Water and fertilizer integrated irrigation control system and control method

Abstract

The application relates to the field of agricultural irrigation technology, in particular to a water and fertilizer integrated irrigation control system and a control method, which specifically comprises the following steps: calculating a water and nutrient loss factor according to test field irrigation data, and fitting a mapping relationship between soil initial root layer water and nutrient data and corresponding loss factors, so as to help ordinary cultivated fields to quickly obtain corresponding loss factors according to root layer water and nutrients during use, and to adaptively adjust water and nutrient irrigation amounts; in view of the problem that individual areas do not reach the requirements after preliminary irrigation of ordinary cultivated fields, corresponding loss factors are adjusted according to post-irrigation data, and then the irrigation amount is adjusted for supplementary irrigation; the problem that the traditional integrated irrigation lacks consideration of the fact that part of water and nutrients will be lost before reaching the root layer, leading to the fact that the water and nutrient amounts of the crop root layer may still be lower than the required amount after the irrigation is completed, is avoided, and the irrigation precision of crops is improved.

Description

Technical Field

[0001] This application relates to the field of agricultural irrigation technology, specifically to an integrated water and fertilizer irrigation control system and control method. Background Technology

[0002] Integrated water and fertilizer irrigation technology combines soil conditions and crop needs, providing liquid fertilizer and irrigation water to crops in a controlled and proportional manner through a controlled pipeline network. In recent years, severe wind and sandstorms and low rainfall have led to soil drought in the black soil region of Northeast China. The lack of water and nutrients seriously affects the growth of crops planted in this region. Therefore, it is necessary to use integrated water and fertilizer irrigation technology to provide precise irrigation for crops planted in this region based on their water and nutrient requirements.

[0003] However, traditional integrated water and fertilizer irrigation mainly sets uniform irrigation parameters in advance based on soil and crop conditions. It cannot provide precise irrigation based on soil conditions in different windy and sandy areas and the water and nutrient requirements of crop roots. The irrigation control methods are relatively simple, mainly generating irrigation strategies based on the water and nutrient requirements of crops. However, the in-situ monitoring of soil water and nutrients in the root zone of crops in windy and sandy black soil areas is insufficient. It is possible that the water and nutrient content in the root zone after irrigation is lower than the actual irrigation amount due to soil infiltration loss in windy and sandy black soil areas. For example, in windy and sandy black soil areas, the soil is dry, and some of the water and nutrients irrigated have been lost before reaching the root zone, resulting in insufficient water and nutrient supply to crops and affecting the irrigation effect. Summary of the Invention

[0004] To address the aforementioned technical problems, the purpose of this application is to provide an integrated water and fertilizer irrigation control system and method, the specific technical solution of which is as follows:

[0005] In a first aspect, embodiments of this application provide a method for integrated water and fertilizer irrigation control, the method comprising the following steps:

[0006] Time-series data of nutrient composition in the topsoil and root zone at various locations in the fertigation experimental field were collected. The nutrient composition data included water data and nutrient data.

[0007] For each nutrient component data, when irrigating the experimental field with a preset irrigation amount, based on the similarity between the changes in nutrient component data of the soil surface layer and root layer at each location during the irrigation process, and the difference in nutrient component data of the soil surface layer and root layer at each location when the irrigation is completed, a nutrient loss factor for each location in the experimental field is constructed. Combined with the nutrient component data of the root layer at each location in the experimental field before irrigation, a curve is fitted to obtain the fitting equation.

[0008] When performing preliminary irrigation on cultivated land, the nutrient composition data of each location in the cultivated land before preliminary irrigation is used as the input of the fitting equation. The preset demand for crop nutrients at each location in the cultivated land is adjusted based on the loss factor of the output nutrient composition. The cultivated land is then irrigated using the adjusted demand. The location for supplementary irrigation in the cultivated land is determined based on the nutrient composition data of the root layer at each location at the end of the preliminary irrigation.

[0009] Based on the differences in nutrient composition data between the soil surface layer and root layer at each re-irrigation location during the initial irrigation of cultivated land, the output nutrient loss factor is adjusted to obtain the re-irrigation loss factor for each re-irrigation location. Combined with the nutrient composition data of the root layer at the end of the initial irrigation, re-irrigation is carried out at each re-irrigation location.

[0010] In one embodiment, the process for obtaining the nutrient loss factors at various locations in the experimental field is as follows:

[0011] During the irrigation of the experimental field, the cumulative increase in nutrient content in the soil surface layer and root layer at each location at each time point was obtained to construct the nutrient content increase sequence of the soil surface layer and root layer at each location; the similarity between the nutrient content increase sequences of the soil surface layer and root layer at each location was calculated.

