A method for estimating rice evapotranspiration considering the depth of the flooded layer

Abstract

This invention discloses a method for estimating rice evapotranspiration considering flooded layer depth, belonging to the field of crop evapotranspiration simulation technology. The method includes the following steps: acquiring meteorological data, flooded layer depth data of paddy fields, rice growth data, and measured evapotranspiration data within the study area; considering the influence mechanism of flooded layer depth on evapotranspiration, adding the influence of flooded layer depth on canopy resistance to the canopy resistance model (such as the Jarvis canopy resistance model); considering the influence of flooded layer depth on water layer heat storage, constructing a water temperature-surface heat flux model; coupling the canopy resistance model and the surface heat flux model into the Shuttleworth-Wallace model to improve the evapotranspiration model; and using the improved Shuttleworth-Wallace model to predict evapotranspiration throughout the entire growth period under irrigation at different flooded depths, for evaluating the water-saving effects of various irrigation methods. This invention, by improving the Shuttleworth-Wallace model and incorporating the influence mechanism of flooded layer depth on evapotranspiration into rice evapotranspiration simulation, helps improve the accuracy of rice evapotranspiration simulation and provides a basis for formulating reasonable irrigation systems.

Description

Technical Field

[0001] This invention relates to the field of crop evapotranspiration simulation technology, specifically to a method for estimating rice evapotranspiration that takes into account the depth of the flooded layer. Background Technology

[0002] Evapotranspiration is a major form of agricultural water consumption and a key component of the surface water heat cycle. Accurate quantification of evapotranspiration is crucial for agricultural water management and a better understanding of the interactions between the natural environment and ecosystems. Rice is my country's main food crop, and irrigation water consumption accounts for 70% of total agricultural water use. Developing rational irrigation systems and improving rice water use efficiency are vital for food security and water resource security. Therefore, accurate quantification of rice evapotranspiration is of great significance.

[0003] Monitoring and simulation are the two main methods for quantifying evapotranspiration. Crop evapotranspiration monitoring methods include lysimeters, eddy covariance systems, and Bowen specific energy balance systems, but these methods are costly and have strong scalability. Crop evapotranspiration simulation methods generally use the crop coefficient method and mechanistic models. The crop coefficient method is convenient to use, but crop coefficients that have not undergone regional correction often have low accuracy. Mechanistic models can take into account mechanisms such as meteorological driving and vegetation control, and have higher simulation accuracy.

[0004] In mechanistic models, the Shuttleworth-Wallace dual-source evapotranspiration model divides the land surface into a soil layer and a vegetation layer, introducing five resistance parameters to describe the turbulent diffusion process of water vapor generated from the soil and vegetation layers. It is widely used to estimate evapotranspiration (ET) and its components under various vegetation cover conditions. Estimating canopy resistance is a major challenge in the Shuttleworth-Wallace model. Current canopy resistance models consider the influence of meteorology, crop growth, and soil moisture. However, for rice, the flooded layer is a unique growing environment, and the impact of flooded layer depth on canopy resistance has not yet been reflected in canopy resistance models. Furthermore, the presence of a flooded layer has a significant impact on energy balance, and the existing Shuttleworth-Wallace model framework cannot consider the impact of flooded layer depth on water layer heat storage. Therefore, it is necessary to study methods for simulating rice evapotranspiration in the presence of a flooded layer. Summary of the Invention

[0005] The purpose of this invention is to address the problems existing in the prior art by providing a method for estimating rice evapotranspiration that takes into account the depth of the flooded layer.

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

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

[0008] Acquire meteorological data, water depth of paddy fields, rice growth data, and measured evapotranspiration data within the study area;

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

[0010] 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 the improved Shuttleworth-Wallace model.

[0011] The improved Shuttleworth-Wallace model was used to predict evapotranspiration of rice throughout its entire growth period under irrigation at different flood depths, and to evaluate the water-saving effect of each irrigation method.

[0012] It should be noted that the prediction of evapotranspiration of rice throughout its entire growth period is based on the improved Shuttleworth-Wallace model: including the calculation of evapotranspiration, evaporation and transpiration of rice throughout its entire growth period under irrigation at different flood depths.

[0013] As a further technical solution, considering the influence mechanism of flooded layer depth on evapotranspiration, a canopy resistance model considering flooded layer depth is established, including the following steps: calculating the actual canopy resistance based on measured evapotranspiration data, considering the influence of flooded layer depth on canopy resistance, determining the response function of canopy resistance to water depth (water depth influence function); and establishing a canopy resistance model considering water depth based on the water depth influence function.

[0014] More specifically, considering the influence mechanism of floodplain depth on evapotranspiration, a canopy resistance model considering floodplain depth is established, including the following steps:

[0015] Based on the measured evapotranspiration data at different flooding depths and combined with the canopy resistance model, the actual canopy resistance at different flooding depths is calculated.

[0016] Based on the actual canopy resistance at different flooding depths, a water depth influence function is established with the flooding depth as the independent variable and the measured canopy resistance as the dependent variable.

