Rainwater collection infiltrating irrigation water quantity control method and system

Abstract

The invention provides a rainwater collection infiltrating irrigation water quantity control method and system, and relates to the technical field of rainwater collection infiltrating irrigation. The water yield and the water outlet rate of the reservoir are respectively measured in the two states of closing and opening of the main pipe network valve, so that the pipeline leakage rate and the total water outlet rate when the main pipe network is opened can be accurately identified. On the basis, the effective irrigation rate actually used for irrigation can be accurately determined by calculating the difference value between the actual water yield and the theoretical design value, and the problem that in the prior art, due to the fact that an infiltrating irrigation pipe network and a water dropper are blocked, the actual water yield does not accord with the theoretical design value seriously is solved. By acquiring the real effective irrigation rate, the system can accurately calculate the required irrigation duration according to the target water volume, and controls the water pump to execute the irrigation task according to the required irrigation duration.

Description

Technical Field

[0001] This application relates to the field of rainwater harvesting and infiltration irrigation technology, and more specifically, to a method and system for controlling the amount of rainwater harvested and infiltration irrigation. Background Technology

[0002] In arid or semi-arid regions where water resources are increasingly scarce, the demand for water-saving irrigation technologies in agricultural production is particularly urgent. Rainwater harvesting and drip irrigation systems are widely used to efficiently utilize limited water resources, such as in the cultivation of high-value crops like goji berries. These systems collect rainfall and store it in reservoirs, then deliver the water directly to the crop roots through a drip irrigation network. To achieve precise water control, the system is typically equipped with a control device that determines the start, stop, and duration of irrigation based on preset programs or feedback from soil moisture sensors. Ideally, the control device calculates the operating time of pumps and valves based on the designed water flow rate and total number of drippers, aiming to achieve precise control over the total irrigation volume and maximize water conservation.

[0003] However, in actual field operations, especially in areas with strong winds and sandstorms, rainwater carries a large amount of fine sediment into the reservoir as it flows through the catchment area. Although a preliminary filter screen is installed at the reservoir inlet, its filtering effect on fine sediment particles is limited. Over time, a large amount of sediment accumulates at the bottom of the reservoir, forming silt. When the irrigation system is started and the pump draws water from the reservoir, especially when the water level is low, the pump stirs up the silt at the bottom, causing a large amount of fine sediment particles to be sucked into the irrigation network. These sediment particles are carried by the water flow through the main pipes and branch pipes, eventually reaching the drip irrigation lines and drippers. The drippers are usually designed with narrow and tortuous flow channels, making it easy for sediment particles to adhere to and deposit on the inner walls of the channels, gradually causing blockages.

[0004] This type of blockage is gradual, uneven, and difficult to detect externally. This uneven blockage severely disrupts the uniformity of water distribution throughout the irrigation area. At this point, the central control system still operates based on the ideal assumption that "all drippers are working normally at their designed flow rates." For example, when the system determines that a certain area needs 1000 liters of water, it calculates the operating time for one hour based on the theoretical total flow rate. However, in reality, due to dripper blockage, the actual total water output in that area may be far lower than the theoretical value. This means that at the end of an irrigation cycle, the crops actually receive far less water than they need for growth. The control system cannot detect the decline in the actual water output capacity of the pipeline network, leading to stunted growth, reduced fruit set, and poor quality of crops due to long-term insufficient water supply, resulting in economic losses. Farm managers, only viewing the irrigation data from the control system, may mistakenly believe that water management is appropriate, thus failing to identify and address the deeper problems in a timely manner.

[0005] Furthermore, in a goji berry rainwater harvesting and infiltration irrigation system that primarily uses collected rainwater, when the sediment carried by the rainwater inevitably causes gradual and uneven blockage of the drippers, leading to a continuous and unpredictable decline in the actual water output capacity of the entire irrigation network, how can a water control method be established to overcome the uncertainties caused by dripper blockage, obtain real-time or periodic information on the actual water delivery capacity of the irrigation network, and adjust irrigation operations based on this information? This would ensure that the amount of water received by the goji berry root zone is consistent with the preset target water requirement, preventing goji berry yield reduction due to long-term hidden water shortage, and achieving truly precise water control.

[0006] To address the aforementioned issues, existing technologies urgently need improvement. Summary of the Invention

[0007] This application discloses a method and system for controlling the amount of rainwater collected and seepage irrigation water, which aims to solve the technical problems in the practical application of existing rainwater collected and seepage irrigation systems, such as the actual irrigation water volume not matching the theoretical design water volume due to blockage of the seepage irrigation network and drippers, resulting in insufficient water supply for crops, affecting growth, and farm managers being unable to detect problems in a timely manner, thereby ensuring that the amount of water obtained by the root zone of wolfberry accurately matches the preset target.

[0008] The technical solution of this application is as follows:

[0009] In a first aspect, this application discloses a method for controlling the amount of rainwater collected for infiltration irrigation, the method comprising:

[0010] Start the water pump, and when the main pipeline valve is closed, determine the first water output and the first water output rate of the water storage tank within the first preset time period; when the main pipeline valve is opened, determine the second water output and the second water output rate of the water storage tank within the second preset time period.

[0011] The effective irrigation rate is determined based on the first water outflow rate and the second water outflow rate.

[0012] Determine the target water volume to be irrigated in the target area, determine the remaining irrigation time based on the target water volume and the effective irrigation rate, and control the water pump to perform the irrigation task based on the remaining irrigation time.

[0013] Furthermore, when the main pipeline valve is closed, determining the first outflow volume and the first outflow rate of the water storage tank within the first preset time period includes:

[0014] Within a first preset time period, the water pump is started, the main pipeline valve is closed, and the first drop in the water level of the rainwater collection tank is monitored; the first outflow volume is determined based on the first drop in the water level and the cross-sectional area of ​​the rainwater collection tank; and the first outflow rate is determined based on the ratio of the first outflow volume to the first preset time; wherein, the first outflow rate indicates the leakage rate of the pipeline section between the water pump and the main pipeline valve.

[0015] When the main pipeline valve is opened, determine the second outflow volume and second outflow rate of the water storage tank within the second preset time period, including:

[0016] Within the second preset time period, the water pump is started, the main pipeline valve is opened, and the second drop in the rainwater collection tank is monitored; the second outflow rate is determined based on the second drop in the water level and the cross-sectional area of ​​the rainwater collection tank; and the second outflow rate is determined based on the ratio of the second outflow rate to the second preset time.

[0017] Based on the above, this application further proposes to determine the effective irrigation rate according to the first water outflow rate and the second water outflow rate, including: the difference between the second water outflow rate and the first water outflow rate is determined as the effective irrigation rate.

[0018] In some preferred embodiments, determining the target water volume for irrigation of the target area includes: acquiring current ambient temperature and light intensity information; determining the initial target water volume based on the ambient temperature, light intensity, and water demand coefficient; delivering the initial target water volume to the target area according to the effective irrigation rate, while simultaneously monitoring plant canopy temperature and ambient air temperature; determining the temperature difference between the plant canopy temperature and ambient air temperature; evaluating the irrigation effect based on the trend of the temperature difference data; and adjusting the water demand coefficient based on the irrigation effect.

[0019] More specifically, in some implementation schemes, the initial target water volume is determined based on ambient temperature information, light intensity information, and water demand coefficient, including: V_initial = K_demand * (T_ambient - T_base) * L_factor; where V_initial is the initial target water volume; K_demand is the water demand coefficient, used to reflect the basic water demand under environmental stimuli, and the initial value of this water demand coefficient is preset; T_ambient is the real-time ambient temperature; T_base is a preset reference temperature, and when the ambient temperature is lower than the reference temperature, the water demand decreases; L_factor is the light influence factor calculated based on the real-time light intensity.

[0020] Preferably, the temperature difference data between plant canopy temperature and ambient air temperature is determined, and the irrigation effect is evaluated based on the trend of the temperature difference data. This includes: initiating a response observation period after the irrigation task is completed; periodically collecting plant canopy temperature and ambient air temperature data during the response observation period; calculating temperature difference trend data based on the periodically collected plant canopy temperature and ambient air temperature data; and comparing the temperature difference trend data with a preset temperature difference change threshold to evaluate the irrigation effect.

[0021] Building upon the above, this application further proposes comparing the temperature difference trend data with a preset temperature difference change threshold. Previously, the method also included: filtering the temperature difference data to obtain smooth temperature difference trend data; wherein, filtering the temperature difference data to obtain smooth temperature difference trend data includes: acquiring current environmental condition information and the current growth stage information of the plant; dynamically adjusting the filtering parameters based on the current environmental condition information and the current growth stage information; and filtering the temperature difference data based on the adjusted filtering parameters to obtain smooth temperature difference trend data.