[0012] The rate of nutrient degradation in the root layer during irrigation at each location of the experimental field was determined based on the cumulative increase in nutrient content in the soil surface and root layer at the time of irrigation completion.

[0013] The loss factor at each location of the experimental field is determined based on the similarity and the decay rate. The loss factor is positively correlated with the decay rate and negatively correlated with the similarity.

[0014] In one embodiment, the attenuation rate is obtained as follows:

[0015] The difference between the cumulative rise of the soil surface layer and the root layer at each location when irrigation is completed is calculated, and the difference is divided by the cumulative rise of the root layer at each location when irrigation is completed to obtain the attenuation rate.

[0016] In one embodiment, the fitting equation is the equation of a fitted curve obtained by fitting the nutrient composition data of the root layer before irrigation as the independent variable and the loss factor as the dependent variable through a curve fitting algorithm.

[0017] In one embodiment, the loss factor based on the output nutrient composition adjusts the preset nutrient requirements of crops at various locations in the cultivated field, specifically as follows:

[0018] The adjusted nutrient requirements of crops at each location in the cultivated field are proportional to the loss factor of the nutrient components output by the crops at each location in the cultivated field and the preset nutrient requirements.

[0019] In one embodiment, determining the location for supplemental irrigation in the cultivated field based on nutrient composition data of the root layer at each location at the end of the initial irrigation specifically involves:

[0020] If the nutrient content data of the root layer at the end of the initial irrigation in a certain location of the cultivated field is less than the adjusted requirement, then that location will be designated as a supplementary irrigation location.

[0021] In one embodiment, the process of obtaining the supplementary irrigation loss factor is as follows:

[0022] The fitting curves of nutrient composition data during the initial irrigation process of the soil surface and root layer at each location are obtained by using a power function fitting algorithm, and are denoted as time-composition curves. The slope changes of the time-composition curves of the soil surface and root layer at each location are calculated to determine the boundary points between the early and late stages of the irrigation process at each location, thus obtaining the late stage of irrigation at each location. Based on the correlation of changes in nutrient composition data of the soil surface and root layer at each supplementary irrigation location and the differences in data change trends, combined with the output nutrient loss factors, the supplementary irrigation loss factors at each supplementary irrigation location are determined.

[0023] In one embodiment, the process of obtaining the supplementary irrigation loss factor is as follows:

[0024] The fitting lines of nutrient composition data of the soil surface layer and root layer at each irrigation location in the later stage of irrigation are obtained by using a linear fitting algorithm; the slope difference of the fitting lines of the soil surface layer and root layer at each irrigation location is calculated.

[0025] Sliding windows are set on each fitted line, and the difference between the last value and the first value in each window is recorded as the change in each window. The correlation between the sequence of the changes in all windows on the fitted lines of the soil surface and root layer at each irrigation location is calculated by the correlation algorithm.

[0026] The expression for the supplemental irrigation loss factor is: In the formula, This represents the re-irrigation loss factor at the j-th re-irrigation location; The loss factor of the output nutrients at the j-th irrigation location; The relevance of the j-th irrigation location is indicated; The slope difference at the j-th irrigation location is represented by the slope difference. Represents a predefined, extremely small positive number; This represents the hyperbolic tangent function.

[0027] In one embodiment, the step of combining the nutrient composition data of the root layer at the end of the initial irrigation with the supplementary irrigation data for each location specifically involves:

[0028] Calculate the difference between the adjusted nutrient demand at each irrigation location and the nutrient composition data of the root layer at the end of the initial irrigation, and record it as the first difference; the amount of nutrient supplementation at each irrigation location is proportional to the irrigation loss factor and the first difference; use the amount of supplementation to irrigate each irrigation location.

[0029] Secondly, embodiments of this application also provide an integrated water and fertilizer irrigation control system, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the steps of any of the methods described above.

