Winter wheat winter irrigation quota regulation method based on freeze-thaw prediction

Abstract

This invention discloses a method for regulating winter irrigation quotas for winter wheat based on freeze-thaw prediction, relating to the field of agricultural irrigation. The method includes: collecting basic field data of winter wheat; establishing a soil freeze-thaw hydrothermal coupling model based on the basic data; inputting candidate winter irrigation quotas; simulating the freeze-thaw process under different winter irrigation quotas based on the soil freeze-thaw hydrothermal coupling model; identifying the soil freeze-thaw stage for each winter irrigation quota based on the simulation results; calculating the evaluation index for each winter irrigation quota based on the simulation results and the corresponding soil freeze-thaw stage identification results; constructing a comprehensive evaluation model and calculating the comprehensive score for each winter irrigation quota based on the evaluation index; and performing constraint screening on each winter irrigation quota based on the simulation results, the comprehensive score, and constraints to determine the recommended winter irrigation quota. This invention achieves dynamic optimization of winter irrigation quotas, improves soil moisture stability during the greening period, reduces the risk of shallow ice accumulation and frost heave, and improves water use efficiency.

Description

Technical Field

[0001] This invention relates to the field of agricultural irrigation technology, and more specifically to a method for quota control of winter irrigation for winter wheat based on freeze-thaw prediction. Background Technology

[0002] In winter wheat production in cold and arid regions, winter irrigation is an important measure to ensure the safe overwintering of wheat and its greening up in spring. Proper winter irrigation can increase the initial soil moisture content, promote the formation of a stable frozen layer, and provide a water base for spring greening.

[0003] However, existing winter irrigation methods mostly rely on manual experience, and the amount of irrigation water is usually determined based on the average climate conditions over many years or a fixed irrigation system. This has the following problems: (1) The winter irrigation quota cannot be dynamically adjusted according to the temperature, snowfall and initial soil moisture content of the year; (2) It is difficult to predict the freezing, stable freezing and thawing process of the soil under different winter irrigation water volumes; (3) It is not possible to effectively judge the problems of shallow ice richness, frost heave risk and prolonged thawing period; (4) Excessive irrigation is likely to cause water waste and even lead to a delay in the recovery of spring ground temperature; (5) Insufficient irrigation may lead to weak development of the frozen layer, insufficient deep water supply and unstable soil moisture during greening.

[0004] Therefore, how to take into account soil temperature, water migration, ice content evolution, freeze-thaw stages, and water use efficiency to carry out intelligent regulation of winter irrigation quotas is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0005] In view of this, the present invention provides a method for regulating winter irrigation quotas for winter wheat based on freeze-thaw prediction. By predicting the soil freeze-thaw process under different winter irrigation quotas, the method comprehensively evaluates the formation of a stable frozen layer, deep water enrichment, shallow ice enrichment risk, duration of thawing period and water use efficiency, thereby determining the appropriate amount of winter irrigation water.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: This invention discloses a method for quota regulation of winter irrigation for winter wheat based on freeze-thaw prediction, comprising: Step 1: Collect basic field data for winter wheat; Step 2: Establish a soil freeze-thaw hydrothermal coupling model based on the aforementioned basic data; Step 3: Enter candidate winter irrigation quotas; Step 4: Based on the aforementioned soil freeze-thaw hydrothermal coupling model, simulate the freeze-thaw process under different winter irrigation quotas; Step 5: Based on the simulation results, identify the soil freeze-thaw stage for each winter irrigation quota; Step 6: Calculate the evaluation index for each winter irrigation quota based on the simulation results of each winter irrigation quota and the corresponding soil freeze-thaw stage identification results; Step 7: Construct a comprehensive evaluation model and calculate the comprehensive score of each winter irrigation quota based on the evaluation indicators; Step 8: Based on the simulation results, the comprehensive score, and the constraints, perform constraint screening on each winter irrigation quota to determine the recommended winter irrigation quota.

[0007] Furthermore, step 1 includes: deploying soil temperature sensors, soil moisture sensors, meteorological data acquisition devices, and irrigation flow monitoring devices in the winter wheat field to collect: soil temperature at different soil layers; soil moisture content at different soil layers; soil bulk density; saturated moisture content; residual moisture content; soil thermal conductivity; soil specific heat capacity; soil permeability; daily average air temperature, maximum air temperature, and minimum air temperature; snowfall or snow cover thickness; winter irrigation date; and target soil moisture data during the greening period.

