Rice field evapotranspiration estimation method and system considering water heat storage item and advection item

Abstract

The invention provides a rice field evapotranspiration estimation method considering a water heat storage item and an advection item. The rice field evapotranspiration estimation method comprises the following steps: step 1, obtaining a time sequence of meteorological data, flux data, water depth data and water temperature data of a research area; 2, calculating a rice field growth period water heat storage item based on the time sequence of the water depth data and the water temperature data; 3, calculating an advection item based on the time sequence of the meteorological data; and 4, respectively adding the water heat storage item and the advection item into an energy balance equation to correct the P-M model, and calculating an evapotranspiration estimated value based on the corrected P-M model. According to the method, the particularity that the rice field is in the waterflooding state in the growth period is comprehensively considered, the energy balance closure degree is improved by introducing two secondary energy items, namely the water heat storage item and the advection item, and all forms of energy participating in the energy transmission process are quantified to the maximum extent; the improvement of the estimation precision of the traditional P-M model and the more accurate estimation of the water consumption of the rice in the rice field are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of evapotranspiration estimation, and particularly to a method and system for estimating paddy field evapotranspiration considering water heat storage term and advection term. Background Art

[0002] Evapotranspiration is the key link connecting water and energy transfer between the earth's surface and the atmosphere, and is also the main way of farmland water consumption. It directly affects the surface temperature, water transfer, vegetation growth and the overall productivity of the ecosystem. As a key parameter controlling the water cycle and climate change of the global terrestrial ecosystem, evapotranspiration has a decisive impact on the cycles of energy and carbon. Approximately 70% of the surface precipitation re-enters the atmosphere through evaporation and transpiration, and in arid and semi-arid regions, this proportion can be as high as 90%. Rice is one of the food crops with the highest water demand. It needs to be flooded during most of its growth period, which makes the paddy field different from dryland agriculture and other ecosystems in terms of gas exchange. On the other hand, rice has a large water consumption. In-depth study of paddy field evapotranspiration can better understand the water demand law of rice growth, optimize the irrigation system, and has important practical significance for the rational development and utilization of water resources and the expansion of rice planting scale.

[0003] There are many methods for observing evapotranspiration, which can be mainly divided into several categories: micrometeorological method, hydrological method, infrared remote sensing method and plant physiological method. With the progress of technology, more models based on meteorological data have been widely used. Among them, the P-M model is a semi-empirical method based on the principles of energy balance and water transport. It is recognized as one of the most widely used and accurate formulas because it comprehensively considers heat factors and aerodynamic factors. The energy balance equation is an important theoretical basis for evapotranspiration models, expressed as Rn - G = LE + H. However, a large number of observations by eddy covariance systems show that the sum of turbulent energy LE + H is systematically lower than the available energy Rn - G, and the difference between the two reaches 10% - 30% of the available energy. This phenomenon is called the energy imbalance problem. This problem causes great uncertainty in the establishment and verification of evapotranspiration models.

[0004] Although the existing energy forced closure methods have improved the energy closure rate to a certain extent, the assumptions and simplifications introduced by the models may ignore some key physical processes, and there is still some uncertainty in the accurate estimation of paddy field evapotranspiration. Therefore, it is urgent to develop a paddy field evapotranspiration model considering the energy imbalance problem, add other forms of energy participating in the energy transfer process to the energy balance equation and the evapotranspiration estimation process, so as to improve the energy balance closure degree and the accuracy of the evapotranspiration model, and provide technical support for accurately estimating rice water consumption, optimizing the irrigation system and improving water resource utilization efficiency. Summary of the Invention