[0030] The embodiments of this application have at least the following beneficial effects:

[0031] This application utilizes soil moisture and nutrient monitoring information from the topsoil and root zone in a field to assist in decision-making regarding irrigation adjustments. This avoids the problem in traditional integrated irrigation systems where some water and nutrients are lost before reaching the root zone, potentially resulting in root zone water and nutrient levels remaining below requirements after irrigation. This application first conducts irrigation experiments in a test field. Based on the similarity between changes in soil moisture and nutrient data in the topsoil and root zone during the experimental irrigation period, and the rate of water and nutrient decay in the root zone after initial irrigation, water and nutrient loss factors are calculated. A mapping relationship is then fitted between initial root zone water and nutrient data and the corresponding water and nutrient loss factors to assist general... When used in cultivated fields, the corresponding water and nutrient loss factors are quickly obtained based on the water and nutrient content of the root zone to adaptively adjust the water and nutrient irrigation amount. Addressing the issue that soil water and nutrient levels in the root zone of some areas still do not meet requirements after initial irrigation in ordinary cultivated fields, the time-water curves of surface and root zone water data from the initial irrigation are further fitted. The boundary time points before and after the initial irrigation are determined based on the difference in curve slope, and the original water and nutrient loss factors are adjusted using later irrigation data, thereby adjusting the supplementary irrigation amount. This takes into account the differences in water and nutrient losses between the early and later stages of initial irrigation, and adjustments are made using later irrigation data to avoid a large discrepancy between the required and actual supplementary irrigation amounts, thus improving the accuracy of supplementary irrigation. Attached Figure Description

[0032] To more clearly illustrate the technical solutions and advantages in the embodiments of this application 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 some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0033] Figure 1 A flowchart illustrating the steps of an integrated water and fertilizer irrigation control method provided in one embodiment of this application;

[0034] Figure 2 This is a schematic diagram illustrating the process of obtaining the loss factor. Detailed Implementation

[0035] To further illustrate the technical means and effects adopted by this application to achieve the intended purpose of the invention, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a water and fertilizer integrated irrigation control system and method proposed in this application. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0036] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains.

[0037] The following description, in conjunction with the accompanying drawings, details the specific scheme of the integrated water and fertilizer irrigation control system and control method provided in this application.

[0038] Please see Figure 1 The diagram illustrates a flowchart of a water and fertilizer integrated irrigation control method according to an embodiment of this application. The method includes the following steps:

[0039] Step S1: Collect time-series data of nutrient composition data of the soil surface layer and root layer at various locations in the integrated water and fertilizer irrigation experimental field. The nutrient composition data includes water data and nutrient data.

[0040] In this embodiment, a shallow-buried drip irrigation method was used to irrigate an experimental field in a wind-blown black soil region. Various monitoring locations were set up in the experimental field, with significant differences in moisture and nutrient content at each location. At each monitoring location, a humidity sensor and an ion-selective electrode were buried 3 cm below the drip inlet in the soil to collect moisture and nutrient data from the soil surface. At the same time, a humidity sensor and an ion-selective electrode were buried at the root zone depth to collect moisture and nutrient data from the root zone. In this embodiment, the crop was maize, so the root zone depth was set to 30 cm. Adjacent monitoring locations were spaced 2 meters apart, and the data collection frequency for both moisture and nutrients was set to once per minute.

[0041] Both moisture and nutrient data are used as nutritional component data.

[0042] In other embodiments of this application, the implementer may set the soil surface depth and root layer depth according to the actual crops growing in the field, and may set the data collection frequency and monitoring location according to the actual situation.

[0043] Simultaneously, high-definition cameras installed around the experimental field capture images of the maize crop. These images are used as input to a pre-trained crop growth stage detection model to identify the growth stage of the crop in the images, and the output is the growth stage of the maize in the experimental field. In this embodiment, the crop growth stage detection model uses the ST-YOLOv8s model. Implementers may also use other models, such as the YOLOv11 model, to train the crop growth stage detection model; this application does not impose any special restrictions. The ST-YOLOv8s model, the YOLOv11 model, and the model training process are all well-known, and the specific process will not be elaborated further. Furthermore, the nutrient requirements corresponding to each growth stage of the maize in the experimental field are obtained from the China Agricultural and Rural Information Network, where the water requirement is recorded as water demand and the nutrient requirement is recorded as fertilizer application rate.

[0044] Step S2: For each nutrient component data, when irrigating the experimental field with a preset irrigation amount, based on the similarity between the changes in nutrient component data of the soil surface layer and root layer at each location during the irrigation process, and the difference in nutrient component data of the soil surface layer and root layer at each location when irrigation is completed, a nutrient component loss factor for each location in the experimental field is constructed. Combined with the nutrient component data of the root layer at each location in the experimental field before irrigation, a curve fitting is performed to obtain the fitting equation.

