Method for estimating water-carbon fluxes of terrestrial ecosystems considering water balance constraints

Abstract

The present application relates to the technical field of ecology and hydrology, and particularly relates to a land ecosystem water-carbon flux estimation method considering water balance constraints, comprising: estimating leaf scale photosynthesis rate and stomatal conductance by using a photosynthesis model, and upscales the leaf scale photosynthesis rate and stomatal conductance to canopy vegetation gross primary productivity and canopy conductance to construct an evapotranspiration model to estimate evapotranspiration data; constructing a water balance model according to the evapotranspiration data to estimate soil available water; constructing a soil water stress function according to the soil available water to constrain the estimation process of the photosynthesis model and the evapotranspiration model; obtaining long sequence daily scale historical water-carbon flux data and historical remote sensing observation data to calibrate the aforementioned model, and obtaining a land ecosystem water-carbon flux estimation model considering water balance constraints which can estimate water-carbon flux data. Thus, the problems of the prior art, such as difficulty in adapting to climate change and low prediction accuracy, are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of ecology and hydrology, and in particular to a method for estimating water and carbon flux in a terrestrial ecosystem taking into account water balance constraints. Background Art

[0002] Total primary productivity of terrestrial ecosystem vegetation ( Gross Primary Productivity, GPP ) refers to the total amount of organic matter fixed by vegetation through photosynthesis, which directly affects the changes in atmospheric carbon dioxide concentration and regulates the basic functions of the ecosystem. Evapotranspiration , ET ) is an important part of the water cycle and has a significant impact on basin humidity and regional precipitation patterns. As key processes in the water cycle and carbon cycle, photosynthesis and transpiration are closely coupled through vegetation stomata. In the context of climate change, a deeper understanding of GPP and ET The dynamic evolution process of water and carbon fluxes can provide a scientific basis and effective support for monitoring regional water and carbon flux changes, evaluating ecosystem functions, and formulating water resources and carbon management strategies.

[0003] In recent years, the emergence of statistical models, remote sensing models and process models has promoted the global GPP and ET Although these independent estimates GPP and ET The method is relatively mature. GPP and ET Intrinsic physiological coupling through stomatal behavior is often overlooked and cannot be guaranteed GPP and ET The biophysical characteristics of plants in the same location are consistent. The simple combination of different models will also lead to GPP and ET There is a lot of uncertainty when the interaction of GPP and ET Ratio of water use efficiency ( Water Use Efficiency , WUE ). Therefore, the biophysical properties of water and carbon flux coupled with stomatal behavior must be considered from a process perspective to ensure GPP and ET The vegetation characteristics reflected in the estimates are consistent. However, existing process water-carbon coupling models usually use the water vapor pressure deficit as the (Vapor Pressure Deficit , VPD ) as a key driver of the coupled water and carbon cycles to meet the high spatial and temporal resolution requirements of remote sensing inversion. This framework often ignores the time-varying feedback of soil moisture, resulting in reduced model performance in predicting future water and carbon flux responses under changing soil moisture conditions, making it difficult to adapt to the high-precision model simulation requirements under climate change.

[0004] Therefore, a robust method is needed to estimate the soil moisture dynamics under the condition of keeping consistent vegetation physiological characteristics. GPP and ET A dynamic process solution is proposed to solve the current technical problems. Summary of the Invention

[0005] The present invention provides a method for estimating water and carbon flux in terrestrial ecosystems that takes into account water balance constraints, in order to address the problems that the existing framework for predicting future water and carbon fluxes is difficult to adapt to climate change and has low prediction accuracy.

[0006] The first embodiment of the present invention provides a method for estimating water and carbon flux in terrestrial ecosystems considering water balance constraints, comprising the following steps: using a pre-built photosynthesis model ( Farquhar-von Caemmerer-Berry , FWf ) estimate the current leaf-scale photosynthetic rate and the current stomatal conductance of multiple target flux sites; upscale the current leaf-scale photosynthetic rate and the current stomatal conductance respectively to obtain the total primary productivity of canopy vegetation and canopy conductance; according to the total primary productivity of canopy vegetation, the canopy conductance and the pre-constructed ( Penman-Monteith , PM ) an evapotranspiration model is constructed based on the evapotranspiration model to estimate current evapotranspiration data using the actual evapotranspiration model; a water balance model is constructed based on the current evapotranspiration data and a pre-constructed water balance equation to estimate current soil available water using the water balance model; a soil water stress function is constructed based on the current soil available water to dynamically constrain the estimation process of the photosynthesis model and the actual evapotranspiration model using the soil water stress function; long-sequence daily-scale historical water and carbon flux data and historical remote sensing observation data of the multiple target flux sites are obtained, and the photosynthesis model, the evapotranspiration model and the water balance model are calibrated using the historical water and carbon flux data and the historical remote sensing observation data to obtain a terrestrial ecosystem water and carbon flux estimation model that considers water balance constraints; the historical water and carbon flux data are input into the terrestrial ecosystem water and carbon flux estimation model that considers water balance constraints to estimate water and carbon flux data of the multiple target flux sites.

[0007] Optionally, the estimating the current leaf-scale photosynthetic rate and the current stomatal conductance of the plurality of target flux sites using a pre-built photosynthesis model comprises:

[0008] based on Fick Diffusion law, integration FWf The photosynthesis model and the stomatal conductance model are used to construct the photosynthesis model; and the current leaf-scale photosynthetic rate and the current stomatal conductance of multiple target flux sites are estimated using the photosynthesis model.

