A physical inversion method for root zone soil moisture based on vegetation transpiration

Abstract

The present invention discloses a physical inversion method for root layer soil moisture based on vegetation transpiration, which relates to the technical field of quantitative inversion of surface parameters, and includes: S1, determining the quantitative relationship between the vegetation transpiration ratio and the root layer soil volumetric water content, and normalizing the root layer soil moisture; S2, determining the upper limit of the pressure head at which the vegetation transpiration changes from energy limitation to water limitation; S3, calculating the wilting coefficient and the critical soil moisture under different soil types, vegetation parameters and meteorological factor conditions; S4, obtaining the transpiration ratio by the ratio of the vegetation transpiration to the potential vegetation transpiration; S5, converting the normalized root layer soil moisture into the root layer soil volumetric water content by using the wilting coefficient and the critical soil moisture. The physical inversion method for root layer soil moisture based on vegetation transpiration adopting the above steps has high generalization ability and can meet the high-precision requirements for root layer soil moisture in the fields of modern agriculture, water resources and climate change, etc.

Description

Technical Field

[0001] The present invention relates to the technical field of quantitative inversion of surface parameters, and particularly to a physical inversion method of root layer soil moisture based on vegetation transpiration. Background Art

[0002] Root layer soil moisture is a key parameter driving the three major circulation systems of water, energy and carbon on the earth's surface. It has an important feedback effect on the carbon sink efficiency and temperature regulation of the surrounding environment by controlling the growth and physiological mechanisms of vegetation (transpiration, water absorption, stomatal opening and closing, etc.), and greatly affects the surface-atmosphere interaction and energy exchange process. Under the dual drive of global change and population explosion, the dynamic change of root layer soil moisture is of great significance to the research of agriculture, hydrology, ecology, climate change and social economy.

[0003] At present, the shortage of water resources has become a major challenge that needs to be solved urgently globally. Especially in densely populated areas, the groundwater resources are experiencing a severe situation of decreasing year by year. As the main body of water resource consumption, agriculture accounts for about 70% of the global available water resources. Therefore, the scientific water resource management policy based on root layer soil moisture is of great significance for alleviating water resource pressure, promoting the rational allocation and efficient utilization of water resources. Therefore, obtaining the spatio-temporal distribution and change information of root layer soil moisture has important scientific significance and application value for the research of agricultural situation monitoring, water resource management, and global climate change, and belongs to one of the frontier topics in the fields of agriculture, water resources, and climate change.

[0004] Traditional root-zone soil moisture monitoring mainly relies on direct point measurements of the soil profile or extends point observation data to the grid scale by means of grid interpolation. This method can roughly reflect the spatial distribution of root-zone soil moisture, but the accuracy of the interpolation results is affected by the number and distribution of observation points, and the cost is high. In the context of the big data era, there are many challenges in data assimilation or data-driven methods that rely on surface soil moisture observation information, including the decline in accuracy caused by the accumulation of initial errors in observation data, insufficient spatial resolution to capture fine topographic features, complex error sources and difficult to accurately quantify, and the parameter calibration process is easily interfered by various factors such as surface characteristics and vegetation cover. The inversion methods based on remote sensing technology generally have the problem of low accuracy and do not consider the influence of vegetation on the "saturation" of root-zone soil moisture. This limitation is mainly due to the insufficient explanation of the complex process mechanism of the conduction of surface moisture stress (such as potential evaporation ratio, evaporation ratio, and transpiration ratio). Generally speaking, the current root-zone soil moisture inversion algorithms are difficult to meet the high-precision requirements for root-zone soil moisture in the fields of modern agriculture, water resources, and climate change. Therefore, developing a physical inversion method for root-zone soil moisture that does not rely on surface soil moisture information, has high generalization ability, and high precision is not only the basic premise for obtaining high-precision root-zone soil moisture data at the regional and even global scales, but also the inevitable trend and core direction to promote the development of future quantitative inversion technology for root-zone soil moisture. Summary of the Invention

[0005] The object of the present invention is to provide a physical inversion method for root-zone soil moisture based on vegetation transpiration, which does not rely on surface soil moisture information, has high generalization ability, and can meet the high-precision requirements for root-zone soil moisture in the fields of modern agriculture, water resources, and climate change.

[0006] To achieve the above object, the present invention provides a physical inversion method for root-zone soil moisture based on vegetation transpiration, and the steps are as follows:

[0007] S1. Based on the water balance principle, distinguish the contributions of surface soil moisture and root-zone soil moisture in the processes of soil evaporation and vegetation transpiration, construct a response function between the transpiration ratio and the root-zone soil pressure head through the Feddes root water uptake model, introduce the van Genuchten-Mualem soil water retention curve model to convert the soil pressure head into volumetric water content, so as to determine the quantitative relationship between the transpiration ratio and the root-zone soil volumetric water content; simplify the quantitative relationship between the transpiration ratio and the root-zone soil volumetric water content by normalizing the root-zone soil moisture.