[0008] Furthermore, step 2 includes: Based on Fourier's law, considering the two-dimensional hydrothermal coupling effect, and taking the latent heat of phase change as an internal heat source, the governing equation of the frozen soil temperature field is derived. Based on the movement law of unsaturated thawed soil moisture, a water-ice phase transition term is added to establish the control equation of frozen soil moisture field; based on the hindering effect of ice crystals on the flow of liquid water, the calculation expression of frozen soil moisture diffusivity is derived. With solid-liquid ratio As a coupling term, establish a connection equation; By combining the control equations for the frozen soil temperature field, the control equations for the frozen soil moisture field, and the relationship equations, a soil freeze-thaw hydrothermal coupling model incorporating both temperature and moisture fields is established.

[0009] Furthermore, the governing equation for the frozen soil temperature field is: ; In the formula, Soil density; C is the density of ice; C is the heat capacity. Thermal conductivity; Latent heat of phase transition; For temperature; For time; volumetric water content ,in This refers to the volumetric content of frozen water. The density of water, This indicates the volumetric water content of unfrozen water; The governing equation for the moisture field of the frozen soil is: ; The formula for calculating the water diffusivity of frozen soil is as follows: ; In the formula, This indicates the water content by volume of ice; Indicates the density of ice; Soil permeability (m / s); Water volume (1 / m); It is the impedance factor; The connection equation is: ; In the formula, This refers to the freezing temperature of the soil. The solid-liquid ratio correlation coefficient; The soil freeze-thaw hydrothermal coupling model is expressed as follows: .

[0010] Furthermore, the simulation of the freeze-thaw process under different winter irrigation quotas includes: establishing soil profile calculation units and assigning corresponding soil physical parameters to each unit; setting initial soil conditions, meteorological conditions, and boundary conditions; and calculating the temperature field, moisture field, and soil volume ice content of each unit based on the soil freeze-thaw hydrothermal coupling model.

[0011] Furthermore, the soil freeze-thaw stage includes: Irrigation to the beginning of freezing stage: The stage from the completion of winter irrigation until the soil temperature first falls below the freezing threshold; Continuous freezing stage: The stage in which a stable frozen layer forms in the soil profile and the volumetric ice content is maintained; The melting process from the beginning to the end: the soil temperature rises, the volumetric ice content decreases, until the frozen layer disappears.

[0012] Furthermore, the evaluation indicators include: freezing start delay time, stable freezing duration, thawing time, uniformity of volumetric ice content distribution, risk of shallow ice enrichment, degree of deep water enrichment, coefficient of variation of soil temperature energy distribution, and stability of temperature information transmission.

[0013] Furthermore, the comprehensive evaluation model is as follows: ; in, For the overall score, To stabilize the score of the frozen layer; Scoring for deep water enrichment; Score for thermal stability; Scoring is given for the uniformity of ice content; Points will be deducted for shallow ice-rich areas; Points will be deducted for excessively long melting period; Points will be deducted for irrigation water consumption.

[0014] Furthermore, step 8 includes: sorting the candidate winter irrigation quotas from high to low according to the comprehensive score, and conducting a constraint screening based on factors such as the duration of stable freezing, the degree of deep water enrichment, the risk of shallow ice enrichment, the duration of melting, and the soil moisture requirements during the greening period, and determining the candidate winter irrigation quota that meets the constraints and has the highest comprehensive score as the recommended winter irrigation quota.

[0015] As can be seen from the above technical solution, compared with the prior art, the present invention provides a method for quota control of winter irrigation for winter wheat based on freeze-thaw prediction, which has the following beneficial effects: (1) It can automatically recommend winter irrigation water volume based on soil moisture, temperature and meteorological conditions, and realize dynamic optimization of winter irrigation quota. (2) By promoting the enrichment of deep water, it provides a more stable water base for winter wheat greening and improves the stability of soil moisture during the spring greening period. (3) By evaluating the distribution of ice content, it avoids excessive winter irrigation leading to shallow ice enrichment and reduces the risk of shallow ice enrichment and frost heave. (4) Under the premise of meeting the requirements of stable freezing and greening soil moisture, it reduces unnecessary winter irrigation water volume and improves water use efficiency. (5) It can be connected to soil sensors, weather stations, solenoid valves, water pumps and drip irrigation systems to realize automated control and is suitable for intelligent irrigation system applications. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the intelligent control method for winter irrigation quotas provided by the present invention.

[0018] Figure 2 This is a schematic diagram of the layout of the farmland soil monitoring and irrigation control device provided by the present invention.

[0019] Figure 3 This is a schematic diagram illustrating the soil freeze-thaw stage and the identification of freezing front migration provided by the present invention.

[0020] Figure 4 This is a schematic diagram illustrating the evaluation of soil ice content profile distribution under different winter irrigation quotas provided by the present invention.

[0021] Figure 5 This is a schematic diagram of the comprehensive evaluation model for winter irrigation quotas provided by the present invention.

[0022] Figure 6 This is a schematic diagram of the winter irrigation quota decision output and irrigation execution control provided by the present invention. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only 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.