[0045] In the windy, sandy, and black soil regions of Northeast China, the soil is typically quite dry, leading to significant water and nutrient loss during irrigation. After irrigation based on the needs of corn crops, the surface soil may contain sufficient water and nutrients for corn growth, but the root zone may not meet these requirements. Since corn roots are the primary site for absorbing water and nutrients, insufficient water and nutrient content in the root zone directly impacts corn growth. To address this, it is necessary to analyze the characteristics of water and nutrient loss based on monitoring data of the corn root zone and supplement irrigation in areas with insufficient water and nutrients.

[0046] Taking irrigation in an experimental field as an example, the required water volume is used to irrigate various locations within the field. During irrigation, the surface soil moisture gradually rises and eventually reaches the required level. However, the root zone moisture is affected by soil infiltration losses, causing the rise to deviate from the surface rise. The greater the deviation, the more severe the loss. Any monitoring location in the experimental field is taken as the current monitoring location. Taking the current monitoring location as an example, since there are slight differences in soil moisture at different depths—that is, the initial surface soil moisture content differs from the initial root zone moisture content at the start of irrigation—the cumulative rise in surface soil moisture at each moment during irrigation at the current monitoring location is obtained. This cumulative rise is the difference between the surface soil moisture data at the current monitoring location at that moment and the surface soil moisture data at the current monitoring location at the moment before irrigation began. Similarly, the cumulative rise in root zone moisture is obtained at each moment during the current irrigation period. The cumulative rise in moisture then represents the relationship between surface soil moisture and root zone moisture. Theoretically, since the irrigation amount is the same at the same location, the cumulative increase in water content in the soil surface and root zone should be consistent. However, in reality, due to infiltration losses, the increase in water content differs between the two, resulting in a lower water content in the root zone compared to the surface zone after irrigation. Therefore, time series sequences of the cumulative increase in soil surface water and root zone water content at the current monitoring location during irrigation are obtained separately and denoted as the soil surface water increase sequence and root zone water increase sequence, respectively. The similarity between these two water increase sequences is then calculated. In this embodiment, the similarity is specifically the Pearson correlation coefficient between the water increase sequences. Since there is a positive correlation between the soil surface and root zone water increase sequences during irrigation, the Pearson correlation coefficient ranges from 0 to 1. The lower the similarity, the more severe the water loss.

[0047] It should be noted that there are many existing similarity algorithms for calculating the similarity between moisture-increasing sequences, and implementers may also use other similarity algorithms, such as cosine similarity, to calculate the similarity between moisture-increasing sequences. This application does not impose any specific restrictions.

[0048] Furthermore, the cumulative increase in soil surface and root zone moisture at the current monitoring location upon completion of irrigation is obtained, and the moisture decay rate of the root zone during irrigation at the current monitoring location is calculated, expressed as: In the formula, A represents the water attenuation rate of the root zone during irrigation at the current monitoring location; a and b represent the cumulative increase in water content of the soil surface and root zone at the end of irrigation at the current monitoring location, respectively. The higher the attenuation rate, the greater the water loss during this irrigation at the current monitoring location.

[0049] Based on the above analysis, a water loss factor is calculated at the current monitoring location upon completion of irrigation, used to characterize the degree of water loss at the current monitoring location after irrigation in the experimental field. Preferably, in this embodiment, the expression for the water loss factor is:

[0050]

[0051] In the formula, A represents the water loss factor at the current monitoring location; C represents the water decay rate at the current monitoring location; and C represents the similarity between the water rise sequences in the soil surface and root zone during irrigation at the current monitoring location. This represents a preset, extremely small positive number, used to avoid a denominator of 0. Its value range is 0.001-0.01. In this embodiment... The value is 0.005.

[0052] The larger the value of A, the greater the difference between the cumulative increase in water content in the soil surface layer and the root zone at the end of the initial irrigation, indicating a more severe water loss. The larger the value of C, the greater the difference in the water rise sequence between the soil surface and root zone during irrigation, and the more severe the water loss. The larger.

[0053] Furthermore, to analyze the relationship between soil dryness before irrigation and water loss factor in the aeolian black soil region, root layer moisture data at each monitoring location in the experimental field was obtained at the moment before irrigation began, denoted as initial root layer moisture. The initial root layer moisture and water loss factor at each monitoring location in the experimental field were combined to form a moisture data pair. Using all moisture data pairs from all monitoring locations in the experimental field as input, a least squares fitting algorithm was used for curve fitting, and the relationship equation of the fitted curve was output, denoted as the fitting equation. The least squares fitting algorithm is a well-known technique, and its specific implementation will not be described in detail.