[0009] Optionally, upscaling the current leaf-scale photosynthetic rate and the current stomatal conductance to obtain the total primary productivity of canopy vegetation and canopy conductance respectively includes:

[0010] The current leaf-scale photosynthetic rate and the current stomatal conductance are upscaled to the total primary productivity of the canopy vegetation and the canopy conductance by using a preset vegetation yin-yang leaf upscaling scheme, wherein the preset vegetation yin-yang leaf upscaling scheme is:

[0011]

[0012] in, is the canopy photosynthetic rate, is the photosynthetic rate of sun-growing leaves, is the leaf area index of sun-growing leaves, is the photosynthetic rate of shade-growing leaves, is the leaf area index of shade leaves.

[0013] Optionally, the water balance model is expressed as:

[0014]

[0015]

[0016]

[0017] in, is the amount of water available in the soil, is the daily precipitation, To simulate daily evapotranspiration, For runoff, and They are t Moment and t -1 moment of available water for vegetation, The maximum amount of water available for vegetation.

[0018] A second embodiment of the present invention provides a terrestrial ecosystem water and carbon flux estimation device taking into account water balance constraints, comprising:

[0019] The photosynthesis estimation module is used to estimate the current leaf-scale photosynthetic rate and the current stomatal conductance of multiple target flux sites using a pre-built photosynthesis model; the upscaling module is used to upscale the current leaf-scale photosynthetic rate and the current stomatal conductance respectively to obtain the total primary productivity of canopy vegetation and canopy conductance; the evapotranspiration estimation module is used to estimate the total primary productivity of canopy vegetation, the canopy conductance and the pre-built evapotranspiration model. PMAn evapotranspiration model is used to construct an actual evapotranspiration model to estimate current evapotranspiration data using the actual evapotranspiration model; a water estimation module is used to construct a water balance model based on the current evapotranspiration data and a pre-constructed water balance equation to estimate current soil available water using the water balance model; a constraint module is used to construct a soil water stress function based on the current soil available water to dynamically constrain the estimation process of the photosynthesis model and the actual evapotranspiration model using the soil water stress function; a calibration module is used to obtain long-sequence daily-scale historical water and carbon flux data and historical remote sensing observation data of the multiple target flux sites, and use the historical water and carbon flux data and the historical remote sensing observation data to calibrate the photosynthesis model, the evapotranspiration model and the water balance model to obtain a terrestrial ecosystem water and carbon flux estimation model that considers water balance constraints; a water and carbon flux estimation module is used to input the historical water and carbon flux data into the terrestrial ecosystem water and carbon flux estimation model that considers water balance constraints to estimate water and carbon flux data of the multiple target flux sites.

[0020] Optionally, the photosynthesis estimation module includes:

[0021] Photosynthesis model building unit for Fick Diffusion law, integration FWf The photosynthesis model and the stomatal conductance model are used to construct the photosynthesis model; and the photosynthesis estimation unit is used to estimate the current leaf-scale photosynthetic rate and the current stomatal conductance of multiple target flux sites using the photosynthesis model.

[0022] Optionally, the upscaling module includes:

[0023] The current leaf-scale photosynthetic rate and the current stomatal conductance are upscaled to the total primary productivity of the canopy vegetation and the canopy conductance by using a preset vegetation yin-yang leaf upscaling scheme, wherein the preset vegetation yin-yang leaf upscaling scheme is:

[0024]

[0025] in, is the canopy photosynthetic rate, is the photosynthetic rate of sun-growing leaves, is the leaf area index of sun-growing leaves, is the photosynthetic rate of shade-growing leaves, is the leaf area index of shade leaves.

[0026] Optionally, the expression of the water balance model includes:

[0027]

[0028]

[0029]

[0030] in, is the amount of water available in the soil, is the daily precipitation, To simulate daily evapotranspiration, For runoff, and They are t Moment and t -1 moment of available water for vegetation, The maximum amount of water available for vegetation.

[0031] A third aspect of the present invention provides an electronic device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for estimating water and carbon flux in terrestrial ecosystems taking into account water balance constraints as described in the above embodiment.

[0032] A fourth aspect of the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-mentioned method for estimating water and carbon flux in terrestrial ecosystems considering water balance constraints.

[0033] The method for estimating water and carbon fluxes in terrestrial ecosystems considering water balance constraints proposed in the embodiment of the present invention is based on water and carbon flux data of long-series daily-scale flux stations and remote sensing observation data. By integrating photosynthesis model and evapotranspiration model with stomatal conductance equation and dynamic soil water stress derived from water balance constraints, a robust estimation method is constructed under the conditions of maintaining consistent vegetation physiological characteristics and considering dynamic soil water feedback. GPP and ET A terrestrial ecosystem water and carbon flux model considering water balance constraints based on the dynamic process of Farquhar-Penman-Monteith-Leuning , FPML ), the model has the characteristics of complete process and transparent structure, so it has good applicability; it can be used to simulate the spatiotemporal characteristics of water and carbon fluxes in terrestrial ecosystems and the laws of water-carbon coupling, robustly evaluate the evolution of water and carbon cycles, help understand the response of terrestrial ecosystems to the changing climate environment, and provide an effective scientific basis for sustainable water resources and carbon management.