[0024] This invention discloses a method for quota control of winter irrigation for winter wheat based on freeze-thaw prediction, such as... Figure 1 As shown, it includes: Step 1: Collect basic field data for winter wheat; Step 2: Establish a soil freeze-thaw hydrothermal coupling model based on basic data; Step 3: Input candidate winter irrigation quotas; specifically, the system sets multiple candidate winter irrigation quotas, including: 0mm; 45mm; 90mm; 135mm; or multiple candidate values ​​within the range of 30-150mm according to the local irrigation system; Step 4: Simulate the freeze-thaw process under different winter irrigation quotas based on the soil freeze-thaw hydrothermal coupling model; Step 5: Based on the simulation results, identify the soil freeze-thaw stage for each winter irrigation quota; Step 6: Calculate the evaluation index for each winter irrigation quota based on the simulation results of each winter irrigation quota and the corresponding soil freeze-thaw stage identification results; Step 7: Construct a comprehensive evaluation model and calculate the comprehensive score of each winter irrigation quota based on the evaluation indicators; Step 8: Based on the simulation results, comprehensive scores, and constraints, conduct constraint screening on each winter irrigation quota to determine the recommended winter irrigation quota.

[0025] In one specific embodiment, step 1 includes: deploying soil temperature sensors, soil moisture sensors, meteorological data acquisition devices, and irrigation flow monitoring devices in a winter wheat field to collect: soil temperature at different soil layers; soil moisture content at different soil layers; soil bulk density; saturated moisture content; residual moisture content; soil thermal conductivity; soil specific heat capacity; soil permeability coefficient; daily average air temperature, maximum air temperature, and minimum air temperature; snowfall or snow cover thickness; winter irrigation date; and target soil moisture data during the greening period. The different soil layers include 10cm, 25cm, 40cm, and 60cm soil layers.

[0026] In one specific embodiment, step 2 includes: Based on Fourier's law, considering the two-dimensional hydrothermal coupling effect, and taking the latent heat of phase change as an internal heat source, the governing equation of the frozen soil temperature field is derived. Based on the movement law of unsaturated thawed soil moisture, a water-ice phase transition term is added to establish the governing equation of frozen soil moisture field (Richards equation); based on the hindering effect of ice crystals on the flow of liquid water, the calculation expression of frozen soil moisture diffusivity is derived. With solid-liquid ratio As a coupling term, a correlation equation is established; the frozen soil hydrothermal coupling model needs to correlate three variables—temperature, pore ice, and unfrozen water—through the correlation equation, using the solid-liquid ratio. As a coupling term, it essentially describes the temperature-dependent characteristics of unfrozen water and can optimize the calculation of the ice-to-water volume ratio. By combining the governing equations of the frozen soil temperature field, the governing equations of the frozen soil moisture field, and the correlation equations, a soil freeze-thaw hydrothermal coupling model including the temperature field and the moisture field is established. Among them, the temperature field model is used to describe the soil heat conduction and the release or absorption of latent heat of water-ice phase change, while the moisture field model is used to describe soil moisture migration, unsaturated moisture movement, moisture redistribution at the freezing front, and the hindering effect of ice crystals on liquid water migration. The relationship between soil temperature, unfrozen water content, and volumetric ice content is established through the solid-liquid ratio function.

[0027] In a specific embodiment, the governing equation for the frozen soil temperature field is: ; In the formula, Soil density (kg / cm³) 3 ); The density of ice (kg / cm³) 3 C represents heat capacity [J / (kg·℃)]; Thermal conductivity [W / (m·℃)]; The value of the latent heat of phase change is 334.56 (kJ / kg). Temperature (°C); Time (s); Volumetric water content (kg / m 3 ),in The volume percentage of frozen water is %. The density of water (kg / m³) 3 ), This indicates the volumetric water content of unfrozen water; The governing equation for the water field of frozen soil is: ; The formula for calculating the water diffusivity of frozen soil is: ; In the formula, This indicates the water content by volume of ice; Indicates the density of ice; Soil permeability (m / s); Water volume (1 / m); The impedance factor describes the effect of ice in soil on water migration; The relationship equation is: ; In the formula, The freezing temperature of the soil (°C); The solid-liquid ratio correlation coefficient is a constant that varies with soil type and salt content, typically 0.56. The soil freeze-thaw hydrothermal coupling model is represented as follows: .