[0008] S2. According to empirical data, construct a database of pressure heads of the Feddes model under different vegetation conditions, and determine the upper limit of the pressure head at which vegetation transpiration changes from energy limitation to water limitation according to different underlying surfaces and meteorological conditions.

[0009] S3. Based on the conversion function of the Rosetta model, the soil hydraulic parameters of the van Genuchten-Mualem model are calculated by the soil texture information. Using the soil hydraulic parameters and the Feddes model pressure head database, the wilting coefficient and the critical soil moisture under different soil types, vegetation parameters and meteorological factors are calculated by the van Genuchten-Mualem model;

[0010] S4. Using the data of the total primary productivity of vegetation and the saturation vapor pressure difference of meteorological factors, the actual evapotranspiration is separated by the bottom layer water use efficiency model to obtain the vegetation transpiration; the potential evapotranspiration without water evaporation pressure under the given radiation and meteorological conditions is calculated by the Penman formula; based on the Lambert-Beer law, the potential vegetation transpiration is derived by using the leaf area index and the potential evapotranspiration, and the transpiration ratio is obtained by the ratio of the vegetation transpiration to the potential vegetation transpiration;

[0011] S5. Through the normalized root layer soil moisture model constructed by S1, the Feddes model parameters determined by S2, and the van Genuchten-Mualem model parameters determined by S3, the normalized root layer soil moisture is calculated by the transpiration ratio; finally, the normalized root layer soil moisture is converted into the root layer soil volume water content by using the wilting coefficient and the critical soil moisture.

[0012] Preferably, S1.1. Based on the water balance principle, the contributions of the surface soil moisture and the root layer soil moisture to the soil evaporation and vegetation transpiration processes are distinguished, and the response function between the vegetation transpiration ratio and the root layer soil pressure head is constructed by the Feddes root water uptake model, specifically including:

[0013] According to the water balance, assuming that the root water uptake of vegetation is completely used for transpiration, the response function between the root layer soil pressure head and the vegetation transpiration is derived as follows:

[0014] (1)

[0015] In the formula, T r is the transpiration ratio; φ is the root water uptake efficiency; h is the soil pressure head; h 3 is the upper limit of the pressure water head of the soil when the vegetation is water-limited; h 4 is the pressure head of the wilting coefficient.

[0016] Preferably, in S1.2, the van Genuchten-Mualem soil water retention curve model is introduced to convert the soil pressure head into the volumetric water content, thereby determining the quantitative relationship between the transpiration ratio and the volumetric water content of the root zone soil, which is expressed as follows:

[0017] (2)

[0018] In the formula, θ r is the residual water content; θ s is the saturated water content; α is the shape parameter, which is related to the slope of the soil pore size distribution curve and determines the shape of the curve near the saturated zone and the drying zone; n is another shape parameter, which is related to the uniformity of the soil pore size distribution, n The larger the value, the more uniform the pore size distribution and the smoother the curve; m = 1 - 1 / n; θ(h) is the volumetric water content, h is the soil pressure head.

[0019] Preferably, in S1.3, the quantitative relationship between the vegetation transpiration ratio and the volumetric water content of the root zone soil is simplified by normalizing the root zone soil moisture, which is expressed as follows:

[0020] (3)

[0021] (4)

[0022] After obtaining the expression of the normalized root zone soil moisture it is further assumed that:

[0023] (5)

[0024] Subsequently, the relevant terms of the normalized root zone soil moisture model can be expressed as:

[0025] (6)

[0026] A simple expression of the normalized root zone soil moisture is obtained through the simplification of the model:

[0027] (7)

[0028] (8)

[0029] Wherein, a 、 b 、 c and d are coefficients, which depend on soil, vegetation and atmospheric demand conditions; ψThe error term caused by simplifying the process, where θ represents soil water content, represents the soil water content when the transpiration ratio is the largest, and represents the soil water content when the transpiration ratio is the smallest.

[0030] Preferably, in S2, the upper limit of the pressure head of soil when vegetation is water-limited h 3 is expressed as:

[0031] (9)

[0032] In the formula, T p is the potential transpiration; h 3l represents the upper limit of the pressure head when the atmospheric water vapor demand is low. At this time, T p = T 3l ; h 3h represents the upper limit of the pressure head when the atmospheric water vapor demand is high. At this time, T p = T 3h ; T 3l The value of is set to 1 mmd -1 , T 3h The value of is set to 5mmd -1 .