[0034] Additional aspects and advantages of the present invention will be set forth in part in the description which follows and, in part, will be obvious from the description which follows, or may be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0036] Figure 1 A schematic flow chart of a method for estimating water and carbon flux in terrestrial ecosystems considering water balance constraints provided by an embodiment of the present invention;

[0037] Figure 2 A summary graph of GPP and ET simulated NSE for each daily scale of different ecosystems provided by an embodiment of the present invention;

[0038] Figure 3 A different ecosystem provided by an embodiment of the present invention GPP and ET Simulated scatter plot;

[0039] Figure 4 A different site provided by an embodiment of the present invention GPP Multi-year average seasonal dynamic simulation process diagram;

[0040] Figure 5 A different site provided by an embodiment of the present invention ET Multi-year average seasonal dynamic simulation process diagram;

[0041] Figure 6 A different ecosystem provided by an embodiment of the present invention WUE Simulated scatter plot;

[0042] Figure 7 A schematic block diagram of a device for estimating water and carbon flux in a terrestrial ecosystem taking into account water balance constraints provided by an embodiment of the present invention;

[0043] Figure 8 The present invention provides a schematic structural diagram of an electronic device.

[0044] Explanation of the accompanying figures: 70-water and carbon flux estimation device for terrestrial ecosystems considering water balance constraints, 701-photosynthesis estimation module, 702-scaling module, 703-evapotranspiration estimation module, 704-water estimation module, 705-constraint module, 706-calibration module, 707-water and carbon flux estimation module, 801-memory, 802-processor and 803-communication interface. DETAILED DESCRIPTION

[0045] The following describes embodiments of the present invention in detail, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and are not to be construed as limiting the present invention.

[0046] The following describes a method for estimating water and carbon fluxes in a terrestrial ecosystem considering water balance constraints according to an embodiment of the present invention with reference to the accompanying drawings.

[0047] Figure 1 A schematic flow chart of a method for estimating water and carbon flux in terrestrial ecosystems taking into account water balance constraints provided by an embodiment of the present invention.

[0048] like Figure 1 As shown in FIG, the method for estimating water carbon flux in terrestrial ecosystems considering water balance constraints includes the following steps:

[0049] In step S101 , a pre-built photosynthesis model is used to estimate the current leaf-scale photosynthetic rate and the current stomatal conductance of multiple target flux sites.

[0050] In some embodiments, estimating the current leaf-scale photosynthetic rate and the current stomatal conductance of a plurality of target flux sites using a pre-built photosynthesis model includes:

[0051] based on Fick Diffusion law, integration FWf The photosynthesis model and stomatal conductance model were used to construct the photosynthesis model;

[0052] The photosynthesis model was used to estimate the current leaf-scale photosynthetic rate and current stomatal conductance at multiple target flux sites.

[0053] In the actual implementation process, through the integration FWf Photosynthesis model, stomatal conductance equation and Fick The diffusion law is used to construct a photosynthesis model to estimate the leaf-scale photosynthetic rate, intercellular carbon dioxide concentration, and stomatal conductance. The specific expression is as follows:

[0054] (1)

[0055] (2)

[0056] (3)

[0057] Where, is the net photosynthetic rate, A c Shuttle limiting photosynthetic rate, for RuBPRegenerated limited photosynthetic rate, Transport limited photosynthetic rate, for dark respiration, for maximum rate of sucrose production, for intercellular CO2 concentration, for CO2 compensation point, for intercellular O2 concentration, and for enzyme reaction constant, for electron transport rate and is given by:

[0058] (4)

[0059] where, is a curvature parameter set to 0.7, is the maximum electron transport rate and can be expressed as a function of , is the number of light electrons utilized by photosystem II in the electron transport process μmol m -2 s -1 The light utilized by the photosystem II in the electron transport process can be converted from the absorbed photosynthetically active radiation φ , W m -2 by multiplying by 4.6 μmol J -1 (5)

[0060] where, is the quantum yield of photosystem II and is set to 0.7.

[0061] To solve for the remaining unknown variables (i.e. and ), the stomatal conductance model and Fick diffusion law are coupled with the model: FWf

[0062] (6)

[0063] (7)

[0064] where, ( μmol m -2 s -1 ) is the stomatal conductance of the leaf to CO2, CO ( μmol m -2 s -1 ) is a constant, ​​​is the stomatal conductance coefficient, ( kPa ) is the water vapor pressure difference on the blade surface ( VPD ), To reflect right Sensitivity parameters, and ( μmol mol -1 ) is the carbon dioxide concentration of the blade and the atmosphere, ignoring the blade boundary layer resistance Approximately equal to By combining equations (1), (6) and (7), we can solve 、 and and other variables.

[0065] Furthermore, the photosynthesis model was used to estimate the current leaf-scale photosynthetic rate and current stomatal conductance at multiple target flux sites.

[0066] In step S102, the current leaf-scale photosynthetic rate and the current stomatal conductance are upscaled respectively to obtain the total primary productivity of the canopy vegetation and the canopy conductance.