[0017] In the Jarvis canopy resistance model, the water depth influence function is replaced with the soil moisture influence function to obtain a Jarvis canopy resistance model that considers the depth of the flooded layer.

[0018] As a further technical solution, considering the impact of flooding depth on water layer heat storage, a water temperature-surface heat flux model is established: based on the energy balance of the water body below the canopy, an expression for surface heat flux is established, and combined with the calculation formulas for surface heat flux components such as water body heat storage (flooded water body heat flux) and soil heat flux, a water temperature-surface heat flux model (a water temperature-surface heat flux model considering flooding depth) is established.

[0019] More specifically, considering the impact of flooded layer depth on water layer heat storage, a water temperature-surface heat flux model is established: 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. According to the energy balance of the water body below the canopy, the surface heat flux expression is established. The surface heat flux expression is combined with the water heat flux of the flooded layer and the soil heat flux calculation formula to form a water temperature-surface heat flux model for calculating water temperature and surface heat flux.

[0020] The meteorological data mentioned in S1.1 refers to net solar radiation, air temperature at reference altitude, relative humidity, and wind speed in the study area; the evapotranspiration data refers to evapotranspiration data measured by monitoring methods such as eddy covariance system, Bowen specific energy balance monitoring system, and lysimeter, as well as inter-row evaporation data measured by lysimeter; the rice growth data refers to leaf area data obtained by one or more methods such as remote sensing image inversion and canopy analyzer monitoring, plant height data and leaf width data read by ruler, and growth stage data determined based on rice growth status; the flooding depth data refers to the flooding depth data read daily by ruler or water level gauge.

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

[0022] S2.1. Based on the measured evapotranspiration data and 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, Canopy resistance, expressed in s / m; The aerodynamic drag inside the canopy is expressed in s / m. Net solar radiation, measured in MJ / (m²). 2 ·d); Net radiation over water surface, in MJ / (m²) 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; Evapotranspiration, expressed in mm / d, can be obtained by subtracting measured inter-tree evaporation data from measured evapotranspiration data. This represents the slope of the saturated water vapor pressure-temperature curve, in kPa / °C. This refers to air density, expressed in kg / m³. Specific heat of air, expressed in J / (kg·°C); The pressure of water vapor in saturated air. The air vapor pressure is given in kPa, and the calculation formula is as follows: ,in, For reference altitude temperature, Relative humidity at reference altitude; The latent heat of vaporization is expressed in MJ / kg. This is the hygrometer constant, measured in kPa / °C.

[0025] S2.2. Determine the form of the water depth influence function in the Jarvis canopy resistance model based on canopy resistance at different water depths. Since canopy resistance increases with decreasing water depth and also increases at excessively high water depths, the water depth influence function is determined to be a quadratic function of water depth:

[0026] (2)

[0027] In the formula, h w denoted as the depth of the flooded layer, in meters; a and b are parameters.

[0028] S2.3. Add a water depth influence function to the Jarvis canopy drag model to account for the effect of water depth on canopy drag:

[0029] The Jarvis model, which considers the effects of radiation, water vapor pressure difference, air temperature and soil moisture, is shown in equation (3):

[0030] (3)

[0031] In the formula, Canopy resistance, expressed in s / m; Minimum canopy resistance, determined based on the rice growth stage, is expressed in s / m; LAI a For effective leaf area, LAI a =(0.5LAI+1) / LAI, where LAI is the measured leaf area; , , and These are the response functions of canopy resistance to various environmental factors, and the specific calculation formulas are as follows:

[0032] (4)

[0033] (5)

[0034] (6)

[0035] (7)

[0036] In the formula, Net solar radiation, measured in W / m² 2 D represents the water vapor pressure difference at the reference altitude. The unit is kPa; Air temperature at reference altitude, in °C; , , These are soil volumetric water content (m³) 3 / m 3 ), saturated soil moisture content (m 3 / m 3 ) and wilting point (m 3 / m 3 ); , , , These parameters are determined based on the actual canopy resistance rate.

[0037] Since the depth of the flooded layer affects canopy resistance, and the soil moisture is saturated at this time, the Jarvis model, which considers the effects of radiation, water vapor pressure difference, air temperature, and soil moisture, is difficult to reflect the actual canopy resistance. Therefore, this invention introduces a water depth influence function to replace the soil moisture influence function, in order to characterize the influence of water depth on 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 to water depth is as follows:

[0043] (9)

[0044] In the formula, The minimum canopy resistance is determined based on the rice growth stage; LAI a For effective leaf area, LAIa =(0.5LAI+1) / LAI; , , and This is the response function of canopy resistance to various environmental factors; D represents net solar radiation; D represents the water vapor pressure difference at the reference altitude. ; Temperature at reference altitude; h w This refers to the depth of the flooded layer. , , , , These parameters are determined based on the actual canopy resistance rate.