[0033] Preferably, in S4.1, using the data of the total primary productivity of vegetation and the saturation vapor pressure deficit of meteorological factors, the actual evapotranspiration is separated by the underlying layer water use efficiency model to obtain vegetation transpiration, specifically including:

[0034] Through the uWUE model, the transpiration is indirectly estimated using the biological information amount GPP and the meteorological factor VPD. On a relatively large time scale, the evapotranspiration ET is decomposed into evaporation E and transpiration T, which is expressed as follows:

[0035] (10)

[0036] Among them, uWUE a represents the apparent water use efficiency, GPP represents the total primary productivity of vegetation, and VPD represents the saturation vapor pressure deficit;

[0037] T Close to ET When, it means that the vegetation coverage rate is relatively high and the evaporation E can be ignored. At this time, the uWUE model is expressed as:

[0038] (11)

[0039] Wherein, uWUE p represents the potential water use efficiency, which is determined by the time series data statistical method;

[0040] The transpiration amount T is obtained through formulas (10) and (11), and is expressed as:

[0041] (12).

[0042] Preferably, in S4.2, the Penman formula is used to calculate the potential evapotranspiration without water evaporation pressure under given radiation and meteorological conditions, which is expressed as follows:

[0043] (13)

[0044] Wherein, ET p is the potential evapotranspiration. The Penman formula divides evapotranspiration into two parts. The first part is the evaporation caused by the absorbed radiation of water ET rad , and the second part is the evaporation driven by aerodynamics ET aero ; R n and G are the net surface radiation and the soil heat flux respectively, with the unit of W / m 2 ; r c is the canopy impedance under sufficient water supply condition, with the unit of s / m; r a is the aerodynamic impedance, with the unit of s / m; c p is the specific heat at constant pressure of air, with the unit of J / (kg·°C); γ is the psychrometric constant, set as 0.0658 kPa / °C; Δ is the slope of the saturated water vapor pressure and temperature, with the unit of kPa / °C; ρ is the air density, with the unit of kg / m 3 .

[0045] Preferably, in S4.3, based on the Lambert-Beer law, the potential vegetation transpiration is derived by using the leaf area index and the potential evapotranspiration, and the transpiration ratio is obtained by the ratio of the vegetation transpiration to the potential vegetation transpiration, which specifically includes:

[0046] The potential vegetation transpiration is obtained through the Lambert-Beer law T p , and is expressed as:

[0047] (14)

[0048] In the formula, LAI represents the leaf area index, k represents the extinction coefficient, which is set to 0.5 - 0.75;

[0049] Vegetation transpiration ratio T r is expressed as:

[0050] (15).

[0051] Preferably, in S5, the shape parameters determined by S2 and S3 n , the upper limit of the pressure head of soil water when vegetation is water - limited h 3 , the pressure head of the wilting coefficient h 4 , the vegetation transpiration ratio determined by S4 Tr , calculate the normalized root - layer soil moisture through formula (7) and formula (8) ;

[0052] Then, convert the normalized root - layer soil moisture to the root - layer soil volumetric water content by using the wilting coefficient and the critical soil moisture, which is expressed as follows:

[0053] (16)

[0054] Wherein, represents the root - layer soil volumetric water content, represents the critical soil moisture, represents the wilting coefficient.

[0055] According to the specific embodiments provided by the present invention, the following technical effects are disclosed:

[0056] Based on the principle of water balance, it is assumed that the water absorption of vegetation roots is completely used for transpiration, and the contributions of surface / root - layer soil moisture to soil evaporation / vegetation transpiration are distinguished; at the same time, the concept of critical soil moisture is introduced, fully considering the "saturation" effect of vegetation on root - layer soil moisture, and solving the complex and variable coupling relationship problem between surface evaporation and root - layer soil moisture in different regions; this method has clear physical meaning and can be derived from the Feddes root water uptake model and the van Genuchten - Mualem soil physics model, overcoming the limitations of poor universality and dependence on surface soil moisture of traditional methods, being applicable to the inversion of root - layer soil moisture under different underlying surfaces and atmospheric conditions, and being conducive to the expansion of the time scale.

[0057] The technical solutions of the present invention will be further described in detail below through the accompanying drawings and embodiments. Description of the Drawings

[0058] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0059] Figure 1 It is a flowchart of an embodiment of a physical inversion method for root layer soil moisture based on vegetation transpiration of the present invention;

[0060] Figure 2 It is a scatter plot comparison of the root layer soil moisture calculated by the method of this application in the embodiment of the present invention and the HYDRUS-1D hydrological model;

[0061] Figure 3 It is a result diagram of the root layer soil moisture of the US-ARM site in the embodiment of the present invention planted in an irrigation multi-crop rotation mode;

[0062] Figure 4 It is a result diagram of the root layer soil moisture of the US-Bi1 site in the embodiment of the present invention planted in a rain-fed alfalfa grass mode;

[0063] Figure 5 It is a result diagram of the root layer soil moisture of the US-Ne1 site in the embodiment of the present invention planted in an irrigation corn mode;

