Water conservancy irrigation data collection method and system

Abstract

The application relates to the field of agricultural irrigation technology, in particular to a water conservancy facility irrigation data collection method and system. The method comprises the following steps: calibrating and storing a reference state of a target plot when soil moisture is sufficient and salt content is lower than a first preset value, wherein the reference state comprises a reference soil moisture content parameter and a reference soil conductivity parameter; comparing the real-time soil moisture content parameter and the real-time soil conductivity parameter with the reference soil moisture content parameter and the reference soil conductivity parameter in the reference state to determine whether physiological drought caused by salt accumulation exists in crops of the target plot, and generating a determination result; by comparing the real-time soil moisture content and conductivity of the crop root zone with the baseline reference state, whether the stress of the crops is caused by physiological drought caused by salt accumulation can be accurately determined, so that the irrigation water volume is prevented from being incorrectly increased when physiological drought occurs.

Description

Technical Field

[0001] This invention relates to the field of agricultural irrigation technology, and in particular to a method and system for collecting irrigation data for water conservancy facilities. Background Technology

[0002] Existing agricultural irrigation systems typically rely on water metering and evapotranspiration-based water demand calculations to formulate and execute irrigation plans. This method works effectively under conditions of stable water source quality and uniform soil properties. However, in certain specific environments, such as when irrigation water salinity fluctuates significantly and the irrigated soil exhibits significant salt accumulation characteristics, this water metering-based irrigation decision-making system reveals significant technical shortcomings. Specifically, when the salinity of irrigation water increases, if the soil in the irrigated area (especially heavy loam with high clay content) has poor permeability, salt will accumulate in the crop root zone. With continuous irrigation, the osmotic pressure of the root zone soil solution will increase significantly. At this point, even if the soil's physical moisture content is sufficient, the crop roots will struggle to absorb water normally, resulting in physiological drought.

[0003] Existing field soil moisture sensors typically measure soil physical water content based on the dielectric constant principle, failing to directly reflect the impact of soil solution osmotic pressure or salinity on crop water absorption capacity. Furthermore, while crop growth monitoring (such as analyzing vegetation indices from drone aerial images) can detect signs of water stress, existing irrigation decision-making systems lack effective means to distinguish between physical water shortage (insufficient soil physical water content) and physiological drought caused by salt accumulation. When the system receives crop stress signals, its built-in decision logic often simply interprets it as insufficient irrigation, leading to an erroneous increase in irrigation volume. This incorrect decision results in more highly saline water being applied to the already salt-accumulated root zone, further exacerbating soil salinization and causing irreversible damage to crops. Existing data acquisition systems, such as flow meters deployed at canal branch points, accurately record the amount of irrigation water executed, but this data itself cannot reveal the true cause of crop stress or prevent erroneous decisions.

[0004] To address the aforementioned issues, existing technologies urgently need improvement. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies by proposing a method and system for collecting irrigation data for water conservancy facilities.

[0006] In a first aspect, the present invention provides a method for collecting irrigation data of water conservancy facilities, the method comprising the following steps:

[0007] The reference state of the target plot when the soil moisture is sufficient and the salinity is lower than a first preset value is calibrated and stored. The reference state includes reference soil moisture content parameters and reference soil electrical conductivity parameters.

[0008] Before the scheduled irrigation operation is carried out on the target plot, real-time soil moisture content parameters and real-time soil electrical conductivity parameters of the crop root zone of the target plot are collected.

[0009] The real-time soil moisture content parameters and the real-time soil electrical conductivity parameters are compared with the reference soil moisture content parameters and the reference soil electrical conductivity parameters in the reference state to determine whether the crops in the target plot are experiencing physiological drought caused by salt accumulation, and a determination result is generated.

[0010] If the determination result indicates the presence of physiological drought, an irrigation control command is generated to suspend irrigation operations on the target plot.

[0011] The core innovation of this application lies in the fact that by comparing the real-time soil moisture content and real-time soil electrical conductivity parameters in the crop root zone with the calibrated and stored reference state, it can accurately determine whether the water stress exhibited by the crop is due to physical water shortage or physiological drought caused by salt accumulation, thereby avoiding the execution of incorrect irrigation operations due to misjudgment and exacerbating salt damage.

[0012] Secondly, a water conservancy facility irrigation data acquisition system is provided, the system comprising:

[0013] The reference state storage module is used to calibrate and store the reference state of the target plot when the soil moisture is sufficient and the salinity is lower than a first preset value. The reference state includes a reference soil moisture content parameter and a reference soil electrical conductivity parameter.

[0014] The real-time data acquisition module is used to collect real-time soil moisture content parameters and real-time soil electrical conductivity parameters of the crop root zone of the target plot before the scheduled irrigation operation is performed on the target plot.

[0015] The discrimination module is used to compare the real-time soil moisture content parameters and the real-time soil electrical conductivity parameters with the reference soil moisture content parameters and the reference soil electrical conductivity parameters in the reference state, so as to determine whether the crops in the target plot have physiological drought caused by salt accumulation, and generate discrimination results.

[0016] The instruction generation module is used to generate an irrigation control instruction to stop irrigation operations on the target plot if the discrimination result indicates the existence of physiological drought.