[0022] In some preferred embodiments, temperature difference trend data is compared with preset temperature difference change thresholds to evaluate irrigation effectiveness, including: if the temperature difference data rapidly decreases and stabilizes below a preset healthy temperature difference threshold during the observation period, or if the average rate of decrease of the temperature difference data exceeds a preset value, then the irrigation effectiveness is determined to be sufficient; if the temperature difference data fails to decrease below the healthy temperature difference threshold during the observation period, or if the rate of decrease is too slow, then the irrigation effectiveness is determined to be insufficient; and the water demand coefficient is adjusted according to the irrigation effectiveness, including: in response to the irrigation effectiveness being sufficient, reducing the water demand coefficient for the next irrigation; and in response to the irrigation effectiveness being insufficient, increasing the water demand coefficient for the next irrigation.

[0023] Based on the above, this application further proposes to correct the water demand coefficient according to the irrigation effect, including: performing anomaly detection on temperature difference data to identify abnormal data that exceeds the normal fluctuation range or rate of change; suspending the water demand coefficient correction based on the temperature difference data in response to the existence of abnormal data and triggering an anomaly alarm; and re-collecting data and evaluating the irrigation effect after the anomaly is resolved, and restoring the normal water demand coefficient correction process.

[0024] Secondly, this application also discloses a rainwater harvesting and infiltration irrigation water control system, which includes:

[0025] The calibration module is used to start the water pump and determine the first water output and first water output rate of the water storage tank within a first preset time period when the main pipeline valve is closed; and to determine the second water output and second water output rate of the water storage tank within a second preset time period when the main pipeline valve is open.

[0026] The determination module is used to determine the effective irrigation rate based on the first water outflow rate and the second water outflow rate;

[0027] The control module is used to determine the target amount of water to be irrigated to the target area, determine the remaining irrigation time based on the target amount of water and the effective irrigation rate, and control the water pump to perform the irrigation task based on the remaining irrigation time.

[0028] The rainwater harvesting and seepage irrigation water control method disclosed in this application measures the outflow and rate of water from the storage tank under both closed and open main pipeline valve conditions. This allows for precise identification of the pipeline leakage rate and the total outflow rate when the main pipeline is open. Based on this, by calculating the difference between the two, this application can accurately determine the effective irrigation rate actually used for irrigation. This innovative measurement and calculation method directly solves the problem in existing technologies for goji berry rainwater harvesting and seepage irrigation systems that rely primarily on collected rainwater, where the actual outflow is significantly different from the theoretical design value due to blockages in the seepage irrigation network and drippers. By obtaining the true effective irrigation rate, the system can accurately calculate the required irrigation duration based on the target water volume and control the water pump accordingly to perform the irrigation task. Therefore, this application overcomes the shortcomings of traditional systems that cannot detect a decline in the actual outflow capacity of the pipeline network, avoiding problems such as slow growth, reduced fruit set, and deteriorated quality caused by long-term insufficient water supply to crops, and significantly improving water resource utilization efficiency and agricultural production benefits. Attached Figure Description

[0029] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0030] Figure 1 This is a flowchart illustrating the steps of the rainwater harvesting and infiltration irrigation water volume control method disclosed in the embodiments of the present invention;

[0031] Figure 2 This is a schematic diagram of the rainwater collection and infiltration irrigation water control system disclosed in an embodiment of the present invention. Detailed Implementation

[0032] 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 these embodiments belong; the terminology used herein and in the specification of the application is for the purpose of describing particular embodiments only and is not intended to limit these embodiments; the terms "comprising" and "having," and any variations thereof, in the specification of these embodiments and the foregoing drawings, are intended to cover non-exclusive inclusion. The terms "first," "second," etc., in the specification of these embodiments and the foregoing drawings are used to distinguish different objects, not to describe a particular order.

[0033] The implementation details of the technical solution in this embodiment are described in detail below:

[0034] In practical applications, especially in windy and sandy areas, traditional rainwater harvesting and drip irrigation systems are increasingly plagued by dripper clogging due to sediment deposition. This clogging is not only gradual and uneven but also difficult to detect externally, preventing the irrigation system from accurately sensing the actual water output capacity of the network. The central control system continues to operate based on ideal assumptions, resulting in crops receiving far less water than they require for growth, leading to stunted growth, reduced quality, and even economic losses. Consequently, farm managers are unable to promptly identify and address the underlying problems.

[0035] For example, on the same drip irrigation pipeline, drippers closer to the branch pipes may experience less clogging due to higher water pressure; while drippers at the end of the pipeline, with lower water pressure and slower flow, are more prone to sediment deposition and tend to become more severely clogged. Some drippers may only be partially clogged, with the actual water output dropping from the designed 2 liters per hour to 1.5 liters or even 1 liter; others may be completely blocked, unable to output any water at all. The central control system then faces a serious challenge. Its control logic still operates based on the ideal assumption that "all drippers are operating normally at the designed flow rate." When the system determines that an area needs 1000 liters of water, it calculates the required operation time of one hour based on the theoretical total flow rate of 500 drippers in that area (500 drippers multiplied by 2 liters per hour, i.e., 1000 liters per hour). After one hour of operation, the system records in the log "1000 liters of irrigation task completed." However, in reality, due to widespread dripper clogging, the actual total water output in that area may only be 600 liters per hour, or even lower. This means that at the end of an irrigation cycle, the goji berry plants in the area actually received only 600 liters of water, far less than their growth requirements. The control system was "blinded" by this physical performance degradation, failing to detect the actual decrease in water output from the pipe network. Farm managers, simply looking at the irrigation data from the control system, mistakenly assumed that water management was proper, thus failing to identify and address the deeper problems in a timely manner.

[0036] In response, this application proposes a method for controlling the amount of rainwater collected for infiltration irrigation, such as... Figure 1 As shown, the method includes:

[0037] S101, start the water pump, and when the main pipeline valve is closed, determine the first water output and the first water output rate of the water storage tank within the first preset time period; when the main pipeline valve is opened, determine the second water output and the second water output rate of the water storage tank within the second preset time period.

[0038] S102, determine the effective irrigation rate based on the first water outflow rate and the second water outflow rate;

[0039] S103, determine the target water volume to be irrigated in the target area, determine the remaining irrigation time based on the target water volume and the effective irrigation rate, and control the water pump to perform the irrigation task based on the remaining irrigation time.

[0040] This application introduces a calibration mechanism for the actual water output capacity of the pipeline network, which can dynamically evaluate and correct the actual water output efficiency of the irrigation system, thereby achieving precise control of the rainwater collection and infiltration irrigation volume. This effectively solves the problem of inaccurate irrigation water volume caused by dripper blockage in the prior art, and ensures that crops receive a sufficient and uniform water supply.

[0041] To better understand the rainwater harvesting and seepage irrigation water control method proposed in this application, the key terms and implementation environment involved will be explained below. In this application, "rainwater harvesting and seepage irrigation system" refers to an irrigation system that collects rainwater and stores it in a reservoir, then delivers the water directly to the roots of crops through a seepage irrigation network. This system typically includes components such as a rainwater harvesting field, a reservoir, a water pump, main network valves, seepage irrigation pipelines, and drippers. "First discharge volume" and "second discharge volume" refer to the volume of water discharged from the reservoir by the water pump within a preset time period under specific operating conditions. "First discharge rate" and "second discharge rate" represent the ratio of the corresponding discharge volume to the preset time period, respectively. "Effective irrigation rate" refers to the effective water delivery rate to the crop roots during actual irrigation, after deducting losses such as pipeline leakage. "Target water volume" refers to the total amount of water needed to irrigate the target area based on crop water requirements and environmental conditions. "Remaining irrigation time" refers to the remaining time required to deliver the target water volume under the current effective irrigation rate. This method typically operates on a rainwater harvesting and infiltration irrigation control system, which may include hardware devices such as sensors, controllers, and actuators, as well as software modules for data processing and control logic.

[0042] The core of the rainwater harvesting and infiltration irrigation water control method proposed in this application lies in achieving precise control of irrigation water volume through accurate measurement and calibration of the actual water output capacity of the pipeline network.

[0043] Specifically, the method first starts the water pump and, when the main pipeline valve is closed, determines the first water output and first water output rate of the storage tank within a first preset time period. For example, a level sensor can be installed in the storage tank to monitor the drop in the tank level when the pump is running and the main pipeline valve is closed. The first water output is obtained by multiplying the drop in level by the cross-sectional area of ​​the storage tank. The first water output is then divided by the first preset time period to obtain the first water output rate. This first water output rate primarily reflects the leakage rate of the pipeline section between the pump and the main pipeline valve. Since the main pipeline valve is closed at this time, water cannot enter the irrigation area; if water is still output, it is mainly due to pipeline leakage.