[0064] Figure 6 It is a result diagram of the root layer soil moisture of the US-Ne2 site in the embodiment of the present invention planted in an irrigation corn-soybean rotation mode;

[0065] Figure 7 It is a result diagram of the root layer soil moisture of the US-Ne3 site in the embodiment of the present invention planted in a rain-fed corn-soybean rotation mode;

[0066] Figure 8 It is a result diagram of the root layer soil moisture of the US-Var site in the embodiment of the present invention planted in a rain-fed grassland mode. Detailed implementation manners

[0067] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0068] To make the above objects, features, and advantages of the present invention more obvious and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0069] Embodiment

[0070] A physical inversion method for root layer soil moisture based on vegetation transpiration is as Figure 1 shown, and the steps are as follows:

[0071] S1.1. Based on the principle of water balance, distinguish the contributions of surface soil moisture and root layer soil moisture in the processes of soil evaporation and vegetation transpiration, and construct a response function between the vegetation transpiration ratio and the root layer soil pressure head through the Feddes root water uptake model, specifically including:

[0072] Assume that the root water uptake of vegetation is completely used for transpiration, and the response function between the root layer soil pressure head and vegetation transpiration is derived as follows:

[0073] (1)

[0074] In the formula, T r is the transpiration ratio; φ is the root water uptake efficiency; h is the soil pressure head; h 3 is the upper limit of the pressure head of soil when vegetation is water-limited; h 4 is the pressure head of the wilting coefficient.

[0075] S1.2. Introduce the van Genuchten-Mualem soil water retention curve model to convert the soil pressure head into volumetric water content, thereby determining the quantitative relationship between the transpiration ratio and the root layer soil volumetric water content, expressed as follows:

[0076] (2)

[0077] In the formula, θ r is the residual water content; θ s is the saturated water content; α is the shape parameter, related to the slope of the soil pore distribution curve, and determines the shape of the curve near the saturated zone and the drying zone; n is another shape parameter, related to the uniformity of the soil pore distribution, n the larger the value, the more uniform the pore distribution and the smoother the curve; m = 1 - 1 / n; θ(h) is the volumetric water content, h is the soil pressure head.

[0078] S1.3. Simplify the quantitative relationship between the normalized root layer soil moisture and the root layer soil volume water content to eliminate some soil parameters that are difficult to obtain in practice, and enhance the operability and flexibility of the method, as shown below:

[0079] (3)

[0080] (4)

[0081] After obtaining the expression of the normalized root layer soil moisture , further assume:

[0082] (5)

[0083] Subsequently, the relevant terms of the normalized root layer soil moisture model can be expressed as:

[0084] (6)

[0085] Obtain a simple expression of the normalized root layer soil moisture through model simplification:

[0086] (7)

[0087] (8)

[0088] where a 、 b 、 c and d are coefficients, depending on soil, vegetation, and atmospheric demand conditions; ψ is the error term caused by the simplification process.

[0089] S2. Based on empirical data, construct a pressure head database of the Feddes model under different vegetation conditions, and determine the upper limit of the pressure head at which vegetation transpiration changes from energy limitation to water limitation according to different underlying surfaces and meteorological conditions h 3 , h 3 represents the critical point at which transpiration changes from water limitation to energy limitation, considering the interaction of multiple factors comprehensively. These factors cover the comprehensive influence of the physical properties of the soil (such as bulk density, porosity, etc.), plant species and their physiological characteristics (such as the distribution pattern of roots, the relationship between transpiration rate and leaf area, etc.), and external environmental conditions (such as temperature, humidity, wind speed, etc.), expressed as:

[0090] (9)

[0091] In the formula, T pis the potential transpiration; h 3l represents the upper limit of the pressure head at low atmospheric water vapor demand, at this time T p = T 3l ; h 3h represents the upper limit of the pressure head at high atmospheric water vapor demand, at this time T p = T 3h ; T 3l The value of is set to 1 mmd -1 , T 3h The value of is set to 5 mmd -1 .

[0092] The conversion function of the S3 and Rosetta models calculates the soil hydraulic parameters of the van Genuchten-Mualem model through soil texture information, and calculates the wilting coefficient and critical soil moisture under different soil types, vegetation parameters and meteorological factors by using the pressure head databases of the van Genuchten-Mualem model and the Feddes model;

[0093] S4.1. Using the data of the gross primary production (GPP) of vegetation and the vapor pressure deficit (VPD) of meteorological factors, the underlying water use efficiency model (uWUE) is adopted to separate the actual evapotranspiration to obtain vegetation transpiration, specifically including:

[0094] Through the uWUE model, the transpiration is indirectly estimated by using the biological information GPP and the meteorological factor VPD. The evapotranspiration ET is decomposed into evaporation E and transpiration T on a relatively large time scale, which is expressed as follows:

[0095] (10)

[0096] Among them, uWUE a represents the apparent water use efficiency, GPP represents the gross primary production of vegetation, and VPD represents the vapor pressure deficit;

[0097] T Close to ET When, it means that the vegetation coverage rate is relatively high and the evaporation E can be ignored. At this time, the uWUE model is expressed as:

[0098] (11)

[0099] Among them, uWUE p represents the potential water use efficiency, which is determined by time series data statistical method, that is, using multi-year uWUE a data to estimate the uWUE a value at the 95% quantile level for each location, and taking this value as an alternative reference index for evaluating uWUE p the potential upper limit.