[0017] Compared with the prior art, the present invention has the following beneficial effects:

[0018] By comparing the real-time soil moisture content and electrical conductivity in the crop root zone with the baseline reference state, it is possible to accurately determine whether crop stress is physiological drought caused by salt accumulation. This avoids erroneously increasing irrigation water during physiological drought, and has the advantages of accurately determining whether crop stress is caused by salt accumulation, avoiding erroneous irrigation that exacerbates salt damage, and protecting crops. Attached Figure Description

[0019] Figure 1 This is a flowchart of the method of the present invention.

[0020] Figure 2 This is a schematic diagram of the system structure of the present invention.

[0021] In the diagram: 201, Reference state storage module; 202, Real-time data acquisition module; 203, Judgment module; 204, Instruction generation module. Detailed Implementation

[0022] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0023] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0024] Traditional irrigation data collection systems are unable to identify the true causes of crop stress when irrigation water salinity fluctuates significantly and irrigated soils have salt accumulation characteristics. This leads to irrigation responses that exacerbate salt damage. This affects the accuracy of irrigation decisions, potentially hindering crop growth or even causing death, thus reducing agricultural productivity.

[0025] For example, suppose a coastal agricultural area experiences periodic increases in salinity due to seawater intrusion affecting irrigation. This area grows salt-sensitive crops in heavy loam soils where salt easily accumulates. Existing irrigation systems calculate water demand based on evapotranspiration models and use canal flow data as the primary data source for scheduling. When high-salinity irrigation water enters the heavy loam area, salt accumulates in the crop root zone, causing physiological drought symptoms. At this time, soil moisture sensors show sufficient physical soil moisture, while crop growth monitoring indicates water stress. The existing system interprets this contradictory information as physical water shortage and increases irrigation. This decision leads to more high-salinity water entering the soil, exacerbating salt accumulation and damaging crops.

[0026] If the aforementioned problems are not addressed, existing irrigation decision-making systems will continue to misjudge the causes of crop stress under conditions of fluctuating water salinity and soil salt accumulation. This will lead the system to increase irrigation when crops suffer from physiological drought, instead of taking measures such as salt drainage or using low-salinity water sources. This response will accelerate salt accumulation in the root zone, damaging crops, affecting crop yield and quality, and even leading to reduced yields or crop failure, causing economic losses to agricultural production.

[0027] Therefore, this application is as follows Figure 1 The method for collecting irrigation data for water conservancy facilities, as shown, includes the following steps:

[0028] S101. Calibrate and store the reference state of the target plot when the soil moisture is sufficient and the salinity is lower than the first preset value. The reference state includes the reference soil moisture content parameter and the reference soil electrical conductivity parameter.

[0029] S102. Before the scheduled irrigation operation is carried out on the target plot, collect the real-time soil moisture content parameters and real-time soil electrical conductivity parameters of the crop root zone of the target plot.

[0030] S103. Compare the real-time soil moisture content parameters and real-time soil electrical conductivity parameters with the reference soil moisture content parameters and reference soil electrical conductivity parameters in the reference state to determine whether the crops in the target plot are experiencing physiological drought caused by salt accumulation, and generate the determination result.

[0031] S104. If the judgment result indicates that there is physiological drought, an irrigation control command is generated to stop the irrigation operation on the target plot.

[0032] Among them, the reference state refers to the soil environmental baseline of the target plot when soil moisture is sufficient and salt content is lower than the first preset value. It can be achieved by calibration and storage before the start of the crop growing season or after soil improvement, for example, by measuring and recording with sensors. It is mainly to provide a reference for soil parameters under healthy, non-stress conditions. The reference soil moisture content parameter refers to the soil volumetric or mass moisture content value calibrated under the reference state. It can be obtained by measuring with dielectric constant sensors or resistance sensors. It is mainly used to characterize the sufficiency of soil physical moisture. The reference soil conductivity parameter refers to the soil solution conductivity or soil conductivity value calibrated under the reference state. It can be obtained by measuring with conductivity sensors. It is mainly used to characterize the mineralization or salt content of the soil solution. The real-time soil moisture content parameter refers to the current soil moisture content value of the crop root zone of the target plot collected before the scheduled irrigation operation. It can be obtained using the same sensors and methods as when calibrating the reference state. It is mainly used to reflect the current physical moisture status of the crop root zone. Soil electrical conductivity parameters refer to the current soil electrical conductivity values ​​collected in the crop root zone of the target plot before the scheduled irrigation operation. These parameters can be acquired using the same sensors and methods as those used for calibrating the reference state, and are mainly used to reflect the current salinity status of the crop root zone. Comparison refers to the analysis of real-time collected soil parameters compared with stored reference state parameters. This can be achieved using methods such as numerical difference calculation, ratio calculation, or trend analysis, and is mainly used to identify the deviation between the current soil state and the healthy baseline. The discrimination result refers to the conclusion drawn from the comparative analysis regarding whether the crop experiences physiological drought caused by salt accumulation. This conclusion can be expressed using Boolean values ​​(yes / no) or classification labels (normal, physical drought, physiological drought), and is mainly used to guide subsequent irrigation decisions. Irrigation control commands are signals or commands generated when the discrimination result indicates the presence of physiological drought, used to prevent or cancel the scheduled irrigation operation. These commands can be sent to the irrigation execution system in the form of electrical signals, network messages, or control codes, and are mainly used to prevent further exacerbation of salt damage under high salinity conditions.

