Rice evapotranspiration estimation method considering depth of flooded layer

Abstract

The invention, which relates to the technical field of crop evapotranspiration simulation, discloses a paddy rice evapotranspiration estimation method considering the depth of a waterflooding layer, comprising the following steps: acquiring meteorological data in a research area, waterflooding layer depth data of a paddy field, paddy rice growth data and actually measured evapotranspiration data; considering an influence mechanism of the depth of the flooded layer on evapotranspiration, and adding the influence of the depth of the flooded layer on the canopy resistance to a canopy resistance model (such as a Jarvis canopy resistance model); considering the influence of the depth of the waterflooding layer on water layer heat storage, and constructing a water temperature-surface heat flux model; the canopy resistance model and the earth surface heat flux model are coupled into a Shuttleworth-Wallace model to improve the evapotranspiration model; based on an improved Shuttleworth-Wallace model, whole-growth-period evapotranspiration prediction under irrigation of different flooding depths is realized, and the method is used for evaluating the water-saving effect of each irrigation mode. By improving the Shuttleworth-Wallace model, the influence mechanism of the depth of the flooded layer on evapotranspiration is brought into rice evapotranspiration simulation, the rice evapotranspiration simulation precision can be improved, and a basis is provided for formulating a reasonable irrigation system.

Description

Technical Field

[0001] The present invention relates to the technical field of crop evapotranspiration simulation, and specifically relates to a method for estimating rice evapotranspiration considering the depth of the flooded layer. Background Art

[0002] Evapotranspiration is the main form of agricultural water consumption and a key link in the surface water-heat cycle. Its accurate quantification is helpful for agricultural water management and a better understanding of the interaction between the natural environment and the ecosystem. Rice is the main food crop in China, and the irrigation water consumption accounts for 70% of the total agricultural water consumption. Formulating a reasonable irrigation system and improving the water use efficiency of rice are crucial for food security and water resource security. Accurately quantifying rice evapotranspiration is of great significance.

[0003] Monitoring and simulation are two major means for quantifying evapotranspiration. Crop evapotranspiration monitoring methods include lysimeters, eddy covariance systems, and Bowen ratio energy balance systems, etc. However, the monitoring cost is relatively high, and each monitoring method has strong scale dependence; crop evapotranspiration simulation methods generally adopt the crop coefficient method and mechanistic models. The crop coefficient method is convenient to apply, but the crop coefficients without regional calibration often have low accuracy. Mechanistic models can consider mechanisms such as meteorological driving and vegetation control, and have relatively high simulation accuracy.

[0004] In mechanistic models, the Shuttleworth-Wallace two-source evapotranspiration model divides the land surface into a soil layer and a vegetation layer, and introduces five resistance parameters to describe the vapor turbulent diffusion process generated from the soil layer and the vegetation layer. It is widely used to estimate ET and its components under various vegetation-covered land surface conditions. In the Shuttleworth-Wallace model, the estimation of canopy resistance is the main challenge. The current canopy resistance models consider the influences of meteorology, crop growth, and soil moisture, but for rice, the flooded layer is a unique growth environment, and the influence of the flooded layer depth on canopy resistance has not been reflected in the canopy resistance models; moreover, the existence of the flooded layer has a great impact on the energy balance, and the existing Shuttleworth-Wallace model framework cannot consider the influence of the flooded layer depth on the heat storage of the water layer. Therefore, it is necessary to study the method for simulating rice evapotranspiration with a flooded layer. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for estimating rice evapotranspiration considering the depth of the flooded layer in view of the problems existing in the prior art.

[0006] To achieve the above purpose, the technical solution adopted by the present invention is as follows:

[0007] In the first aspect, the present invention provides a method for estimating rice evapotranspiration considering the depth of the flooded layer, including the following steps:

[0008] Obtain meteorological data, the depth of the flooded layer in paddy fields, rice growth, and measured evapotranspiration data in the study area;

[0009] Considering the influence mechanism of the flooded layer depth on evapotranspiration, establish a canopy resistance model considering the flooded layer depth; considering the influence of the flooded layer depth on the heat storage of the water layer, establish a water temperature - surface heat flux model;

[0010] Couple the canopy resistance model considering the flooded layer depth and the water temperature - surface heat flux model into the Shuttleworth - Wallace model to obtain an improved Shuttleworth - Wallace model;

[0011] Based on the improved Shuttleworth - Wallace model, predict the evapotranspiration during the entire growth period of rice under different flooded layer depth irrigation, and evaluate the water - saving effects of each irrigation method.

[0012] It should be noted that predicting the evapotranspiration during the entire growth period of rice under different flooded layer depth irrigation based on the improved Shuttleworth - Wallace model: includes calculating the evapotranspiration amount, evaporation amount, and transpiration amount during the entire growth period of rice under different flooded layer depth irrigation.

[0013] As a further technical solution, considering the influence mechanism of the flooded layer depth on evapotranspiration, establish a canopy resistance model considering the flooded layer depth, including the steps: calculate the actual canopy resistance according to the measured evapotranspiration data, consider the influence of the flooded layer depth on the canopy resistance, and determine the response function of the canopy resistance to the water layer depth (water depth influence function); establish a canopy resistance model considering the water layer depth based on the water depth influence function.

[0014] More specifically, considering the influence mechanism of the flooded layer depth on evapotranspiration, establish a canopy resistance model considering the flooded layer depth, including the steps:

[0015] According to the measured evapotranspiration data at different flooded layer depths combined with the canopy resistance model, calculate the actual canopy resistance at different flooded layer depths;

[0016] Based on the actual canopy resistance at different flooded layer depths, establish a water depth influence function with the flooded layer depth as the independent variable and the measured canopy resistance as the dependent variable;

[0017] Replace the soil moisture influence function with the water depth influence function in the Jarvis canopy resistance model to obtain a Jarvis canopy resistance model considering the flooded layer depth.