[0100] The transpiration amount T is obtained through formulas (10) and (11), and is expressed as:

[0101] (12).

[0102] S4.2. Calculate the potential evapotranspiration without moisture evaporation pressure under given radiation and meteorological conditions using the Penman formula (Penman-Monteith), which is expressed as follows:

[0103] (13)

[0104] Among them, ET p is the potential evapotranspiration. The Penman formula divides evapotranspiration into two parts. The first part is the evaporation caused by water absorption radiation ET rad , and the second part is the evaporation driven by aerodynamics ET aero ; R n and G are the net surface radiation and soil heat flux respectively, with the unit of W / m 2 ; r c is the canopy resistance under sufficient water supply condition, with the unit of s / m; r a is the aerodynamic resistance, with the unit of s / m; c p is the specific heat at constant pressure of air, with the unit of J / (kg·°C); γ is the psychrometric constant, set as 0.0658 kPa / °C; Δ is the slope of saturated water vapor pressure and temperature, with the unit of kPa / °C; ρ is the air density, with the unit of kg / m 3 .

[0105] S4.3. Based on the Lambert-Beer law, the potential vegetation transpiration is derived using the Leaf Area Index (LAI) and potential evapotranspiration, and the transpiration ratio is obtained by the ratio of vegetation transpiration to potential vegetation transpiration, specifically including:

[0106] Obtaining the potential vegetation transpiration through the Lambert-Beer law T p , expressed as:

[0107] (14)

[0108] In the formula, LAI represents the leaf area index, k represents the extinction coefficient, set to 0.5 - 0.75;

[0109] Vegetation transpiration ratio T r Expressed as:

[0110] (15).

[0111] S5. Using the normalized root layer soil moisture model constructed in S1, the Feddes model parameters determined in S2, and the van Genuchten-Mualem model parameters determined in S3, the normalized root layer soil moisture is calculated using the transpiration ratio; finally, the normalized root layer soil moisture is converted to the root layer soil volume water content using the wilting coefficient and critical soil moisture. Using the shape parameters determined in S2 and S3 n , the upper limit of the pressure water head of the soil when the vegetation is water-limited h 3 , the pressure water head of the wilting coefficient h 4 , the vegetation transpiration ratio determined in S4 Tr , calculate the normalized root layer soil moisture through formula (7) and formula (8) ;

[0112] Then, the normalized root layer soil moisture is ω root converted to the root layer soil volume water content, expressed as follows:

[0113] (16)

[0114] Among them, represents the root layer soil volume water content, represents the critical soil moisture, represents the wilting coefficient.

[0115] In this embodiment, HYDRUS-1D hydrological model simulation data and AmeriFlux (American Flux Network) field experiment data are used as data sources to invert the root zone soil moisture under different underlying surfaces and atmospheric conditions, including the following steps:

[0116] First, a root zone soil moisture database under different underlying surfaces and atmospheric conditions is constructed based on the HYDRUS-1D model, and this database is used to verify the accuracy of the method of this application to demonstrate the applicability and reliability of the method for inverting root zone soil moisture in a wide area, as shown in the appendix Figure 2 as follows Figure 2 In it, (a) represents the scatter plot of root zone soil moisture under clear sky conditions in the semi-arid region (US-Bi1); (b) represents the scatter plot of root zone soil moisture under cloudy conditions in the semi-arid region (US-Bi1); (c) represents the scatter plot of root zone soil moisture under clear sky conditions in the semi-humid region (US-Ne3); (d) represents the scatter plot of root zone soil moisture under cloudy conditions in the semi-humid region (US-Ne3).

[0117] Overview of simulation settings: (1) Soil types: A total of 30 soil types are considered, which are different in physical, chemical, and biological characteristics, representing a wide range of soil type diversity; (2) Vegetation types: Five vegetation types (corn, soybean, wheat, alfalfa, grassland) are included in the simulation, and these vegetations differ in physiological and ecological characteristics, transpiration intensity, and water use efficiency, etc.; (3) Meteorological conditions: The simulation covers 24 meteorological conditions, which are derived from the measured atmospheric data in the semi-arid region (US-Bi1) and the semi-humid region (US-Ne3), including clear sky and cloudy weather, as shown in Table 1; (4) Vegetation coverage: 19 vegetation coverage levels are set at intervals of 0.05 to simulate different situations from bare soil to complete vegetation coverage. This simulation design fully considers the effects of different soil types, vegetation species, climate conditions (such as rainfall, temperature, humidity, radiation, etc.) and vegetation coverage on soil moisture dynamics.