[0005] The present invention aims to solve the limitations existing in the prior art in improving the energy imbalance problem and further enhancing the estimation accuracy of the evapotranspiration model. A method for estimating paddy field evapotranspiration considering the water heat storage term and the advection term is proposed. This method does not rely on forcing the energy balance to close, but instead improves the energy closure degree by adding secondary energy terms, namely the water heat storage term and the advection term, to the energy balance equation, thereby improving the accuracy of the evapotranspiration model. It overcomes the estimation biases caused by the assumptions and simplifications introduced in existing studies that neglect some key physical processes. By adding secondary energy terms, namely the water heat storage term and the advection term, to the energy balance equation, the present invention deeply explores the contribution of the water heat storage term and the advection term in paddy fields to the energy transfer process, and adds the secondary energy terms to the energy balance equation to obtain an energy balance equation different from the traditional one that only considers net radiation, surface heat flux, latent heat flux, and sensible heat flux, thus achieving a higher energy closure degree. On this basis, the water heat storage term and the advection term are added to the classical P-M formula to obtain a paddy field evapotranspiration model considering the water heat storage term and the advection term. The model estimation results are verified through the actual observation results of the eddy covariance system, thereby obtaining a higher evapotranspiration estimation accuracy. The present invention innovatively solves the problem of structural errors caused by energy imbalance in traditional evapotranspiration models, comprehensively considers the particularity of paddy fields being in a flooded state during the growth period, and improves the energy balance closure degree by introducing two secondary energy terms, namely the water heat storage term and the advection term, to maximize the quantification of all forms of energy participating in the energy transfer process, realizing the improvement of the estimation accuracy of the traditional P-M model and more accurate estimation of the water consumption of paddy rice.

[0006] To solve the above technical problems, the present invention adopts the following technical solutions:

[0007] A method for estimating paddy field evapotranspiration considering the water heat storage term and the advection term, comprising the following steps:

[0008] Step 1, obtaining the time series of meteorological data, flux data, water depth data, and water temperature data of the research area;

[0009] Step 2, calculating the water heat storage term during the growth period of the paddy field based on the time series of the water depth data and the water temperature data;

[0010] Step 3, calculating the advection term based on the time series of the meteorological data;

[0011] Step 4, respectively adding the water heat storage term and the advection term to the energy balance equation to correct the P-M model, and calculating the evapotranspiration estimation value based on the corrected P-M model.

[0012] Further, the Step 1 includes the following sub-steps:

[0013] Step 1-1: Taking the center of the paddy field in the study area as the coordinate origin, proximal and distal meteorological observation stations are arranged in four directions to form a nine-point observation network. The Kriging spatial interpolation method is used to generate the temperature and humidity fields of the entire region, and the wind speed data of the study area is obtained;

[0014] Step 1-2: The net radiation Rn, soil heat flux G, latent heat flux LE, and sensible heat flux H of the study area are obtained through the eddy covariance system;

[0015] Step 1-3: A water level gauge is installed in the paddy field of the study area to monitor the water depth and water temperature data during the rice growth period, and the average water depth and water temperature at different scales are calculated respectively.

[0016] Furthermore, Step 2 includes the following sub-steps:

[0017] Step 2-1: Based on the average water temperature at different scales, the temperature gradient of the paddy field water temperature is calculated using the five-point derivative method; including central difference, forward difference, and backward difference;

[0018] Step 2-2: Based on the heat balance principle of the water body, a water body heat storage change equation under general conditions is established to calculate the water heat storage term at the corresponding scale.

[0019] Furthermore, the water heat storage term is expressed as:

[0020]

[0021] where S w represents the water heat storage term, C w is the specific heat capacity of water; ρ w is the density of water; D is the depth of the paddy field water layer, m; is the temperature gradient of the paddy field water temperature, K / s, Δt represents the time step, and Tw represents the paddy field water temperature.

[0022] Furthermore, Step 3 includes the following sub-steps:

[0023] Step 3-1: Calculate the specific humidity based on the actual water vapor pressure and atmospheric pressure;

[0024] Step 3-2: The finite difference method is used to calculate the air heat storage term, heat advection term, and water vapor advection term, where the water vapor advection term is calculated based on the specific humidity in Step 3-1.