[0045] As a further technical solution, considering the impact of flooded layer depth on aquifer thermal storage, 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 transport theory, establish the expressions for the sensible heat and latent heat of the water surface:

[0047] Based on the Penman formula, the latent heat of evaporation from the water surface is calculated as follows:

[0048] (10)

[0049] In the formula, Latent heat of evaporation at water surface, W / m 2 ; Net radiation over water surface, W / m 2 G represents the Earth's surface heat flux, in W / m³. 2 ; The aerodynamic drag at the base of the canopy is expressed in s / m. Soil surface resistance, s / m; The saturated vapor pressure at the canopy height. This represents the actual water vapor pressure at the canopy height. The actual water vapor pressure at the reference altitude is given in kPa.

[0050] The saturated vapor pressure difference between the canopy height and the reference height can be approximately calculated using the temperature difference between the canopy height and the reference height.

[0051] (11)

[0052] In the formula, The temperature is the canopy temperature, in °C. The temperature at the reference altitude is in °C.

[0053] Based on the water vapor flux transport law, the actual water vapor pressure difference and temperature difference at the reference height and the canopy height are calculated as follows:

[0054] (12)

[0055] (13)

[0056] In the formula, The total latent heat flux is expressed in W / m³. 2 ; The total sensible heat flux is expressed in W / m³. 2 ; The aerodynamic drag above the canopy is expressed in s / m.

[0057] In the above formula, the total latent heat The total sensible heat H is an unknown quantity, and the Priestley-Taylor formula can be used to initialize and calculate the total latent heat flux. H is calculated using the energy balance remainder method:

[0058] (14)

[0059] (15)

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

[0061] Substituting equations (11) to (15) into equation (10), we obtain the latent heat of the water surface. The expression is as follows:

[0062] (16)

[0063] Similarly, based on the formulas for calculating the sensible heat flux of the water surface and the PT formula, the sensible heat flux of the water surface can be obtained. Expression (Equation (19)):

[0064] (17)

[0065] (18)

[0066] (19)

[0067] In the formula, H s Sensible heat flux over water surface, in W / m² 2 ; The water surface temperature is expressed in °C.

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

[0069] (20)

[0070] (twenty one)

[0071] In the formula, G is the surface heat flux; For the aerodynamic drag at the base of the canopy, For the aerodynamic drag of the upper canopy, For soil surface resistance; As an intermediate quantity, ; The water surface temperature; Net radiation from the water surface.

[0072] S3.3. Based on the definition of thermal storage, establish the expressions for water layer thermal storage 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 water body heat storage and soil heat flux based on the water body heat storage and forced-recovery model are as follows:

[0074] (twenty two)

[0075] In the formula, For heat storage in the flooded water layer, Soil heat flux, W / m 2 ; is the specific heat capacity of water, J / (kg·K); The density of water is kg / m³. 3 ; The depth of the water layer is in meters (m). This represents the change in water temperature. For water temperature, The temperature of the irrigation water, The temperature of the water drained from the field, in °C; The flow rate of irrigation water is expressed in m / s. The drainage flow rate is given in m / s. Soil heat flux is calculated based on a forced-recovery model. It can be expressed as soil surface temperature. The function. The average daily temperature of the soil surface, in K; Angular frequency, ; For soil volumetric heat capacity, Jm -3 K-1 ; For soil thermal conductivity, Wm -1 K -1 . The value is taken from the 24 hours calculated the previous day. average value. and The value is calculated based on typical paddy soil properties.

[0076] Since heat exchange occurs at the surface of the water layer, and the soil surface is in contact with the water layer, it can be considered that... .according to By combining equations (21) and (22), the water temperature is determined. and surface heat flux The computational model is a water temperature-surface heat flux model that takes into account the depth of the water layer.

[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. Based on the aerodynamic drag formulas for the top of the canopy, the bottom of the canopy, the internal aerodynamic drag of the canopy, the Jarvis canopy drag model considering the depth of the flooded layer, and the soil surface drag calculation formula, calculate the five drags in the Shuttleworth-Wallace model:

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

[0080] (twenty three)

[0081] In the formula, The canopy height is obtained from plant height data, in meters (m). For reference height, in meters (m); Zero planar displacement ,m; For canopy surface roughness, ,m; is the Karman constant, taken as 0.41; The turbulent diffusion coefficient at the top of the canopy is... ; The attenuation coefficient is set to 2.5. Wind speed at reference altitude, in m / s.

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

[0083] (twenty four)

[0084] In the formula, The leaf width is obtained from the leaf width data, in meters (m). The wind speed at the top of the canopy. , m / s.

[0085] The aerodynamic drag at the base of the canopy is calculated as follows:

[0086] (25)

[0087] In the formula, To control the roughness length of hydrothermal transfer, , m.

[0088] The canopy resistance is calculated as follows:

[0089] (26)

[0090] Soil surface resistance can be considered a constant. m / s.