[0018] As a further technical solution, a water temperature-surface heat flux model is established considering the influence of the depth of the flooded layer on the heat storage of the water layer: the surface heat flux expression is established according to the energy balance of the water body below the canopy, and the surface heat flux component calculation formulas such as water body heat storage (flooded layer water body heat flux), soil heat flux, etc. are combined to establish a water temperature-surface heat flux model (water temperature-surface heat flux model considering the depth of the flooded layer).

[0019] Specifically, considering the influence of the depth of the flooded layer on the heat storage of the water layer, a water temperature-surface heat flux model is established: the sensible heat and latent heat of the water surface are calculated based on the sensible heat calculation formula and the latent heat calculation formula based on the water vapor transfer theory, and the surface heat flux expression is established according to the energy balance of the water body under the canopy; the surface heat flux expression is combined with the heat flux calculation formula of the flooded layer water body and the soil heat flux calculation formula to form a water temperature-surface heat flux model for calculating the water body temperature and surface heat flux.

[0020] S1.1 The meteorological data mentioned above refer to the net solar radiation, air temperature at the reference height, relative humidity and wind speed in the study area; the evapotranspiration data mentioned above refer to the evapotranspiration data measured by monitoring means such as the eddy covariance system, the Bowen ratio energy balance monitoring system, and the lysimeter, as well as the inter-tree evaporation data measured by the lysimeter; the rice growth data mentioned above refer to the leaf area data obtained by one or more means of remote sensing image inversion and canopy analyzer monitoring, the plant height data and leaf width data read by a ruler, and the growth period data judged based on the growth of rice; the waterlogged layer depth data refer to the waterlogged layer depth data read every day by a ruler or a water level meter.

[0021] As a further technical solution, considering the influence mechanism of flooded layer depth on evapotranspiration, a canopy resistance model considering the flooded layer depth is established, including the following steps:

[0022] S2.1. Based on the measured evapotranspiration data and the measured meteorological data, the actual canopy resistance is calculated using the Shuttleworth-Wallace model, as shown in the following formula (1):

[0023] (1)

[0024] In the formula, is the canopy resistance, in s / m; is the aerodynamic resistance inside the canopy, in s / m; is the net solar radiation, in MJ / (m 2 d); is the net radiation of the water surface, in MJ / (m 2 ·d), can be calculated as , where k is the extinction coefficient, which can be taken as 0.5 for rice, and LAI is the measured leaf area; is the transpiration rate, with the unit of mm / d, which can be obtained by subtracting the measured soil evaporation data from the measured evapotranspiration data; is the slope of the saturation vapor pressure-temperature curve, with the unit of kPa / °C; is the air density, with the unit of kg / m³; is the specific heat of air, with the unit of J / (kg·°C); is the saturated vapor pressure of air, is the vapor pressure of air, in kPa, and the calculation formula is where, is the air temperature at the reference height, is the relative humidity at the reference height; is the latent heat of vaporization, with the unit of MJ / kg; is the hygrometer constant, with the unit of kPa / °C.

[0025] S2.2. Determine the form of the water depth influence function in the Jarvis canopy resistance model according to the canopy resistance at different water depths Since the canopy resistance increases as the water layer depth decreases and also increases when the water layer depth is too high, the water depth influence function is determined to be a quadratic function of the water depth:

[0026] (2)

[0027] In the formula, h w is the flooded layer depth, with the unit of m; a and b are parameters.

[0028] S2.3. Add the water depth influence function to the Jarvis canopy resistance model to consider the influence of the water layer depth on the canopy resistance:

[0029] The Jarvis model considering the influence of radiation, vapor pressure difference, air temperature and soil moisture is shown in Equation (3):

[0030] (3)

[0031] In the formula, is the canopy resistance, with the unit of s / m; is the minimum canopy resistance, determined according to the rice growth stage, with the unit of s / m; LAI a is the effective leaf area, LAI a =(0.5LAI + 1) / LAI, where LAI is the measured leaf area; 、 、 and are the response functions of the canopy resistance to each environmental factor, and the specific calculation formulas are as follows:

[0032] (4)

[0033] (5)

[0034] (6)

[0035] (7)

[0036] wherein, is the net solar radiation, in W / m 2 ; D is the vapor pressure deficit at the reference height, , in kPa; is the air temperature at the reference height, in °C; , , are the volumetric soil water content (m 3 / m 3 ), the saturated soil water content (m 3 / m 3 ) and the wilting point (m 3 / m 3 ) respectively; , , , are the parameters calibrated according to the actual canopy resistance.

[0037] Since the depth of the flooded layer affects the canopy resistance, and the soil moisture is in a saturated state at this time, the Jarvis model considering the effects of radiation, vapor pressure deficit, air temperature and soil moisture is difficult to reflect the actual canopy resistance. Therefore, the present invention introduces a water depth influence function to replace the soil moisture influence function to characterize the influence of the water layer depth on the canopy resistance in flooded paddy fields. The improved Jarvis canopy resistance model (i.e., the canopy resistance model considering the depth of the flooded layer) is shown in Equation (8):

[0038] (8)

[0039]

[0040]

[0041]

[0042] Its response function for the water layer depth is as follows:

[0043] (9)

[0044] wherein, is the minimum canopy resistance, determined according to the growth stage of rice; LAI a is the effective leaf area, LAIa =(0.5LAI + 1) / LAI; 、 、 and are the response functions of canopy resistance to various environmental factors; is the net solar radiation; D is the vapor pressure deficit at the reference height, ; is the air temperature at the reference height; h w is the depth of the flooded layer; , , , , are the parameters calibrated according to the actual canopy resistance.

