoring data with consistent spatiotemporal resolution.

[0152] The evapotranspiration determination module 04 is used to calculate vegetation evaporation, soil evaporation, canopy intercepted evaporation, water evaporation and snow sublimation in the target area based on surface remote sensing monitoring data with consistent spatiotemporal resolution.

[0153] The Surface Evapotranspiration Determination Module 06 is used to determine the total surface evapotranspiration in the target area based on vegetation evaporation, soil evaporation, canopy intercepted evaporation, water evaporation, and snow and ice sublimation.

[0154] In one embodiment, the surface remote sensing monitoring data includes: surface temperature, air pressure, wind speed, surface downwave radiation, surface longwave radiation, surface humidity, and vegetation index.

[0155] The surface remote sensing monitoring data preprocessing module is specifically used for:

[0156] Processing surface remote sensing data into surface remote sensing data with consistent spatiotemporal resolution includes:

[0157] Using statistical downscaling methods, surface temperature, air pressure, wind speed, surface downwave radiation, and surface longwave radiation are processed into surface remote sensing monitoring data with consistent spatiotemporal resolution.

[0158] By using irregular triangle regression, brightness temperature scale, or spatial downscaling method based on thermal inertia, surface humidity is processed into surface remote sensing monitoring data with consistent spatiotemporal resolution.

[0159] Using the time series harmonic analysis method based on Fourier transform, vegetation index monitoring data are processed into surface remote sensing monitoring data with consistent spatiotemporal resolution.

[0160] Surface remote sensing monitoring data with different projections are processed into surface remote sensing monitoring data with consistent spatiotemporal resolution.

[0161] In one embodiment, each evaporation rate determination module is specifically used for:

[0162] Calculate the net surface radiation based on surface albedo, emissivity, downward shortwave radiation, downward longwave radiation, and surface temperature; calculate the net radiation consumed by vegetation transpiration and the net radiation consumed by soil evaporation based on the net surface radiation.

[0163] The vegetation transpiration rate in the target area is calculated based on net radiation consumed by vegetation transpiration, aerodynamic impedance of the vegetation canopy, vegetation canopy resistance, and surface temperature. The soil evaporation rate in the target area is calculated based on net radiation consumed by soil evaporation, surface heat flux, soil aerodynamic impedance, and soil surface resistance. The canopy interception evaporation rate in the target area is calculated based on rainfall and rainfall frequency. The water evaporation rate in the target area is calculated based on net surface radiation and surface heat flux. The snow and ice sublimation rate in the target area is calculated based on wind speed.

[0164] This invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-described method for determining surface evapotranspiration.

[0165] This invention also provides a computer-readable storage medium storing a computer program that performs the above-described method for determining surface evapotranspiration.

[0166] The technical solution provided by the embodiments of the present invention has the following advantages and effects:

[0167] (1) The algorithm of the present invention considers the key processes that control the actual evapotranspiration of the land surface, such as the surface water cycle, energy balance, and vegetation physiology and ecology. It has a stronger mechanism than the traditional remote sensing algorithm and can realize the estimation of global spatiotemporal continuous evapotranspiration.

[0168] (2) This algorithm can effectively separate evapotranspiration components, distinguish between vegetation transpiration, soil evaporation, precipitation interception, water surface evaporation, snow and ice sublimation, etc., and provide more detailed and comprehensive evapotranspiration estimation results.

[0169] (3) Combining multiple remote sensing information to estimate evapotranspiration can improve the accuracy of evapotranspiration estimation.

[0170] Obviously, those skilled in the art should understand that the modules or steps of the above-described embodiments of the present invention can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented here, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the embodiments of the present invention are not limited to any particular hardware and software combination.