[0091] S4.2. Based on the water temperature-surface heat flux model, and combined with the calculated net surface radiation of the water body, aerodynamic drag at the top of the canopy, aerodynamic drag 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. Based on surface heat flux, five resistances, meteorological data, and water depth, a dual-source evapotranspiration model considering water depth (the improved Shuttleworth-Wallace model) is constructed based on the 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 also includes the step of evaluating the effectiveness of the improved Shuttleworth-Wallace model. Specifically, the accuracy of the simulation results of the improved Shuttleworth-Wallace model is verified by combining measured evapotranspiration data. For example, the effectiveness of the improved Shuttleworth-Wallace model is evaluated using the coefficient of determination, root mean square error, and consistency index combined with measured evapotranspiration data from a lysimeter, eddy covariance system, or eddy covariance system.

[0105] As a further technical solution, the prediction method for evapotranspiration data throughout the entire growth period based on the improved Shuttleworth-Wallace model is as follows:

[0106] The Shuttleworth-Wallace model is calculated by combining the meteorological data, crop growth data, and flooding depth data, including aerodynamic drag at the top of the canopy, aerodynamic drag at the bottom of the canopy, aerodynamic drag inside the canopy, Jarvis canopy drag considering flooding depth, and soil surface drag.

[0107] The net radiation of the water surface is calculated using the meteorological data, and the water temperature and the surface heat flux are calculated based on the flooded layer depth data and the water temperature-surface heat flux model.

[0108] The calculated five resistance parameters and the surface heat flux are combined with the improved Shuttleworth-Wallace model to simulate the evapotranspiration of rice throughout its entire growth period at different flooding depths.

[0109] Secondly, the present invention provides a rice evapotranspiration estimation system that takes into account the depth of the flooded layer, comprising:

[0110] The first main module is used to acquire meteorological, rice flooding depth, rice growth, and measured evapotranspiration data within the study area.

[0111] The second main module is used to establish a Jarvis canopy resistance model and a water temperature-surface heat flux model that take into account the depth of the flooded layer based on measured evapotranspiration data.

[0112] The third main module is used to couple the canopy resistance model that considers 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 evapotranspiration data of crops throughout their entire growth period under irrigation at different flooding depths, based on the improved Shuttleworth-Wallace model.

[0114] Thirdly, the present invention provides a non-transitory computer read storage medium storing computer instructions that cause the computer to execute any of the above-described methods for estimating rice evapotranspiration considering the depth of the flooded layer.

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

[0116] 1. This invention fully considers the influence of the flooded layer depth on rice evapotranspiration, improves the accuracy of the model in simulating the rice evapotranspiration process, and is beneficial for formulating reasonable irrigation systems, improving water use efficiency, and achieving water-saving irrigation.

[0117] 2. This invention improves the Shuttleworth-Wallace model by incorporating the influence mechanism of flooding depth on evapotranspiration into the simulation of rice evapotranspiration. The improved model can more accurately simulate the rice evapotranspiration process, thereby more accurately estimating the evapotranspiration and its components (evaporation and transpiration) of paddy fields at different flooding depths.

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

[0119] 4. This invention can calculate the evapotranspiration and evapotranspiration content of paddy fields based on meteorological data and field water depth. It can predict the evapotranspiration of rice at different flood depths through easily accessible monitoring data, saving time and effort. Attached Figure Description

[0120] Figure 1 A schematic diagram of a method for simulating rice evapotranspiration that takes into account the depth of the flooded layer;

[0121] Figure 2 Flowchart of a rice evapotranspiration model considering the depth of the flooded layer;

[0122] Figure 3 This is a verification diagram showing the results of evapotranspiration simulation using the improved evapotranspiration model in an embodiment of the present invention;

[0123] Figure 4This is a verification diagram showing the results of evaporation simulation using the improved evaporation model in an embodiment of the present invention;

[0124] Figure 5 This is a verification diagram showing the results of evapotranspiration simulation using the improved evapotranspiration model in an embodiment of the present invention;

[0125] Figure 6 This is a graph showing the variation of evapotranspiration with water depth during the entire growth period of rice under meteorological conditions and rice growth status, as described in an embodiment of the present invention. Detailed Implementation

[0126] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

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

[0128] S1. Collect meteorological data, paddy field flooding depth data, rice growth data, and measured evapotranspiration data within the study area;

[0129] Meteorological data refers to net solar radiation, atmospheric pressure, air temperature at reference altitude, relative humidity at reference altitude, and wind speed at reference altitude within the study area. These meteorological data are obtained through monitoring by automatic weather stations in the experimental area. In this implementation, the reference altitude is 2m. Evapotranspiration data includes evapotranspiration measured by one or more of the following methods: eddy covariance system, Bowen specific energy balance monitoring system, and lysimeter monitoring, and inter-row evaporation measured by lysimeter. Rice growth data includes leaf area data obtained through one or more of the following methods: remote sensing image inversion, canopy analyzer monitoring, plant height data and leaf width data read by a ruler, and growth stage data determined based on rice growth status. Flood depth data is data read daily by a ruler or water level gauge.