[0054] It should be noted that this application provides only one fitting method for curve fitting of moisture data pairs. There are many existing fitting methods, and implementers may also use other fitting algorithms to perform curve fitting of moisture data pairs. This application does not impose any specific restrictions.

[0055] Step S3: When performing preliminary irrigation on the cultivated field, the nutrient composition data of each location in the cultivated field before preliminary irrigation is used as the input of the fitting equation. The preset demand for crop nutrients at each location in the cultivated field is adjusted based on the loss factor of the output nutrient composition. The cultivated field is then irrigated with the adjusted demand. The location for supplementary irrigation in the cultivated field is determined based on the nutrient composition data of the root layer at each location at the end of the preliminary irrigation.

[0056] Moisture sensors and ion-selective electrodes were embedded in the soil surface and root zone at various locations within a conventionally cultivated field to collect moisture and nutrient data at these locations. Simultaneously, before initial irrigation of the conventionally cultivated field, images of the maize crop at each location were used to determine its corresponding growth stage, and the water and fertilizer requirements for this stage were obtained as the initial water and fertilizer requirements for each location.

[0057] Furthermore, the water requirement for irrigation of ordinary cultivated land is appropriately adjusted based on the soil moisture content. Specifically, just before the initial irrigation of the ordinary cultivated land, the root layer moisture data at various locations within the land are acquired and used as input to the fitting equation for the aforementioned moisture data pair. The output water loss factor is recorded as the predicted water loss factor. The initial water requirement is adjusted based on the predicted water loss factor at each location within the ordinary cultivated land, as expressed by:

[0058]

[0059] In the formula, Let represent the adjusted water requirement at the i-th position in a conventionally cultivated field, denoted as the initial irrigation water requirement; This represents the initial water requirement at the i-th position in a typical cultivated field; This represents the predicted water loss factor at the i-th location in a conventionally cultivated field. The initial irrigation water requirement at each location is then used to perform initial irrigation at each location in the conventionally cultivated field.

[0060] Furthermore, since the loss factor is obtained through curve fitting, it inevitably deviates from the actual loss situation in complex real-world application scenarios. This can lead to situations where, even after initial irrigation according to the adjusted irrigation parameters, the actual water requirements of the crop may still not be met. In such cases, timely supplementary irrigation is necessary for areas with insufficient water. Specifically, in determining the supplementary irrigation location in ordinary cultivated fields, in this embodiment, the location where the water content at the end of the initial root zone irrigation is less than the corresponding initial water requirement is designated as the supplementary irrigation location.

[0061] Based on all nutrient data collected from various locations in the experimental field and the ordinary cultivated field, the initial irrigation fertilization amount for each location in the ordinary cultivated field was obtained using the same acquisition method as the initial irrigation water requirement.

[0062] Step S4: Based on the difference between the changes in nutrient composition data of the soil surface layer and root layer at each re-irrigation location during the initial irrigation of the cultivated field, the output nutrient loss factor is adjusted to obtain the re-irrigation loss factor for each re-irrigation location. Combined with the nutrient composition data of the root layer at the end of the initial irrigation, re-irrigation is carried out at each re-irrigation location.

[0063] When setting the amount of supplemental irrigation based on the amount of water loss, it is not possible to simply adjust the amount of supplemental irrigation based on the loss factor fitted to the current root zone water, because the loss factor fitted above is based on the full-time irrigation data. However, during supplemental irrigation, since the soil moisture has already been replenished to a certain extent and it is close to the time of the initial irrigation, the soil moisture loss pattern during supplemental irrigation is closer to the pattern in the later stage of the initial irrigation. Therefore, it is necessary to adjust the loss factor during supplemental irrigation.

[0064] Specifically, time-series data of soil surface and root zone moisture were acquired during the initial irrigation. Power function fitting was used to fit the moisture data of the soil surface and root zone at various locations during the initial irrigation of ordinary cultivated land, respectively denoted as the soil surface time-moisture curve and the root zone time-moisture curve. In the early stage of initial irrigation, soil moisture content is low, but increases rapidly as irrigation progresses. In the later stage, as soil moisture gradually becomes saturated, the cumulative increase in moisture slows down and becomes more uniform. First, the slope of each point on the two time-moisture curves at each location is calculated. In this embodiment, the first derivative method is used to calculate the slope of each point on the time-moisture curve. However, other slope calculation methods can be used, and this application does not impose specific limitations. Then, the slope of each point on each time-moisture curve is used as input to the maximum inter-class variance algorithm to obtain a slope threshold. Slopes greater than or equal to the slope threshold are considered to have large slope variations, belonging to the early stage of initial irrigation; slopes less than the slope threshold are considered to have stable slopes, belonging to the later stage of initial irrigation. The earliest point in the time-water curves of the soil surface and root zone with a slope less than the corresponding slope threshold was used as the boundary point. To ensure consistent data length for soil surface and root zone moisture time series data in the later stages of initial irrigation, the later boundary point in the two time-water curves at each location was selected as the pre- and post-initial irrigation time point for that location. Power function fitting, the first derivative method, and the maximum inter-class variance algorithm are all well-known techniques, and their specific processes are not detailed here.