[0118]

[0119] In the embodiment of the measured data, to test the applicability of the method of this application under natural and variable conditions, the observed data of six AmeriFlux sites (US-ARM, US-Bi1, US-Ne1, US-Ne2, US-Ne3, US-Var) are used to estimate the root zone soil moisture, and the results are as shown in Figure 3 — Figure 8 as follows, and the ground-observed root zone soil moisture is used to verify the inversion results of the method of this application. The observed root zone soil moisture takes the weighted average value at a fixed depth as the relative true value:

[0120] (17)

[0121] In the above formula, represents the average root zone soil moisture, θ i represents the soil moisture content observed at different soil depths L i .

[0122] In this embodiment, the selection of sites ensures that the method of this application can span different climate regions, from humid to semi-arid, to achieve a full-range and multi-level verification of the model performance. The vegetation types cover key crop species such as wheat, corn, soybeans, and alfalfa, demonstrating their unique value in agricultural research, as shown in Table 2.

[0123]

[0124] Meanwhile, the aridity index (AI) is used to distinguish the drought degrees of different sites:

[0125] (18)

[0126] In the above formula, PET represents the potential evapotranspiration, P represents the precipitation.

[0127] In S2, a pressure head database of the Feddes model under different vegetation conditions is constructed, fully considering the adaptation mechanisms of plants to water stress and the differences in their ecological strategies under different plant types and different environmental conditions. The parameters h 3l and T 3l represent that under low atmospheric water vapor evaporation environments, such as low radiation, high humidity, and low wind speed conditions, the pressure on transpiration is relatively small. At the same time, there is a key soil water pressure head threshold h 3l . When the soil water potential drops below this threshold, the transpiration rate will begin to decline significantly. Under low atmospheric demand conditions, when the soil moisture is in an abundant state, the potential transpiration rate that plants can reach is defined as T 3l to reflect the environmental conditions of low evaporation potential.

[0128] Relatively speaking, h 3h and T 3h are closely related to high evaporation demand environments. Under conditions such as high radiation, low humidity, and high wind speed, transpiration may be extremely strong. At this time, there is also a critical value of soil water potential h 3h . When the soil water potential is lower thanh 3h Transpiration rate is severely restricted by soil moisture at this time. Under the condition of high evaporation demand on the ground surface, if the soil moisture is sufficient, the potential transpiration rate that plants can reach is defined as T 3h , to reflect the environmental conditions of high evaporation potential. h 3l and h 3h The specific values mainly depend on the plant type. These values are obtained by referring to previous research materials or conducting field tests, which comprehensively consider various factors such as the growth stage of plants, soil type, soil moisture status, and environmental conditions, as shown in Table 3.

[0129]

[0130] In this example, the parameters of the van Genuchten-Mualem model are derived by the Rosetta model using the transfer function through the soil texture information of the input site, so as to improve the efficiency and accuracy of parameter acquisition of the method of this application and realize the inversion of root zone soil moisture at the field scale. The wilting coefficient is calculated by h 4 substituting into the van Genuchten-Mualem model, and the critical soil moisture is calculated by h 3 substituting into the van Genuchten-Mualem model. The determination of the wilting coefficient mainly depends on the soil type and vegetation species.

[0131] In the method of this application, by introducing the concept of critical soil moisture and fully considering the "saturation" effect of vegetation on root zone soil moisture, the complex and variable coupling relationship problem between vegetation transpiration and root zone soil moisture under different soil characteristics and environmental factors, such as soil texture, soil structure, vegetation type, meteorological factors, etc. is solved. The critical soil moisture ( θ c ) is defined as the soil moisture content when plant transpiration begins to be restricted by soil moisture, and its value is between the field capacity ( θ fc ) and the wilting coefficient ( θ wp ), which is used to evaluate the adequacy of water supply during the vegetation growth process. When the soil moisture content is between θ c and θ fc , it is considered that the plant is in a relatively ideal water environment, and the transpiration rate is close to its potential maximum value, that is, T r= 1. At this stage, plant transpiration is not restricted by soil moisture, can fully meet the growth requirements of plants, and at the same time indicates that vegetation transpiration loses sensitivity to the change of soil moisture in the root layer.

[0132] In this example, necessary data quality control is carried out: (1) Given that the basic principle of the method of this application is to reflect the dynamic change of soil moisture in the root layer through the stress state of vegetation, this example specifically focuses on the growth season of vegetation, and selects the date with the observed values required for the input of the method of this application (soil properties, vegetation parameters, and meteorological factors) for inversion; (2) Exclude the situation where the soil moisture in the root layer may be in an unstable state, generally before and after precipitation.