[0130] In this embodiment, a rice evapotranspiration monitoring experiment was conducted in a rice-growing area in China. The experimental plot consisted of several 7.5m × 16m fields. Four different treatments were set up, including four flooding depths ranging from 0 to 10cm: 1cm, 4cm, 7cm, and 10cm, with three replicates for each treatment. Flooding was conducted from the rice tillering stage to the milk stage, and the fields were dried at the end of the tillering stage. Water was replenished to each field every morning at 6:00 AM through inlet pipes to maintain the water depth at the set depth.

[0131] The lysimeter was weighed at fixed times every morning and evening (7:00 am and 6:00 pm) using a micro lysimeter weighing method. The amount of water reduced was the amount of water consumed daily through evaporation and evaporation. The evaporation and evaporation of rice during the day were calculated based on the amount of water. The transpiration was calculated as the difference between evaporation and evaporation.

[0132] The Jarvis resistance model, which considers the effects of net solar radiation, vapor pressure difference at reference altitude, air temperature at reference altitude, and soil volumetric water content, takes the following form:

[0133]

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

[0135]

[0136]

[0137]

[0138]

[0139] In the formula, Net solar radiation, measured in W / m² 2 D represents the water vapor pressure difference at the reference altitude. The unit is kPa; Temperature at reference altitude, in °C; , , These are soil volumetric water content, saturated soil water content, and wilting point, all in meters (m). 3 / m 3 ; The parameters are calibrated with net solar radiation as the independent variable and actual canopy drag as the dependent variable. The parameters are calibrated with the vapor pressure difference at a reference height as the independent variable and the actual canopy resistance as the dependent variable. The parameter is calibrated with air temperature at a reference altitude as the independent variable and actual canopy resistance as the dependent variable. The parameters are determined with soil volumetric water content as the independent variable and actual canopy resistance as the dependent variable.

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

[0141] S2. The measured evapotranspiration data, flooded layer depth data, and meteorological data are used to improve the Jarvis canopy resistance model, resulting in a Jarvis canopy resistance model that takes into account the flooded layer depth.

[0142] The steps to improve the Jarvis canopy resistance model are as follows:

[0143] S2.1. Evapotranspiration data were obtained from actual measurements at different flooding depths. Evapotranspiration was obtained by subtracting intergranular evaporation from evapotranspiration. Combined with measured meteorological data, the actual canopy resistance was calculated using the Shuttleworth-Wallace model.

[0144]

[0145] In the formula, This represents the aerodynamic drag inside the canopy, expressed in s / m. The calculation formula can be found in the drag calculation section. Net solar radiation, measured in MJ / (m²). 2 ·d); Net radiation over water surface, in MJ / (m²) 2 ·d); Evapotranspiration, expressed in mm / d; The slope of the saturated water vapor pressure-temperature curve is expressed in kPa / °C. This refers to air density, expressed in kg / m³. Specific heat of air, expressed in J / (kg·°C); For reference altitude, the air saturation water vapor pressure The actual water vapor pressure at the reference altitude is expressed in kPa. The latent heat of vaporization is expressed in MJ / kg. This is the hygrometer constant, measured in 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] Based on the actual canopy resistance at different water depths, the form of the water depth influence function in the Jarvis resistance model was determined. Experiments showed that the actual canopy resistance first decreases and then increases with water depth, reaching a minimum at around 6 cm. Therefore, the water depth influence function was proposed as a quadratic function of water depth, with the following basic form:

[0148]

[0149] In the formula, h w , where is the depth of the flooded layer, in 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 (Jarvis canopy resistance model considering the depth of the flooded layer);

[0151]

[0152]

[0153]

[0154]

[0155]

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

[0157] Sure , , , , The possible values ​​for are as follows.

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

[0159]

[0160] S3. Establish a surface heat flux expression based on the energy balance model below the canopy, and combine the surface heat flux expression and the surface heat flux component calculation formula to form the water temperature-surface heat flux model.

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

[0162] S3.1 Establish the expression for surface heat flux based on the energy balance beneath the canopy;

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

[0164]

[0165] in, This refers to the sensible heat flux at the surface of the water body. Let G be the latent heat flux at the water surface and G be the surface heat flux.

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

[0167]

[0168] In the formula, The aerodynamic drag at the base of the canopy is expressed in s / m. Soil surface resistance, expressed in s / m; This represents the saturated vapor pressure at the canopy height, expressed in kPa. This represents the actual water vapor pressure at the canopy height, in kPa. The actual water vapor pressure at the reference altitude is expressed in kPa.

[0169] The saturated vapor pressure difference between the canopy height and the reference height can be approximately calculated using the temperature difference between the canopy height and the reference height.

[0170]

[0171] In the formula, Temperature at canopy height, in °C; The temperature at the reference altitude is expressed in °C.

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

[0173]

[0174] In the formula, The total latent heat flux is expressed in W / m³. 2 ; The aerodynamic drag above the canopy is expressed in 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, The total sensible heat flux is expressed in W / m³. 2 .