[0025] Furthermore, the air heat storage term, heat advection term, and water vapor advection term are respectively:

[0026]

[0027] where F s is the air heat storage term, representing the heat stored by the unit volume of the atmosphere in a certain period of time; FTHA is the heat advection term, representing heat transport caused by the horizontal wind speed; F qHA is the water vapor advection term, representing water vapor transport under the action of the wind field. Similar to the heat advection term, this term measures the coupling effect of wind speed and water vapor gradient; T a is the air temperature; q is the specific humidity, representing the mass of water vapor per unit mass of moist air; are the average components of the wind speed in the x and y directions respectively; V m represents the control volume unit of the study area; Δz is the vertical thickness of the calculation area; z r is the reference height, i.e., the measurement point height; N is the total number of grid points; t is the time interval of the calculation; is the time rate of change of temperature; and are the horizontal gradients of temperature, representing the rates of change of temperature in the x and y directions; and are the horizontal gradients of water vapor concentration, representing the rates of change of water vapor concentration in the x and y directions; is the air temperature at the i-th moment; (x j , y k ) are the coordinates of the grid point.

[0028] Furthermore, step 5 includes the following sub-steps:

[0029] Step 5-1: Use Jarvis's surface impedance calibration model to estimate the surface impedance r s ,

[0030] Step 5-2: Add the water heat storage term and the advection term to the energy balance equation to correct the P-M model, and calculate the estimated evapotranspiration value based on the corrected P-M model.

[0031] Furthermore, the estimated evapotranspiration value calculated based on the corrected P-M model is expressed as:

[0032]

[0033] where ET represents the evapotranspiration amount; M represents the water heat storage term or the advection term; ρ a represents the air density; C p represents the specific heat capacity of air; e s and e a represent the saturated water vapor pressure and the actual water vapor pressure respectively; r s and r a are the surface impedance and the aerodynamic impedance respectively; Δ is the slope of the saturated vapor pressure curve, representing the sensitivity of the saturated water vapor pressure to temperature change at the current temperature; γ is the psychrometric constant.

[0034] Further, it also includes: calculating the energy balance ratios before and after introducing the water storage heat term and the advection term respectively, analyzing the energy balance ratio and the evapotranspiration estimation value after introducing the water storage heat term and the advection term year by year, revealing the dynamic variation laws of the secondary energy terms, namely the water storage heat term and the advection term, and their impacts on the evapotranspiration estimation value; verifying the evapotranspiration estimation value through the evapotranspiration data observed by the eddy covariance system.

[0035] On the other hand, the present invention provides a paddy field evapotranspiration estimation system considering the water storage heat term and the advection term, including:

[0036] A data acquisition module, which is used to acquire the time series of meteorological data, flux data, water depth data and water temperature data of the research area;

[0037] A water storage heat term calculation module, which is used to calculate the water storage heat term during the growth period of the paddy field based on the time series of the water depth data and the water temperature data;

[0038] An advection term calculation module, which is used to calculate the advection term based on the time series of the meteorological data;

[0039] A correction module, which is used to add the water storage heat term and the advection term to the energy balance equation respectively to correct the P-M model, and calculate the evapotranspiration estimation value based on the corrected P-M model;

[0040] A verification module, which is used to verify the evapotranspiration estimation value through the evapotranspiration data observed by the eddy covariance system.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] (1) The present invention focuses on the structural error caused by the energy imbalance problem in the evapotranspiration model, fully considers the advection term and the water storage heat term, and breaks through the modeling assumptions of steady state and one-dimensional vertical transfer of water and heat in the traditional evapotranspiration model;

[0043] (2) The present invention designs an experiment combining eddy covariance system observation and meteorological element matrix observation, makes full use of the spatio-temporal gradient information of meteorological elements, explores the mechanism of the energy imbalance problem and the variation laws of secondary energy terms in the paddy field system, and applies this law to the construction of the evapotranspiration model, which is a further deepening of the traditional research on the energy imbalance problem. Description of the Drawings

[0044] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0045] Figure 1 This is the technical roadmap of the rice evapotranspiration estimation method considering the water storage heat term and the advection term in the embodiments of the present invention.

[0046] Figure 2 This is a schematic diagram of the eddy covariance system and the wind, humidity, and temperature profile stations in the embodiments of the present invention.

[0047] Figure 3 This is a schematic diagram of the calculation results of the water storage heat term during the growth period of the rice field in the embodiments of the present invention.

[0048] Figure 4 This is a schematic diagram of the calculation results of the advection term in the rice field in the embodiments of the present invention.

[0049] Figure 5 This is a schematic diagram of the estimation accuracy of rice evapotranspiration considering the water storage heat term in the embodiments of the present invention.