[0067] In the actual implementation process, the current leaf-scale photosynthetic rate is scaled to the total primary productivity of canopy vegetation, and the current stomatal conductance is scaled to the canopy conductance through the preset vegetation yin-yang leaf upscaling scheme. Among them, the preset vegetation yin-yang leaf upscaling scheme is:

[0068] (8)

[0069] in, is the canopy photosynthetic rate, is the photosynthetic rate of sun-growing leaves, is the leaf area index of the sun-growing leaves, which is obtained by the following formula (9): is the photosynthetic rate of shade-growing leaves, is the leaf area index of shade leaves, which is obtained by the following formula (10).

[0070] (9)

[0071] (10)

[0072] Where, is the solar zenith angle, is the parameter representing the leaf overlap in the canopy radiation system, the maximum shuttle rate and leaf nitrogen content ( ) and the latter is linearly correlated with the leaf area index in the vertical direction. The increase in decreases exponentially:

[0073] (11)

[0074] (12)

[0075] Where, and is the nitrogen content at the top of the canopy and the maximum shuttle rate at 25°C, = 0.3, is the attenuation rate, Water stress factor and maximum shuttle rate multiplied by the leaf-scale photosynthetic rate constraining the photosynthesis model, The maximum fusiformization rate of the yin-yang leaf is obtained by integrating the vertical LAI. It can be expressed as:

[0076] (13)

[0077] (14)

[0078] Where, , is the maximum shuttle rate of the sun leaf, is the maximum shuttle rate of shaded leaves, taking into account the fact that the sun-exposed leaves and shaded leaves do not absorb direct and diffuse radiation.

[0079] In step S103, the total primary productivity of canopy vegetation, canopy conductance and pre-constructed PM Evapotranspiration model builds actual evapotranspiration model to estimate current evapotranspiration data using actual evapotranspiration model.

[0080] In the actual implementation process, according to the total primary productivity of canopy vegetation, canopy conductance and pre-constructed PM The evapotranspiration model constructs the actual evapotranspiration model and uses the actual evapotranspiration model to estimate the current evapotranspiration data. The specific expression of the actual evapotranspiration model is:

[0081] (15)

[0082] (16)

[0083] (17)

[0084] Where, for vegetation transpiration ( mm d -1 ), is the saturated vapor pressure difference (Pd), kPa is the soil evaporation (Es), mm d -1 is the actual evapotranspiration (ET), mm d -1 is the slope of the temperature curve (S), kPa℃ -1 VPD is the psychrometer constant (C), -1 kPa℃ is the leaf area index (LAI), MJ m -2 d -1 is the absorbed energy by the canopy and soil from the total energy (Rn), is the extinction coefficient (K), m 2 m -2 is the air density (p), gm -3 is the specific heat of air at constant pressure (cp), J g -1 ℃ -1 is the aerodynamic and canopy conductance (g), m s -1 f 1 is a dimensionless variable representing the available water capacity of soil evaporation.

[0085] In step S104, a water balance model is constructed according to the current evapotranspiration data and the pre-constructed water balance equation to estimate the current soil available water capacity using the water balance model.

[0086] In actual implementation, a water balance module for estimating soil available water capacity is constructed according to the current evapotranspiration data and the pre-constructed water balance equation, wherein the expression of the water balance model is:

[0087] (18)

[0088] (19)

[0089] ​​​​​​​​​​​​​​​​(20)

[0090] in, is the current soil available water content, Daily precipitation ( mm ), To simulate daily evapotranspiration ( mm ), For runoff ( mm ), and They are t Moment and t -1 moment of available water for vegetation ( mm ), is the parameter of the maximum available water for vegetation ( mm ), the available water obtained is further used to constrain photosynthesis and evapotranspiration, achieving dynamic feedback of soil moisture on water and carbon fluxes.

[0091] In step S105, a soil water stress function is constructed according to the current available soil water content, so as to utilize the soil water stress function to dynamically constrain the estimation process of the photosynthesis model and the actual evapotranspiration model.

[0092] In the actual implementation process, the moisture scalar f 2 as a water stress factor and the maximum rate of Multiplying the leaf-scale photosynthetic rate of the constrained photosynthesis model, and combining it with the actual soil available water content to construct the soil water stress function, and then using the soil water stress function to constrain the evapotranspiration data of the actual evapotranspiration model. The specific expression of the soil water stress function is:

[0093] (twenty one)

[0094] (twenty two)

[0095] Where, is a dimensionless variable that characterizes the amount of water available for evaporation from the soil. for t The simulated soil available water content at each moment (mm), is the parameter of the maximum available water for vegetation ( mm ), and It is the parameter that controls the effect of water stress on carbon assimilation rate.

[0096] In step S106, long-sequence daily-scale historical water and carbon flux data and historical remote sensing observation data of multiple target flux sites are obtained, and the photosynthesis model, evapotranspiration model and water balance model are calibrated using the historical water and carbon flux data and historical remote sensing observation data to obtain a terrestrial ecosystem water and carbon flux estimation model that takes into account water balance constraints.

[0097] In step S107, the historical water and carbon flux data are input into a terrestrial ecosystem water and carbon flux estimation model that considers water balance constraints to estimate water and carbon flux data for multiple target flux sites.