[0065] It should be noted that this application provides only one threshold segmentation algorithm for slope threshold. There are many existing threshold segmentation algorithms, and implementers may also use other threshold segmentation algorithms to calculate the slope threshold. This application does not impose any specific restrictions.

[0066] Furthermore, since the changes in root zone moisture data during supplementary irrigation are similar to those in the later stages of the initial irrigation (with a gradual and uniform increase in accumulated moisture), but differ significantly from the overall root zone moisture data changes during the entire initial irrigation process, the water loss in the later irrigation stages is relatively smaller compared to the overall water loss during the initial irrigation process. Therefore, when adjusting the water demand for supplementary irrigation using a water loss factor, the water loss factor used should be appropriately reduced.

[0067] First, linear fitting was performed on the soil surface moisture data and root layer moisture data at each location during the later stages of initial irrigation, resulting in fitted lines for soil surface moisture and root layer moisture at each location. The absolute value of the difference between the slopes of these two fitted lines at each location was calculated and denoted as the slope difference. The more consistent the slopes of the lines, the less the amount of water loss during the later stages of irrigation, and the more the water loss factor should be reduced.

[0068] Furthermore, sliding windows with a window length of 3 and a sliding step size of 1 are set in the time series of soil surface and root zone moisture data in the later stage of initial irrigation. The moisture change in the window is calculated, and the moisture change is equal to the difference between the last value and the first value in the window. The sequence of moisture changes in all sliding windows in the time series of soil surface moisture data at each location is arranged in chronological order and is denoted as the first sequence. The sequence of moisture changes in all sliding windows in the time series of root zone moisture data at each location is arranged in chronological order and is denoted as the second sequence. The correlation between the first sequence and the second sequence is calculated and denoted as the first correlation. In this embodiment, the first correlation is the Pearson correlation coefficient between the first sequence and the second sequence. In other embodiments of this application, the implementer may also use other correlation algorithms to calculate the correlation between the first sequence and the second sequence. The larger the first correlation, the closer the moisture changes in the root zone and soil surface in the later stage of initial irrigation are, the less water loss, and the more the water loss factor should be reduced.

[0069] Based on the above analysis, the re-irrigation loss factor for each re-irrigation location is calculated to characterize the degree of water loss at that location during re-irrigation. The expression is as follows:

[0070]

[0071] In the formula, This represents the re-irrigation loss factor at the j-th re-irrigation location; This represents the predicted loss factor corresponding to the initial irrigation at the j-th supplementary irrigation location; This indicates the first correlation at the j-th re-irrigation location during the later stage of initial irrigation; This represents the absolute value of the difference between the slopes of the straight lines in the surface layer and the root layer during the initial irrigation period at the j-th re-irrigation location; This represents a preset, extremely small positive number, used to avoid a denominator of 0. Its value range is 0.001-0.01. In this embodiment... The value is 0.005; This represents the hyperbolic tangent function.

[0072] use This indicates the consistency of the slopes of the lines. The smaller the absolute difference in the slopes, the higher the consistency of the slopes. Higher consistency of the slopes indicates a greater correlation. (This is related to the re-irrigation loss factor.) The smaller the value, the less water loss occurs at that location during rehydration; the higher the correlation, the better. The larger the value, the closer the changes in moisture between the root layer and the surface layer are in the later stages of initial irrigation, and the less water loss there is. The smaller the value, the lower the re-irrigation loss factor. The smaller.

[0073] Based on all nutrient data collected from various locations in the experimental field and the ordinary cultivated field, the nutrient loss factors during initial irrigation of the ordinary cultivated field and the nutrient loss factors during supplementary irrigation of the locations requiring supplementary irrigation were obtained using the same acquisition methods as those used for predicting water loss factors and supplementary irrigation loss factors.