[0050] Figure 6 This is a schematic diagram of the estimation accuracy of rice evapotranspiration considering the advection term in the embodiments of the present invention. Detailed implementation manners

[0051] To make the above objects, features, and advantages of the present application more obvious and understandable, the following describes the detailed implementation manners of the present application with reference to the accompanying drawings. Many specific details are set forth in the following description in order to fully understand the present application. However, the present application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without departing from the connotation of the present application. Therefore, the present application is not limited by the specific embodiments disclosed below.

[0052] Embodiment 1

[0053] As Figure 1 shown, the present invention provides a method for estimating rice evapotranspiration considering the water storage heat term and the advection term. The process of the embodiments of the present invention includes the following steps:

[0054] Step 1, obtain the time series of flux data, meteorological data, water depth data, and water temperature data in the study area, and specifically include the following sub-steps:

[0055] Step 1-1, obtain the meteorological data in the study area:

[0056] Taking the eddy covariance system deployed at the center of the paddy field as the coordinate origin (0, 0), and setting up two meteorological observation stations in each of its four directions: east, south, west, and north. The proximal stations are 125 m away from the origin (such as North 1 (0, 125), East 1 (125, 0), etc.), and the distal stations are 250 m away from the origin (such as North 2 (0, 250), East 2 (250, 0), etc.). Together with the central station, a nine-point observation network is formed. Based on the temperature and humidity data of these nine stations within a research range of 500 m × 500 m (with a resolution of 1 m × 1 m), the Kriging spatial interpolation method is used to generate a spatially continuous temperature and humidity field over the entire area. In the embodiment, the arrangement of the nine temperature and humidity profile observation points in the paddy field area is as Figure 2 shown. Utilize the spatial autocorrelation of the known temperature and humidity data of these nine stations (that is, adjacent sample points are more similar than distant sample points) to predict the temperature and humidity values of all pixel points in the entire paddy field area.

[0057] Step 1-2: Obtain the flux data of the research area:

[0058] The flux data is observed by the eddy correlation system and mainly includes net radiation (Rn), soil heat flux (G), latent heat flux (LE), sensible heat flux (H), etc.

[0059] Step 1-3: Obtain the water depth and water temperature data of the research area:

[0060] A number of water level gauges are deployed in the research area to monitor and record the water depth and water temperature data during the rice growth period. During the research period, the water depth and water temperature data recorded by all water level gauges during the rice growth period are averaged to obtain the representative water depth and water temperature values at each moment. Subsequently, their 30-minute scale and daily scale averages are calculated respectively to analyze the temporal variation characteristics of the water depth and water temperature. In the embodiment, since the paddy field is only in a flooded state during the growth period, the water depth and water temperature data are all obtained during the rice growth period.

[0061] Step 2: Calculate the water heat storage term during the paddy field growth period based on the time series of the water depth data and water temperature data; specifically, it includes the following sub-steps:

[0062] Step 2-1: Calculation of the temperature gradient:

[0063] Based on the meteorological data obtained in Step 1-2, the five-point derivative method is used to calculate the temperature gradient ΔT / Δt. The five-point derivative method is a high-precision numerical differentiation method. It is based on Taylor expansion and finite difference methods. By linearly combining data points, low-order error terms are eliminated, and the accuracy of derivative calculation is improved. Its central difference formula (1), forward difference formula (2), and backward difference formula (3) are as follows:

[0064]

[0065] Among them, Tw i represents the temperature at time t i , in K; Δt represents the time step; N is the total number of data points; Tw i+1 , Tw i+2 , Tw i-1 , Tw i-2 are the temperature data points of the paddy field water temperature adjacent before and after respectively. For the data at the starting time (such as at i = 0) and the ending time (such as at i = N - 1), the central difference formula cannot be used, and the forward difference and backward difference formulas need to be used respectively.