[0045] As a further technical solution, considering the influence of the depth of the flooded layer on the heat storage of the water layer, a water temperature - surface heat flux model is established, including the following steps:

[0046] S3.1. Based on the Priestley - Taylor formula, the sensible heat calculation formula, and the latent heat calculation formula based on the water vapor transfer theory, establish the sensible heat and latent heat expressions on the water surface:

[0047] According to the water surface evaporation latent heat calculation formula based on the Penman formula, the water surface evaporation latent heat is calculated as follows:

[0048] (10)

[0049] In the formula, is the water surface evaporation latent heat, W / m 2 ; is the water surface net radiation, W / m 2 ; G is the surface heat flux, W / m 2 ; is the aerodynamic resistance of the air at the bottom of the canopy, s / m; is the soil surface resistance, s / m; is the saturated water vapor pressure at the canopy height, is the actual water vapor pressure at the canopy height, is the actual water vapor pressure at the reference height, kPa.

[0050] Among them, the difference in saturated water vapor pressure between the canopy height and the reference height can be approximately calculated by the temperature difference between the canopy height and the reference height:

[0051] (11)

[0052] In the formula, is the canopy temperature, °C; is the air temperature at the reference height, °C.

[0053] According to the law of water vapor flux transport, the actual water vapor pressure difference and temperature difference between the reference height and the canopy height are calculated as follows:

[0054] (12)

[0055] (13)

[0056] In the formula, is the total latent heat flux, W / m 2 ; is the total sensible heat flux, W / m 2 ; is the aerodynamic resistance above the canopy, s / m.

[0057] In the above formula, the total latent heat , the total sensible heat H are unknowns. The total latent heat flux can be initialized and calculated using the Priestley-Taylor formula , and H is calculated using the energy balance residual method:

[0058] (14)

[0059] (15)

[0060] In the formula, is the Priestley-Taylor coefficient. Generally, 1.26 is taken for water surface evaporation; is the net solar radiation, W / m 2 .

[0061] Substitute equations (11) to (15) into equation (10) to obtain the expression of the latent heat of the water surface as follows:

[0062] (16)

[0063] Similarly, according to the calculation formula of the sensible heat flux of the water surface and the PT formula, the expression of the sensible heat of the water surface (formula (19)) is obtained:

[0064] (17)

[0065] (18)

[0066] (19)

[0067] In the formula, H s is the sensible heat flux of the water surface, with the unit of W / m 2 ; is the water surface temperature, with the unit of °C.

[0068] S3.2. Based on the surface energy balance of water bodies (20), by combining equations (16), (19), and (20), establish the expression for surface heat flux (Equation (21)):

[0069] (20)

[0070] (21)

[0071] In the formula, G is the surface heat flux; is the aerodynamic resistance at the bottom of the canopy, is the aerodynamic resistance above the canopy, is the soil surface resistance; is an intermediate quantity, ; is the water surface temperature; is the net radiation of the water surface.

[0072] S3.3. Based on the definition of heat storage, establish the expressions for heat storage in the water layer and soil heat flux (Equation (22)), and combine them with Equation (21) in Section S2.2 to form a water temperature - surface heat flux calculation model:

[0073] The expressions for heat storage in water bodies and soil heat flux based on water body heat storage and the forced - recovery model are as follows:

[0074] (22)

[0075] In the formula, is the heat storage in the flooded water layer, is the soil heat flux, W / m 2 ; is the specific heat capacity of water, J / (kg·K); is the density of water, kg / m 3 ; is the depth of the water layer, m; is the change in water temperature, is the water body temperature, is the temperature of the irrigation water, is the temperature of the water discharged from the field, °C; is the flow rate of the irrigation water, m / s; is the flow rate of the drained water. Based on the forced - recovery model, the soil heat flux can be expressed as a function (formula) of the soil surface temperature . is the daily average temperature of the soil surface, K; is the angular frequency, ; is the volumetric heat capacity of the soil, Jm-3 K -1 ; is the soil thermal conductivity, Wm -1 K -1 . takes the 24-hour average calculated the previous day average value. and are calculated based on the properties of typical paddy soils.

[0076] Since heat exchange occurs at the water layer surface and the soil surface is in contact with the water layer, it can be considered . According to , by combining Equation (21) and Equation (22), a water temperature and surface heat flux calculation model is formed, that is, a water temperature - surface heat flux model considering the water layer depth.

[0077] As a further technical solution, the canopy resistance model considering the flooded layer depth and the water temperature - surface heat flux model are coupled into the Shuttleworth - Wallace model to obtain an improved Shuttleworth - Wallace model. The specific steps include:

[0078] S4.1. Calculate the five resistances in the Shuttleworth - Wallace model according to the aerodynamic resistance formula at the canopy top, the aerodynamic resistance formula at the canopy bottom, the aerodynamic resistance inside the canopy, the Jarvis canopy resistance model considering the flooded layer depth, and the soil surface resistance calculation formula:

[0079] The aerodynamic resistance above the canopy is calculated as follows:

[0080] (23)

[0081] In the formula, is the canopy height, obtained from plant height data, m; is the reference height, m; is the zero plane displacement, , m; is the canopy surface roughness, , m; is the Karman constant, taking 0.41; is the turbulent diffusion coefficient at the canopy top, ; is the attenuation coefficient, taking 2.5; is the wind speed at the reference height, m / s.

[0082] The aerodynamic resistance inside the canopy is calculated as follows:

[0083] (24)

[0084] In the formula, is the leaf width, obtained from the leaf width data, m; is the wind speed at the top of the canopy, , m / s.

[0085] The aerodynamic resistance at the bottom of the canopy is calculated as follows:

[0086] (25)

[0087] In the formula, is the roughness length for controlling water and heat transfer, , m.

[0088] The canopy resistance is calculated as follows:

[0089] (26)

[0090] The soil surface resistance can be considered a constant, m / s.