[0044] Subsequently, when the main pipeline valve is opened, the second water output and second water output rate corresponding to the reservoir within the second preset time period are determined. Similarly, when the water pump starts and the main pipeline valve is open, the drop in the reservoir level is monitored, and the second water output and second water output rate are calculated. At this point, the second water output rate reflects the total water output rate of the pump to the entire irrigation network (including the main pipeline, branch pipes, and drippers), which includes the effective irrigation water volume and the network leakage water volume.

[0045] After obtaining the first and second outflow rates, the effective irrigation rate is determined based on these two values. For example, the difference between the second and first outflow rates can be used to determine the effective irrigation rate. This calculation method effectively deducts ineffective irrigation water volumes such as those caused by pipeline leakage, thereby obtaining the actual water delivery rate used for crop irrigation.

[0046] Next, the target water volume for irrigation of the target area is determined. This target water volume can be based on various factors, such as current ambient temperature, light intensity, and the water requirement coefficient. For example, a baseline temperature can be preset; when the ambient temperature is higher than the baseline temperature, the water requirement increases, and when the ambient temperature is lower than the baseline temperature, the water requirement decreases. Light intensity information can be used to calculate the light impact factor to reflect the effect of light on crop transpiration. The water requirement coefficient is a parameter that comprehensively reflects factors such as crop type and growth stage.

[0047] Finally, based on the target water volume and effective irrigation rate, the remaining irrigation time is determined, and the water pump is controlled to perform the irrigation task according to the remaining irrigation time. For example, the required irrigation time can be obtained by dividing the target water volume by the effective irrigation rate. The control system starts or stops the water pump according to this time, thereby achieving precise control of the irrigation task.

[0048] The rainwater harvesting and infiltration irrigation water control method of this application introduces a calibration mechanism for the actual water output capacity of the pipe network, which can dynamically evaluate and correct the actual water output efficiency of the irrigation system, thereby achieving precise control of rainwater harvesting and infiltration irrigation water volume.

[0049] Specifically, this method first measures the water output and rate from the reservoir under two operating conditions: with the main pipeline valve closed and open, respectively, to distinguish between the leakage rate and the total water output rate of the pipeline network. The first water output rate reflects the leakage in the pipeline from the pump to the main pipeline valve, while the second water output rate includes the effective irrigation water volume and all pipeline leakage. By calculating the difference between the second and first water output rates, the effective irrigation rate actually used for crop irrigation can be accurately obtained. This step is the core innovation of this application, directly solving the problem in existing technologies where the reduction in actual water output capacity due to dripper blockage cannot be detected.

[0050] After determining the accurate effective irrigation rate, this method can calculate the target water volume based on the actual water requirements of the crop (determined by a combination of ambient temperature, light intensity, and water requirement coefficient). Subsequently, using the precise effective irrigation rate and target water volume, the required remaining irrigation time is calculated, and the water pump is controlled accordingly. This dynamic adjustment mechanism based on actual water output capacity and crop water requirements ensures that the crop receives just the right amount of water, avoiding resource waste and poor crop growth caused by insufficient or excessive irrigation.

[0051] Compared with existing technologies, the rainwater harvesting and seepage irrigation water control method of this application has significant advantages and innovations. Traditional methods typically rely on the design flow rate and number of drippers to calculate irrigation duration. This method cannot detect the decrease in actual water output when drippers become clogged, leading to a discrepancy between the irrigation water volume and the actual needs of the crop. For example, when dripper clog causes a 50% decrease in actual water output, the traditional system will still irrigate according to the theoretical value, resulting in the crop actually receiving only half of the required water.

[0052] This application dynamically determines the effective irrigation rate by introducing measurements of the first and second water discharge rates. This innovative step allows the system to perceive the actual water discharge capacity of the pipe network in real time, including efficiency losses caused by factors such as dripper blockage and pipe leakage. By subtracting the first water discharge rate from the second water discharge rate, ineffective irrigation water volume is precisely eliminated, thereby obtaining the truly effective irrigation rate used for crop growth. This calibration mechanism makes irrigation control no longer dependent on idealized design parameters, but based on real-time system performance.

[0053] Therefore, this application can accurately calculate the required irrigation duration based on the actual effective irrigation rate and crop water requirements, and control the water pump accordingly. This method not only effectively solves the problem of inaccurate irrigation water volume caused by dripper clogging, ensuring that crops receive sufficient and uniform water supply, but also maximizes water conservation and improves water resource utilization efficiency. Furthermore, through continuous monitoring and calibration, this method can adapt to the changing characteristics of pipeline network performance over time, achieving long-term stable precision irrigation.

[0054] Specifically, the steps of determining the first outflow volume and first outflow rate of the water storage tank within the first preset time period when the main pipeline valve is closed, and determining the second outflow volume and second outflow rate of the water storage tank within the second preset time period when the main pipeline valve is open, can be further refined as follows.

[0055] During the first preset time period, the water pump is started, the main pipeline valve is closed, and the first drop in the water level of the rainwater collection tank is monitored; the first outflow volume is determined based on the first drop in the water level and the cross-sectional area of ​​the rainwater collection tank; and the first outflow rate is determined based on the ratio of the first outflow volume to the first preset time; wherein, the first outflow rate indicates the leakage rate of the pipeline section between the water pump and the main pipeline valve.

[0056] The step of determining the second outflow volume and second outflow rate of the water storage tank within the second preset time period when the main pipeline valve is opened includes: starting the water pump and opening the main pipeline valve within the second preset time period, and monitoring the second liquid level drop in the rainwater collection and storage tank; determining the second outflow volume based on the second liquid level drop and the cross-sectional area of ​​the rainwater collection and storage tank; and determining the second outflow rate based on the ratio of the second outflow volume to the second preset time period.

[0057] Specifically, the first and second liquid level drops can be monitored and collected in real time by liquid level sensors installed in the rainwater harvesting tank. The liquid level sensors can be ultrasonic level gauges, float-type level gauges, or pressure level gauges, which can accurately measure changes in the water level within the tank. The cross-sectional area of ​​the rainwater harvesting tank can be obtained in advance through measurement or design drawings and stored in the control system. The first and second outflow rates are calculated by multiplying the corresponding liquid level drop by the cross-sectional area of ​​the rainwater harvesting tank. For example, if the cross-sectional area of ​​the rainwater harvesting tank is A, and the first liquid level drop is Δh1, then the first outflow rate V1 = A * Δh1. The first and second outflow rates are calculated by dividing the corresponding outflow rate by the corresponding preset time period (first preset time period or second preset time period). For example, if the first outflow rate is V1, and the first preset time period is Δt1, then the first outflow rate R1 = V1 / Δt1.

[0058] The first outflow rate indicates the leakage rate of the pipeline section between the pump and the main pipeline valve. This means that when the main pipeline valve is closed, the water output from the pump, besides filling the pipeline, mainly represents leakage losses within the pipeline itself. Accurate measurement of this leakage rate provides precise baseline data for subsequent calculations of the effective irrigation rate.

[0059] This application's solution measures the outflow and outflow rate of the reservoir under two different valve states (main pipeline valve closed and main pipeline valve open), thereby accurately separating the losses caused by pipeline leakage from the effective flow rate actually used for irrigation. When the main pipeline valve is closed, the water pump starts, and the drop in the reservoir level primarily reflects the leakage in the pipeline section between the pump and the main pipeline valve. By monitoring the first drop in level and combining it with the cross-sectional area of ​​the rainwater harvesting reservoir, the first outflow can be accurately calculated, thus obtaining the first outflow rate, which is defined as the pipeline leakage rate. When the main pipeline valve is open, the water pump starts, and the drop in the reservoir level includes both pipeline leakage and the effective irrigation volume to the target area. By monitoring the second drop in level and calculating the second outflow and second outflow rate, which includes both leakage and effective irrigation, this comparative measurement effectively separates the leakage rate from the total outflow rate, laying the foundation for subsequently determining a more accurate effective irrigation rate.

[0060] The above technical solution enables precise quantification of the actual effective irrigation flow in a rainwater harvesting and seepage irrigation system. Traditional methods may struggle to accurately distinguish between pipe leakage and actual irrigation water usage, leading to inaccurate irrigation volume estimates and resulting in water waste or insufficient irrigation. This application measures the water outlet rate under different valve conditions and identifies the first outlet rate as the leakage rate, allowing the system to more accurately calculate the effective water volume used for actual irrigation, thereby significantly improving irrigation efficiency and water resource utilization. This refined measurement and calculation method helps achieve precision irrigation, avoiding over-irrigation or under-irrigation, and ultimately ensuring healthy plant growth.