[0066] Step 2-2, calculation of the water heat storage term:

[0067] Based on the temperature gradient ΔTw / Δt calculated in Step 2-1, according to the heat balance principle of the water body, a water body heat storage change equation in a general scenario is constructed to calculate the water heat storage term. Its formula can be expressed as:

[0068]

[0069] Among them, C w is the specific heat capacity of water, usually taken as 4186 J / (kg·K); ρ w is the density of water, usually taken as 1000 kg / m 3 ; D is the depth of the paddy field water layer, in m; ΔT / Δt is the time change rate of the paddy field water temperature, in K / s. Substitute the temperature gradients at the half-hour scale and daily scale obtained in Step 2-1 into formula (4) respectively to calculate the time series change of the water heat storage term at the corresponding scale. In the embodiment, the daily values of the water heat storage term from 2022 to 2024 for three years are calculated, and its change curve is as Figure 3 shown. The average value of the water heat storage term during the paddy field growth period in three years is 5.47 W / m2, the maximum value is 70.57 W / m2, and the minimum value is 68.41 W / m2. It shows that the magnitude of the water heat storage term is sometimes comparable to the turbulent flux, so its role in energy transfer cannot be ignored.

[0070] Step 3, calculate the advection term based on the time series of the meteorological data; specifically, it includes the following sub-steps:

[0071] Step 3-1, calculation of specific humidity:

[0072] Specific humidity refers to the mass of water vapor contained in a unit mass of moist air, that is, the ratio of the mass of water vapor to the total mass of moist air. It is an important meteorological variable describing the water vapor content in the air. The calculation formula is as follows:

[0073]

[0074] Among them, q is the specific humidity; mv is the mass of water vapor; m d is the mass of dry air. Since the density ratio of water vapor to dry air can be expressed by the actual water vapor pressure and atmospheric pressure, the specific humidity can be further expressed as:

[0075]

[0076] Where e is the actual water vapor pressure, p is the atmospheric pressure; 0.622 is the gas constant R of water vapor v The gas constant R of dry air d The ratio of 0.622 = R v / R d .

[0077] Step 3-2, calculation of air heat storage term, heat advection term, and water vapor advection term:

[0078] For continuous data, the following differential form formula is used for calculation:

[0079]

[0080] For discrete data, the finite difference method is used to discretize the formula, and the results are as follows:

[0081]

[0082] Among them, F s F is the air heat storage term, which indicates the amount of heat stored in a unit volume of atmosphere within a certain period of time; THA is the heat advection term, which indicates the heat transport caused by horizontal wind speed; F qHA is the water vapor advection term, which represents the water vapor transport under the action of the wind field. Similar to the heat advection term, this term measures the coupling effect of wind speed and water vapor gradient; T a is the air temperature; q is the specific humidity, which indicates the mass of water vapor per unit of wet air; are the average components of wind speed in the x and y directions respectively; V m represents the control volume unit of the study area; Δz is the vertical thickness of the calculation area; z r is the reference height, i.e. the height of the measurement point; N is the total number of grid points; t is the time interval for calculation; is the time rate of change of temperature; and is the horizontal gradient of temperature, which indicates the rate of change of temperature in the x and y directions; and is the horizontal gradient of water vapor concentration, which represents the rate of change of water vapor concentration in the x and y directions; is the air temperature at time i; (x j ,y k) are the coordinates where the grid points are located.

[0083] Based on the regional air temperature data and wind speed data obtained in Step 1-1 and the specific humidity data obtained in Step 3-1, the advection term results of the study area can be calculated. The advection term was calculated using the 2022 data, and its half-hour scale variation and daily scale variation were plotted as line graphs. The results are as Figure 4 shown. It can be seen that in the embodiment, the water vapor advection is generally positive, the heat advection is generally negative, and the positive and negative distributions of air heat storage are relatively uniform (its mean value is close to 0).

[0084] Step 4: Add the water heat storage term and the advection term to the energy balance equation to correct the P-M model, and calculate the evapotranspiration estimation value based on the corrected P-M model; specifically, it includes the following sub-steps:

[0085] Step 4-1: Inversion of surface impedance:

[0086] Use Jarvis's surface impedance calibration model to estimate the surface impedance r s , and its calculation formula is as follows:

[0087]

[0088] Among them, r smin is the minimum stomatal impedance, f1(R n ), f2(VPD), f3(T a ), f4(θ) represent the weight functions of solar net radiation, humidity, air temperature, and soil moisture on plant stress respectively; VPD is the vapor pressure deficit; θ is the actual soil moisture content, θ s and θ w are the saturated soil water content and the wilting point respectively; a1, a2, and a3 are the correlation coefficients obtained during the calibration model process. Since the research object, the paddy field, is in a flooded state for a long time, the response function f4(θ) of the surface impedance to the soil moisture content can be regarded as a constant 1.