[0033] The proposed solution establishes a baseline of soil parameters for the target plot under healthy conditions, known as a reference state. This reference state includes reference soil moisture content and reference soil electrical conductivity parameters, providing a basis for subsequent assessments. Before irrigation, the system collects real-time soil moisture content and electrical conductivity parameters from the crop root zone to obtain the current environmental data. These real-time parameters are then compared with the pre-stored reference state parameters. This comparison considers not only physical moisture conditions but also the impact of salinity on crop water absorption. Based on the comparison results, the system can determine whether the crop is currently experiencing physiological drought—a state where physical moisture is sufficient but salinity prevents normal water absorption—and generates a corresponding assessment result. Due to this ability to identify physiological drought, when the assessment result clearly indicates physiological drought caused by salinity accumulation, the system can promptly generate a control command to halt the planned irrigation operation. This series of steps forms a complete decision-making chain, from perceiving the root zone state to judging the causes of stress, and then to adjusting irrigation behavior, effectively avoiding the erroneous operation of supplementing water under salt stress, thereby protecting crops from further salt damage.

[0034] As one embodiment of the present invention, when the determination result indicates the presence of physiological drought, the method further includes:

[0035] Apply a fluid pulse with a preset low solute concentration to the target area of ​​the crop root zone;

[0036] Within a preset time period after the application of the fluid pulse, the soil electrical conductivity parameters of the target area are monitored to obtain the response curve of the soil electrical conductivity parameters;

[0037] Based on the response curve, the rebound characteristics of soil electrical conductivity parameters after the initial decrease were determined.

[0038] Based on the rebound characteristics, identify the source of salt accumulation.

[0039] The fluid pulse with a preset low solute concentration refers to the water or solution injected into the soil whose dissolved substance concentration is lower than the current concentration of the soil solution or lower than a specific threshold. It can be implemented using pure water, deionized water, or diluted low-mineralized water. Its purpose is to temporarily reduce the conductivity of the soil solution in a localized area by introducing a low-conductivity fluid, forming a conductivity gradient and providing an initial condition for subsequent observation of salt behavior in the soil. The target area refers to the soil space where the crop roots are mainly distributed. This can be achieved by sampling or monitoring near the crop plants in areas where root activity is most active. Its purpose is to ensure that the applied fluid pulse and the monitored conductivity changes accurately reflect the root zone environment affecting crop growth. The preset time period refers to a pre-set time length from the start of the fluid pulse application to the end of monitoring. This can be achieved using a fixed time interval determined based on factors such as soil type, crop species, and ambient temperature. Its purpose is to capture the entire dynamic process of soil conductivity from its initial decrease to its rebound and eventual stabilization. The response curve of the soil conductivity parameter refers to... Within a preset time period, the continuous recording or discrete sampling data sequence of soil electrical conductivity parameters in the target area over time can be achieved by real-time data acquisition and graph plotting using continuously operating soil electrical conductivity sensors. Its purpose is to visually demonstrate the dynamic response of soil electrical conductivity to fluid pulse disturbances. The rebound characteristic refers to the characteristics exhibited by the soil electrical conductivity parameters after an initial decrease due to a low-solute-concentration fluid pulse, followed by a rebound and eventual equilibrium due to the dissolution, diffusion, and migration of salts in the soil. This can be characterized by parameters such as the rebound speed, amplitude, duration, and curve shape, reflecting the salt occurrence state, migration capacity, and interaction with the soil matrix. Identifying the source of salt accumulation involves analyzing the rebound characteristics of the soil electrical conductivity response curve to determine the main factors or pathways leading to salt accumulation. This can be achieved by comparing the measured rebound characteristics with typical rebound characteristics of known salt sources (such as irrigation water, groundwater, and soil mineral weathering) in specific soil types, providing a basis for subsequent targeted soil improvement or water management measures.

[0040] The proposed solution, upon identifying physiological drought, goes beyond simply halting irrigation; instead, it applies a fluid pulse with a preset low solute concentration to the crop root zone, creating a temporary low-conductivity environment in the target area. This low-conductivity environment allows subsequent monitoring of soil conductivity parameters to capture the dynamic process of salt redistribution and dissolution in the soil, resulting in a response curve with a specific morphology. By analyzing the rebound characteristics of conductivity after the initial decrease in this response curve—such as the speed and amplitude of the rebound—the dissolution rate, diffusion capacity, and adsorption / desorption behavior of salts in the soil can be inferred. Because salts from different sources (such as soluble salts from irrigation water, salts from groundwater upwelling, and salts released from soil mineral weathering) have different occurrence forms and physicochemical properties in the soil, their dissolution, diffusion, and interaction with the soil matrix differ after being disturbed by a low-concentration fluid pulse, thus exhibiting different rebound characteristics on the conductivity response curve. It is precisely by recognizing these differentiated rebound characteristics that the main sources of salt accumulation can be identified. This approach, which involves further diagnosing the sources of salt after identifying physiological drought, combined with the basic approach of simply stopping irrigation, allows for the immediate cessation of erroneous irrigation practices when crop damage due to salt stress is confirmed, preventing further damage. It also enables in-depth analysis of the root causes of the problem, providing data support for subsequent targeted soil improvement (such as leaching or application of soil conditioners) or adjustments to water use strategies. This leads to a fundamental solution to the salinization problem and improves the scientific rigor and effectiveness of irrigation management.

[0041] As one embodiment of the present invention, the step of determining the rebound characteristics of soil electrical conductivity parameters after an initial decrease based on the response curve includes:

[0042] Calculate the rate of change of the response curve over time to obtain a rate of change curve;

[0043] Local extrema are identified on the rate of change curve, and the response curve is divided into multiple response segments based on these local extrema.