[0171] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, various modifications and variations can be made to the embodiments of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for determining surface evapotranspiration, characterized in that, include: Surface remote sensing monitoring data is processed into surface remote sensing monitoring data with consistent spatiotemporal resolution; The surface remote sensing monitoring data includes: surface temperature, air pressure, wind speed, surface downwave radiation, surface longwave radiation, surface humidity, and vegetation index. The surface remote sensing monitoring data is processed to achieve consistent spatiotemporal resolution, including: using statistical downscaling methods to process surface temperature, air pressure, wind speed, surface downwave radiation, and surface longwave radiation into data with consistent spatiotemporal resolution; using spatial downscaling methods based on irregular triangle regression, brightness temperature scaling, or thermal inertia to process surface humidity into data with consistent spatiotemporal resolution; using time-series harmonic analysis based on Fourier transform to process vegetation index into spatiotemporally continuous surface remote sensing monitoring data; and using the GDAL tool to process the projections of surface temperature, air pressure, wind speed, surface downwave radiation, surface longwave radiation, surface humidity, and vegetation index into a consistent projection. Based on consistent spatiotemporal resolution surface remote sensing data, the following calculations are performed on vegetation transpiration, soil evaporation, canopy intercepted evaporation, water evaporation, and snow and ice sublimation within the target area. These calculations include: calculating net surface radiation based on surface albedo, surface emissivity, downward shortwave radiation, downward longwave radiation, and surface temperature; calculating net radiation consumed by vegetation transpiration and net radiation consumed by soil evaporation based on net surface radiation; calculating vegetation transpiration within the target area based on net radiation consumed by vegetation transpiration, vegetation canopy aerodynamic impedance, vegetation canopy resistance, and surface temperature; calculating soil evaporation within the target area based on net radiation consumed by soil evaporation, surface heat flux, soil aerodynamic impedance, and soil surface impedance; calculating canopy intercepted evaporation within the target area based on rainfall and rainfall frequency; calculating water evaporation within the target area based on net surface radiation and surface heat flux; and calculating snow and ice sublimation within the target area based on wind speed. The total surface evapotranspiration in the target area is determined based on vegetation evaporation, soil evaporation, canopy intercepted evaporation, water evaporation, and snow and ice sublimation.

2. The method for determining surface evapotranspiration as described in claim 1, characterized in that, The net surface radiation is calculated based on surface albedo, surface emissivity, downward shortwave radiation, downward longwave radiation, and surface temperature, including the following formula: ； in, Net surface radiation It is the surface albedo. For surface emissivity, It is shortwave radiation descending from the Earth's surface. It is long-wave radiation flowing down to the Earth's surface. The Stefan-Boltzmann constant is... This refers to the Earth's surface temperature.

3. The method for determining surface evapotranspiration as described in claim 1, characterized in that, Calculate the net radiation loss due to vegetation transpiration and the net radiation loss due to soil evaporation based on the net surface radiation, including: calculating the net radiation loss due to vegetation transpiration using the following formula: ； Based on the net surface radiation, calculate the net radiation loss due to vegetation transpiration and the net radiation loss due to soil evaporation, including: calculating the net radiation loss due to soil evaporation using the following formula: ； in, Net surface radiation , The canopy traps net radiation lost through evaporation. Net radiation is consumed by vegetation transpiration. Net radiation is consumed by soil evaporation. This represents the vegetation coverage index.

4. The method for determining surface evapotranspiration as described in claim 1, characterized in that, Based on the net radiation consumed by vegetation transpiration, the aerodynamic impedance of the vegetation canopy, the canopy resistance, and the surface temperature, the vegetation transpiration in the target area is calculated, including: the vegetation transpiration evapotranspiration in the target area according to the following formula: T r = C c PM c / λ ； ； C c = {1 + R c R a / [ R s ( R c + R a )]} -1 ； R a = (D + ) r a,a ; R s = (D + ) r a,s + r s,s ; R c = (D + ) r a,c + r s,c ; in, T r Evaporation rate of vegetation G For surface heat flux, Δ The temperature-saturated vapor pressure relationship curve at temperature T The slope of the tangent at (K), ρ For air density, c p For the isothermal specific heat of air, λ For the latent heat of vaporization, γ This is the constant of the wet and dry meter. D Due to the water vapor pressure deficit at the height of the vegetation canopy, r s,s , r s,c , r a,c , r a,s and r a,a These are, respectively, soil surface impedance, canopy surface impedance, canopy boundary layer aerodynamic impedance, aerodynamic impedance between the soil surface and the canopy source-sink height, and aerodynamic impedance between the canopy source-sink height and the reference height. PM c This represents the potential transpiration of vegetation. C c This represents the vegetation transpiration resistance coefficient. R n Net surface radiation R n,s For net radiation flux in soil, R a , R c and R s This is an intermediate variable used in the calculation of the vegetation transpiration impedance coefficient.