[0091] S4.2. According to the water temperature - surface heat flux model, combined with the calculated net radiation at the water surface, aerodynamic resistance at the top of the canopy, aerodynamic resistance at the bottom of the canopy, soil surface resistance, meteorological data, and water depth, calculate the water temperature and surface heat flux:

[0092] (27)

[0093] (28)

[0094] (29)

[0095] S4.3. According to the surface heat flux, five resistances, meteorological data, and water layer depth, based on the Shuttleworth - Wallace model, construct a two - source evapotranspiration model considering water depth (the improved Shuttleworth - Wallace model):

[0096] (30)

[0097] (31)

[0098] (32)

[0099] (33)

[0100] (34)

[0101] (35)

[0102] (36)

[0103] (37)

[0104] As a further technical solution, the above estimation method further includes the step of evaluating the effect of the improved Shuttleworth-Wallace model. Specifically, the accuracy of the simulation results of the improved Shuttleworth-Wallace model is tested by combining the measured evapotranspiration data. For example, the coefficient of determination, root mean square error, and consistency index are used in combination with the measured evapotranspiration data of the lysimeter, eddy covariance system, or eddy covariance system to evaluate the effect of the improved Shuttleworth-Wallace model.

[0105] As a further technical solution, the prediction method for the evapotranspiration data of the whole growth period under different waterlogging layer depths based on the improved Shuttleworth-Wallace model is as follows:

[0106] Calculate the aerodynamic resistance at the top of the canopy, the aerodynamic resistance at the bottom of the canopy, the aerodynamic resistance inside the canopy, the Jarvis canopy resistance considering the waterlogging layer depth, and the soil surface resistance in the Shuttleworth-Wallace model by combining the meteorological data, the crop growth data, and the waterlogging layer depth data;

[0107] Calculate the net radiation of the water surface using the meteorological data, and calculate the water temperature and the surface heat flux according to the waterlogging layer depth data in combination with the water temperature - surface heat flux model;

[0108] Combine the five calculated resistance parameters and the surface heat flux with the improved Shuttleworth-Wallace model to simulate the evapotranspiration of the whole growth period of rice under different waterlogging layer depths.

[0109] In a second aspect, the present invention provides a rice evapotranspiration estimation system considering the waterlogging layer depth, including:

[0110] A first main module for obtaining meteorological, rice waterlogging layer depth, rice growth, and measured evapotranspiration data in the study area;

[0111] A second main module for establishing a Jarvis canopy resistance model considering the waterlogging layer depth and a water temperature - surface heat flux model based on the measured evapotranspiration data;

[0112] The third main module is used to couple the canopy resistance model considering the depth of the flooded layer and the water temperature - surface heat flux model into the Shuttleworth-Wallace model to obtain the improved Shuttleworth-Wallace model;

[0113] The fourth main module is used to predict the evapotranspiration data of the whole growth period of crops under irrigation with different depths of the flooded layer based on the improved Shuttleworth-Wallace model.

[0114] In a third aspect, the present invention provides a non-transitory computer-readable storage medium storing computer instructions that cause a computer to execute any one of the above-described rice evapotranspiration estimation methods considering the depth of the flooded layer.

[0115] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0116] 1. The present invention fully considers the influence of the depth of the flooded layer on rice evapotranspiration, improves the accuracy of the model in simulating the rice evapotranspiration process, is beneficial to formulating a reasonable irrigation system, improving water use efficiency, and realizing water-saving irrigation.

[0117] 2. By improving the Shuttleworth-Wallace model, the present invention incorporates the influence mechanism of the depth of the flooded layer on evapotranspiration into the simulation of rice evapotranspiration. The improved model can more accurately simulate the rice evapotranspiration process, thereby more precisely estimating the evapotranspiration amount and its components (evaporation and transpiration) of paddy fields under different depths of the flooded layer.

[0118] 3. The present invention proposes a mechanistic model. Compared with the crop coefficient method, it can fully consider crop responses, is not affected by factors such as time and region, and has a wider range of applications.

[0119] 4. The present invention can calculate the evapotranspiration and its components of paddy fields based on meteorological data and the depth of the field water layer, and can predict the rice evapotranspiration under different depths of the flooded layer through easily obtainable monitoring data, saving time and effort. BRIEF DESCRIPTION OF THE DRAWINGS

[0120] Figure 1 It is a schematic flow chart of a rice evapotranspiration simulation method considering the depth of the flooded layer;

[0121] Figure 2 It is a flow chart of a rice evapotranspiration model considering the depth of the flooded layer;

[0122] Figure 3 It is a result verification diagram of the improved evapotranspiration model simulating evapotranspiration in an embodiment of the present invention;

[0123] Figure 4Verification diagram of the evaporation simulation results of the improved evapotranspiration model according to the embodiments of the present invention;

[0124] Figure 5 Verification diagram of the transpiration simulation results of the improved evapotranspiration model according to the embodiments of the present invention;

[0125] Figure 6 Variation diagram of the evapotranspiration of rice during the whole growth period with water depth under the meteorological conditions and rice growth conditions according to the embodiments of the present invention. Detailed implementation manners

[0126] Next, the technical solutions of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts belong to the scope of protection of the present invention.

[0127] As Figure 1 shown, the present invention provides a method for simulating the evapotranspiration of rice considering the depth of the flooded layer, including the following steps:

[0128] S1. Collect meteorological data, data on the depth of the flooded layer in paddy fields, rice growth data, and measured evapotranspiration data in the study area;

[0129] The meteorological data refers to the net solar radiation, atmospheric pressure, air temperature at the reference height, relative humidity at the reference height, and wind speed data at the reference height in the study area. These meteorological data are monitored by an automatic weather station in the test area. In this embodiment, the reference height is 2m; the evapotranspiration data is the evapotranspiration measured by one or more of the eddy covariance system, Bowen ratio energy balance monitoring system, and lysimeter, and the inter-row evaporation measured by the lysimeter; the rice growth data is the leaf area data obtained by one or more of remote sensing image inversion and canopy analyzer monitoring, the plant height data and leaf width data read by a ruler, and the growth stage data judged according to the growth trend of rice; the data on the depth of the flooded layer is the data read by a ruler or a water level gauge every day.