[0178] In the above formula, the total latent heat flux The overall sensible heat flux H is an unknown quantity, and the overall latent heat flux can be approximately calculated using the Priestley-Taylor formula. H is calculated using the energy balance remainder method:

[0179]

[0180]

[0181] In the formula, This is the Priestley-Taylor coefficient, typically taken as 1.26 for water surface evaporation.

[0182] This yields the latent heat flux at the water surface. The expression is as follows:

[0183]

[0184] Similarly, based on the formula for calculating the sensible heat flux at the water surface and the Priestley-Taylor formula, the sensible heat flux at the water surface can be obtained. expression:

[0185]

[0186]

[0187]

[0188] In the formula, H s Sensible heat flux over water surface, in W / m² 2 ; The water surface temperature is expressed in °C.

[0189] Will and Substituting the expression into the energy balance model of the water body beneath the canopy, we obtain the formula for calculating the surface heat flux:

[0190]

[0191] In the formula, G is the surface heat flux, with units of W / m³. 2 ; For the aerodynamic drag at the base of the canopy, For the aerodynamic drag of the upper canopy, The values ​​represent soil surface resistance, all in s / m. As an intermediate quantity, ; The water surface temperature is expressed in °C. Net radiation over water surface, measured in W / m² 2 .

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

[0193] Formula for calculating thermal storage in a water layer based on the definition of thermal storage in a water layer:

[0194]

[0195] In the formula, Thermal energy storage in the flooded water body, measured in W / m³ 2 ; is the specific heat capacity of water, expressed in J / (kg·K); This is the density of water, expressed in kg / m³. 3 ; The depth of the water layer is expressed in meters (m). This represents the change in water temperature. Water temperature, in °C. The temperature of the irrigation water, in °C. The temperature of the water drained from the field, expressed in °C; The flow rate of irrigation water is expressed in m³ / s. This represents the drainage flow rate, expressed in m³ / s.

[0196] Based on the forced-recovery model, a formula for calculating soil heat flux is established:

[0197]

[0198] In the formula, Soil heat flux, in W / m³ 2 Soil heat flux based on the forced-recovery model It can be expressed as soil surface temperature. The function, This represents the daily average temperature of the soil surface, expressed in Kelvin (K). Angular frequency, unit: ; Soil volumetric heat capacity, in J / (m³) 3 ·K); Soil thermal conductivity, expressed in W / (m·K). The value is taken from the 24 hours calculated the previous day. average value. Calculated from the heat capacity and component content of soil components, The Kersten value is calculated from the thermal conductivity of dry and saturated soils, based on soil properties. Typical paddy soils... =2.9 MJ / (m 3 ·K), =1.21W / (m·K).

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

[0200]

[0201] Since heat exchange occurs at the surface of the water layer, and the water thickness is generally 0-10 cm, the soil surface is in contact with the water layer, which can be considered as... Solve for Substitute the result into the above formula for calculating surface heat flux, and solve for G.

[0202] S4. Couple the improved Jarvis canopy resistance model and 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, It is the crop latent heat flux. It is the latent heat flux of the soil, measured in W / m³. 2 ; and These are terms similar to those in the Penman-Monteith model, applicable to canopy transpiration and soil evaporation, respectively. and These are the canopy resistance coefficient and the soil surface resistance coefficient, respectively, and are the median values ​​calculated from each resistance factor. , , get.

[0212] Net solar radiation, D represents the net radiation over the water surface, and D represents the water vapor pressure difference at the reference height. The slope of the saturated vapor pressure-temperature curve can be calculated from the air temperature and saturated vapor pressure. ; This is the hygrometer constant. P represents air pressure, which can be calculated based on the altitude Z (m) of the location. , The latent heat of vaporization can be calculated from the air temperature. The above data were calculated using net radiation, humidity, temperature data, location elevation information, and leaf area data monitored by meteorological stations. Surface heat flux G was calculated using the S3 water temperature-surface heat flux model; actual canopy resistance... Other resistances were calculated using the improved Jarvis canopy resistance model, while those calculated using their respective resistance models.

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

[0214]

[0215] In the formula, This represents the canopy height, obtained from plant height data, in meters (m). For reference height, the unit is meters (m). Zero planar displacement The unit is meters (m). For canopy surface roughness, The unit is meters (m). is the Karman constant, taken as 0.41; The turbulent diffusion coefficient at the top of the canopy is... ; Let be the attenuation coefficient, taken as 2.5. Wind speed at reference altitude, in m / s.

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

[0217]

[0218] In the formula, The leaf width is obtained from leaf width data and is in meters (m). The wind speed at the top of the canopy. The unit is m / s.

[0219] The aerodynamic drag at the base of the canopy is calculated as follows:

[0220]

[0221] In the formula, To control the roughness length of hydrothermal transfer, The unit is meters (m).

[0222] Soil surface resistance can be considered a constant. m / s.