[0061] In some embodiments described above in this application, a step of determining the effective irrigation rate based on a first water outflow rate and a second water outflow rate is proposed. Specifically, this step may include the following methods.

[0062] According to the above-mentioned method for controlling the amount of rainwater collected and seepage irrigation, the step of determining the effective irrigation rate based on the first water outflow rate and the second water outflow rate specifically includes: determining the difference between the second water outflow rate and the first water outflow rate as the effective irrigation rate.

[0063] Specifically, the first outflow rate indicates the leakage rate of the pipeline section between the water pump and the main pipeline valve. This rate is calculated by monitoring the first drop in the rainwater collection tank during a first preset time period, after starting the water pump and closing the main pipeline valve. The first outflow rate is determined based on the first drop in the water level and the cross-sectional area of ​​the rainwater collection tank, and then calculated based on the ratio of the first outflow rate to the first preset time period. Its purpose is to quantify the water loss of the pipeline system under non-irrigation conditions.

[0064] The second water discharge rate is calculated by monitoring the drop in the second liquid level of the rainwater collection tank during a second preset time period, through starting the water pump and opening the main pipeline valve. The second water discharge rate is determined based on the drop in the second liquid level and the cross-sectional area of ​​the rainwater collection tank, and then calculated as the ratio of the second water discharge rate to the second preset time period. This rate reflects the total water discharge capacity of the water pump when the main pipeline valve is open, including the actual amount of irrigation water delivered to the target area and the amount of water leaking from the pipeline.

[0065] The proposed solution accurately determines the effective irrigation rate by calculating the difference between a second and a first water outlet rate. The working principle is as follows: the second water outlet rate represents the total water flow rate of the pump under normal operating conditions (i.e., when the main pipeline valve is open), which includes the actual amount of water used for irrigation as well as the inherent leakage from the pipeline system. The first water outlet rate, on the other hand, is specifically used to quantify the leakage from the pipeline system under non-irrigation conditions (i.e., when the main pipeline valve is closed). Therefore, by subtracting the leakage from the total water flow rate, the effective irrigation water volume actually delivered to the target area can be accurately extracted, thus calculating the effective irrigation rate. This method effectively eliminates the interference of pipeline leakage in the calculation of irrigation water volume, ensuring the accuracy of irrigation decisions.

[0066] The above technical solution enables a direct and accurate determination of the effective irrigation rate used for irrigation. By quantifying and deducting leakage losses in the pipeline system, this method avoids overestimating irrigation water volume due to leakage, thus ensuring that the water delivered to the target area is the truly effective irrigation volume. This improves irrigation efficiency, reduces water waste, and provides more accurate data support for subsequent irrigation tasks, thereby optimizing the overall operation of the rainwater harvesting and infiltration irrigation system.

[0067] This application further proposes a method for determining the target amount of water to irrigate a target area, comprising: acquiring current ambient temperature information and light intensity information; determining an initial target amount of water based on the ambient temperature information, light intensity information, and water demand coefficient; delivering the initial target amount of water to the target area according to the effective irrigation rate, while simultaneously monitoring plant canopy temperature information and ambient air temperature information; determining the temperature difference data between the plant canopy temperature information and the ambient air temperature information; evaluating the irrigation effect based on the changing trend of the temperature difference data; and correcting the water demand coefficient based on the irrigation effect.

[0068] Specifically, acquiring current ambient temperature and light intensity information refers to the real-time collection of temperature and light intensity data in the target area using environmental sensors deployed there. This information is crucial environmental parameters for assessing plant transpiration and water requirements. The water requirement coefficient can be understood as a proportional factor reflecting a plant's water demand under specific environmental conditions; its initial value can be preset or determined based on empirical values. Based on these environmental parameters and the water requirement coefficient, an initial target water volume can be preliminarily calculated as a baseline for this irrigation.

[0069] During the delivery of the initial target water volume to the target area, plant canopy temperature and ambient air temperature are monitored simultaneously. Plant canopy temperature directly reflects the plant's physiological state. When plants have sufficient water, transpiration is vigorous, and leaf temperature drops below ambient air temperature due to heat dissipation through transpiration; conversely, when plants are short of water, transpiration weakens, and leaf temperature rises. Therefore, real-time collection of plant canopy temperature data using devices such as infrared sensors, and ambient air temperature data using environmental sensors, provides crucial information for subsequent irrigation effectiveness evaluation.

[0070] Subsequently, based on the collected plant canopy temperature and ambient air temperature information, the temperature difference between the two is calculated. This temperature difference data directly reflects the plant's water status. By analyzing the trend of this temperature difference data, such as the rate of decrease and stable value, the actual effect of the irrigation task can be evaluated. For example, if the temperature difference decreases rapidly and remains at a low level, it usually indicates good irrigation effect and sufficient plant water; if the temperature difference decreases slowly or fails to reach the expected level, it may indicate insufficient irrigation.

[0071] Finally, the water requirement coefficient is adjusted based on the assessed irrigation effect. If the assessment indicates sufficient water, the water requirement coefficient can be appropriately reduced to avoid over-irrigation in the next irrigation; if the assessment indicates insufficient water, the water requirement coefficient can be appropriately increased to ensure sufficient water is provided in the next irrigation. This dynamic adjustment mechanism allows the irrigation strategy to adaptively adjust according to the actual physiological response of the plant and environmental changes.

[0072] This application's solution effectively addresses the static and non-adaptive issues that may exist in the basic scheme when determining the target water volume by introducing a real-time monitoring and feedback mechanism for plant physiological responses. Specifically, while the basic scheme can determine a target water volume, this volume may not accurately match the dynamic water requirements of plants under different environmental conditions. This application preliminarily determines the initial target water volume by acquiring environmental temperature and light intensity information, combined with the water requirement coefficient, providing a reasonable starting point for irrigation. More importantly, during irrigation, by monitoring the plant canopy temperature and ambient air temperature in real time and calculating their temperature difference data, the actual water status and transpiration heat dissipation effect of the plant can be directly reflected. When the plant has sufficient water, transpiration is vigorous, and the canopy temperature will be relatively low; conversely, it will rise. Therefore, the trend of temperature difference data becomes a direct physiological indicator for evaluating the irrigation effect. Based on this evaluation result, the water requirement coefficient is dynamically corrected, so that the target water volume for the next irrigation can more accurately adapt to the real-time water requirements of the plant, thus forming a closed-loop adaptive irrigation control system. This mechanism ensures that irrigation decisions are no longer based on static presets, but on the actual physiological feedback of plants, thereby significantly improving the accuracy and efficiency of irrigation.

[0073] Through the above technical solution, this application enables precise and adaptive control of rainwater infiltration irrigation. Compared to schemes that determine the target water volume solely based on preset parameters, this application introduces the temperature difference between the plant canopy temperature and the ambient air temperature as an evaluation basis for irrigation effectiveness, and dynamically adjusts the water demand coefficient accordingly. This allows the irrigation water volume to more accurately match the real-time water needs of the plants, avoiding the problems of over-irrigation or under-irrigation common in traditional irrigation. Therefore, it not only effectively saves water resources and reduces irrigation costs, but also significantly improves the growth and health of plants and their yield, maximizing water resource utilization efficiency. This adaptive adjustment mechanism based on plant physiological feedback greatly enhances the intelligence and responsiveness of the irrigation system.

[0074] In some preferred embodiments, assuming a smart greenhouse requires rainwater harvesting and infiltration irrigation for tomato plants, the system first acquires the current ambient temperature (e.g., 28 degrees Celsius) using a temperature and humidity sensor and the light intensity (e.g., 80,000 lux) using a light sensor. Combining this with a preset water demand coefficient (e.g., 0.5), the system calculates the initial target water volume (e.g., 10 liters) according to a preset formula (e.g., V_initial = K_demand * (T_ambient - T_base) * L_factor, where T_base is the base temperature and L_factor is the light influence factor). Subsequently, a water pump is activated to deliver these 10 liters of water to the tomato area according to a calibrated effective irrigation rate. During irrigation, an infrared thermal imager continuously monitors the canopy temperature of the tomato plants, while environmental sensors monitor the ambient air temperature. For example, before irrigation begins, the canopy temperature might be 30 degrees Celsius, and the ambient air temperature might be 28 degrees Celsius, a temperature difference of 2 degrees Celsius. As irrigation progresses, the plants absorb water, transpiration increases, and the canopy temperature gradually decreases. For a period after irrigation, the system continuously monitors temperature difference data. If the temperature difference drops rapidly and stabilizes below 0.5 degrees Celsius, it indicates good irrigation results and sufficient water. In this case, the system will responsively reduce the water demand coefficient for the next irrigation, for example, adjusting it to 0.48, to avoid over-irrigation. Conversely, if the temperature difference drops slowly or fails to reach the expected level, it indicates insufficient water, and the system will increase the water demand coefficient, for example, adjusting it to 0.52, to ensure more sufficient water for the next irrigation. Through this dynamic feedback and correction mechanism, the irrigation system can continuously optimize the irrigation strategy, ensuring that the tomato plants are always in an optimal water supply state.