[0130] In this embodiment, a rice evapotranspiration monitoring experiment was carried out in a certain rice planting area in China. The experimental plots consisted of several plots with a size of 7.5m×16m. A total of 4 groups of different treatments were set in the experiment, including 4 depths of the flooded layer of 0-10cm, namely 1cm, 4cm, 7cm, and 10cm, and each treatment had 3 replicates. The flooding experiment was carried out from the tillering stage to the milk-ripe stage of rice, and the fields were drained at the end of the tillering stage. Water was replenished into each plot through the water inlet pipe at 6:00 every morning to keep the water depth in the plot at the set depth.

[0131] The weighing method using a micro-lysimeter was adopted to weigh the lysimeter at fixed times every morning and evening (7:00 in the morning and 18:00 in the evening). The reduced water volume was the amount of water consumed daily through evapotranspiration and evaporation. The evapotranspiration and evaporation of rice during the day were calculated based on the water volume, and transpiration was calculated as the difference between evapotranspiration and evaporation.

[0132] The Jarvis resistance model considering the effects of net solar radiation, vapor pressure deficit at the reference height, air temperature at the reference height, and soil volumetric water content is in the following form:

[0133]

[0134] In the formula, is the minimum canopy resistance, obtained from the data of the rice growth stage. For example, during the tillering, jointing, booting, heading, and milk-ripe stages of indica rice, they are 34 s / m, 34 s / m, 38 s / m, 42 s / m, and 50 s / m respectively; LAI a is the effective leaf area, LAI a =(0.5LAI + 1) / LAI, where LAI is the measured leaf area, obtained from the leaf area data; 、 、 and are the response functions of net solar radiation, vapor pressure deficit at the reference height, air temperature at the reference height, and soil volumetric water content to the actual canopy resistance respectively. The specific calculation formulas are as follows:

[0135]

[0136]

[0137]

[0138]

[0139] In the formula, is the net solar radiation, with the unit of W / m 2 ; D is the vapor pressure deficit at the reference height, , with the unit of kPa; is the air temperature at the reference height, with the unit of °C; , , are the soil volumetric water content, saturated soil water content, and wilting point respectively, and their units are all m 3 / m 3 ; is the parameter calibrated with the net solar radiation as the independent variable and the actual canopy resistance as the dependent variable, is the parameter calibrated with the vapor pressure deficit at the reference height as the independent variable and the actual canopy resistance as the dependent variable, is a parameter calibrated with the air temperature at the reference height as the independent variable and the actual canopy resistance as the dependent variable. is a parameter calibrated with the soil volumetric water content as the independent variable and the actual canopy resistance as the dependent variable.

[0140] Since in fact the depth of the flooded layer will also affect the canopy microclimate and thus change the actual canopy resistance, and at this time the soil moisture is in a saturated state, the original resistance model is difficult to reflect the actual canopy resistance. Therefore, the present invention introduces a water depth influence function to replace the soil moisture influence function to characterize the influence of the depth of the flooded layer on the actual canopy resistance in flooded paddy fields.

[0141] S2. Improve the Jarvis canopy resistance model with the measured evapotranspiration data, the depth data of the flooded layer, and the meteorological data to obtain the Jarvis canopy resistance model considering the depth of the flooded layer;

[0142] The improvement steps of the Jarvis canopy resistance model are as follows:

[0143] S2.1. Measure the evapotranspiration data at different depths of the flooded layer, obtain the transpiration amount by subtracting the intergranular evaporation from the evapotranspiration, and combine the measured meteorological data to inversely calculate the actual canopy resistance through the Shuttleworth-Wallace model:

[0144]

[0145] In the formula, is the aerodynamic resistance inside the canopy, with the unit of s / m, and the calculation formula can be found in the resistance calculation part; is the net solar radiation, with the unit of MJ / (m 2 ·d); is the net radiation of the water surface, with the unit of MJ / (m 2 ·d); is the transpiration amount, with the unit of mm / d; is the slope of the saturation vapor pressure-temperature curve, with the unit of kPa / °C; is the air density, with the unit of kg / m³; is the specific heat of air, with the unit of J / (kg·°C); is the saturated water vapor pressure of air at the reference height, is the actual water vapor pressure at the reference height, with the unit of kPa; is the latent heat of vaporization, with the unit of MJ / kg; is the psychrometer constant, with the unit of kPa / °C.

[0146] S2.2. Establish a water depth influence function with the depth of the flooded layer as the independent variable and the actual canopy resistance as the dependent variable;

[0147] According to the actual canopy resistance at different water depths, determine the form of the water depth influence function in the Jarvis resistance model. It is found through experiments that the actual canopy resistance first decreases and then increases with the water depth, and reaches the minimum value at about 6 cm. The water depth influence function is formulated as a quadratic function of the water depth, and the basic form is as follows:

[0148]

[0149] In the formula, h w is the depth of the flooded layer, with the unit of cm; a and b are parameters.

[0150] S2.4. Replace the soil moisture influence function in the unimproved Jarvis canopy resistance model with the water depth influence function to obtain the improved Jarvis canopy resistance model (the Jarvis canopy resistance model considering the depth of the flooded layer) as;

[0151]

[0152]

[0153]

[0154]

[0155]

[0156] In the formula, 、 、 and are the response functions of the Jarvis canopy resistance to the net solar radiation, the vapor pressure deficit at the reference height, the air temperature at the reference height, and the depth of the flooded layer, respectively; is the parameter calibrated with the net solar radiation as the independent variable and the actual canopy resistance as the dependent variable, is the parameter calibrated with the vapor pressure deficit at the reference height as the independent variable and the actual canopy resistance as the dependent variable, is the parameter calibrated with the air temperature at the reference height as the independent variable and the actual canopy resistance as the dependent variable, 、 are the parameters calibrated with the depth of the flooded layer as the independent variable and the actual canopy resistance as the dependent variable.