[0133] For the rest of the technical features in the above embodiments, those skilled in the art can flexibly select them according to the actual situation to meet different specific actual needs. However, it is obvious to those of ordinary skill in the art that these specific details do not have to be adopted to implement the present invention. In other examples, in order to avoid confusing the present invention, the well-known components, structures, or parts are not specifically described, and they are all within the scope of the technical solution claimed in the claims of the present invention.

[0134] The changes and modifications made by those skilled in the art without departing from the spirit and scope of the present invention shall fall within the protection scope of the appended claims of the present invention. In the above description, in order to provide a thorough understanding of the present invention, a large number of specific details are set forth. However, it is obvious to those of ordinary skill in the art that these specific details do not have to be adopted to implement the present invention. In other examples, in order to avoid confusing the present invention, the well-known technologies are not specifically described, such as specific construction details, operating conditions, and other technical conditions.

[0135] Specific examples are used in this article to elaborate on the principles and implementation manners of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention; at the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to the present invention.

Claims

1. A physical inversion method for root layer soil moisture based on vegetation transpiration, characterized by: Here are the steps: S1. Based on the principle of water balance, the contribution of surface soil moisture and root layer soil moisture in soil evaporation and vegetation transpiration is distinguished. The response function between vegetation transpiration ratio and root layer soil pressure head is constructed through the Feddes root water absorption model. The van Genuchten-Mualem soil water retention curve model is introduced to convert soil pressure head into volumetric water content, thereby determining the quantitative relationship between transpiration ratio and root layer soil volumetric water content; the quantitative relationship between vegetation transpiration ratio and root layer soil volumetric water content is simplified by normalizing root layer soil moisture; S2. Based on empirical data, construct a pressure head database of the Feddes model under different vegetation conditions, and determine the upper limit of the pressure head when vegetation transpiration changes from energy limitation to water limitation according to different underlying surfaces and meteorological conditions; S3, based on the conversion function of the Rosetta model, the soil hydraulic parameters of the van Genuchten-Mualem model are inferred through soil texture information, and the wilting coefficient and critical soil moisture under different soil types, vegetation parameters and meteorological factors are calculated through the van Genuchten-Mualem model using soil hydraulic parameters and the Feddes model pressure head database; S4. Using the vegetation gross primary productivity and the saturated water vapor pressure deficit data of meteorological factors, the bottom water use efficiency model is used to separate the actual evapotranspiration to obtain vegetation transpiration; The Penman formula is used to calculate the potential evapotranspiration without water evaporation pressure under given radiation and meteorological conditions. Based on the Lambert-Beer law, the leaf area index and potential evapotranspiration are used to derive the potential vegetation transpiration, and the transpiration ratio is obtained by the ratio of vegetation transpiration to potential vegetation transpiration. S5. The normalized root layer soil moisture model constructed by S1, the Feddes model parameters determined by S2 and the van Genuchten-Mualem model parameters determined by S3 are used to calculate the normalized root layer soil moisture using the transpiration ratio; finally, the normalized root layer soil moisture is converted into the root layer soil volume moisture content using the wilting coefficient and critical soil moisture.

2. The root layer soil moisture physical inversion method based on vegetation transpiration according to claim 1 is characterized by: S1.

1. Based on the principle of water balance, the contribution of surface soil moisture and root layer soil moisture in soil evaporation and vegetation transpiration is distinguished, and the response function between vegetation transpiration ratio and root layer soil pressure head is constructed through the Feddes root water absorption model, including: According to the water balance, assuming that the water absorbed by the vegetation roots is completely used for transpiration, the response function of the root layer soil pressure head and vegetation transpiration is derived as follows: Where, T r is the vegetation transpiration ratio; is the root water absorption efficiency; h is the soil pressure head; h3 is the upper limit of the soil pressure head when the vegetation is limited by water; h4 is the pressure head of the wilting coefficient.

3. The method for physical inversion of root layer soil moisture based on vegetation transpiration according to claim 2 is characterized in that: S1.

2. The van Genuchten-Mualem soil water retention curve model is introduced to convert soil pressure head into volumetric water content, thereby determining the quantitative relationship between transpiration ratio and root layer soil volumetric water content, which is expressed as follows: In the formula, θ r is the residual water content; θ s is the saturated water content; α is a shape parameter, which is related to the slope of the soil pore distribution curve and determines the shape of the curve when it is close to the saturated zone and the dry zone; n is another shape parameter, which is related to the uniformity of the soil pore distribution. The larger the n value, the more uniform the pore distribution and the smoother the curve; m = 1-1 / n; θ(h) is the volumetric water content, and h is the soil pressure head.

4. The method for physical inversion of root layer soil moisture based on vegetation transpiration according to claim 3 is characterized by: S1.