[0098] In the actual implementation process, long-series daily-scale historical water and carbon flux data such as meteorological, GPP, and ET data and historical remote sensing observation data are obtained for multiple target flux sites. The parameters of the photosynthesis model, evapotranspiration model, and water balance model at different flux sites are calibrated using the historical water and carbon flux data and remote sensing observation data to obtain a terrestrial ecosystem water and carbon flux estimation model that takes into account water balance constraints. The specific expression of the terrestrial ecosystem water and carbon flux estimation model is:

[0099]

[0100] in, is the net photosynthetic rate, A c Shuttle limiting photosynthetic rate, for RuBP Regeneration limits photosynthetic rate, To limit photosynthetic rate, Breathing in the dark, is the maximum shuttle rate, is the intercellular carbon dioxide concentration, is the carbon dioxide concentration compensation point, is the intercellular oxygen concentration, and is the enzyme reaction constant, is the electron transfer rate, For leaf pairs CO 2 stomatal conductance, is a constant, is the stomatal conductance coefficient, is the carbon dioxide concentration in the leaves, is the water vapor pressure difference on the blade surface, To reflect right Sensitivity parameters, is the atmospheric carbon dioxide concentration, For vegetation transpiration, , yes VPD The slope of the temperature curve, is the hygrometer constant, is the saturation vapor pressure difference, and are the aerodynamic conductance and canopy conductance, For soil evaporation, f 1 is a dimensionless variable representing the amount of water available for evaporation from the soil, and is the energy absorbed by the canopy and soil divided from the total energy, is the actual evaporation, is the current soil available water content, is the daily precipitation, To simulate daily evapotranspiration, For runoff ( mm ), and They are t Moment and t -1 The amount of water available for vegetation simulated at time 1, It is the parameter of the maximum available water for vegetation.

[0101] Furthermore, after the calibration of the terrestrial ecosystem water and carbon flux estimation model considering water balance constraints is completed, preset evaluation indicators are selected to evaluate the simulation accuracy of water and carbon fluxes such as GPP, ET and WUE. When the simulation accuracy reaches the preset threshold, the terrestrial ecosystem water and carbon flux estimation model considering water balance constraints is used to estimate the water and carbon flux data of multiple target flux sites.

[0102] The method for estimating water and carbon flux in terrestrial ecosystems considering water balance constraints proposed in the embodiment of the present invention is further described below through a specific example.

[0103] Select from the resolution of 500 m and 8 d Leaf area index of remote sensing product MOD15A2H ( LAI ) data from 2003 to 2015. LAI The data were further interpolated and extracted to match the daily flow observation data. It should be noted that the meteorological and flux observation data used are from the FLUXNET2015 dataset, and only the flux observation data and soil moisture content ( SWC ) were used for analysis.

[0104] A total of 32 flux sites were selected, covering a variety of vegetation types, including shrubland ( CSH and OSH ),grassland( GRA ), savanna ( WSA )、Mixed forest( MF ), evergreen coniferous forest ( ENF ) and deciduous broad-leaved forests ( DBF ).

[0105] By inputting flux observations, conventional meteorological data, water and carbon flux data, and remote sensing LAI Data, with GPP The minimum total error of ET is used as the objective function to calibrate the model parameters and evaluate the model simulation daily scale GPP , ET and WUE The performance of the evaluation index is the Nash efficiency coefficient. NSE and R 2 , the formula is as follows:

[0106] (twenty three)

[0107] (twenty four)

[0108] Where, and are the observed and simulated values, yes The average value, yes The average value ( = 1, 2,..., ).

[0109] like Figure 2 The results show that the proposed method exhibits robust performance in simulating gross primary productivity and evapotranspiration in different ecosystem types. GPP In the simulation, the average NSE values ​​of different ecosystem types were always higher than 0.6, with the deciduous broad-leaved forest having the highest performance ( NSE = 0.80), with evergreen coniferous forests performing the worst ( NSE = 0.62). Across all flux sites, the estimated daily annual GPP The overall average NSE About 0.64 ± 0.24. ET In terms of estimation, the average accuracy of this method is slightly higher than GPP ,average NSE Value from shrubs ( CSH / OSH ) of 0.55 to grass ( GRA ) ranged from 0.83 to 1. ETThe average NSE value is approximately 0.65 ± 0.22. Notably, the method tends to perform better for evapotranspiration in open-canopy ecosystems such as grasslands and savannas than in closed-canopy forest systems, likely due to the stronger coupling between stomatal conductance and atmospheric drivers in these ecosystems. Figure 3 Shows the model's simulated daily values ​​for all six ecosystem types. GPP and ET. GPP Perform well, NSE Value from ENF 0.66 to CSH / OSH Evapotranspiration is estimated to be 0.82. NSE The values ​​range from 0.58 to 0.85. The scatter plot of simulated water and carbon fluxes versus observed water and carbon fluxes further demonstrates the model's ability to simulate daily flux variations in different ecosystem types. Most points are concentrated near the 1:1 line, especially in the open canopy system, which reflects the robust agreement between the simulated and observed values. In addition, Figure 4 and 5 As shown in Figure 2, the model successfully captures the GPP and ET The seasonal dynamics of the simulated monthly averages are highly correlated with the observed values. GPP and ET Simulated R 2 All exceeded 0.45 and passed the significance test ( p <0.01), indicating that the simulated GPP and ET The seasonal characteristics of the model are strongly correlated with the observed characteristics. In summary, the consistency of model performance across a variety of climates and vegetation types demonstrates the robustness of the approach in simulating water and carbon fluxes.