[0157] Determine , , , , The values are as follows.

[0158] Table 1 Parameter values in the improved Jarvis canopy resistance model

[0159]

[0160] S3. Establishing a surface heat flux expression according to the energy balance model under the canopy, and combining the surface heat flux expression with the surface heat flux component calculation formula to form the water temperature-surface heat flux model;

[0161] The steps to establish the water temperature-surface heat flux model are as follows:

[0162] S3.1. Develop an expression for surface heat flux based on the energy balance below the canopy.

[0163] The energy balance model of the water body below the canopy is as follows:

[0164]

[0165] in, is the sensible heat flux on the water surface, is the latent heat flux on the water surface, and G is the surface heat flux.

[0166] Similar to the Penman-Montieth formula, It can be calculated by the following formula:

[0167]

[0168] In the formula, is the aerodynamic resistance at the bottom of the canopy, in s / m; is the soil surface resistance, in s / m; is the saturated water vapor pressure at the canopy height, in kPa, is the actual water vapor pressure at the canopy height, in kPa, is the actual water vapor pressure at the reference height, in kPa.

[0169] The saturated water vapor pressure difference between the canopy height and the reference height can be approximately calculated by the temperature difference between the canopy height and the reference height:

[0170]

[0171] In the formula, is the temperature at the canopy height, in °C; is the air temperature at the reference height in °C.

[0172] According to the water vapor flux transmission law, the actual water vapor pressure difference between the reference height and the canopy height is calculated as follows:

[0173]

[0174] In the formula, is the total latent heat flux, with the unit of W / m 2 ; is the aerodynamic resistance above the canopy, with the unit of s / m.

[0175] According to the heat flux transport law, the temperature difference between the reference height and the canopy height is calculated as follows:

[0176]

[0177] In the formula, is the total sensible heat flux, with the unit of W / m 2 .

[0178] In the above formula, the total latent heat flux , the total sensible heat flux H are unknowns. The total latent heat flux can be approximately calculated using the Priestley-Taylor formula , and H is calculated using the energy balance residual method:

[0179]

[0180]

[0181] In the formula, is the Priestley-Taylor coefficient. Generally, 1.26 is taken for the evaporation of the water surface.

[0182] Thus, the expression of the latent heat flux of the water surface is as follows:

[0183]

[0184] Similarly, according to the calculation formula of the sensible heat flux of the water surface and the Priestley-Taylor formula, the expression of the sensible heat flux of the water surface is obtained:

[0185]

[0186]

[0187]

[0188] In the formula, H s is the sensible heat flux of the water surface, with the unit of W / m 2 ; is the water surface temperature, with the unit of °C.

[0189] Substitute the and expressions into the water body energy balance model below the canopy to obtain the calculation formula of the surface heat flux:

[0190]

[0191] Wherein, G is the surface heat flux, with the unit of W / m 2 ; is the aerodynamic resistance at the bottom of the canopy, is the aerodynamic resistance at the upper part of the canopy, is the soil surface resistance, and the units are all s / m; is an intermediate quantity, ; is the water surface temperature, with the unit of °C; is the net radiation of the water surface, with the unit of W / m 2 .

[0192] S3.2. Establish calculation formulas for components of surface heat flux such as water layer heat storage and soil heat flux;

[0193] Calculate the water layer heat storage formula according to the definition of water layer heat storage:

[0194]

[0195] Wherein, is the heat storage of the water body in the flooded layer, with the unit of W / m 2 ; is the specific heat capacity of water, with the unit of J / (kg·K); is the density of water, with the unit of kg / m 3 ; is the water layer depth, with the unit of m; is the change in water temperature, is the water body temperature, with the unit of °C, is the temperature of the irrigation water, with the unit of °C, is the temperature of the water discharged from the field, with the unit of °C; is the flow rate of the irrigation water, with the unit of m / s; is the water flow rate of the drainage, with the unit of m / s.

[0196] Based on the forced-restore model, establish the soil heat flux calculation formula:

[0197]

[0198] Wherein, is the soil heat flux, with the unit of W / m 2 ; Based on the forced-restore model, the soil heat flux can be expressed as a function of the soil surface temperature , is the daily average temperature of the soil surface, with the unit of K; is the angular frequency, with the unit of ; is the volumetric heat capacity of the soil, with the unit of J / (m 3 ·K); is the soil thermal conductivity, with the unit of W / (m·K). The value of adopts the 24-hour average value calculated the previous day. is calculated from the heat capacity of soil components and the component contents, is calculated from the thermal conductivities of dry soil and saturated soil according to the Kersten value, and the Kersten value is calculated according to the soil properties. For typical paddy soil, 3 = 2.9 MJ / (m ·K),

[0199] S3.3. The surface heat flux calculated from the surface heat flux model should be equal to the sum of the surface heat flux components, as shown in the following equation;

[0200]

[0201] Since heat exchange occurs at the water layer surface, and the water layer thickness is generally 0 - 10 cm, and the soil surface is in contact with the water layer, it can be considered that . Solve for and then substitute it into the above-mentioned surface heat flux calculation formula to solve for G.

[0202] S4. Coupling the improved Jarvis canopy resistance model and the water temperature - surface heat flux model into the existing Shuttleworth - Wallace model to obtain the improved Shuttleworth - Wallace model;

[0203]

[0204]

[0205]

[0206]

[0207]

[0208]

[0209]

[0210]

[0211] In the formula, is the crop latent heat flux, is the latent heat flux of the soil, with the unit of W / m 2 ; and are terms in a similar Penman-Monteith model, applicable to canopy transpiration and soil evaporation respectively; and are the canopy resistance coefficient and the soil surface resistance coefficient respectively, which are the intermediate values calculated from each resistance , , obtained.