[0089] Step 4-2: Estimation of evapotranspiration:

[0090]

[0091] Among them, ET represents the evapotranspiration amount; M represents the water heat storage term or the advection term; ρ a represents the air density; C p represents the specific heat capacity of air; e s and e a represent the saturated vapor pressure and the actual vapor pressure respectively; r s and r aThey are surface impedance and aerodynamic impedance respectively; Δ is the slope of the saturation vapor pressure curve, indicating the sensitivity of the saturation water vapor pressure to temperature change at the current temperature; γ is the psychrometric constant, and the meanings of the remaining variables are the same as those in formula (1). The formula for calculating aerodynamic resistance is as follows:

[0092]

[0093] Among them, z m represents the wind speed measurement height; z h represents the humidity measurement height; d represents the zero-plane displacement elevation, taking 0.63hc; z om represents the roughness length controlling momentum transfer, taking 0.123hc; z oh represents the roughness length controlling heat and water vapor transfer, which is set here to be 10% of the momentum roughness length z om ; k is the von Kármán constant, taking 0.4; u z represents the wind speed at height z.

[0094] The slope of the saturation vapor pressure curve is an important parameter describing the vaporization process, and its calculation formula is:

[0095]

[0096] Among them, Δ represents the slope of the saturation water vapor pressure curve, kPa / °C; T a represents the air temperature, °C.

[0097] Substitute the net radiation, surface heat flux and meteorological data obtained in steps 1-2, the water storage heat term result obtained in step 3-2, the aerodynamic resistance obtained by combining the surface impedance obtained in step 5-1 with formula (19), and the slope of the saturation vapor pressure curve obtained by formula (20) into formula (18) to calculate the evapotranspiration estimation result obtained after considering the water storage heat term in the energy balance calculation.

[0098] Step 5. Calculate the energy balance ratios before and after introducing the water storage heat term and the advection term respectively, analyze the energy balance ratio and evapotranspiration estimation value year by year after introducing the water storage heat term and the advection term, reveal the dynamic change laws of the secondary energy terms, namely the water storage heat term and the advection term, and their impacts on the evapotranspiration estimation value; verify the evapotranspiration estimation value through the evapotranspiration data observed by the eddy covariance system.

[0099] The energy balance equation (21) is an important theoretical basis for the evapotranspiration model, which is expressed as the net radiation minus the surface heat flux equals the sum of the latent heat flux and the sensible heat flux:

[0100] R n -G = LE + H (21)

[0101] Among them, Rn represents the net radiation (W / m 2 ), which is the difference between the total surface radiation and the reflected radiation, representing the total energy input; G represents the soil heat flux (W / m 2 ), which is the heat conducted from the surface to the soil; LE represents the latent heat flux (W / m 2 ), which is the phase change energy exchange caused by water evaporation and plant transpiration; H represents the sensible heat flux (W / m 2 ), which is the non-phase change energy transferred by conduction or convection between the surface and the atmosphere due to the temperature difference. Generally, due to the existence of the energy imbalance problem, the equal sign in the above formula does not hold. The energy balance ratio (2) can be used to measure the degree of energy closure:

[0102]

[0103] The closer the energy balance ratio EBR is to 1, the better the energy closure.

[0104] Similarly, substituting the advection term and calculating the EBR and evapotranspiration estimation results obtained after considering the advection term in the energy balance calculation. By analyzing the EBR and evapotranspiration estimation results after introducing the water storage heat term and the advection term year by year, the dynamic variation laws of the secondary energy terms (i.e., the water storage heat term and the advection term) and their impacts on the evapotranspiration model estimation results are revealed. After obtaining the evapotranspiration estimation value, the evapotranspiration observed by the eddy covariance system is used to verify the estimation results, and indicators such as the coefficient of determination (R 2 ) and the root mean square error (RMSE) are used to evaluate the accuracy of the model. The daily evapotranspiration estimation results after considering the water storage heat term are as Figure 5 shown, and the half-hourly and daily evapotranspiration estimation results after considering the advection term are as Figure 6 shown, indicating that the model effectively estimates the paddy field evapotranspiration after considering the water storage heat term and the advection term, and realizes the dynamic inversion of the paddy field evapotranspiration.