[0075] In some embodiments of this application described above, determining the target water volume for irrigation of the target area requires obtaining current ambient temperature information and light intensity information, and then determining the initial target water volume based on this information and the water demand coefficient. Specifically, the method for determining the initial target water volume based on ambient temperature information, light intensity information, and the water demand coefficient can be performed in the following manner:

[0076] The step of determining the initial target water volume based on the ambient temperature information, light intensity information, and water demand coefficient includes:

[0077] V_initial = K_demand * (T_ambient - T_base) * L_factor;

[0078] Wherein, V_initial is the initial target water volume; K_demand is the water demand coefficient, which reflects the basic water demand under environmental stimuli, and the initial value of the water demand coefficient is preset; T_ambient is the real-time ambient temperature; T_base is a preset reference temperature, and when the ambient temperature is lower than the reference temperature, the water demand decreases; L_factor is the light influence factor calculated based on the real-time light intensity.

[0079] Specifically, V_initial represents the amount of irrigation water required by the target area under current environmental conditions. K_demand is the water demand coefficient, which quantifies the basic water requirement of plants under specific environmental stimuli. The initial value of this coefficient is usually preset based on experience or experimental data. T_ambient refers to the ambient temperature information collected in real time by sensors, reflecting the current climate conditions. T_base is the preset baseline temperature. When the real-time ambient temperature T_ambient is lower than this baseline temperature T_base, it indicates that plant transpiration is reduced, and the water requirement is correspondingly reduced. L_factor is the light influence factor calculated based on real-time light intensity information, reflecting the impact of light intensity on plant transpiration and water requirement. Generally, the stronger the light, the greater the water requirement.

[0080] This application's solution incorporates environmental temperature, light intensity, and water requirement coefficients, and employs a specific calculation formula to make the determination of the initial target water volume more scientific and accurate. This formula comprehensively considers the impact of environmental temperature on plant transpiration; that is, when the environmental temperature rises, plant transpiration increases, and water requirement increases; when the environmental temperature is below the baseline temperature, plant water requirement decreases. Simultaneously, light intensity, as another key environmental factor, is incorporated into the calculation through the light influence factor L_factor, ensuring that the actual water requirement of plants under different light conditions can be accurately estimated. This approach avoids the inaccuracies of traditional methods that rely solely on experience or fixed values ​​to determine irrigation water volume, thus providing a more reasonable initial water volume basis for subsequent irrigation tasks.

[0081] In some embodiments described above, an initial target water volume is determined based on ambient temperature, light intensity, and water demand coefficient. This initial target water volume is then delivered to the target area according to an effective irrigation rate. Simultaneously, plant canopy temperature and ambient air temperature are monitored to determine the temperature difference between the two. The irrigation effect is then evaluated based on the trend of this temperature difference. However, simply mentioning "evaluating the irrigation effect based on the trend of the temperature difference" may lack a detailed explanation of the specific evaluation process, affecting the accuracy and consistency of the evaluation results. For example, failure to systematically collect data or the lack of clear evaluation standards may prevent accurate assessment of the plant's actual water demand, thus affecting subsequent corrections to the water demand coefficient and potentially leading to insufficient or excessive irrigation.

[0082] In response, this application further proposes a method for determining the temperature difference between the plant canopy temperature and the ambient air temperature, and for evaluating the irrigation effect based on the trend of the temperature difference data, aiming to provide a more accurate and systematic irrigation effect evaluation mechanism.

[0083] The above-mentioned determination of the temperature difference data between the plant canopy temperature and the ambient air temperature, and the evaluation of irrigation effectiveness based on the changing trend of the temperature difference data, includes:

[0084] After the irrigation task is completed, a response observation period is initiated; during the response observation period, plant canopy temperature information and ambient air temperature information are collected periodically.

[0085] Temperature difference trend data is calculated based on periodically collected plant canopy temperature information and ambient air temperature information.

[0086] The temperature difference trend data is compared with a preset temperature difference change threshold to evaluate the irrigation effect.

[0087] Specifically, the "response observation period" refers to a time period set after the irrigation task is completed to observe the physiological response of the plants to irrigation. The length of this observation period can be preset or dynamically adjusted according to factors such as plant species, environmental conditions, and irrigation volume; for example, it can be set to several hours to several days. The purpose is to ensure that data collection and evaluation are carried out only after the plants have fully absorbed water and produced a physiological response, thereby obtaining more accurate feedback on the irrigation effect.

[0088] "Periodic acquisition of plant canopy temperature and ambient air temperature information" refers to continuously acquiring plant canopy temperature and ambient air temperature data at fixed time intervals (e.g., every 5 minutes, 15 minutes, or 30 minutes) during the response observation period. This periodic acquisition method helps to capture the dynamic process of temperature changes, rather than relying solely on a single or a few measurements. Plant canopy temperature information can be measured non-contactly using an infrared thermal imager or infrared temperature sensor, while ambient air temperature information can be acquired using standard meteorological sensors.

[0089] In practical applications, "calculating and obtaining temperature difference trend data" refers to pairing periodically collected plant canopy temperature information with ambient air temperature information one by one and calculating their differences to form a series of temperature difference data points. These temperature difference data points are then analyzed to reveal their trends over time. For example, temperature difference trend data can be obtained by plotting temperature difference-time curves, calculating the average rate of temperature decrease, or performing time series analysis.

[0090] Furthermore, "comparing the temperature difference trend data with a preset temperature difference change threshold" refers to comparing the calculated temperature difference trend data (e.g., the magnitude of the temperature difference decrease, the rate of decrease, or the stable temperature difference value) with a pre-set standard. The "preset temperature difference change threshold" can be determined based on the typical temperature difference response pattern of healthy plants under sufficient water supply conditions. For example, after sufficient irrigation, the temperature difference between the canopy temperature and the ambient air temperature of healthy plants typically decreases rapidly and remains at a low level. This comparison allows for a quantitative assessment of whether the irrigation has achieved the desired effect.

[0091] This application's solution introduces a response observation period after irrigation, during which plant canopy temperature and ambient air temperature information are periodically collected, thus systematically capturing the plant's physiological response to irrigation. When plants are short of water, their transpiration decreases, leading to an increase in canopy temperature; conversely, after receiving sufficient water, transpiration increases, and canopy temperature decreases. By calculating and analyzing temperature difference trend data, changes in plant water status can be intuitively reflected. Comparing these temperature difference trend data with preset temperature difference change thresholds transforms the assessment of irrigation effectiveness from a vague qualitative judgment to a precise quantitative analysis. This mechanism ensures that the assessment of irrigation effectiveness is based on the actual physiological feedback of the plant, rather than relying solely on preset empirical parameters, thereby effectively solving the problem of lack of objectivity and accuracy in traditional methods of irrigation effectiveness assessment.

[0092] Through the above technical solution, this application provides a more refined and reliable method for evaluating irrigation effectiveness. By setting a response observation period and periodically collecting data, the plant's response to irrigation can be monitored comprehensively and dynamically, avoiding evaluation biases caused by single measurements or unstructured observations. Calculating temperature difference trend data and comparing it with preset thresholds provides a clear quantitative standard for evaluating irrigation effectiveness, significantly improving the objectivity and accuracy of the evaluation. This precise evaluation result provides a solid data foundation for subsequent correction of the water demand coefficient, thereby enabling smarter and more water-saving precision irrigation, effectively avoiding over-irrigation or under-irrigation, and ensuring the healthy growth of plants.