[0028] In a specific embodiment, the freeze-thaw process under different winter irrigation quotas is simulated, including: establishing soil profile calculation units and assigning corresponding soil physical parameters to each unit, including soil bulk density, saturated water content, residual water content, thermal conductivity, specific heat capacity, permeability coefficient, and freezing characteristic parameters; setting initial soil conditions and meteorological conditions, as well as boundary conditions; and calculating the temperature field, moisture field, and soil volumetric ice content of each unit based on a soil freeze-thaw hydrothermal coupling model, and determining soil temperature changes, soil moisture content changes, soil volumetric ice content changes, freezing front location, thawing front location, stable frozen layer thickness, deep water-rich areas, and shallow ice-rich areas. Specifically: 1. Establish soil profile calculation unit A vertical one-dimensional soil profile model was established using winter wheat root zone soil as the computational object. The soil profile can be set to a depth range of 0 to 60 cm or 0 to 100 cm, and divided into multiple computational layers according to preset intervals. For example, the soil profile can be divided into soil layers of 0 to 10 cm, 10 to 25 cm, 25 to 40 cm, and 40 to 60 cm, or discretized according to fixed spatial step sizes of 1 cm, 5 cm, and 10 cm. Each computational layer is assigned corresponding soil physical parameters, including soil bulk density, saturated water content, residual water content, thermal conductivity, specific heat capacity, permeability coefficient, and freezing characteristic parameters.

[0029] 2. Set initial and boundary conditions

[0030] For each candidate winter irrigation quota, the same initial soil and meteorological conditions are set.

[0031] Initial conditions include: initial soil temperature distribution; initial soil moisture content distribution; initial unfrozen water content; initial volumetric ice content; and initial groundwater or deep water boundary conditions. Initial soil temperature and moisture content can be obtained from field measurements using sensors; when no measured values ​​are available for some soil layers, linear interpolation or stratified assignment methods can be used to determine these values.

[0032] Boundary conditions include: soil surface temperature boundary; soil surface water flux boundary; soil bottom heat flux boundary; and soil bottom water flux boundary. The soil surface temperature boundary can be determined by the daily average air temperature, maximum air temperature, minimum air temperature, snow cover thickness, and surface heat transfer coefficient. The soil surface water flux boundary is jointly determined by candidate winter irrigation quotas, precipitation, evaporation, and surface infiltration capacity. For candidate winter irrigation quotas, they are converted into infiltration volume per unit area. For example, candidate winter irrigation quotas of 45mm, 90mm, or 135mm are used as the irrigation infiltration flux inputs for the upper boundary of the model, respectively.

[0033] 3. Establish a method for calculating soil temperature field

[0034] Soil temperature variations at different times and depths are calculated using the soil temperature field governing equation. The following processes are considered in the soil temperature field calculation: the difference in heat capacity between soil water and ice; the variation in soil thermal conductivity under different water contents; the release or absorption of latent heat during the water-ice phase transition; the transfer of soil temperature from changes in surface air temperature; and the influence of snow cover or surface cover on heat exchange.

[0035] The changes in the soil temperature field can be described in the following form: Soil effective heat capacity × temperature change rate = soil heat conduction term + water ice phase change latent heat term; Among them, the latent heat of water-ice phase change is used to reflect the heat released or absorbed when soil water changes from liquid to ice or from ice to liquid.

[0036] The system calculates the temperature value of each soil layer at each time step, forming a two-dimensional data matrix of soil temperature variation with time and depth: T(z, t); where T represents soil temperature, z represents soil depth, and t represents time.

[0037] 4. Establish a method for calculating soil moisture field

[0038] The water migration process in different soil layers was calculated using the governing equations of the frozen soil moisture field. The following processes were considered in the calculation of the soil moisture field: infiltration of winter irrigation water into the topsoil; downward migration of liquid water in unsaturated soil; redistribution of water near the freezing front; migration of liquid water into the frozen zone during freezing; the hindering effect of ice crystal formation on the movement of liquid water; and the re-conversion of ice water into liquid water during thawing.

[0039] The system calculates the liquid water content of each soil layer at each time step and combines this with the ice content to calculate the total soil moisture content. The total soil moisture content can be expressed as: Total moisture content = Liquid water content + Ice water equivalent moisture content; Through the above calculations, the system obtains the data matrix of soil moisture content changes with time and depth under different candidate winter irrigation quotas: θ(z,t); where θ represents the soil volumetric water content.

[0040] 5. Calculate the volumetric ice content of the soil.

[0041] The system calculates the volumetric ice content based on the relationship between soil temperature and unfrozen water content. When the temperature of a soil layer is higher than or equal to the preset freezing temperature, the soil layer is considered unfrozen, and its volumetric ice content is 0. When the temperature of a soil layer is lower than the preset freezing temperature, the system calculates the amount of water remaining in liquid state at that temperature based on the unfrozen water content function, and then subtracts the unfrozen water content from the total water content to obtain the volumetric ice content. That is: Volumetric ice content = Total soil moisture content - Unfrozen water content; The unfrozen water content can be determined based on the soil freezing characteristic curve. The lower the temperature, the lower the unfrozen water content and the greater the volumetric ice content. The system thus obtains a data matrix of volumetric ice content varying with time and depth: Ice(z,t); where Ice represents the soil volumetric ice content.