[0105] Example 2

[0106] A specific embodiment of the present invention provides a paddy field evapotranspiration estimation system considering the water storage heat term and the advection term, including:

[0107] A data acquisition module, which is used to acquire the time series of meteorological data, flux data, water depth data, and water temperature data in the study area;

[0108] A water storage heat term calculation module, which is used to calculate the water storage heat term during the growth period of the paddy field based on the time series of the water depth data and the water temperature data;

[0109] An advection term calculation module, which is used to calculate the advection term based on the time series of the meteorological data;

[0110] A correction module, which is used to add the water heat storage term and the advection term to the energy balance equation respectively to correct the P-M model, and calculate the evapotranspiration estimation value based on the corrected P-M model;

[0111] A verification module, which is used to verify the evapotranspiration estimation value through the evapotranspiration data observed by the eddy covariance system.

[0112] As mentioned above, it is only a preferred specific embodiment of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by those skilled in the technical field of the present application within the technical scope disclosed by the present application should be covered within the protection scope of the present application.

[0113] It should be understood that the parts not elaborated in detail in this specification all belong to the prior art.

[0114] It should be understood that the above description of the preferred embodiment is relatively detailed, and it should not be considered as a limitation to the protection scope of the invention patent of the present application. Under the inspiration of the present invention, those of ordinary skill in the art can also make substitutions or deformations without departing from the protection scope defined by the claims of the present invention, and all fall within the protection scope of the present invention. The scope of protection claimed by the present invention shall be subject to the appended claims.

Claims

1. A method for estimating paddy field evapotranspiration considering water storage heat term and advection term, characterized in that, It includes the following steps: Step 1: Obtain the time series of meteorological data, flux data, water depth data, and water temperature data of the research area; Step 2: Calculate the water heat storage term during the rice growth period based on the time series of the water depth data and the water temperature data; Step 3: Calculate the advection term based on the time series of the meteorological data; Step 4: Add the water heat storage term and the advection term to the energy balance equation to correct the P-M model, and calculate the evapotranspiration estimation value based on the corrected P-M model.

2. The method for estimating paddy field evapotranspiration considering the water storage heat item and the advection item as claimed in claim 1, wherein The said Step 1 includes the following sub-steps: Step 1-1: Taking the center of the rice field in the research area as the coordinate origin, deploy proximal and distal meteorological observation stations in four directions to form a nine-point observation network, use the Kriging spatial interpolation method to generate the global temperature and humidity field, and obtain the wind speed data of the research area; Step 1-2: Obtain the net radiation Rn, soil heat flux G, latent heat flux LE, and sensible heat flux H of the research area through the eddy covariance system; Step 1-3: Deploy water level gauges in the rice fields of the research area to monitor the water depth and water temperature data during the rice growth period, and calculate the average water depth and water temperature at different scales respectively.

3. The method for estimating paddy field evapotranspiration considering water heat storage term and advection term according to claim 2, characterized in that, Step 2 includes the following sub-steps: Step 2-1: Based on the average water temperature at different scales, use the five-point derivative method to calculate the temperature gradient of the paddy water temperature respectively; including central difference, forward difference, and backward difference; Step 2-2: Based on the heat balance principle of the water body, establish the water body heat storage change equation under general scenarios, and calculate the water heat storage term at the corresponding scale.

4. The method for estimating paddy field evapotranspiration considering water storage heat item and advection item as claimed in claim 3, wherein The said water heat storage term is expressed as: Among them, S w represents the water heat storage term, C w is the specific heat capacity of water; ρ w is the density of water; D is the depth of the paddy water layer, m; is the temperature gradient of the paddy water temperature, K / s, Δt represents the time step, and T w represents the paddy water temperature.