[0044] For each response segment, its bounce characteristics are determined independently.

[0045] The calculation of the rate of change of the response curve over time involves quantifying the rate of change of electrical conductivity over time by performing differential operations or other mathematical methods on continuous data points on the response curve. Its purpose is to highlight the dynamic characteristics of the response curve for easier subsequent analysis. The rate of change curve is a new curve formed by arranging the calculated rate of change values ​​at different time points in chronological order. This curve visually reflects the slope change of the original response curve. Identifying local extrema involves finding points on the rate of change curve where the curve direction changes. These points correspond to the local maximum or minimum values ​​of the slope of the original response curve, typically indicating key turning points in the process of soil electrical conductivity change. Its purpose is to determine... The process involves identifying representative dividing points in the response curve; dividing the response curve into multiple response segments based on local extrema refers to using the time points corresponding to the identified local extrema as boundaries to divide the complete response curve into several consecutive time intervals corresponding to curve segments. The purpose is to decompose the complex overall response process into relatively simple sub-processes with different characteristics for analysis; for each response segment, independently determining its rebound characteristics means calculating or extracting parameters characterizing the conductivity recovery process of each segment, such as the rebound amplitude, rebound speed, or rebound duration. The purpose is to obtain unique rebound information for each segment, providing a basis for subsequent identification of salt sources.

[0046] This application's approach addresses the challenge of analyzing complex response curves by refining the response curves of soil electrical conductivity parameters. Specifically, it first calculates the rate of change of the response curve over time, obtaining a rate of change curve. This process amplifies the trends and inflection points in the original curve, making the dynamic characteristics related to salt migration more apparent. Furthermore, local extrema are identified on the rate of change curve. These local extrema typically correspond to inflection points or points of significant change in the rate of change in the original response curve, serving as key time markers for distinguishing different salt migration mechanisms or processes. Based on these identified local extrema, the original response curve is divided into multiple response segments. This segmentation decomposes the complex overall response process into several relatively independent sub-processes, potentially dominated by different mechanisms. Finally, for each response segment, its rebound characteristics are independently determined. By analyzing parameters such as rebound amplitude and rebound rate for each segment, information on salt behavior at different stages or under different mechanisms can be obtained. For example, rapid rebound may be related to upward salt migration, while slow rebound may be related to cation exchange. This segmented analysis allows for a more accurate capture of the diverse information contained within the response curve, overcoming the shortcomings of holistic analysis that may overlook important local features. Combined with the technique of applying fluid pulses to the crop root zone and monitoring the response curve, this approach enables the extraction of more accurate and detailed rebound characteristic information from the acquired response curve. This provides a reliable data foundation for subsequently identifying the source of salt accumulation based on rebound characteristics, improving the accuracy of salt source identification. Consequently, it enables a more accurate determination of whether crop physiological drought is caused by salt accumulation, avoiding incorrect irrigation strategies due to misjudgment, and solving the technical problem of exacerbating salt damage described in the background section.

[0047] As one embodiment of the present invention, the step of identifying the source of salt accumulation based on rebound characteristics includes:

[0048] A second fluid pulse is applied to a second target region in the crop root zone. The second fluid pulse contains chemical components for inhibiting cation exchange in the soil.

[0049] After applying the second fluid pulse, the soil electrical conductivity parameters of the second target area were monitored to obtain the second response curve;

[0050] Based on the comparison of the rebound characteristics of the first response curve and the second response curve, it is possible to distinguish whether the source of salt accumulation is dominated by upward migration of salt or by cation exchange.

[0051] The second target region refers to a selected local area within the crop root system distribution range used for applying fluid pulses and monitoring soil electrical conductivity parameters. This area can be a point or a finite volume region. The second fluid pulse refers to the liquid applied to the second target region, which differs from the aforementioned fluid pulse in its composition. Specifically, it contains chemical components designed to inhibit soil cation exchange, aiming to temporarily reduce or eliminate the adsorption and release capacity of soil colloids for cations in solution, thereby isolating the influence of cation exchange on soil electrical conductivity response. The chemical components used to inhibit soil cation exchange are substances that can bind to or compete with cation exchange sites on the surface of soil colloids, thereby reducing the soil's adsorption capacity for cations in solution. These can be achieved using high-concentration neutral salt solutions or specific organic compounds. The second response curve refers to the curve showing the change in soil electrical conductivity parameters in the second target region over time after the application of the second fluid pulse, reflecting the change in soil electrical conductivity under conditions where cation exchange is inhibited. Among them, the comparison between the rebound characteristics of the response curve and the second response curve to distinguish whether the source of salt accumulation is dominated by upward migration of salt or by cation exchange refers to comparing the rebound characteristics of the soil conductivity response curve after the initial drop under the two conditions of applying a normal fluid pulse and applying a second fluid pulse containing a component that inhibits cation exchange. This is to determine whether the main mechanism leading to salt accumulation is the upward movement of deep salt with water or the release of soluble salt ions from the soil solid phase. The purpose is to more accurately diagnose the causes of salt damage and provide a basis for taking targeted control measures.