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

[0224] The following is a prediction method for evapotranspiration data throughout the growing season at different flooding depths based on the improved Shuttleworth-Wallace model:

[0225] Five drag parameters in the Shuttleworth-Wallace model were calculated by combining meteorological data, rice growth data, and flooding depth data: aerodynamic drag at the top of the canopy, aerodynamic drag at the bottom of the canopy, aerodynamic drag inside the canopy, soil surface drag, and Jarvis canopy drag considering flooding depth.

[0226] Meteorological data is used to calculate net radiation over water surface, and water temperature and surface heat flux are calculated based on flood depth data and a water temperature-surface heat flux model.

[0227] The calculated five resistance parameters and surface heat flux are combined with the improved Shuttleworth-Wallace model to simulate the evapotranspiration of rice throughout its entire growth period at different flooding depths.

[0228] Model simulation performance evaluation:

[0229] Measured evapotranspiration, evaporation, and transpiration data were selected, and the performance of the improved Shuttleworth-Wallace model was evaluated using linear regression slope and intercept, coefficient of determination, and root mean square error. The validation results of the simulated values ​​of each variable are shown below. Figures 3 to 5 As shown, the R values ​​of the model before and after the improvement are... 2As shown in Table 2, the RMSE and IOA of the improved simulation are better than the original overall, and the simulation accuracy is improved.

[0230] Table 2 Comparison of model simulation results accuracy

[0231]

[0232] ET is evapotranspiration, in mm / d; E is evaporation, in mm / d; Tr is transpiration, in mm / d.

[0233] Figure 6 The graph shows the variation of evapotranspiration with water depth throughout the entire growth period based on model simulation. It can be seen that using a shallower flooded layer can effectively reduce evapotranspiration, thereby achieving the goal of water conservation.

[0234] Based on the same inventive concept as the embodiments, this embodiment introduces a rice evapotranspiration estimation system that considers the depth of the flooded layer, the system comprising:

[0235] The first main module is used to acquire meteorological, rice flooding depth, rice growth, and measured evapotranspiration data within the study area.

[0236] The second main module is used to establish a Jarvis canopy resistance model and a water temperature-surface heat flux model that take into account the depth of the flooded layer based on measured evapotranspiration data.

[0237] The third main module is used to couple the canopy resistance model that considers 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.

[0238] The fourth main module is used to predict evapotranspiration data of crops throughout their entire growth period under irrigation at different flooding depths, based on the improved Shuttleworth-Wallace model.

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

[0240] The methods in the embodiments of the present invention are implemented using electronic devices; therefore, it is necessary to describe the relevant electronic devices. For this purpose, embodiments of the present invention provide an electronic device comprising: at least one processor, a communication interface, at least one memory, and a communication bus, wherein the at least one processor, the communication interface, and the at least one memory communicate with each other via the communication bus. The at least one processor invokes logical instructions stored in the at least one memory to execute all or part of the steps of the methods provided in the foregoing method embodiments.

[0241] Furthermore, when the logical instructions in at least one of the aforementioned memories are implemented as software functional units and sold or used as independent products, they are stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the 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 cause a computer device (a personal computer, server, or network device) to execute all or part of the steps of the methods described in the various method embodiments of the present invention. The aforementioned storage medium includes: USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks—various media for storing program code.

[0242] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

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

Claims

1. A method for estimating evapotranspiration of rice considering depth of waterlogged layer, characterized in that: It comprises the following steps: Obtaining meteorological data, rice field water depth, rice growth and measured evapotranspiration data in the study area; Considering the influence of water depth on evapotranspiration and water layer heat storage, a canopy resistance model considering water depth and a water temperature-surface heat flux model are established; The canopy resistance model considering water depth and the water temperature-surface heat flux model are coupled into the Shuttleworth-Wallace model to obtain an improved Shuttleworth-Wallace model; Based on the improved Shuttleworth-Wallace model, evapotranspiration prediction of rice in the whole growth period under different water depths is realized; The water temperature-surface heat flux model is established as follows: Based on the sensible heat calculation formula and the latent heat calculation formula based on water vapor transport theory, the surface sensible heat and latent heat of the water body are calculated, and the surface heat flux expression is established according to the energy balance of the water body below the canopy; The surface heat flux expression, water body heat flux and soil heat flux calculation formula are combined to form a water temperature-surface heat flux model for calculating water temperature and surface heat flux; the water temperature-surface heat flux model is: ； ； ； ； where G is the surface heat flux, for air density, for air specific heat, for the aerodynamic resistance at the bottom of the canopy, for the air saturation vapor pressure at the reference height, for the actual vapor pressure at the reference height, for the slope of the saturation vapor pressure-temperature curve; ; for the water surface temperature, for the aerodynamic resistance at the top of the canopy, for the soil surface resistance; for the net radiation at the water surface; for the PT coefficient; for the psychrometer constant; for the water body heat flux of the flooded layer, for the soil heat flux; for the specific heat capacity of water; for the density of water; for the water layer depth; for the water temperature change amount, for the water body temperature, for the temperature of the irrigation water, for the temperature of the water discharged from the field plot; for the flow rate of the irrigation water; for the water flow rate of the drainage; for the daily average temperature of the soil surface; for the angular frequency; for the volumetric heat capacity of the soil; for the thermal conductivity of the soil; ; for the solar net radiation; for the air temperature at the reference height.