5. The method for determining surface evapotranspiration as described in claim 1, characterized in that, Based on net radiation consumed by soil evaporation, surface heat flux, soil aerodynamic impedance, and soil surface impedance, the soil evaporation rate within the target area is calculated, including the following formula: E s = C s PM s / λ ； ； C s = {1 + R s R a / [ R c ( R s + R a )]} -1 ； R a = (D + ) r a,a ; R s = (D + ) r a,s + r s,s ; R c = (D + ) r a,c + r s,c ; in, E s This refers to soil evaporation. G For surface heat flux, Δ The temperature-saturated vapor pressure relationship curve at temperature T The slope of the tangent at (K), ρ For air density, c p The specific heat of air isothermal λ For the latent heat of vaporization, γ This is the constant of the wet and dry meter. D Due to the water vapor pressure deficit at the height of the vegetation canopy, r s,s , r s,c , r a,c , r a,s and r a,a These are, respectively, soil surface impedance, canopy surface impedance, canopy boundary layer aerodynamic impedance, aerodynamic impedance between the soil surface and the canopy source-sink height, and aerodynamic impedance between the canopy source-sink height and the reference height. PM s Potential soil evaporation C s The soil evaporation resistance coefficient, R n Net surface radiation R n,c Net radiation flux of the canopy R a , R c and R s This is an intermediate variable used in the calculation of the vegetation transpiration impedance coefficient.

6. A device for determining surface evapotranspiration, characterized in that, include: The surface remote sensing monitoring data preprocessing module is used to process surface remote sensing monitoring data into surface remote sensing monitoring data with consistent spatiotemporal resolution; The surface remote sensing monitoring data includes: surface temperature, air pressure, wind speed, surface downwave radiation, surface longwave radiation, surface humidity, and vegetation index. The surface remote sensing monitoring data is processed to achieve consistent spatiotemporal resolution, including: using statistical downscaling methods to process surface temperature, air pressure, wind speed, surface downwave radiation, and surface longwave radiation into data with consistent spatiotemporal resolution; using spatial downscaling methods based on irregular triangle regression, brightness temperature scaling, or thermal inertia to process surface humidity into data with consistent spatiotemporal resolution; using time-series harmonic analysis based on Fourier transform to process vegetation index into spatiotemporally continuous surface remote sensing monitoring data; and using the GDAL tool to process the projections of surface temperature, air pressure, wind speed, surface downwave radiation, surface longwave radiation, surface humidity, and vegetation index into a consistent projection. Each evapotranspiration determination module is used to calculate vegetation evaporation, soil evaporation, canopy intercepted evaporation, water evaporation, and snow and ice sublimation within a target area based on surface remote sensing monitoring data with consistent spatiotemporal resolution. This includes: calculating net surface radiation based on surface albedo, surface emissivity, downward shortwave radiation, downward longwave radiation, and surface temperature; calculating net radiation consumed by vegetation evaporation and net radiation consumed by soil evaporation based on net surface radiation; calculating vegetation evaporation within the target area based on net radiation consumed by vegetation evaporation, vegetation canopy aerodynamic impedance, vegetation canopy resistance, and surface temperature; calculating soil evaporation within the target area based on net radiation consumed by soil evaporation, surface heat flux, soil aerodynamic impedance, and soil surface impedance; calculating canopy intercepted evaporation within the target area based on rainfall and rainfall frequency; calculating water evaporation within the target area based on net surface radiation and surface heat flux; and calculating snow and ice sublimation within the target area based on wind speed. The module for determining total surface evapotranspiration is used to determine the total surface evapotranspiration within a target area based on vegetation evaporation, soil evaporation, canopy intercepted evaporation, water evaporation, and snow and ice sublimation.

7. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 5.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that performs the method of any one of claims 1 to 5.

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