[0052] This application improves the accuracy of identifying sources of salt accumulation by introducing comparative experiments. First, based on the established presence of physiological drought and the obtained response curves and rebound characteristics after applying a normal fluid pulse, a second fluid pulse containing a chemical component designed to inhibit cation exchange in the soil is applied to a second target region in the crop root zone. This second fluid pulse temporarily reduces or eliminates the soil solids' ability to adsorb and release cations from the solution. Subsequently, the soil conductivity parameters of this second target region are monitored, and a second response curve is obtained. This second response curve reflects the change in soil conductivity over time when cation exchange is inhibited. Since the rebound characteristics of the response curve after the normal fluid pulse are the result of both salt uplift and cation exchange, while the rebound characteristics of the second response curve after the second fluid pulse primarily reflect the influence of salt uplift, comparing the rebound characteristics of these two response curves allows for the differentiation of the relative contributions of the two mechanisms to salt accumulation. If the rebound amplitude or rate of the second response curve is significantly smaller than that of the ordinary response curve, it indicates that cation exchange is the main source of salt accumulation; conversely, if the rebound characteristics of the two are similar, it indicates that upward migration of salt is the dominant factor. This comparative analysis makes the judgment of the cause of salt damage more accurate, thus providing a basis for taking more targeted control measures and solving the problem that it is difficult to accurately distinguish complex sources of salt by relying solely on a single response curve.

[0053] In one embodiment of the present invention, when a chemical component is conductive or reacts with soil to generate conductive products, the step of identifying the source of salt accumulation based on a comparison of the rebound characteristics of the first response curve and the rebound characteristics of the second response curve includes:

[0054] The conductivity response of the second fluid pulse in a reference medium without cation exchange capacity is obtained to generate a pseudo-effect response curve;

[0055] The second response curve is corrected based on the pseudo-effect response curve to generate the corrected response curve;

[0056] The sources of salt accumulation are identified by comparing the rebound characteristics of the response curve with those of the corrected response curve.

[0057] The reference medium, which lacks cation exchange capacity, refers to a material whose contribution to conductivity when in contact with the second fluid pulse mainly stems from the conductivity of the second fluid pulse itself or the conductive products generated by its non-cation exchange reaction with the reference medium, without significant cation adsorption or release. This simulates the conductivity behavior of chemical components unaffected by soil cation exchange. It can be achieved using pure quartz sand, glass beads, or inert materials that have undergone special treatment to remove cation exchange capacity. Its purpose is to provide a benchmark for isolating and quantifying the direct influence of chemical components in the second fluid pulse on conductivity. The pseudo-response curve is a curve recording the change in conductivity over time caused by a second fluid pulse in a reference medium lacking cation exchange capacity. This curve reflects the contribution of the chemical component's own conductivity or the conductivity of its reaction products with the reference medium to the conductivity. Specifically, it can be generated by filling a measurement container with a reference medium lacking cation exchange capacity, applying a fluid with the same composition and concentration as the second fluid pulse, and monitoring the change in conductivity over time using a conductivity sensor. Its purpose is to characterize the conductivity response of the chemical component in the absence of cation exchange interference. Correcting the second response curve based on the pseudo-response curve involves adjusting the value of the second response curve according to the influence of the chemical component on conductivity reflected in the pseudo-response curve. This eliminates or reduces the interference from the chemical component, thereby obtaining a conductivity response closer to that caused by changes in soil salinity. Specifically, this can be achieved by subtracting the contribution of the pseudo-response curve from the second response curve. The purpose is to remove the non-target influence of the chemical component on conductivity and obtain the true response reflecting changes in soil salinity. The corrected response curve refers to the second response curve after correction by the pseudo-effect response curve. This curve more accurately reflects the change in electrical conductivity caused by salt accumulation or migration in the soil. Its purpose is to provide a purer signal for subsequent comparison with the rebound characteristics of the response curve, thereby improving the accuracy of the judgment of the source of salt accumulation.

[0058] This application's method generates a pseudo-effect response curve by acquiring the conductivity response of a second fluid pulse in a reference medium lacking cation exchange capacity. This pseudo-effect response curve characterizes the influence of the chemical components themselves or their reaction products with the inert medium on conductivity, eliminating interference from soil cation exchange. Next, the second response curve measured in soil is corrected based on this pseudo-effect response curve, thereby removing the conductivity contribution from the chemical components and generating a corrected response curve. The corrected response curve thus more accurately reflects the conductivity changes caused by soil salts (rather than chemical components), particularly those related to cation exchange. This correction mechanism allows the principle of suppressing cation exchange using the second fluid pulse to be effectively utilized even when chemical components are conductive or reactive. By comparing the rebound characteristics of the response curve obtained from applying a normal fluid pulse with those of the corrected second response curve, it is possible to more accurately determine whether salt accumulation is dominated by upward migration or cation exchange. This method improves the reliability of determining the source of salt accumulation and solves the problem of accurate determination of chemical component interference.

[0059] As one embodiment of the present invention, the step of correcting the second response curve based on the pseudo-effect response curve to generate a corrected response curve includes:

[0060] In the second response curve and the pseudo-response curve, a time period in which the response is dominated by chemical components is determined;

[0061] A correction parameter is determined based on the correspondence between the second response curve and the pseudo-response curve over a time period. The correction parameter is used to characterize the interaction between chemical components and soil matrix.

[0062] The pseudo-effect strain curve is adjusted according to the correction parameters to generate an adjusted pseudo-effect strain curve;

[0063] The corrected response curve is generated by removing the contribution of the adjusted spurious response curve from the second response curve.