[0042] Furthermore, based on the soil temperature field, soil moisture field, and soil volumetric ice content, the location of the freezing front, the location of the melting front, the thickness of the stable frozen layer, the deep water-rich area, and the shallow ice-rich area are determined.

[0043] In one specific embodiment, the soil freeze-thaw stage includes: Irrigation to the beginning of freezing stage: The stage from the completion of winter irrigation until the soil temperature first falls below the freezing threshold; Continuous freezing stage: The stage in which a stable frozen layer forms in the soil profile and the volumetric ice content remains at a high level; The melting process from the beginning to the end: the soil temperature rises, the volumetric ice content decreases, until the frozen layer basically disappears.

[0044] In one specific embodiment, the evaluation indicators include: freezing initiation delay time, stable freezing duration, thawing time, uniformity of volumetric ice content distribution, risk of shallow ice enrichment, degree of deep water enrichment, coefficient of variation of soil temperature energy distribution, and stability of temperature information transmission. Specifically: For each candidate winter irrigation quota Q k The system outputs soil temperature based on a hydrothermal coupling model. T i (t) Soil moisture content Ice content by volume I i (t) Calculate the evaluation indicators. Among them, i Indicates the first i Each soil layer t Indicates a time step. T f The soil freezing temperature threshold.I 0 The threshold for ice content, t 0 This refers to the completion time of winter irrigation.

[0045] 1. Freeze startup delay time

[0046] The freezing start time refers to the time when the soil first enters a frozen state after winter irrigation. When a certain soil layer meets the following conditions: T i (t) < T f and At that time, the system determined that the soil layer had begun to freeze. Candidate winter irrigation quota. Q k The startup time is: The freeze startup delay time is: ;in, This represents the time elapsed from the completion of winter irrigation to the start of soil freezing. The relative delay time can also be calculated for comparisons with the non-irrigated treatment or the baseline treatment. ;in, This refers to the quota for winter irrigation that is not carried out in winter or the quota for conventional winter irrigation in the local area.

[0047] 2. Duration of stable freezing

[0048] The system determines whether each soil layer is frozen at each time step. A soil layer is considered frozen when it simultaneously satisfies the following conditions: T i (t) < T f and When this time, it is recorded as a frozen state. Let... Candidate winter irrigation quota The frozen thickness at a certain time step. When the frozen thickness is greater than the preset minimum frozen thickness. If the frozen state persists for more than a preset number of days, a stable frozen layer is considered to have formed. The stable freezing time is: ;in: In the formula, To stabilize the duration of freezing, For time step, This is a preset stable freezing thickness threshold.

[0049] 3. Melting time

[0050] When a certain soil layer simultaneously satisfies: T i (t) < T m and When the time is reached, it is recorded as the molten state. T m This is the threshold for the melting temperature, typically taken as 0 degrees Celsius or determined based on actual measurements. Candidate winter irrigation quotas. The melting time is: ;in, The melting time begins. This is the melting end time.

[0051] 4. Uniformity of ice content distribution by volume

[0052] Uniformity of volumetric ice content distribution is used to determine whether the ice content in different soil layers is excessively concentrated. At a certain time step... t Calculate the average volumetric ice content of each soil layer: ; Calculate the standard deviation of ice content in the physical examination: Volumetric ice content variation coefficient: ;in, To avoid setting extremely low values ​​where the denominator is 0. Candidate winter irrigation quotas. The uniformity of ice content distribution under the following conditions is expressed as: ;in ; The closer it is to 1, the more uniform the distribution of volumetric ice content in the soil profile; The smaller the value, the more likely there is a problem of localized ice abundance or excessive vertical differences in ice content.

[0053] 5. Risk of shallow, ice-rich layers

[0054] The shallow ice-rich risk is used to determine whether there is excessively high ice content in the 0-20cm or 0-30cm shallow soil layer. Let the shallow soil aggregate be S, the middle and lower soil aggregate be M, and the average volumetric ice content of the shallow layer be: When satisfied and At that time step, the system determined that there was a risk of shallow ice enrichment. This is the risk threshold for shallow ice. This is the threshold value for the difference in ice content between the shallow and middle-lower layers.

[0055] The shallow ice-rich layer risk index is expressed as: ;in, ; ; The time step for the occurrence of shallow ice-rich risk. This represents the total number of time steps during the freeze period; These are the weighting coefficients. The larger the value, the higher the risk of shallow, ice-rich layers.

[0056] 6. Degree of deep water accumulation

[0057] The degree of deep soil water accumulation is used to evaluate whether winter irrigation effectively replenishes the middle and lower root zone soil. Let the deep soil accumulation be... For example, the soil layer of 20-60cm or 40-60cm. The average moisture content of the deep soil layer before winter irrigation is: The average moisture content at depth during the greening period or at the end of thawing is: ;in, This refers to the end of the greening or melting period. Deep water accumulation: .