[0110] like Figure 6 As shown in the figure, by evaluating the ecosystem water use efficiency of different vegetation types at monthly and annual scales ( WUE ), further verifying the performance of this method in capturing the water-carbon coupling characteristics. Compared with the annual scale, the ecosystem water use efficiency varies more at the monthly scale. WUE There is a moderate correlation with the observed value ( R 2 = 0.51), in WUE At higher values, there is significant dispersion ( Figure 6 In contrast, on the annual scale, the model performance improves significantly, with the simulated values ​​being in close agreement with the observed values. R 2 Reached 0.79 ( Figure 6At the ecosystem scale, this method robustly reproduces the water use efficiency of six vegetation types ( WUE ) variation characteristics, the simulated values ​​are very close to the observed values ​​( Figure 6 In three forest ecosystems (including MF 、 ENF and DBF ), the model slightly overestimates the observed mean water use efficiency, with observed and simulated values ​​ranging from 3.38 to 4.10, respectively. gC -1 H 2 O d -1 and 3.09 to 4.52 gC -1 H 2 O d -1 In the three non-forest ecosystems, the model also showed good agreement, with observed and simulated values ​​ranging from 1.69 to 2.68, respectively. gC -1 H 2 O d -1 and 1.60 to 3.11 gC -1 H 2 O d -1 These results indicate that the approach captures the trade-offs between carbon and water cycles in ecosystems well, especially at annual timescales.

[0111] It can be seen from this that the embodiment of the present invention can effectively simulate GPP 、 ET and WUE , robustly capturing its spatiotemporal variation characteristics.

[0112] In summary, the method for estimating water and carbon fluxes in terrestrial ecosystems considering water balance constraints proposed in an embodiment of the present invention is based on water and carbon flux data of long-series daily-scale flux stations and remote sensing observation data. By integrating the photosynthesis model and evapotranspiration model with the stomatal conductance equation and the dynamic soil water stress derived from the water balance constraint, a water and carbon flux model for terrestrial ecosystems considering water balance constraints is constructed, which can robustly estimate the dynamic process of GPP and ET while maintaining consistent vegetation physiological characteristics and considering the dynamic feedback of soil moisture. The model has the characteristics of complete process and transparent structure, and therefore has good applicability. It can be used to simulate the spatiotemporal characteristics of water and carbon fluxes in terrestrial ecosystems and the water-carbon coupling laws, robustly evaluate the evolution dynamics of water and carbon cycles, help understand the response of terrestrial ecosystems to the changing climate environment, and provide an effective scientific basis for sustainable water resources and carbon management.

[0113] Next, a device for estimating water and carbon flux in a terrestrial ecosystem considering water balance constraints according to an embodiment of the present invention will be described with reference to the accompanying drawings.

[0114] Figure 7 A schematic block diagram of a device for estimating water and carbon flux in a terrestrial ecosystem taking into account water balance constraints provided by an embodiment of the present invention.

[0115] like Figure 7 As shown, the terrestrial ecosystem water-carbon flux estimation device 70 considering water balance constraints includes: a photosynthesis estimation module 701, a scaling module 702, an evapotranspiration estimation module 703, a water estimation module 704, a constraint module 705, a calibration module 706 and a water-carbon flux estimation module 707.

[0116] Among them, the photosynthesis estimation module 701 is used to estimate the current leaf-scale photosynthetic rate and current stomatal conductance of multiple target flux sites using a pre-constructed photosynthesis model. The upscaling module 702 is used to upscale the current leaf-scale photosynthetic rate and current stomatal conductance respectively to obtain the total primary productivity of canopy vegetation and canopy conductance. The evapotranspiration estimation module 703 is used to construct an actual evapotranspiration model based on the total primary productivity of canopy vegetation, canopy conductance and a pre-constructed PM evapotranspiration model, so as to estimate the current evapotranspiration data using the actual evapotranspiration model. The water estimation module 704 is used to construct a water balance model based on the current evapotranspiration data and a pre-constructed water balance equation, so as to estimate the current available soil water using the water balance model. The constraint module 705 is used to construct a soil water stress function based on the current available soil water, so as to dynamically constrain the estimation process of the photosynthesis model and the actual evapotranspiration model using the soil water stress function. Calibration module 706 is used to obtain long-sequence daily-scale historical water and carbon flux data and historical remote sensing observation data for multiple target flux sites, and use the historical water and carbon flux data and historical remote sensing observation data to calibrate the photosynthesis model, evapotranspiration model, and water balance model to obtain a terrestrial ecosystem water and carbon flux estimation model that considers water balance constraints. Water and carbon flux estimation module 707 is used to input the historical water and carbon flux data into the terrestrial ecosystem water and carbon flux estimation model that considers water balance constraints to estimate water and carbon flux data for multiple target flux sites.

[0117] In some embodiments, the photosynthesis estimation module 701 includes:

[0118] Photosynthesis model building unit for Fick Diffusion law, integration FWf The photosynthesis model and stomatal conductance model were used to construct the photosynthesis model;

[0119] The photosynthesis estimation unit is configured to estimate, using a photosynthesis model, a current leaf-scale photosynthetic rate and a current stomatal conductance for a plurality of target flux sites.