[0064] The period in which the response is dominated by the chemical component refers to the initial stage after the chemical component is applied, during which its dissolution, diffusion, and mixing with soil pore water occur. The change in conductivity is primarily influenced by the properties of the chemical component itself and its behavior in solution. This can be achieved by analyzing the initial trend of the conductivity curve and identifying rapid change stages. The aim is to identify the period when the chemical component's contribution to conductivity is most significant, providing a basis for subsequent correction. The correction parameter, used to characterize the interaction between the chemical component and the soil matrix, is a numerical value or function that reflects the difference between the conductivity performance of the chemical component in the soil environment (interacting with soil particles and pore water) and its performance in an ideal reference medium. It can be determined by calculating the ratio or difference of the conductivity of two curves within a specific time period, or more complex fitting coefficients. The purpose is to quantify the actual impact of the chemical component in the soil for accurate correction. Based on the correction parameter... Adjusting the pseudo-response curve refers to using determined correction parameters to mathematically transform the pseudo-response curve, enabling it to more accurately simulate the actual electrical conductivity contribution of chemical components in the soil environment. This can be achieved by multiplying the pseudo-response curve by the correction parameters, adding or subtracting offsets related to the correction parameters, or applying more complex functional relationships. The goal is to generate a curve that represents the true electrical conductivity influence of chemical components in the soil. Removing the contribution of the adjusted pseudo-response curve from the second response curve involves mathematically subtracting the electrical conductivity contribution represented by the adjusted pseudo-response curve from the actually monitored second response curve. This can be achieved by subtracting the electrical conductivity value corresponding to the adjusted pseudo-response curve from the electrical conductivity value of the second response curve. The goal is to separate the electrical conductivity signal generated by the chemical components themselves and their interaction with the soil, obtaining a corrected response curve that reflects changes in soil salinity.

[0065] The proposed solution first identifies a time period in the second response curve and the pseudo-response curve where the response is dominated by the chemical component. This is because the chemical component's influence on conductivity is most direct and significant during this period, providing a basis for subsequent quantification of its impact. Based on the correspondence between the second response curve and the pseudo-response curve within this time period, a correction parameter is determined to characterize the interaction between the chemical component and the soil matrix. This parameter captures the difference between the actual conductivity behavior of the chemical component in the complex soil environment and its behavior in an ideal reference medium, quantifying the influence of the soil matrix on the conductivity contribution of the chemical component. The pseudo-response curve is then adjusted according to the correction parameter to generate an adjusted pseudo-response curve, which simulates the actual conductivity contribution of the chemical component in the soil. By removing the contribution of the adjusted pseudo-response curve from the second response curve, a corrected response curve is generated, effectively eliminating the interference of the chemical component itself and its interaction with the soil on the conductivity signal. The corrected response curve more accurately reflects the changes in electrical conductivity caused by salt accumulation in the soil. When comparing the rebound characteristics with the response curve obtained after applying a low-solute-concentration fluid pulse, it can more clearly distinguish between rebound characteristics dominated by salt upward migration and those dominated by cation exchange, because the inhibitory effect of chemical components on cation exchange is reflected, and their own conductivity interference is eliminated. This allows for accurate identification of the source of salt accumulation even when chemical components are conductive or generate conductive products, solving the problem of accuracy in judging chemical component interference in existing technologies.

[0066] As one embodiment of the present invention, the step of determining a correction parameter based on the correspondence between the second response curve and the pseudo-response curve within a time period includes:

[0067] Obtain the average conductivity value of the second response curve within the time period;

[0068] Obtain the average conductivity value of the pseudo-effect curve within the time period;

[0069] Calculate the ratio or average difference between the average conductivity value of the second response curve and the average conductivity value of the spurious response curve to determine the correction parameters.

[0070] Here, "time period" refers to a specific time range within which changes in soil electrical conductivity are primarily influenced by the applied chemical component. The average electrical conductivity value of the second response curve refers to the average electrical conductivity value of the second response curve obtained by monitoring the soil electrical conductivity parameters of the second target area within the stated time period. The average electrical conductivity value of the spurious response curve refers to the average electrical conductivity value of the spurious response curve generated by acquiring the electrical conductivity response of the second fluid pulse in a reference medium without cation exchange capacity within the stated time period. "Ratio" or "average difference" is a mathematical calculation used to quantify the relative proportional relationship or absolute difference between the average electrical conductivity value of the second response curve and the average electrical conductivity value of the spurious response curve. "Correction parameter" is a numerical value used to quantitatively characterize the degree of influence of the chemical component on soil electrical conductivity, including its own conductivity and its interaction with the soil matrix.

[0071] The proposed method involves obtaining the average conductivity value of the second response curve actually monitored during the period when the response is dominated by chemical components, and the average conductivity value of the spurious response curve generated by the chemical components in a reference medium without cation exchange capacity. The ratio or average difference between these two average conductivity values ​​is then calculated to determine a correction parameter characterizing the interaction between the chemical components and the soil matrix. This method can quantitatively capture the comprehensive impact of chemical components in the actual soil environment, including their own conductivity and their interaction with the soil matrix. The correction parameter determined in this way is closer to reality than parameters obtained based on preset values ​​or simple models. Applying this more accurate correction parameter to subsequent correction steps can more precisely isolate the influence of chemical components from the second response curve, generating a more realistic corrected response curve. This makes subsequent comparative analysis based on the rebound characteristics of the response curve more reliable, thereby improving the accuracy of identifying the sources of salt accumulation.