[0058] 7. Coefficient of variation of soil temperature and energy distribution

[0059] The coefficient of variation of soil temperature energy distribution is used to evaluate whether the energy fluctuations in different soil layers are balanced, reflecting the stability of the soil thermal environment. The coefficient of variation can be calculated first. i Energy fluctuation of temperature in a soil layer during the freeze-thaw period: ;in ; Then calculate the average value of the temperature energy of all soil layers: ; Finally, the coefficient of variation of temperature energy distribution was determined to be: ; in, The smaller the value, the more balanced the energy distribution of temperature fluctuations in different soil layers, and the more stable the soil thermal environment. The larger the value, the greater the difference in heat distribution across the soil profile, which may indicate problems such as drastic cooling of the surface layer or unstable heat transfer in the deeper layers.

[0060] 8. Stability of temperature information transmission

[0061] Temperature information transmission stability is used to evaluate whether the transmission of temperature changes from the upper soil layer to the lower soil layer is continuous and stable. The system can calculate this using the lag correlation coefficient of temperature time series from adjacent soil layers. For adjacent soil layers... and Calculate its different lag times The correlation coefficient below: ; The maximum correlation coefficient is taken as the temperature transfer correlation between adjacent soil layers: = ; The corresponding lag time is: ; Candidate winter irrigation quota The average temperature transfer correlation is as follows: ; The coefficient of variation of the lag time is: ;in, ; The stability index of temperature information transmission can be expressed as: ;in, This represents the lag time stability weighting coefficient. The larger the value, the stronger the correlation between temperature changes in adjacent soil layers, the more stable the transmission time, and the more stable the transmission of soil temperature information. The smaller the value, the less stable the downward temperature transfer process becomes.

[0062] In a specific embodiment, the comprehensive evaluation model is as follows: ; in, For the overall score, To stabilize the frozen layer score, 20 points; 20 points for deep water enrichment; Score for thermal stability: 15 points; Scoring is given for uniformity of ice content, 15 points; Deduct 10 points for shallow, ice-rich layer risk; Deduct 10 points for excessively long melting period; Points will be deducted for irrigation water usage, 10 points. Details: The formula for calculating the score of the stable frozen layer is: ; The formula for calculating the deep water enrichment score is: ; The formula for calculating the thermal stability score is: ; The formula for calculating the ice content uniformity score is: ; The formula for calculating the risk deduction for shallow ice-rich layers is as follows: ; The formula for calculating the penalty for excessively long melting period is: ; The formula for calculating the deduction of points for irrigation water consumption is as follows: ; In the formula, To stabilize the duration of freezing, The duration of the target stable freeze; This refers to the amount of deep water accumulation. The target is the amount of deep water enrichment; The coefficient of variation of soil temperature and energy distribution. The maximum allowable coefficient of variation of energy at temperature; The coefficient of variation of volumetric ice content distribution. The maximum allowable coefficient of variation for ice content; This is a shallow ice-rich risk index. The risk threshold for shallow ice-rich layers; For the duration of melting, To allow for the duration of melting, To allow for exceeding the melting time limit; and These are the minimum and maximum values ​​among the candidate winter irrigation quotas, respectively.

[0063] The system calculates the comprehensive score for each candidate winter irrigation quota, sorts them from highest to lowest comprehensive score, and determines the candidate winter irrigation quota with the highest comprehensive score as the recommended winter irrigation quota: The above parameters can be calibrated or adjusted according to different soil types, winter wheat varieties, historical freeze-thaw observation data, and target soil moisture during the greening period in different regions.

[0064] In a specific embodiment, step 8 includes: after the system completes the freeze-thaw process simulation and comprehensive evaluation of each candidate winter irrigation quota, the candidate winter irrigation quotas are sorted from high to low according to the comprehensive score, and the system performs constraint screening based on factors such as the duration of stable freezing, the degree of deep water enrichment, the risk of shallow ice enrichment, the duration of thawing, and the soil moisture requirements during the greening period. The candidate winter irrigation quota that meets the constraints and has the highest comprehensive score is determined as the recommended winter irrigation quota.

[0065] The system further combines candidate winter irrigation quotas with candidate irrigation times to simulate the soil freeze-thaw process under different combinations, and determines the recommended irrigation time based on the comprehensive score and risk constraints. Based on the simulation results corresponding to the recommended winter irrigation quotas and recommended irrigation times, the system outputs the estimated start time of freezing, the estimated duration of stable freezing, the estimated end time of thawing, and the location of maximum ice content.