[0212] is the net solar radiation, is the net radiation of the water surface, D is the vapor pressure difference at the reference height; is the slope of the saturation vapor pressure-temperature curve, which can be calculated from the air temperature and the saturation vapor pressure, ; is the psychrometer constant, , P is the air pressure, which can be calculated according to the elevation Z (m) of the calculation location, , is the latent heat of vaporization, which can be calculated from the air temperature, ; The above are all calculated from the net radiation, humidity, air temperature data, elevation information of the location and leaf area data monitored by the weather station. The surface heat flux G is calculated through the water temperature-surface heat flux model of S3; the actual canopy resistance is calculated by the improved Jarvis canopy resistance model, and other resistances are calculated by each resistance model:

[0213] The aerodynamic resistance above the canopy is calculated as follows:

[0214]

[0215] In the formula, is the canopy height, obtained from the plant height data, with the unit of m; is the reference height, with the unit of m; is the zero plane displacement, , with the unit of m; is the canopy surface roughness, , with the unit of m; is the Karman constant, taking 0.41; is the turbulent diffusion coefficient at the top of the canopy, ; is the attenuation coefficient, taking 2.5, is the wind speed at the reference height, with the unit of m / s.

[0216] The aerodynamic resistance inside the canopy is calculated as follows:

[0217]

[0218] In the formula, is the leaf width, obtained from the leaf width data, with the unit of m; is the wind speed at the top of the canopy, , with the unit of m / s.

[0219] The aerodynamic resistance at the bottom of the canopy is calculated as follows:

[0220]

[0221] In the formula, is the roughness length for controlling water and heat transfer, , with the unit of m.

[0222] The soil surface resistance can be considered a constant, m / s.

[0223] S5. Based on the improved Shuttleworth-Wallace model, predict the evapotranspiration data during the whole growth period under different flooding depths, and evaluate the water-saving effects of each irrigation method.

[0224] The prediction method for the evapotranspiration data during the whole growth period under different flooding depths based on the improved Shuttleworth-Wallace model is as follows:

[0225] Combine the meteorological data, rice growth data, and flooding depth data to calculate the five resistance parameters in the Shuttleworth-Wallace model: the aerodynamic resistance at the top of the canopy, the aerodynamic resistance at the bottom of the canopy, the aerodynamic resistance inside the canopy, the soil surface resistance, and the Jarvis canopy resistance considering the flooding depth;

[0226] Use the meteorological data to calculate the net radiation at the water surface, and calculate the water temperature and surface heat flux according to the flooding depth data combined with the water temperature - surface heat flux model;

[0227] Combine the five calculated resistance parameters and the surface heat flux with the improved Shuttleworth-Wallace model to simulate the evapotranspiration during the whole growth period of rice under different said flooding depths.

[0228] Model simulation effect evaluation:

[0229] Select the measured evapotranspiration, evaporation, and transpiration data, and evaluate the effect of the improved Shuttleworth-Wallace model using the linear regression slope and intercept, determination coefficient, and root mean square error. The verification effects of the simulated values of each variable are as Figures 3 to 5 shown, and the R of the model before and after improvement 2, the RMSE and IOA are shown in Table 2. It is found that the overall simulation effect after improvement is better than the original, and the simulation accuracy has been improved.

[0230] Table 2 Comparison of Model Simulation Result Accuracy

[0231]

[0232] ET is the evapotranspiration, with the unit of mm / d; E is the evaporation, with the unit of mm / d; Tr is the transpiration, with the unit of mm / d.

[0233] Figure 6 is the change diagram of evapotranspiration during the whole growth period based on model simulation with water depth. It can be seen that adopting a shallower flooding layer can effectively reduce the evapotranspiration amount, so as to achieve the purpose of water saving.

[0234] Based on the same inventive concept as the embodiment, this embodiment introduces a rice evapotranspiration estimation system considering the flooding layer depth. The system includes:

[0235] The first main module is used to obtain meteorological, rice flooding layer depth, rice growth and measured evapotranspiration data in the study area;

[0236] The second main module is used to establish a Jarvis canopy resistance model considering the flooding layer depth and a water temperature - surface heat flux model based on the measured evapotranspiration data;

[0237] The third main module is used to couple the canopy resistance model considering the flooding layer depth and the water temperature - surface heat flux model into the Shuttleworth - Wallace model to obtain an improved Shuttleworth - Wallace model;

[0238] The fourth main module is used to predict the evapotranspiration data of crops during the whole growth period under irrigation with different flooding layer depths based on the improved Shuttleworth - Wallace model.

[0239] The present invention further includes a fifth main module, which is used to evaluate the effect of the improved Shuttleworth - Wallace model based on the measured data by using the coefficient of determination, root mean square error, consistency index combined with a lysimeter, an eddy covariance system or an eddy covariance system.

[0240] The method of the embodiment of the present invention is implemented relying on an electronic device. Therefore, it is necessary to introduce the relevant electronic device. For this purpose, an embodiment of the present invention provides an electronic device. As shown in the figure, the electronic device includes: at least one processor, a communication interface, at least one memory, and a communication bus. Among them, the at least one processor, the communication interface, and the at least one memory complete communication with each other through the communication bus. The at least one processor calls the logic instructions in the at least one memory to execute all or part of the steps of the methods provided by the foregoing various method embodiments.

[0241] In addition, when the logic instructions in the foregoing at least one memory are implemented in the form of a software functional unit and sold or used as an independent product, they are stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or part of this technical solution is embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to enable a computer device (a personal computer, a server, or a network device) to execute all or part of the steps of the methods described in the various method embodiments of the present invention. And the foregoing storage medium includes: USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs and other media for storing program codes.

[0242] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program codes.