5. The method for estimating paddy field evapotranspiration considering the water storage heat term and the advection term as claimed in claim 1, wherein Step 3 includes the following sub-steps: Step 3-1: Calculate the specific humidity based on the actual vapor pressure and atmospheric pressure; Step 3-2: Use the finite difference method to calculate the air heat storage term, heat advection term, and water vapor advection term, where the water vapor advection term is calculated based on the specific humidity in Step 3-1.

6. The method for estimating paddy field evapotranspiration considering the water storage heat term and the advection term as claimed in claim 5, wherein The air heat storage term, heat advection term, and water vapor advection term are respectively: Among them, F s is the air heat storage term, representing the heat stored by the unit volume of the atmosphere within a certain time; F THA is the heat advection term, representing the heat transport caused by the horizontal wind speed; F qHA is the water vapor advection term, representing the water vapor transport under the action of the wind field. Similar to the heat advection term, this term measures the coupling effect of the wind speed and the water vapor gradient; T a is the air temperature; q is the specific humidity, representing the mass of water vapor per unit mass of moist air; are the average components of the wind speed in the x and y directions respectively; V m represents the control volume unit of the study area; Δz is the vertical thickness of the calculation area; z r is the reference height, that is, the measurement point height; N is the total number of grid points; t is the time interval of the calculation; is the time change rate of the temperature; and are the horizontal gradients of the temperature, representing the change rates of the temperature in the x and y directions; and are the horizontal gradients of the water vapor concentration, representing the change rates of the water vapor concentration in the x and y directions; is the air temperature at the i-th moment; (x j , y k ) are the coordinates of the grid point.

7. The method for estimating paddy field evapotranspiration considering water heat storage term and advection term as claimed in claim 6, wherein The following sub-steps are included in Step 5: Step 5-1: Use Jarvis' surface impedance calibration model to estimate the surface impedance r s , Step 5-2: Add the water heat storage term and the advection term to the energy balance equation to correct the P-M model, and calculate the evapotranspiration estimation value based on the corrected P-M model.

8. The method for estimating paddy field evapotranspiration considering water heat storage term and advection term as claimed in claim 7, wherein Calculating the evapotranspiration estimation value based on the corrected P-M model is expressed as: Among them, ET represents the evapotranspiration; M represents the water heat storage term or the advection term; ρ a represents the air density; C p represents the specific heat capacity of air; e s and e a represent the saturated water vapor pressure and the actual water vapor pressure respectively; r s and r a are the surface resistance and the aerodynamic resistance respectively; Δ is the slope of the saturated vapor pressure curve, representing the sensitivity of the saturated water vapor pressure to temperature changes at the current temperature; γ is the psychrometric constant.

9. The rice paddy evapotranspiration estimation method considering the water storage heat item and the advection item as claimed in claim 7, wherein, It also includes: Calculate the energy balance ratios before and after introducing the water heat storage term and the advection term respectively, conduct annual analysis on the energy balance ratio and evapotranspiration estimation value after introducing the water heat storage term and the advection term, reveal the dynamic change laws of the secondary energy terms, namely the water heat storage term and the advection term, and their impacts on the evapotranspiration estimation value; verify the evapotranspiration estimation value through the evapotranspiration data observed by the eddy correlation system.

10. A paddy field evapotranspiration estimation system considering water storage heat terms and advection terms, characterized in that, It includes: A data acquisition module, which is used to obtain the time series of meteorological data, flux data, water depth data, and water temperature data of the research area; A water heat storage term calculation module, which is used to calculate the water heat storage term during the rice growth period based on the time series of the water depth data and the water temperature data; An advection term calculation module, which is used to calculate the advection term based on the time series of the meteorological data; A correction module, which is used to add the water heat storage term and the advection term to the energy balance equation to correct the P-M model, and calculate the evapotranspiration estimation value based on the corrected P-M model; A verification module, which is used to verify the estimated evapotranspiration value by using the evapotranspiration data observed by an eddy covariance system; The paddy field evapotranspiration estimation system considering the water heat storage term and the advection term is used to execute the steps in the paddy field evapotranspiration estimation method considering the water heat storage term and the advection term according to any one of claims 1-9.

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