[0066] The system determines the existence of shallow layer ice enrichment risk based on the average volumetric ice content in the shallow layer, the difference in ice content between the shallow and middle-lower layers, and the duration of ice enrichment. Based on the comparison between the average root zone water content during the greening-up period and the target soil moisture range, it outputs a soil moisture assessment for the spring greening-up period. When the shallow layer ice enrichment risk is high, the melting period is too long, or the soil moisture during the greening-up period is too high, the system outputs a suggestion to reduce winter irrigation water. When the stable freezing period is insufficient, deep layer water enrichment is insufficient, or the soil moisture during the greening-up period is too low, the system outputs a suggestion to increase winter irrigation water.

[0067] Through the above steps, the system can generate a complete winter irrigation control plan, including recommended winter irrigation quotas, recommended irrigation times, freeze-thaw process prediction results, shallow ice-rich risk levels, soil moisture assessment during the spring greening period, and water volume adjustment suggestions.

[0068] In one specific embodiment, the invention will be further described with reference to the accompanying drawings.

[0069] This invention first acquires soil temperature, soil moisture content, and meteorological data for different soil layers in a winter wheat field through a data acquisition module. Soil temperature sensors and soil moisture sensors are deployed at soil layers of 10cm, 25cm, 40cm, and 60cm, respectively, and the acquired data is transmitted to the controller via a data acquisition unit.

[0070] The controller receives data from the data acquisition module, soil parameter input module, and meteorological data input module, and inputs it into the hydrothermal coupling simulation module. The hydrothermal coupling simulation module calculates the changes in soil temperature, water content, and volumetric ice content under different winter irrigation quotas based on the soil heat conduction process, water migration process, and water-ice phase change process.

[0071] like Figure 2 As shown, drip irrigation tapes or irrigation pipelines are laid in the field, and the irrigation water volume is controlled by solenoid valves and water pumps. The system can automatically simulate the soil freeze-thaw process after irrigation based on different candidate winter irrigation quotas.

[0072] like Figure 3 As shown, the freeze-thaw stage identification module divides the soil freeze-thaw process into three stages based on changes in soil temperature and ice content: the irrigation to initial freezing stage, the continuous freezing stage, and the thawing stage. It also identifies the locations of the freezing front, thawing front, and stable frozen layer.

[0073] like Figure 4 As shown, the ice content risk assessment module analyzes the distribution of soil ice content profiles under different winter irrigation quotas. When the system identifies an excessively thick shallow ice-rich risk zone or an excessively large vertical gradient in ice content, a risk deduction is applied to that winter irrigation quota. When the system identifies a relatively stable deep water-rich zone and a low shallow ice-rich risk, the evaluation score of that winter irrigation quota is increased.

[0074] like Figure 5 As shown, the comprehensive evaluation module comprehensively evaluates the freezing start time, stable freezing duration, thawing duration, ice content uniformity, deep water enrichment, soil thermal stability, and irrigation water consumption, and obtains the comprehensive score of different candidate winter irrigation quotas.

[0075] like Figure 6 As shown, the irrigation decision output module outputs a recommended winter irrigation quota based on the comprehensive evaluation results and sends control commands to the irrigation execution module, which then completes the winter irrigation operation using solenoid valves and water pumps.

[0076] The system set four candidate winter irrigation quotas: 0mm, 45mm, 90mm, and 135mm. Simulation results showed that under the 0mm winter irrigation condition, the freezing process was weak, and deep water replenishment was insufficient; under the 45mm winter irrigation condition, a certain frozen layer was formed, but the ice content was unevenly distributed; under the 90mm winter irrigation condition, a relatively stable frozen layer was formed, and water enrichment in the middle and lower layers was promoted; under the 135mm winter irrigation condition, although the ice content increased, the shallow layer was significantly rich in ice, the melting period was prolonged, and water use efficiency decreased. The system ultimately recommended 90mm as the preferred winter irrigation quota under these conditions.

[0077] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0078] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for quota regulation of winter irrigation for winter wheat based on freeze-thaw prediction, characterized in that, include: Step 1: Collect basic field data for winter wheat; Step 2: Establish a soil freeze-thaw hydrothermal coupling model based on the aforementioned basic data; Step 3: Enter candidate winter irrigation quotas; Step 4: Based on the aforementioned soil freeze-thaw hydrothermal coupling model, simulate the freeze-thaw process under different winter irrigation quotas; Step 5: Based on the simulation results, identify the soil freeze-thaw stage for each winter irrigation quota; Step 6: Calculate the evaluation index for each winter irrigation quota based on the simulation results of each winter irrigation quota and the corresponding soil freeze-thaw stage identification results; Step 7: Construct a comprehensive evaluation model and calculate the comprehensive score of each winter irrigation quota based on the evaluation indicators; Step 8: Based on the simulation results, the comprehensive score, and the constraints, perform constraint screening on each winter irrigation quota to determine the recommended winter irrigation quota.