[0093] As a specific implementation method, assume that after an irrigation task, the system initiates a 2-hour response observation period. During this period, every 10 minutes, the system collects plant canopy temperature information via infrared sensors and ambient air temperature information via environmental sensors. For example, before irrigation, the plant canopy temperature is 30°C, the ambient air temperature is 25°C, and the temperature difference is 5°C. After the irrigation task, during the response observation period, the system periodically records the temperature difference data: 3.5°C after 10 minutes, 2.0°C after 20 minutes, 1.5°C after 30 minutes, and then gradually stabilizes at around 1.0°C. The system plots these temperature difference data into a trend graph and calculates the average rate of temperature decrease. If the preset temperature difference threshold requires the temperature difference to drop below 2°C within 30 minutes, and the average rate of decrease exceeds 0.1°C / minute, then based on the above data, the system can assess the irrigation effect as sufficient water. Conversely, if the temperature difference decreases slowly or fails to reach the preset threshold, it is assessed as insufficient water.

[0094] In some embodiments described above, plant canopy temperature and ambient air temperature are periodically collected, and temperature difference trend data is calculated. This data is then compared with a preset temperature difference change threshold to evaluate irrigation effectiveness. However, in practical applications, due to rapid changes in environmental factors or noise from the sensors themselves, the directly obtained temperature difference data may contain instantaneous fluctuations or outliers. This can result in insufficient smoothness of the temperature difference trend data, affecting the accuracy and stability of irrigation effectiveness evaluation. If this problem is not addressed, it may lead to misjudgment of the plant's water requirement, thus affecting the rationality of the irrigation strategy. Therefore, this application further proposes an optimization scheme: filtering the temperature difference data to obtain smoother and more reliable temperature difference trend data, thereby improving the accuracy of irrigation effectiveness evaluation.

[0095] Before comparing the temperature difference trend data with a preset temperature difference change threshold, the method further includes: filtering the temperature difference data to obtain smooth temperature difference trend data; wherein, filtering the temperature difference data to obtain smooth temperature difference trend data includes: acquiring current environmental condition information and current growth stage information of the plant; dynamically adjusting filtering parameters based on the current environmental condition information and current growth stage information; and filtering the temperature difference data based on the adjusted filtering parameters to obtain smooth temperature difference trend data.

[0096] Specifically, filtering temperature difference data refers to using specific algorithms to process the temperature difference data between the raw plant canopy temperature information and the ambient air temperature information. This process eliminates or reduces noise, instantaneous fluctuations, or outliers in the data, resulting in more stable, continuous temperature difference trend data that accurately reflects the plant's physiological state. Smooth temperature difference trend data means that after filtering, the data curve becomes flatter, eliminating spikes and irregular fluctuations, making the trend clearer and more discernible.

[0097] Obtaining current environmental conditions information can be understood as real-time monitoring or acquiring environmental parameters related to the irrigation area from external systems, such as wind speed, air humidity, solar radiation intensity, and soil moisture. This information is crucial for understanding the reasons for fluctuations in temperature difference data. The current growth stage information of the plants refers to the life cycle stage of the plants within the target area, such as seedling stage, vegetative growth stage, flowering stage, fruiting stage, or maturity stage. Plants at different growth stages have different sensitivities to environmental changes and different water requirements.

[0098] In practical applications, dynamically adjusting filtering parameters refers to intelligently selecting or modifying the parameter settings of the filtering algorithm based on the acquired information about current environmental conditions and the current growth stage of the plant. For example, when the ambient wind speed is high or the light intensity fluctuates drastically, temperature difference data may be more easily disturbed. In this case, filtering parameters can be adjusted, such as increasing the filter window size (for moving average filtering) or adjusting the filter coefficient (for exponential smoothing filtering), to enhance the filtering strength and more effectively suppress noise. Conversely, when environmental conditions are stable, the filtering strength can be weakened to retain more details of the original data. Similarly, during growth stages where the plant is sensitive to changes in water (such as flowering or fruiting), more refined filtering may be needed to ensure the accuracy of temperature difference trend data and avoid misjudgments.

[0099] The proposed solution effectively eliminates potential noise and instantaneous fluctuations in the original data by introducing a filtering process before comparing the temperature difference trend data with a preset threshold. This smoothing process makes subsequent trend analysis and threshold comparison more accurate and reliable. Specifically, by acquiring information on current environmental conditions and the plant's current growth stage, the system can dynamically adjust the filtering parameters. For example, in environments with high wind speeds or drastic light changes, or when the plant is in a specific growth stage sensitive to water, a stronger filtering algorithm or a larger filtering window can be used to better suppress noise; conversely, in relatively stable environments or when the plant is in a non-sensitive stage, a weaker filter can be used to retain more of the original data characteristics. This dynamic adjustment mechanism ensures the adaptability and effectiveness of the filtering process, avoiding the problems of over-smoothing or under-smoothing that may result from fixed filtering parameters. This allows the obtained smoothed temperature difference trend data to more accurately reflect the plant's actual water requirements.

[0100] Through the above technical solution, this application can significantly improve the accuracy and stability of irrigation effect evaluation. By effectively filtering the temperature difference data, interference from environmental noise and measurement errors is eliminated, allowing the obtained temperature difference trend data to more accurately and smoothly reflect the physiological response of the plants. This improvement avoids misjudgments caused by data fluctuations, thus making subsequent water demand coefficient correction and irrigation task control more precise. Furthermore, by dynamically adjusting the filtering parameters according to environmental conditions and plant growth stages, the solution of this application exhibits higher adaptability, providing optimal data processing results for different scenarios, further enhancing the intelligence level and resource utilization efficiency of the entire rainwater harvesting and infiltration irrigation control system.

[0101] In some preferred embodiments, it is assumed that the target area is planted with tomatoes, and the tomatoes are currently in the fruit enlargement stage, a phase that requires a large amount of water and is sensitive to environmental changes. Simultaneously, the current environmental conditions are monitored to be characterized by high wind speeds and frequent fluctuations in light intensity. In this case, the system first acquires information about the tomato's fruit enlargement stage and the environmental conditions of high wind speeds and frequent light fluctuations. Based on this information, the system dynamically adjusts the filtering parameters. For example, it may change the filtering algorithm for temperature difference data from a simple moving average filter to a more complex Kalman filter, or increase the window size of the moving average filter to enhance noise suppression. Through this dynamically adjusted filtering process, even under unstable environmental conditions, smooth and accurate temperature difference trend data can be extracted from the original, potentially noisy, plant canopy temperature and ambient air temperature information. For example, after filtering, the instantaneous temperature difference decreases or increases caused by wind speed are effectively smoothed, making the temperature difference trend line more stably reflect the plant's true cooling response after irrigation. Subsequently, this smooth temperature difference trend data is compared with the preset healthy temperature difference threshold, which enables a more accurate assessment of irrigation effectiveness, avoids misjudgments caused by noise in the raw data, and ensures that tomatoes are provided with the appropriate amount of water during critical growth stages.

[0102] In some embodiments described above, a method is proposed to calculate temperature difference trend data based on periodically collected plant canopy temperature information and ambient air temperature information, and then compare the temperature difference trend data with a preset temperature difference change threshold to evaluate irrigation effectiveness. However, in its implementation, providing only a general evaluation standard may lead to inaccurate or subjective evaluation results, resulting in a lack of clear basis for subsequent adjustments to the water demand coefficient, thus affecting the optimization of irrigation strategies and the effective utilization of water resources.

[0103] To address this, this application further proposes a specific method for comparing the aforementioned temperature difference trend data with a preset temperature difference change threshold to assess irrigation effectiveness, and for adjusting the water demand coefficient based on the assessment results. Specifically, the method includes: if, during the observation period, the temperature difference data rapidly decreases and stabilizes below a preset healthy temperature difference threshold, or the average rate of decrease of the temperature difference data exceeds a preset value, then the irrigation effectiveness is determined to be sufficient water; if, during the observation period, the temperature difference data fails to decrease below the healthy temperature difference threshold, or the rate of decrease is too slow, then the irrigation effectiveness is determined to be insufficient water; and adjusting the water demand coefficient based on the irrigation effectiveness includes: in response to an sufficient water effect, reducing the water demand coefficient for the next irrigation; and in response to an insufficient water effect, increasing the water demand coefficient for the next irrigation.

[0104] Specifically, "the temperature difference data rapidly decreases and stabilizes below the preset healthy temperature difference threshold" means that after irrigation, the temperature difference between the plant canopy temperature and the ambient air temperature shows a rapid decreasing trend during the observation period, and remains relatively stable after reaching a certain low, preset healthy temperature difference threshold. This healthy temperature difference threshold is usually preset according to different plant species, growth stages, and environmental conditions to indicate the ideal temperature difference for plants under non-stress conditions. For example, this healthy temperature difference threshold can be set to 2℃, indicating that the difference between the canopy temperature and the ambient temperature is within 2℃, and the plant is in a good moisture state.