3. The quantitative relationship between vegetation transpiration ratio and root layer soil volume water content is simplified by normalizing the root layer soil water content, as follows: In order to obtain the normalized root layer soil moisture ω root After the expression, further assume that: The normalized root zone soil moisture model related terms are then expressed as: [1+|α×h4| n ] m ≈|α×h4| n-1 [1+|α×h3| n ] m ≈|α×h3| n-1 (6) [1+|α×(T r ×(h3-h4)+h4)| n ] m ≈|α×(T r ×(h3-h4)+h4)| n-1 The simple expression of normalized root layer soil moisture is obtained by simplification of the model: ω root =a×(b×|cT r +d| 1-n -1)+ψ (7) Among them, a, b, c and d are coefficients, which depend on the soil, vegetation and atmospheric demand conditions; ψ is the error term caused by the simplification process, θ represents the soil moisture content, and θ max represents the soil moisture content when the transpiration ratio is maximum, θ min It indicates the soil moisture content when the transpiration ratio is minimum.

5. The method for physical inversion of root layer soil moisture based on vegetation transpiration according to claim 4 is characterized in that: In S2, the upper limit h3 of the soil pressure head when vegetation is limited by water is expressed as: Where, T p is the potential transpiration; h 3l represents the upper limit of pressure head when the atmospheric water vapor demand is low, at this time T p =T 3l ;h 3h represents the upper limit of pressure head when the atmospheric water vapor demand is high, at this time T p =T 3h ; T 3l The value is set to 1mmd -1 , T 3h The value is set to 5mmd -1 .

6. The method for physical inversion of root layer soil moisture based on vegetation transpiration according to claim 5 is characterized by: S4.

1. Using the vegetation gross primary productivity and the saturated water vapor pressure deficit data of meteorological factors, the bottom water use efficiency model is used to separate the actual evapotranspiration and obtain vegetation transpiration, including: Through the uWUE model, the evapotranspiration is indirectly estimated using the biological information GPP and the meteorological factor VPD. The evapotranspiration ET is decomposed into evaporation E and transpiration T within a larger time scale, as shown below: Among them, uWUE a represents apparent water use efficiency, GPP represents gross primary productivity of vegetation, and VPD represents saturated vapor pressure deficit; When T is close to ET, it means that the vegetation coverage is high and the evaporation E is negligible. The uWUE model at this time is expressed as: Among them, uWUE p represents the potential water use efficiency, determined by statistical methods of time series data; The transpiration rate T is obtained by formula (10) and formula (11), which is expressed as:

7. The method for physical inversion of root layer soil moisture based on vegetation transpiration according to claim 6 is characterized by: S4.

2. The Penman formula is used to calculate the potential evapotranspiration without water evaporation pressure under given radiation and meteorological conditions, expressed as follows: Among them, E.T. p The Penman formula divides evapotranspiration into two parts: the first part is the evaporation caused by water absorbing radiation, rad , the second part is aerodynamically driven evaporation ET aero ; R n and G are the surface net radiation and soil heat flux, respectively, in W / m 2 ; r c is the canopy impedance under sufficient water supply conditions, in s / m; r a is the aerodynamic impedance, in s / m; c p is the specific heat of air at constant pressure, in J / (kg℃); γ is the psychrometric constant, set to 0.0658 kPa / ℃; Δ is the slope of saturated water vapor pressure and temperature, in kPa / ℃; ρ is the air density, in kg / m 3 .

8. The method for physical inversion of root layer soil moisture based on vegetation transpiration according to claim 7 is characterized in that: S4.

3. Based on the Beer-Lambert law, the potential vegetation transpiration is derived using the leaf area index and potential evapotranspiration, and the transpiration ratio is obtained by the ratio of vegetation transpiration to potential vegetation transpiration, which includes: The potential vegetation transpiration T was obtained by Lambert-Beer law. p , expressed as; T p =ET p (1-e -k*LAI ) (14) In the formula, LAI represents the leaf surface index, k represents the extinction coefficient, which is set to 0.5-0.75; Vegetation transpiration ratio T r It is expressed as:

9. The root layer soil moisture physical inversion method based on vegetation transpiration according to claim 8 is characterized by: In S5, the normalized root layer soil moisture ω is calculated by using the shape parameter n determined by S2 and S3, the upper limit of the soil pressure head h3 when the vegetation is limited by water, the pressure head h4 of the wilting coefficient, and the vegetation transpiration ratio Tr determined by S4 through formulas (7) and (8): root ; Then, the normalized root layer soil moisture ω is calculated using the wilting coefficient and critical soil moisture. root Converted to root layer soil volume water content, expressed as follows: in, represents the volumetric water content of the root layer soil, θ c represents the critical soil moisture, θ wp Represents the wilting coefficient.

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