[0072] As one embodiment of the present invention, the step of determining a time period in which the response is dominated by the chemical component between the second response curve and the pseudo-response curve includes:

[0073] Analyze the initial rate of change or slope of the second response curve and the pseudo-response curve;

[0074] Based on the analysis results, the time period in which both the second response curve and the pseudo-response curve showed rapid changes and consistent trends was identified.

[0075] The time period is defined as the time period during which the response is dominated by chemical components.

[0076] The initial rate of change or slope refers to the change in conductivity per unit time during the initial stage of the curve. This can be achieved by calculating the average rate of change or the slope of the fitted tangent line within a small time window near the starting point. A large rate of change means that the conductivity parameter changes significantly in a short period of time, with the absolute value of the rate of change or slope exceeding a preset threshold. Same direction of change means that the conductivity parameters of the two curves change in the same direction within the same time period, such as increasing or decreasing simultaneously. The time period where the response is dominated by chemical components refers to the period after the application of the second fluid pulse, where the change in soil conductivity parameters is mainly affected by the conductivity of the chemical components in the second fluid pulse themselves or the conductivity of their reaction products with the soil, rather than by the influence of soil matrix or salt migration.

[0077] The working principle of this application, through the aforementioned steps, lies in analyzing the initial rate of change or slope of the second response curve and the pseudo-response curve to capture the common conductivity change characteristics caused by the rapid diffusion and reaction of chemical components. Identifying time periods where both curves exhibit large rates of change and the same direction of change indicates that within this time period, the changes in both curves are primarily driven by the influence of chemical components, while the influence of factors such as soil matrix and salt migration is relatively small or not yet fully apparent. Defining this time period as the period where the response is dominated by chemical components provides a basis for subsequently determining correction parameters based on the correspondence within this time period. By accurately identifying this time period, the contribution of chemical components to conductivity can be more precisely quantified, thereby effectively separating this influence from the second response curve in subsequent correction steps, resulting in a corrected response curve that better reflects the source of salt accumulation. This method, by distinguishing the temporal response characteristics of different influencing factors, especially utilizing the rapid response characteristics of chemical components, achieves effective identification and isolation of the influence of chemical components, laying an important foundation for accurately identifying the source of salt accumulation.

[0078] In one embodiment of the present invention, the steps of adjusting the spurious response curve according to the correction parameters and generating the corrected response curve by removing the contribution of the adjusted spurious response curve from the second response curve are achieved by the following formula:

[0079] C_corr(t)=C_soil(t)-k*C_ref(t)

[0080] Where t is the time variable, C_corr(t) is the conductivity value of the corrected response curve at time t, C_soil(t) is the conductivity value of the second response curve at time t, C_ref(t) is the conductivity value of the spurious response curve at time t, and k is the correction parameter.

[0081] The reason this application's scheme can achieve precise correction of the second response curve is because it employs the formulaic expression C_corr(t) = C_soil(t) - k*C_ref(t). This formula directly subtracts the spurious response curve C_ref(t) adjusted by the correction parameter k from the original second response curve C_soil(t), thus quantifying and removing the influence of the chemical components themselves and their behavior in the reference medium on the conductivity response. The introduction of the correction parameter k, based on consideration of the actual behavior of chemical components in the soil matrix, makes the adjustment of the spurious response curve more closely reflect reality. The corrected response curve C_corr(t) obtained in this way can more accurately reflect the contribution of the soil matrix (especially cation exchange) to the conductivity response. This precise correction provides a reliable data foundation for subsequent identification of salt accumulation sources based on the comparison of response curve rebound characteristics, thereby improving the accuracy of the entire identification process.

[0082] like Figure 2 The system shown is an irrigation data acquisition system for water conservancy facilities, used to identify the causes of crop stress and generate irrigation control commands. The system includes:

[0083] The reference state storage module 201 is used to calibrate and store the reference state of the target plot when the soil moisture is sufficient and the salinity is lower than the first preset value. The reference state includes the reference soil moisture content parameter and the reference soil electrical conductivity parameter.

[0084] The real-time data acquisition module 202 is used to collect real-time soil moisture content parameters and real-time soil electrical conductivity parameters of the crop root zone of the target plot before the scheduled irrigation operation is performed on the target plot.

[0085] The discrimination module 203 is used to compare the real-time soil moisture content parameters and real-time soil electrical conductivity parameters with the reference soil moisture content parameters and reference soil electrical conductivity parameters in the reference state, so as to determine whether the crops in the target plot have physiological drought caused by salt accumulation, and generate discrimination results.

[0086] The instruction generation module 204 is used to generate an irrigation control instruction to stop irrigation operations on the target plot if the judgment result indicates that physiological drought exists.

[0087] The proposed solution provides baseline data under ideal conditions through a reference state storage module 201, while a real-time data acquisition module 202 acquires the current actual data of the crop root zone. A discrimination module 203 compares and analyzes the real-time data with the baseline data to identify whether crop stress is caused by salt accumulation. Specifically, when the real-time soil moisture content parameter indicates sufficient soil moisture, but the real-time soil conductivity parameter is significantly higher than the reference soil conductivity parameter, the discrimination module 203 can determine that physiological drought caused by salt accumulation exists. Due to this baseline-based discrimination mechanism, the system can distinguish between physical water shortage and physiological drought, avoiding misjudging salt damage as water shortage. Once the discrimination result indicates physiological drought, the instruction generation module 204 immediately generates an instruction to stop irrigation. This linkage mechanism enables the system to make accurate irrigation decisions based on the actual state of the crop root zone, preventing the application of high-salinity irrigation water under salt stress and thus avoiding exacerbating salt damage.