[0105] The phrase "the average rate of decrease in temperature difference data exceeds a preset value" refers to a rapid decrease in temperature difference data during the response observation period, indicating a rapid and positive response from the plants to irrigation. This preset value can be determined based on historical data or experimental results; for example, it can be set to a decrease of 3°C per hour.

[0106] "The temperature difference data failed to drop below the healthy temperature difference threshold" means that at the end of the response observation period, the temperature difference data was still higher than the preset healthy temperature difference threshold, indicating that the plant may still be under water stress and the irrigation amount is insufficient to restore it to the ideal state. "The rate of decrease is too slow" means that although the temperature difference data has decreased, its rate of decrease has not reached the preset average rate of decrease, or the decreasing trend is not obvious, indicating poor irrigation effect and low water absorption and utilization efficiency of the plant. "Reduce the water requirement coefficient" means that when the assessment result indicates sufficient water, the water requirement coefficient used for the next irrigation will be appropriately lowered to avoid over-irrigation and water waste. For example, it can be decreased in increments of a preset step size (e.g., 0.05). "Increase the water requirement coefficient" means that when the assessment result indicates insufficient water, the water requirement coefficient used for the next irrigation will be appropriately increased to ensure that the plant receives sufficient water. For example, it can be increased in increments of a preset step size (e.g., 0.05).

[0107] This application's solution precisely assesses irrigation effectiveness by introducing specific temperature difference data change standards, resolving the potential ambiguity and subjectivity issues of traditional assessment methods. After irrigation, the temperature difference between the plant canopy temperature and the ambient air temperature directly reflects the plant's water status. When water is sufficient, the plant dissipates heat through transpiration, causing the canopy temperature to drop and approach the ambient temperature, resulting in a smaller temperature difference. Conversely, when water is insufficient, transpiration is limited, causing the canopy temperature to rise and the temperature difference to increase. By setting a "healthy temperature difference threshold" and a "preset value for the average rate of decrease," the system can quantitatively determine whether the plant has received sufficient water. For example, a rapid decrease and stabilization of the temperature difference below the healthy temperature difference threshold, or a decrease rate exceeding the preset value, indicates sufficient water, vigorous transpiration, and good heat dissipation. Conversely, a failure to decrease the temperature difference below the healthy temperature difference threshold or a slow decrease rate indicates that the plant is still under water stress. Based on these clear judgment criteria, the system can automatically and accurately assess irrigation effectiveness and directly correlate the assessment results with the correction of the water demand coefficient. When water availability is assessed as sufficient, reducing the water demand coefficient can prevent over-supply during the next irrigation; conversely, when water availability is assessed as insufficient, increasing the water demand coefficient ensures that the next irrigation will meet the plant's actual needs. This closed-loop feedback mechanism allows irrigation strategies to be dynamically adjusted based on the plant's actual response, thereby achieving precision irrigation.

[0108] Through the above technical solution, this application provides a more accurate and automated irrigation effect evaluation mechanism. Compared with the basic approach that simply compares temperature difference trend data with preset thresholds, this application significantly improves the accuracy and reliability of irrigation effect evaluation by introducing specific temperature difference change patterns (such as the rate of decrease and steady state) as the judgment criteria. This avoids over-irrigation or under-irrigation due to inaccurate evaluation, effectively conserves water resources, and ensures that plants receive optimal growth conditions. Furthermore, by directly mapping the evaluation results to the correction of the water demand coefficient, adaptive adjustment of the irrigation strategy is achieved, enabling the system to optimize based on the real-time physiological response of the plants, thereby improving the intelligence level and operational efficiency of the entire rainwater harvesting and infiltration irrigation system.

[0109] As a specific implementation method, a concrete example is given below. Assume that after an irrigation task, the system initiates a response observation period, periodically collecting plant canopy temperature information and ambient air temperature information, and calculating temperature difference trend data. The preset healthy temperature difference threshold is 2℃, and the preset average temperature decrease rate is 3℃ per hour.

[0110] Scenario 1: During the response observation period, the monitored temperature difference data decreased from an initial 5℃ to 1.5℃ within 2 hours, and then stabilized at around 1.5℃. At this point, the temperature difference data rapidly decreased and stabilized below the preset healthy temperature difference threshold of 2℃, and the system determined that the irrigation effect was sufficient. In response, the system reduced the water demand coefficient for the next irrigation from 0.8 to 0.75.

[0111] Scenario 2: During the response observation period, the monitored temperature difference data decreased from an initial 5℃ to only 3℃ within 2 hours, and the rate of decrease was 1℃ per hour, failing to reach the preset average rate of decrease of 3℃ per hour, and also failing to decrease below the healthy temperature difference threshold of 2℃. In this case, the system determines that the irrigation effect is insufficient water. In response, the system increases the water demand coefficient for the next irrigation from 0.8 to 0.85.

[0112] Through the aforementioned specific judgment criteria and correction mechanisms, the system can dynamically adjust irrigation strategies based on the actual physiological feedback of the plants, thereby achieving refined management and efficient utilization of water resources.

[0113] In some of the embodiments described above in this application, the irrigation effect is evaluated and the water demand coefficient is corrected based on the trend of temperature difference data between plant canopy temperature information and ambient air temperature information. However, in practical applications, temperature difference data may be affected by factors such as sensor failure and sudden environmental changes, resulting in abnormal data. If the water demand coefficient is corrected directly based on abnormal data, errors may be introduced, affecting the accuracy and stability of the irrigation strategy.

[0114] In response, this application further proposes that the steps for correcting the water demand coefficient based on irrigation effect include: performing anomaly detection on the temperature difference data to identify abnormal data that exceeds the normal fluctuation range or rate of change; suspending the water demand coefficient correction based on the temperature difference data and triggering an anomaly alarm when the abnormal data is present; and re-collecting data and evaluating the irrigation effect after the anomaly is resolved, and restoring the normal water demand coefficient correction process.

[0115] Specifically, anomaly detection of the temperature difference data refers to analyzing the temperature difference data between the real-time collected plant canopy temperature information and the ambient air temperature information using specific algorithms or models to determine whether the data deviates from the expected normal pattern. For example, statistical methods (such as Z-score, IQR), machine learning methods (such as isolated forest, LOF), or rule-based methods can be used to identify abnormal data. The purpose is to ensure the reliability of the data used to correct the water demand coefficient.

[0116] Identifying anomalous data that exceeds normal fluctuation ranges or rates of change can be understood as detecting data points that significantly deviate from historical averages, predicted values, or preset thresholds, or data sequences whose rates of change are abnormally fast or slow. For example, when temperature difference data experiences drastic jumps within a short period, or remains at an unreasonably fixed value for an extended period, it can be identified as anomaly. The aim is to filter out inaccurate data caused by external interference or sensor malfunctions.

[0117] In practical applications, upon detecting the aforementioned abnormal data, the system will immediately suspend the water demand coefficient correction operation based on the temperature difference data to prevent erroneous correction instructions from being executed. Simultaneously, the system will trigger an alarm, such as through audible and visual signals, SMS notifications, or interface prompts, alerting administrators to the existence of data anomalies requiring manual intervention. The purpose is to prevent erroneous data from negatively impacting the irrigation system and to promptly notify users to address the anomaly.

[0118] Once the anomaly is resolved, such as when sensors return to normal and environmental interference is eliminated, the system will resume collecting plant canopy temperature and ambient air temperature data, and reassess the irrigation effect based on the new, reliable temperature difference data. Once the assessment confirms that the data has returned to normal and the irrigation effect is reliable, the system will resume its normal water demand coefficient correction process to ensure the continuity and accuracy of the irrigation strategy. The purpose is to ensure that the system can smoothly and accurately resume normal operation after handling anomalies.

[0119] This application's solution effectively addresses the problem of erroneous irrigation strategies that might result from directly correcting the water demand coefficient based on unreliable data when anomalies occur. Specifically, when an anomaly is identified in the temperature difference data, the system immediately suspends the correction of the water demand coefficient, thus preventing the generation of erroneous correction commands. Simultaneously, by triggering an anomaly alarm, operators can be promptly notified to intervene, quickly locate and resolve the problem. Once the anomaly is resolved, the system intelligently resumes data acquisition and evaluation, and restarts the water demand coefficient correction process. This ensures that the irrigation system maintains the accuracy and stability of its decision-making even when facing uncertain data, preventing over-irrigation or under-irrigation caused by data anomalies.