[0243] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for estimating rice evapotranspiration considering the depth of the flooded layer, characterized in that: It includes the following steps: Obtain data on meteorology, flood depth of rice fields, rice growth, and measured evapotranspiration in the study area; Considering the influence of the depth of the flooded layer on evapotranspiration and heat storage in the water layer, a canopy resistance model and a water temperature-surface heat flux model considering the depth of the flooded layer were established. The canopy resistance model considering the depth of the flooded layer and the water temperature-surface heat flux model are coupled into the Shuttleworth-Wallace model to obtain an improved Shuttleworth-Wallace model; The improved Shuttleworth-Wallace model is used to predict evapotranspiration of rice during its entire growth period under irrigation at different flooding depths.

2. The rice evapotranspiration estimation method considering the depth of the flooded layer according to claim 1, characterized in that, Considering the influence of flooded layer depth on evapotranspiration, a canopy resistance model considering flooded layer depth is established, including the following steps: Calculating actual canopy resistance at different flooded layer depths based on measured evapotranspiration data at different flooded layer depths; According to the actual canopy resistance at different flooded layer depths, the water depth influence function is determined with the flooded layer depth as the independent variable and the measured canopy resistance as the dependent variable; In the Jarvis canopy resistance model, the soil moisture influence function is replaced by the water depth influence function, and the Jarvis canopy resistance model considering the depth of the flooded layer is obtained.

3. The rice evapotranspiration estimation method considering the depth of the flooded layer according to claim 1, characterized in that: The Jarvis canopy resistance model considering the depth of the flooded layer is: ； ； ； ； ； In the formula, Canopy resistance, is the minimum canopy resistance; LAI a is the effective leaf area; , , and are the response functions of canopy resistance to various environmental factors; is the net solar radiation; D is the vapor pressure deficit at the reference height; is the air temperature at the reference height; h w is the depth of the flooded layer; , , , , are the parameters calibrated according to the measured data.

4. A method for estimating rice evapotranspiration considering the depth of the flooded layer according to claim 1, characterized in that: The steps for establishing the water temperature-surface heat flux model are as follows: Based on the sensible heat calculation formula and the latent heat calculation formula based on water vapor transport theory, the sensible heat and latent heat of the water surface are calculated, and the surface heat flux expression is established according to the energy balance of the water body under the canopy; The surface heat flux expression is combined with the aquifer water heat flux and soil heat flux calculation formulas to form a water temperature-surface heat flux model for calculating water body temperature and surface heat flux.

5. The rice evapotranspiration estimation method considering the depth of the flooded layer according to claim 1, characterized in that: The water temperature-surface heat flux model is: ； ； ； ； where G is the surface heat flux, is the air density, is the specific heat of air, is the aerodynamic resistance of air at the bottom of the canopy, is the saturated water vapor pressure of air at the reference height, is the actual water vapor pressure at the reference height, is the slope of the saturated water vapor pressure - temperature curve; ; is the water surface temperature, is the aerodynamic resistance of air above the canopy, is the soil surface resistance; is the net radiation of the water surface; is the PT coefficient; is the psychrometer constant; is the heat flux of the water body in the flooded layer, is the soil heat flux; is the specific heat capacity of water; is the density of water; is the water layer depth; is the change in water temperature, is the water body temperature, is the temperature of the irrigation water, is the temperature of the water discharged from the field plot; is the flow rate of the irrigation water; is the water flow rate of the drainage; is the daily average temperature of the soil surface; is the angular frequency; is the volumetric heat capacity of the soil; is the thermal conductivity of the soil; 。 6. The rice evapotranspiration estimation method considering the depth of the flooded layer according to claim 1, characterized in that: The method also includes: based on measured data, using the coefficient of determination, root mean square error, consistency index combined with a lysimeter, an eddy correlation system or an eddy correlation system to evaluate the effect of the improved Shuttleworth-Wallace model.

7. A method for estimating rice evapotranspiration considering the depth of the flooded layer according to claim 1, characterized in that: Includes steps: Calculate the Shuttleworth-Wallace model including the aerodynamic resistance at the top of the canopy, the aerodynamic resistance at the bottom of the canopy, the aerodynamic resistance inside the canopy, the soil surface resistance and the canopy resistance considering the influence of the depth of the flooded layer in combination with the meteorological data, the rice growth data and the flooded layer depth data; Calculating the net radiation of the water surface using the meteorological data, and calculating the water temperature and the surface heat flux according to the flooded layer depth data combined with the water temperature-surface heat flux model; The calculated five resistance parameters and the surface heat flux are combined with the improved Shuttleworth-Wallace model to simulate the evapotranspiration of rice during the entire growth period at different flood layer depths.

8. A rice evapotranspiration estimation system considering the depth of the flooded layer, characterized in that: include: The first main module is used to obtain meteorological data, rice flooding depth, rice growth, and measured evapotranspiration data in the study area; The second main module is used to establish a Jarvis canopy resistance model considering the depth of the flooded layer and a water temperature - surface heat flux model based on measured evapotranspiration data; The third main module is used to couple the canopy resistance model considering the depth of the flooded layer and the water temperature - surface heat flux model into the Shuttleworth - Wallace model to obtain an improved Shuttleworth - Wallace model; The fourth main module is used to predict the evapotranspiration during the whole growth period of rice under irrigation with different depths of the flooded layer based on the improved Shuttleworth - Wallace model.

9. The rice evapotranspiration estimation system considering the depth of the flooded layer according to claim 8, characterized in that: It also includes a fifth main module, which is used to evaluate the effect of the improved Shuttleworth - Wallace model based on measured data using the coefficient of determination, root mean square error, and index of agreement.

10. A non-transitory computer-readable storage medium, characterized in that, The non - transient computer - readable storage medium stores computer instructions, and the computer instructions cause the computer to execute the method described in any one of claims 1 to 7.

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