[0120] In some embodiments, the upscaling module 702 comprises:

[0121] The current leaf-scale photosynthetic rate and the current stomatal conductance are upscaled to a canopy vegetation gross primary productivity and a canopy conductance by a preset vegetation sunshade leaf upscaling scheme, wherein the preset vegetation sunshade leaf upscaling scheme is:

[0122]

[0123] wherein, is the canopy photosynthetic rate, is the photosynthetic rate of sun leaves, is the leaf area index of sun leaves, is the photosynthetic rate of shade leaves, is the leaf area index of shade leaves.

[0124] In some embodiments, the expression of the water balance model comprises:

[0125]

[0126]

[0127]

[0128] wherein, is the soil available water, is the daily precipitation, is the simulated daily evapotranspiration, is the runoff, and are the vegetation available water at t time and t -1 time, respectively, is the maximum vegetation available water.

[0129] It should be noted that the aforementioned explanation of the embodiment of the method for estimating water-carbon fluxes of a terrestrial ecosystem considering water balance constraints is also applicable to the embodiment of the device for estimating water-carbon fluxes of a terrestrial ecosystem considering water balance constraints, and will not be repeated here.

[0130] According to an embodiment of the present invention, a terrestrial ecosystem water and carbon flux estimation device considering water balance constraints is proposed. Based on long-sequence water and carbon flux data of daily-scale flux stations and remote sensing observation data, a photosynthesis model and an evapotranspiration model are integrated with the stomatal conductance equation and the dynamic soil moisture stress derived from the water balance constraint to construct a terrestrial ecosystem water and carbon flux model considering water balance constraints, which can robustly estimate the dynamic process of GPP and ET while maintaining consistent vegetation physiological characteristics and considering the dynamic feedback of soil moisture. The model has the characteristics of complete process and transparent structure, and therefore has good applicability. It can be used to simulate the spatiotemporal characteristics of water and carbon fluxes and the water-carbon coupling laws of terrestrial ecosystems, robustly evaluate the evolution dynamics of water and carbon cycles, help understand the response of terrestrial ecosystems to the changing climate environment, and provide an effective scientific basis for sustainable water resources and carbon management.

[0131] Figure 8 This is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. The electronic device may include:

[0132] A memory 801 , a processor 802 , and a computer program stored in the memory 801 and executable on the processor 802 .

[0133] When the processor 802 executes the program, the method for estimating water and carbon flux in terrestrial ecosystems considering water balance constraints provided in the above embodiment is implemented.

[0134] Furthermore, the electronic device further includes:

[0135] The communication interface 803 is used for communication between the memory 801 and the processor 802 .

[0136] The memory 801 is used to store computer programs that can be run on the processor 802.

[0137] The memory 801 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0138] If the memory 801, processor 802, and communication interface 803 are implemented independently, the communication interface 803, memory 801, and processor 802 can be connected to each other via a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. Buses can be divided into address buses, data buses, control buses, etc. For ease of representation, Figure 8 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0139] Optionally, in a specific implementation, if the memory 801, the processor 802 and the communication interface 803 are integrated on a chip, the memory 801, the processor 802 and the communication interface 803 can communicate with each other through an internal interface.

[0140] The processor 802 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention.

[0141] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned method for estimating water and carbon flux in terrestrial ecosystems considering water balance constraints.

[0142] In the description of this specification, the reference terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and features of different embodiments or examples without contradiction.

[0143] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of technical features indicated. Thus, a feature specified as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "N" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0144] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or N executable instructions for implementing a custom logical function or step of a process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention pertain.

[0145] The logic and / or steps represented in a flowchart or otherwise described herein, for example, can be considered a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" is any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (not exhaustive) of computer-readable media include: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program can be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing it in other suitable ways as necessary, and then storing it in a computer memory.

[0146] It should be understood that various components of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiment, the N steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented using hardware, as in another embodiment, any of the following technologies known in the art or a combination thereof can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application-specific integrated circuits having suitable combinational logic gate circuits, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0147] Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0148] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing module, or each unit may exist physically separately, or two or more units may be integrated into a single module. The aforementioned integrated modules may be implemented in the form of hardware or in the form of software functional modules. If the integrated modules are implemented in the form of software functional modules and sold or used as independent products, they may also be stored in a computer-readable storage medium.

[0149] The storage medium mentioned above may be a read-only memory, a magnetic disk, or an optical disk, etc. Although the embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and are not to be construed as limiting the present invention. Persons skilled in the art may make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for estimating water and carbon flux in terrestrial ecosystems considering water balance constraints, characterized by: The following steps are involved: Use a pre-built photosynthesis model to estimate the current leaf-scale photosynthetic rate and current stomatal conductance at multiple target flux sites; Upscaling the current leaf-scale photosynthetic rate and the current stomatal conductance to obtain the total primary productivity of canopy vegetation and canopy conductance; constructing an actual evapotranspiration model according to the total primary productivity of canopy vegetation, the canopy conductance, and a pre-constructed evapotranspiration model, so as to estimate current evapotranspiration data using the actual evapotranspiration model; constructing a water balance model based on the current evapotranspiration data and a pre-constructed water balance equation to estimate current soil available water using the water balance model; constructing a soil water stress function according to the current available soil water content, so as to dynamically constrain the estimation processes of the photosynthesis model and the actual evapotranspiration model using the soil water stress function; Obtaining long-sequence daily-scale historical water and carbon flux data and historical remote sensing observation data for the multiple target flux sites, and calibrating the photosynthesis model, the evapotranspiration model, and the water balance model using the historical water and carbon flux data and the historical remote sensing observation data to obtain a terrestrial ecosystem water and carbon flux estimation model that considers water balance constraints; The historical water and carbon flux data are input into the terrestrial ecosystem water and carbon flux estimation model considering water balance constraints to estimate the water and carbon flux data of the multiple target flux sites.