2. The method for quota regulation of winter irrigation for winter wheat based on freeze-thaw prediction according to claim 1, characterized in that, Step 1 includes: deploying soil temperature sensors, soil moisture sensors, meteorological data acquisition devices, and irrigation flow monitoring devices in winter wheat fields to collect: soil temperature at different soil layers; soil moisture content at different soil layers; soil bulk density; saturated moisture content; residual moisture content; soil thermal conductivity; soil specific heat capacity; soil permeability coefficient; daily average air temperature, maximum air temperature, and minimum air temperature; snowfall or snow cover thickness; winter irrigation date; and target soil moisture data during the greening period.

3. The method for quota regulation of winter irrigation for winter wheat based on freeze-thaw prediction according to claim 1, characterized in that, Step 2 includes: Based on Fourier's law, considering the two-dimensional hydrothermal coupling effect, and taking the latent heat of phase change as an internal heat source, the governing equation of the frozen soil temperature field is derived. Based on the movement law of unsaturated thawed soil moisture, a water-ice phase transition term is added to establish the control equation of frozen soil moisture field; based on the hindering effect of ice crystals on the flow of liquid water, the calculation expression of frozen soil moisture diffusivity is derived. With solid-liquid ratio As a coupling term, establish a connection equation; By combining the control equations for the frozen soil temperature field, the control equations for the frozen soil moisture field, and the relationship equations, a soil freeze-thaw hydrothermal coupling model incorporating both temperature and moisture fields is established.

4. The method for quota regulation of winter irrigation for winter wheat based on freeze-thaw prediction according to claim 3, characterized in that, The governing equation for the frozen soil temperature field is: ； In the formula, Soil density; C is the density of ice; C is the heat capacity. Thermal conductivity; Latent heat of phase transition; For temperature; For time; volumetric water content ,in This refers to the volumetric content of frozen water. The density of water, This indicates the volumetric water content of unfrozen water; The governing equation for the moisture field of the frozen soil is: ； The formula for calculating the water diffusivity of frozen soil is as follows: ； In the formula, This indicates the water content by volume of ice; Indicates the density of ice; Soil permeability; Water capacity; It is the impedance factor; The connection equation is: ； In the formula, This refers to the freezing temperature of the soil. The solid-liquid ratio correlation coefficient; The soil freeze-thaw hydrothermal coupling model is expressed as follows: 。 5. The method for quota regulation of winter irrigation for winter wheat based on freeze-thaw prediction according to claim 1, characterized in that, The simulation of the freeze-thaw process under different winter irrigation quotas includes: establishing soil profile calculation units and assigning corresponding soil physical parameters to each unit; setting initial soil conditions, meteorological conditions, and boundary conditions; and calculating the temperature field, moisture field, and soil volume ice content of each unit based on the soil freeze-thaw hydrothermal coupling model.

6. The method for quota regulation of winter irrigation for winter wheat based on freeze-thaw prediction according to claim 1, characterized in that, The soil freeze-thaw phase includes: Irrigation to the beginning of freezing stage: The stage from the completion of winter irrigation until the soil temperature first falls below the freezing threshold; Continuous freezing stage: The stage in which a stable frozen layer forms in the soil profile and the volumetric ice content is maintained; The melting process from the beginning to the end: the soil temperature rises, the volumetric ice content decreases, until the frozen layer disappears.

7. The method for quota regulation of winter irrigation for winter wheat based on freeze-thaw prediction according to claim 1, characterized in that, The evaluation indicators include: freezing start delay time, stable freezing duration, thawing time, uniformity of volumetric ice content distribution, risk of shallow ice enrichment, degree of deep water enrichment, coefficient of variation of soil temperature energy distribution, and stability of temperature information transmission.

8. The method for quota regulation of winter irrigation for winter wheat based on freeze-thaw prediction according to claim 1, characterized in that, The comprehensive evaluation model is as follows: ； in, For the overall score, To stabilize the score of the frozen layer; Scoring for deep water enrichment; Score for thermal stability; Scoring is given for the uniformity of ice content; Points will be deducted for shallow ice-rich areas; Points will be deducted for excessively long melting period; Points will be deducted for irrigation water consumption.

9. The method for quota regulation of winter irrigation for winter wheat based on freeze-thaw prediction according to claim 1, characterized in that, Step 8 includes: sorting the candidate winter irrigation quotas from high to low according to the comprehensive score, and conducting a constraint screening based on factors such as the duration of stable freezing, the degree of deep water enrichment, the risk of shallow ice enrichment, the duration of melting, and the soil moisture requirements during the greening period, and determining the candidate winter irrigation quota with the highest comprehensive score that meets the constraints as the recommended winter irrigation quota.

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