[0074] Furthermore, taking supplemental irrigation as an example, the difference between the initial irrigation water requirement at each supplemental irrigation location and the root zone water data at the end of the initial irrigation is calculated and denoted as the first difference; the first difference and the supplemental irrigation loss factor are substituted into the formula. In the middle, the first difference is substituted into The supplementary irrigation loss factor is substituted into The calculated result is used as the water replenishment amount for that replenishment location, and the water replenishment amount is input into the controller of the irrigation system to replenish the location. When the water replenishment amount is reached, the water and fertilizer valve is closed.

[0075] When supplementing nutrient irrigation, based on the initial fertilization amount at each required nutrient irrigation location, the nutrient data of the root layer at the end of the initial nutrient irrigation, and the corresponding nutrient replenishment loss factor, the nutrient replenishment amount for that location is obtained using the same method as the water replenishment amount. This amount is then input into the irrigation system controller, and nutrient replenishment is performed at that location. When the required nutrient replenishment amount is reached, the water and fertilizer valves are closed. This completes an integrated water and fertilizer irrigation control system.

[0076] A schematic diagram of the process for obtaining the loss factor is shown below. Figure 2 As shown.

[0077] Based on the same inventive concept as the above method, this application embodiment also provides an integrated water and fertilizer irrigation control system, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any one of the above-described integrated water and fertilizer irrigation control methods.

[0078] In summary, this application provides a water and fertilizer integrated irrigation control method. By acquiring soil moisture and nutrient monitoring information from the soil surface layer and crop root layer in the field, it assists in decision-making to adjust the irrigation amount. This avoids the problem in traditional integrated irrigation where the lack of consideration for the partial loss of irrigation water and nutrients before reaching the root layer leads to the possibility that the water and nutrient levels in the crop root layer may still be lower than the required levels after irrigation. This application first conducts an irrigation experiment in a test field. Based on the similarity between the changes in water and nutrient data of the soil surface layer and root layer during the experimental irrigation period, and the attenuation rate of water and nutrient in the root layer after the initial irrigation, water and nutrient loss factors are calculated respectively. The initial soil root layer water and nutrient data are then fitted with the corresponding water and nutrient loss factors. The mapping relationship between the components helps ordinary farmland quickly obtain the corresponding water and nutrient loss factors based on the root zone water and nutrient levels, so as to adaptively adjust the water and nutrient irrigation amount. Addressing the issue that the root zone soil water and nutrient levels in some areas of ordinary farmland still do not meet requirements after initial irrigation, the time-water curves of the surface soil and root zone water data from the initial irrigation are further fitted. The boundary time points before and after the initial irrigation are determined based on the difference in curve slope, and the original water and nutrient loss factors are adjusted using later irrigation data, thereby adjusting the supplementary irrigation amount. This takes into account the differences in water and nutrient losses between the early and late stages of initial irrigation, and adjusts using later irrigation data to avoid a large discrepancy between the required supplementary irrigation amount and the actual supplementary irrigation amount, thus improving the accuracy of supplementary irrigation.

[0079] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this application. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0080] The various embodiments in this application are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

[0081] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.

Claims

1. A method for integrated water and fertilizer irrigation control, characterized in that, The method includes the following steps: Time-series data of nutrient composition in the topsoil and root zone at various locations in the fertigation experimental field were collected. The nutrient composition data included water data and nutrient data. For each nutrient component data, when irrigating the experimental field with a preset irrigation amount, based on the similarity between the changes in nutrient component data of the soil surface layer and root layer at each location during the irrigation process, and the difference in nutrient component data of the soil surface layer and root layer at each location when the irrigation is completed, a nutrient loss factor for each location in the experimental field is constructed. Combined with the nutrient component data of the root layer at each location in the experimental field before irrigation, a curve is fitted to obtain the fitting equation. When performing preliminary irrigation on cultivated land, the nutrient composition data of each location in the cultivated land before preliminary irrigation is used as the input of the fitting equation. The preset demand for crop nutrients at each location in the cultivated land is adjusted based on the loss factor of the output nutrient composition. The cultivated land is then irrigated using the adjusted demand. The location for supplementary irrigation in the cultivated land is determined based on the nutrient composition data of the root layer at each location at the end of the preliminary irrigation. Based on the differences in nutrient composition data between the soil surface layer and root layer at each re-irrigation location during the initial irrigation of cultivated land, the output nutrient loss factor is adjusted to obtain the re-irrigation loss factor for each re-irrigation location. Combined with the nutrient composition data of the root layer at the end of the initial irrigation, re-irrigation is carried out at each re-irrigation location.