2. The method for estimating evapotranspiration of rice considering waterlogging depth according to claim 1, wherein, Considering the influence of water depth on evapotranspiration, a canopy resistance model considering water depth is established, comprising the following steps: According to the measured evapotranspiration data under different water depths, the actual canopy resistance under different water depths is calculated; According to the actual canopy resistance under different water depths, the water depth influence function is determined with the water 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 to obtain the Jarvis canopy resistance model considering water depth.

3. The method for estimating evapotranspiration of rice considering waterlogging depth according to claim 1, characterized in that: The Jarvis canopy resistance model considering water depth is: ； ； ； ； ； wherein canopy resistance, is the minimum canopy resistance; is the effective leaf area; , , and is the response function of canopy resistance to each environmental factor; D is the vapor pressure difference at the reference height; , , , , is a parameter calibrated according to the measured data.

4. The method according to claim 1, wherein the method is characterized by: The method further comprises: based on the measured data, using the coefficient of determination, root mean square error, consistency index, combined with the lysimeter, eddy correlation system or eddy correlation system to evaluate the effect of the improved Shuttleworth-Wallace model.

5. The method for estimating evapotranspiration of rice considering waterlogging depth according to claim 1, characterized in that: Comprising the following steps: Combining the meteorological data, rice growth data and water depth data to calculate the canopy top aerodynamic resistance, canopy bottom aerodynamic resistance, canopy internal aerodynamic resistance, soil surface resistance and canopy resistance considering the influence of water depth in the Shuttleworth-Wallace model; Using the meteorological data to calculate the water surface net radiation, and using the water depth data combined with the water temperature-surface heat flux model to calculate the water temperature and the surface heat flux; Combining the calculated five resistance parameters and the surface heat flux with the improved Shuttleworth-Wallace model to simulate the evapotranspiration of rice in the whole growth period under different water depths. 6.A rice evapotranspiration estimation system considering waterlogged depth, characterized by: It comprises: A first main module for obtaining meteorological data, rice water depth, rice growth and measured evapotranspiration data in the study area; The second main module is configured to establish a Jarvis canopy resistance model and a water temperature-surface heat flux model considering the depth of the flooded layer based on the measured evapotranspiration data; The third main module is configured to couple the canopy resistance model and the water temperature-surface heat flux model considering the depth of the flooded layer into the Shuttleworth-Wallace model to obtain an improved Shuttleworth-Wallace model; The fourth main module is configured to predict the evapotranspiration of rice in the whole growth period under irrigation with different depths of the flooded layer based on the improved Shuttleworth-Wallace model; The water temperature-surface heat flux model is established according to the following steps: The sensible heat and latent heat on the surface of the water body are calculated based on the sensible heat calculation formula and the latent heat calculation formula based on the water vapor transport theory, and the surface heat flux expression is established according to the energy balance of the water body below the canopy. The surface heat flux expression, the water body heat flux of the flooded layer, and the soil heat flux calculation formula are combined to form a water temperature-surface heat flux model for calculating the water temperature and the surface heat flux; the water temperature-surface heat flux model is as follows: ； ； ； ； G is the surface heat flux, ρa is the air density, cp is the air specific heat, rc is the canopy bottom aerodynamic resistance, es is the air saturation vapor pressure at the reference height, ea is the actual vapor pressure at the reference height, l is the slope of the saturation vapor pressure-temperature curve; ; Tw is the water surface temperature, rcu is the canopy upper aerodynamic resistance, rs is the soil surface resistance; Rn is the net radiation at the water surface; PT is the coefficient of the PT equation; C is the psychrometer constant; Qw is the water body heat flux of the flooded layer, Qs is the soil heat flux; cpw is the specific heat capacity of water; pw is the density of water; Dw is the water layer depth; Tw is the water temperature change amount, Tw is the water body temperature, Tw is the temperature of the irrigation water, Tw is the temperature of the water discharged from the field plot; Qw is the flow rate of the irrigation water; Qw is the water flow rate of the drainage; Ts is the daily average temperature of the soil surface; ω is the angular frequency; Cv is the volumetric heat capacity of the soil; ks is the thermal conductivity of the soil; ; Rs is the solar net radiation; Ta is the air temperature at the reference height.

7. The system for estimating evapotranspiration of rice considering waterlogged depth according to claim 6, wherein: The fifth main module is configured to evaluate the effect of the improved Shuttleworth-Wallace model based on the measured data by using the coefficient of determination, the root mean square error, and the consistency index.

8. A non-transitory computer readable storage medium, comprising: The non-transitory computer readable storage medium stores computer instructions, and the computer instructions cause the computer to execute the method in any one of claims 1 to 5.

Images