[0120] Through the above technical solution, this application can significantly improve the robustness and reliability of the rainwater harvesting and seepage irrigation water control method. In actual operation, even if sensor failure or sudden environmental changes cause data anomalies, the system can promptly identify and take countermeasures, avoiding the negative impact of correcting the water demand coefficient based on erroneous data. This not only ensures the accuracy of the irrigation strategy and prevents resource waste or poor crop growth due to erroneous corrections, but also improves the maintainability and user experience of the system through an anomaly alarm mechanism, enabling the entire rainwater harvesting and seepage irrigation system to operate more stably and efficiently, thereby extending the service life of the equipment and reducing operational risks.

[0121] In some preferred embodiments, it is assumed that after an irrigation task is completed, the system enters a response observation period, periodically collecting plant canopy temperature information and ambient air temperature information, and calculating temperature difference data. During a certain collection period, due to momentary electromagnetic interference to the sensor, the collected plant canopy temperature data suddenly spikes, causing the calculated temperature difference data to far exceed the normal fluctuation range. At this time, the anomaly detection module of this application will immediately identify the temperature difference data as abnormal. The system will suspend the water demand coefficient correction based on the abnormal temperature difference data and send an anomaly alarm message to the administrator's mobile device, indicating "Temperature difference data abnormal, water demand coefficient correction has been suspended." After receiving the alarm, the administrator checks the sensor and eliminates the interference. When the sensor returns to normal operation, the system re-collects normal temperature difference data and evaluates the irrigation effect. After confirming that the data is normal, the system will resume the normal water demand coefficient correction process. For example, based on the new temperature difference trend data, the water demand coefficient K_demand will be adjusted from 0.8 to 0.75 to adapt to the actual water demand of the crop. This avoids the water demand coefficient being erroneously increased or decreased due to instantaneous data anomalies, and ensures the accuracy of subsequent irrigation.

[0122] This application also discloses a rainwater harvesting and infiltration irrigation water volume control system, such as... Figure 2 As shown, the system includes:

[0123] The calibration module 201 is used to start the water pump and determine the first water output and first water output rate of the water storage tank within a first preset time period when the main pipeline valve is closed; and determine the second water output and second water output rate of the water storage tank within a second preset time period when the main pipeline valve is open.

[0124] The determining module 202 is used to determine the effective irrigation rate based on the first water outflow rate and the second water outflow rate;

[0125] The control module 203 is used to determine the target amount of water to be irrigated to the target area, determine the remaining irrigation time based on the target amount of water and the effective irrigation rate, and control the water pump to perform the irrigation task based on the remaining irrigation time.

[0126] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for controlling rainwater harvesting and infiltration irrigation volume, characterized in that, The method includes: Start the water pump, and when the main pipeline valve is closed, determine the first water output and the first water output rate of the water storage tank within the first preset time period; when the main pipeline valve is opened, determine the second water output and the second water output rate of the water storage tank within the second preset time period. The effective irrigation rate is determined based on the first water outflow rate and the second water outflow rate. Determine the target water volume to be irrigated in the target area, determine the remaining irrigation time based on the target water volume and the effective irrigation rate, and control the water pump to perform the irrigation task based on the remaining irrigation time.

2. The method for controlling rainwater harvesting and infiltration irrigation volume according to claim 1, characterized in that, The step of determining the first outflow volume and first outflow rate of the water storage tank within a first preset time period when the main pipeline valve is closed includes: During the first preset time period, the water pump is started, the main pipeline valve is closed, and the first drop in the water level of the rainwater collection tank is monitored; the first outflow volume is determined based on the first drop in the water level and the cross-sectional area of ​​the rainwater collection tank; and the first outflow rate is determined based on the ratio of the first outflow volume to the first preset time; wherein, the first outflow rate indicates the leakage rate of the pipeline section between the water pump and the main pipeline valve. The step of determining the second outflow volume and second outflow rate of the water storage tank within the second preset time period when the main pipeline valve is opened includes: During the second preset time period, the water pump is started, the main pipeline valve is opened, and the second liquid level drop in the rainwater collection and storage tank is monitored; the second water output is determined based on the second liquid level drop and the cross-sectional area of ​​the rainwater collection and storage tank; and the second water output rate is determined based on the ratio of the second water output to the second preset time.

3. A method for controlling rainwater harvesting and infiltration irrigation volume according to claim 1 or 2, characterized in that, Determining the effective irrigation rate based on the first water outflow rate and the second water outflow rate includes: determining the difference between the second water outflow rate and the first water outflow rate as the effective irrigation rate.

4. The method for controlling rainwater harvesting and infiltration irrigation volume according to claim 1, characterized in that, Determine the target amount of water to irrigate the target area, including: Obtain current ambient temperature and light intensity information; determine the initial target water volume based on the ambient temperature, light intensity, and water demand coefficient. The initial target water volume is delivered to the target area according to the effective irrigation rate, while monitoring plant canopy temperature and ambient air temperature. Determine the temperature difference between the plant canopy temperature and the ambient air temperature, evaluate the irrigation effect based on the trend of the temperature difference data, and adjust the water demand coefficient based on the irrigation effect.

5. The method for controlling rainwater harvesting and infiltration irrigation volume according to claim 4, characterized in that, The step of determining the initial target water volume based on the ambient temperature information, light intensity information, and water demand coefficient includes: V_initial = K_demand * (T_ambient - T_base) * L_factor; Wherein, V_initial is the initial target water volume; K_demand is the water demand coefficient, which reflects the basic water demand under environmental stimuli, and the initial value of the water demand coefficient is preset; T_ambient is the real-time ambient temperature; T_base is a preset reference temperature, and when the ambient temperature is lower than the reference temperature, the water demand decreases; L_factor is the light influence factor calculated based on the real-time light intensity.

6. The method for controlling rainwater harvesting and infiltration irrigation volume according to claim 4, characterized in that, The process of determining the temperature difference between the plant canopy temperature and the ambient air temperature, and evaluating the irrigation effect based on the trend of the temperature difference data, includes: After the irrigation task is completed, a response observation period is initiated; during the response observation period, plant canopy temperature information and ambient air temperature information are collected periodically. Temperature difference trend data is calculated based on periodically collected plant canopy temperature information and ambient air temperature information. The temperature difference trend data is compared with a preset temperature difference change threshold to evaluate the irrigation effect.

7. The method for controlling rainwater harvesting and infiltration irrigation volume according to claim 6, characterized in that, Before comparing the temperature difference trend data with a preset temperature difference change threshold, the method further includes: filtering the temperature difference data to obtain smooth temperature difference trend data. The step of filtering the temperature difference data to obtain smooth temperature difference trend data includes: acquiring current environmental condition information and current growth stage information of the plant; dynamically adjusting the filtering parameters based on the current environmental condition information and current growth stage information; and filtering the temperature difference data based on the adjusted filtering parameters to obtain smooth temperature difference trend data.

8. The method for controlling rainwater harvesting and infiltration irrigation volume according to claim 6, characterized in that, The temperature difference trend data is compared with a preset temperature difference change threshold to evaluate the irrigation effect, including: if the temperature difference data rapidly decreases and stabilizes below the preset healthy temperature difference threshold during the observation period, or if the average rate of decrease of the temperature difference data exceeds a preset value, then the irrigation effect is determined to be sufficient water; if the temperature difference data fails to decrease below the healthy temperature difference threshold during the observation period, or if the rate of decrease is too slow, then the irrigation effect is determined to be insufficient water. Based on the irrigation effect, the water demand coefficient is adjusted, including: in response to the irrigation effect being sufficient water, decreasing the water demand coefficient for the next irrigation; and in response to the irrigation effect being insufficient water, increasing the water demand coefficient for the next irrigation.

9. The method for controlling rainwater harvesting and infiltration irrigation volume according to claim 4, characterized in that, The step of adjusting the water demand coefficient based on the irrigation effect includes: Anomaly detection is performed on the temperature difference data to identify abnormal data that exceeds the normal fluctuation range or rate of change. In response to the presence of the abnormal data, the water demand coefficient correction based on the temperature difference data is suspended and an abnormality alarm is triggered; once the abnormality is resolved, the data is re-collected and the irrigation effect is evaluated, and the normal water demand coefficient correction process is resumed.

10. A rainwater harvesting and infiltration irrigation water volume control system, characterized in that, The system includes: The calibration module is used to start the water pump and determine the first water output and first water output rate of the water storage tank within a first preset time period when the main pipeline valve is closed; and to determine the second water output and second water output rate of the water storage tank within a second preset time period when the main pipeline valve is open. The determining module is used to determine the effective irrigation rate based on the first water outflow rate and the second water outflow rate; The control module is used to determine the target amount of water to be irrigated to the target area, determine the remaining irrigation time based on the target amount of water and the effective irrigation rate, and control the water pump to perform the irrigation task based on the remaining irrigation time.

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