2. The water and fertilizer integrated irrigation control method as described in claim 1, characterized in that, The process for obtaining the nutrient loss factors at various locations in the experimental field is as follows: During the irrigation of the experimental field, the cumulative increase in nutrient content in the soil surface layer and root layer at each location at each time point was obtained to construct the nutrient content increase sequence of the soil surface layer and root layer at each location; the similarity between the nutrient content increase sequences of the soil surface layer and root layer at each location was calculated. The rate of nutrient degradation in the root layer during irrigation at each location of the experimental field was determined based on the cumulative increase in nutrient content in the soil surface and root layer at the time of irrigation completion. The loss factor at each location of the experimental field is determined based on the similarity and the decay rate. The loss factor is positively correlated with the decay rate and negatively correlated with the similarity.

3. The water and fertilizer integrated irrigation control method as described in claim 2, characterized in that, The process of obtaining the attenuation rate is as follows: The difference between the cumulative rise of the soil surface layer and the root layer at each location when irrigation is completed is calculated, and the difference is divided by the cumulative rise of the root layer at each location when irrigation is completed to obtain the attenuation rate.

4. The water and fertilizer integrated irrigation control method as described in claim 1, characterized in that, The fitting equation is the equation of the fitted curve obtained by fitting the nutrient composition data of the root layer before irrigation as the independent variable and the loss factor as the dependent variable through a curve fitting algorithm.

5. The water and fertilizer integrated irrigation control method as described in claim 1, characterized in that, The loss factor based on the output nutrient composition adjusts the preset nutrient requirements of crops at various locations in the cultivated field, specifically as follows: The adjusted nutrient requirements of crops at each location in the cultivated field are proportional to the loss factor of the nutrient components output by the crops at each location in the cultivated field and the preset nutrient requirements.

6. The water and fertilizer integrated irrigation control method as described in claim 1, characterized in that, The determination of supplementary irrigation locations in cultivated fields based on root layer nutrient composition data at various locations at the end of initial irrigation is as follows: If the nutrient content data of the root layer at the end of the initial irrigation in a certain location of the cultivated field is less than the adjusted requirement, then that location will be designated as a supplementary irrigation location.

7. The water and fertilizer integrated irrigation control method as described in claim 1, characterized in that, The process for obtaining the supplementary irrigation loss factor is as follows: The fitting curves of nutrient composition data during the initial irrigation process of the soil surface and root layer at each location are obtained by using a power function fitting algorithm, and are denoted as time-composition curves. The slope changes of the time-composition curves of the soil surface and root layer at each location are calculated to determine the boundary points between the early and late stages of the irrigation process at each location, thus obtaining the late stage of irrigation at each location. Based on the correlation of changes in nutrient composition data of the soil surface and root layer at each supplementary irrigation location and the differences in data change trends, combined with the output nutrient loss factors, the supplementary irrigation loss factors at each supplementary irrigation location are determined.

8. The water and fertilizer integrated irrigation control method as described in claim 7, characterized in that, The process for obtaining the supplementary irrigation loss factor is as follows: The fitting lines of nutrient composition data of the soil surface layer and root layer at each irrigation location in the later stage of irrigation are obtained by using a linear fitting algorithm; the slope difference of the fitting lines of the soil surface layer and root layer at each irrigation location is calculated. Sliding windows are set on each fitted line, and the difference between the last value and the first value in each window is recorded as the change in each window. The correlation between the sequence of the changes in all windows on the fitted lines of the soil surface and root layer at each irrigation location is calculated by the correlation algorithm. The expression for the supplemental irrigation loss factor is: In the formula, This represents the re-irrigation loss factor at the j-th re-irrigation location; The loss factor of the output nutrients at the j-th irrigation location; The relevance of the j-th irrigation location is indicated; The slope difference at the j-th irrigation location is represented by the slope difference. Represents a predefined, extremely small positive number; This represents the hyperbolic tangent function.

9. The water and fertilizer integrated irrigation control method as described in claim 1, characterized in that, The process involves combining the nutrient composition data of the root layer at the end of the initial irrigation with the supplementary irrigation data for each location, specifically as follows: Calculate the difference between the adjusted nutrient demand at each irrigation location and the nutrient composition data of the root layer at the end of the initial irrigation, and record it as the first difference; the amount of nutrient supplementation at each irrigation location is proportional to the irrigation loss factor and the first difference; use the amount of supplementation to irrigate each irrigation location.

10. A water and fertilizer integrated irrigation control system, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1-9.

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