[0088] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention.

Claims

1. A water facility irrigation data collection method, characterized by, The method comprises the following steps: calibrating and storing a reference state of the target plot when the soil moisture is sufficient and the salt content is lower than a first preset value, the reference state comprising a reference soil water content parameter and a reference soil conductivity parameter; collecting a real-time soil water content parameter and a real-time soil conductivity parameter of a crop root zone of the target plot before a predetermined irrigation operation is performed on the target plot; comparing the real-time soil water content parameter and the real-time soil conductivity parameter with the reference soil water content parameter and the reference soil conductivity parameter in the reference state to determine whether the crop of the target plot is suffering from physiological drought caused by salt accumulation, and generating a determination result; if the determination result indicates that the physiological drought exists, generating an irrigation control instruction for suspending the irrigation operation on the target plot; under the condition that the determination result indicates that the physiological drought exists, the method further comprises: applying a fluid pulse with a preset low solute concentration to a target area of the crop root zone; monitoring the soil conductivity parameter of the target area within a preset time period after the fluid pulse is applied to obtain a response curve of the soil conductivity parameter; determining a rebound feature of the soil conductivity parameter after an initial drop based on the response curve; identifying the source of salt accumulation according to the rebound feature; the step of determining the rebound feature of the soil conductivity parameter after the initial drop based on the response curve comprises: calculating the change rate of the response curve over time to obtain a change rate curve; identifying local extreme points on the change rate curve, and dividing the response curve into multiple response sub-segments according to the local extreme points; independently determining the rebound feature of each response sub-segment; the step of identifying the source of salt accumulation according to the rebound feature comprises: applying a second fluid pulse to a second target area of the crop root zone, the second fluid pulse containing a chemical component for inhibiting the cation exchange of soil; monitoring the soil conductivity parameter of the second target area after the second fluid pulse is applied to obtain a second response curve; identifying whether the source of salt accumulation is dominated by salt upward migration or cation exchange based on a comparison of the rebound feature of the response curve and the rebound feature of the second response curve.

2. The method for collecting irrigation data of a water conservancy project according to claim 1, characterized in that, When the chemical component itself has conductivity or will react with the soil to generate a conductive product, the step of identifying the source of salt accumulation based on the comparison of the rebound feature of the response curve and the rebound feature of the second response curve comprises: obtaining the conductivity response of the second fluid pulse in a reference medium without cation exchange capability to generate a pseudo-influence curve; correcting the second response curve according to the pseudo-influence curve to generate a corrected response curve; identifying the source of salt accumulation based on a comparison of the rebound feature of the response curve and the rebound feature of the corrected response curve.

3. The method of claim 2, wherein, the step of correcting the second response curve according to the pseudo-influence curve to generate a corrected response curve comprises: In the second response curve and the pseudo-effect curve, a time period in which a response is dominated by a chemical component is determined; a correction parameter is determined based on a correspondence between the second response curve and the pseudo-effect curve in the time period; the pseudo-effect curve is adjusted according to the correction parameter to generate an adjusted pseudo-effect curve; a corrected response curve is generated by removing the contribution of the adjusted pseudo-effect curve from the second response curve.

4. The method of claim 3, wherein, The correction parameter is used to characterize the interaction between the chemical component and the soil matrix.

5. A method of collecting irrigation data for water infrastructure according to claim 4, wherein, The step of determining a correction parameter based on the correspondence between the second response curve and the pseudo-effect curve in the time period includes: obtaining the average conductivity value of the second response curve in the time period; obtaining the average conductivity value of the pseudo-effect curve in the time period; calculating the ratio or average difference between the average conductivity value of the second response curve and the average conductivity value of the pseudo-effect curve to determine the correction parameter.

6. The method of claim 3, wherein, The step of determining a time period in which a response is dominated by a chemical component in the second response curve and the pseudo-effect curve includes: analyzing the initial change rate or slope of the second response curve and the pseudo-effect curve; based on the analysis result, identifying a time period in which the second response curve and the pseudo-effect curve both show rapid changes and consistent change trends; the time period is taken as the time period in which the response is dominated by the chemical component.

7. An irrigation data acquisition system for water management facilities for performing an irrigation data acquisition method for water management facilities according to any one of claims 1 to 6, for discriminating causes of crop stress and generating irrigation control instructions, characterized in that, The system comprises: a reference state storage module for calibrating and storing a reference state of a target plot when the soil moisture is sufficient and the salt content is lower than a first preset value, the reference state including a reference soil moisture content parameter and a reference soil conductivity parameter; a real-time data acquisition module for acquiring real-time soil moisture content parameters and real-time soil conductivity parameters of a crop root zone of the target plot before a predetermined irrigation operation is performed on the target plot; a discrimination module for comparing the real-time soil moisture content parameters and the real-time soil conductivity parameters with the reference soil moisture content parameters and the reference soil conductivity parameters in the reference state to determine whether the crop in the target plot has physiological drought caused by salt accumulation and generate a discrimination result; an instruction generation module for generating an irrigation control instruction for suspending the irrigation operation on the target plot if the discrimination result indicates that the physiological drought exists.

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