2. The method for estimating water and carbon flux in terrestrial ecosystems considering water balance constraints according to claim 1, characterized in that: The method uses a pre-built photosynthesis model to estimate the current leaf-scale photosynthetic rate and current stomatal conductance of multiple target flux sites, including: based on Fick Diffusion law, integration FWf A photosynthesis model and a stomatal conductance model are used to construct the photosynthesis model; The photosynthesis model was used to estimate the current leaf-scale photosynthetic rate and current stomatal conductance at multiple target flux sites.

3. The method for estimating water and carbon flux in terrestrial ecosystems considering water balance constraints according to claim 1, characterized in that: The upscaling of the current leaf-scale photosynthetic rate and the current stomatal conductance to obtain the total primary productivity of canopy vegetation and canopy conductance includes: The current leaf-scale photosynthetic rate and the current stomatal conductance are upscaled to the total primary productivity of the canopy vegetation and the canopy conductance by using a preset vegetation yin-yang leaf upscaling scheme, wherein the preset vegetation yin-yang leaf upscaling scheme is: in, is the canopy photosynthetic rate, is the photosynthetic rate of sun-growing leaves, is the leaf area index of sun-growing leaves, is the photosynthetic rate of shade-growing leaves, is the leaf area index of shade leaves.

4. The method for estimating water and carbon flux in terrestrial ecosystems considering water balance constraints according to claim 1, characterized in that: The expression of the water balance model is: in, is the amount of water available in the soil, is the daily precipitation, To simulate daily evapotranspiration, For runoff, and They are t Moment and t -1 moment of available water for vegetation, The maximum amount of water available for vegetation.

5. A device for estimating water and carbon flux in terrestrial ecosystems considering water balance constraints, characterized in that: include: A photosynthetic estimation module, which is used to estimate the current leaf-scale photosynthetic rate and current stomatal conductance of multiple target flux sites using a pre-built photosynthesis model; an upscaling module, for upscaling the current leaf-scale photosynthetic rate and the current stomatal conductance, respectively, to obtain the total primary productivity of canopy vegetation and canopy conductance; an evapotranspiration estimation module, configured to construct an actual evapotranspiration model based on the total primary productivity of the canopy vegetation, the canopy conductance, and a pre-constructed evapotranspiration model, so as to estimate current evapotranspiration data using the actual evapotranspiration model; a water estimation module, configured to construct a water balance model based on the current evapotranspiration data and a pre-constructed water balance equation, so as to estimate the current available soil water using the water balance model; a constraint module, configured to construct a soil water stress function according to the current available soil water content, so as to dynamically constrain the estimation processes of the photosynthesis model and the actual evapotranspiration model using the soil water stress function; a calibration module for obtaining long-sequence daily-scale historical water and carbon flux data and historical remote sensing observation data for the plurality of target flux sites, and calibrating the photosynthesis model, the evapotranspiration model, and the water balance model using the historical water and carbon flux data and the historical remote sensing observation data to obtain a terrestrial ecosystem water and carbon flux estimation model that takes into account water balance constraints; The water-carbon flux estimation module is used to input the historical water-carbon flux data into the terrestrial ecosystem water-carbon flux estimation model considering water balance constraints to estimate the water-carbon flux data of the multiple target flux sites.

6. The device for estimating water and carbon flux in terrestrial ecosystems considering water balance constraints according to claim 5, characterized in that: The photosynthetic estimation module comprises: Photosynthesis model building unit for Fick Diffusion law, integration FWf A photosynthesis model and a stomatal conductance model are used to construct the photosynthesis model; A photosynthetic estimation unit is used to estimate the current leaf-scale photosynthetic rate and the current stomatal conductance of multiple target flux sites using the photosynthesis model.

7. The device for estimating water and carbon flux in terrestrial ecosystems considering water balance constraints according to claim 5, characterized in that: The upscaling module includes: The current leaf-scale photosynthetic rate and the current stomatal conductance are upscaled to the total primary productivity of the canopy vegetation and the canopy conductance by using a preset vegetation yin-yang leaf upscaling scheme, wherein the preset vegetation yin-yang leaf upscaling scheme is: in, is the canopy photosynthetic rate, is the photosynthetic rate of sun-growing leaves, is the leaf area index of sun-growing leaves, is the photosynthetic rate of shade-growing leaves, is the leaf area index of shade leaves.

8. The device for estimating water and carbon flux in terrestrial ecosystems considering water balance constraints according to claim 5, characterized in that: The expression of the water balance model includes: in, is the amount of water available in the soil, is the daily precipitation, To simulate daily evapotranspiration, For runoff, and They are t Moment and t -1 moment of available water for vegetation, The maximum amount of water available for vegetation.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for estimating water and carbon flux in terrestrial ecosystems considering water balance constraints as described in any one of claims 1 to 4.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the method for estimating water and carbon flux in terrestrial ecosystems considering water balance constraints as described in any one of claims 1 to 4.

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