A water-saving irrigation system for corn planting based on drought risk management

Abstract

The present invention relates to the field of water-saving irrigation technology, specifically a corn planting water-saving irrigation system based on drought risk management. The system includes a crop stress status monitoring module that obtains the corn canopy temperature and the ambient temperature and calculates the temperature difference between the canopy and the environment. In the present invention, the actual stress state of the crop is quantified by obtaining the difference between the corn canopy temperature and the ambient temperature in real time. Combined with a dynamically calculated crop water stress index, the accuracy of water stress identification and response time are improved, avoiding the problems of delayed and blind irrigation decision-making. Furthermore, the actual evapotranspiration demand of the crop is accurately determined by dynamically monitoring the rate of change of latent heat flux, avoiding the misjudgment that may be caused by single monitoring of temperature difference, and ensuring the accuracy of irrigation demand determination. At the same time, the price, flow rate and available amount of different water sources are comprehensively optimized, and the ratio of water source use is configured based on the lowest total irrigation cost. This makes it possible to optimize water source economy and effectively reduce irrigation operation costs and resource consumption.

Description

Technical Field

[0001] The present invention relates to the technical field of water-saving irrigation, and in particular to a corn planting water-saving irrigation system based on drought risk management. Background Art

[0002] The field of water-saving irrigation technology is an important branch of modern agricultural water resources management. It mainly studies how to maximize agricultural water use efficiency, minimize energy consumption in the irrigation process, and minimize the ecological and environmental burden through scientific allocation of water sources, precise scheduling of irrigation systems, and dynamic monitoring of soil moisture conditions, while ensuring the normal growth needs of crops.

[0003] Existing technologies primarily rely on fixed irrigation schedules and uniform water volumes. These strategies lack real-time, dynamic monitoring and quantitative processing of crop water stress levels, making it difficult to adjust irrigation volumes based on actual crop needs, leading to over-irrigation or under-irrigation. Furthermore, existing technologies often rely on manual experience or periodic data monitoring to determine irrigation timing, making it difficult to accurately capture changes in crop water requirements in a timely manner. This reduces water use efficiency and may affect crop yield stability. Therefore, improvements are needed. Summary of the Invention

[0004] The purpose of the present invention is to solve the shortcomings of the existing technology and propose a corn planting water-saving irrigation system based on drought risk management.

[0005] In order to achieve the above objectives, the present invention adopts the following technical solutions: A corn planting water-saving irrigation system based on drought risk management comprises:

[0006] The crop stress status monitoring module obtains the corn canopy temperature and the ambient temperature, calculates the temperature difference between the canopy and the environment, and calculates the crop water stress index;

[0007] The precise irrigation demand diagnosis module compares the crop water stress index with the synergistic threshold and evaluates whether the latent heat flux change rate is lower than the rate threshold. If both are true, a synergistic irrigation trigger signal is generated to calculate the total water volume of the current irrigation operation and establish the target irrigation water demand.

[0008] The multi-source irrigation cost scheduling module receives the target irrigation water demand, obtains the unit price, maximum available flow rate, and total available quantity limit of multiple water sources, sums the product of the water use amount and the unit price of each water source, and forms a water source extraction plan based on the minimum sum of the total irrigation cost. The water source extraction plan is then integrated into the scheduling cycle to formulate an economic irrigation scheduling plan.

[0009] The irrigation instruction generation and execution module analyzes the economic irrigation scheduling plan, generates a device control timing list based on the water intake and available flow of different water sources, and then combines the sequence and time nodes of each action in the device control timing list into an irrigation control instruction set.

[0010] Preferably, the steps for obtaining the crop water stress index are:

[0011] Synchronously record the corn canopy temperature and the ambient temperature, extract the temperature difference to form a temperature difference sequence, calculate and mark the current moment's canopy and ambient temperature difference, and obtain the canopy and ambient temperature difference;

[0012] Based on the temperature difference between the canopy and the environment, and referring to the lower temperature difference of sufficient water and the upper temperature difference of severe stress set in the field, the sensible heat flux, net radiation and soil heat flux are recorded simultaneously to obtain the stress-related input group;

[0013] Calculate the crop water stress index based on the stress-related input group.

[0014] Preferably, the steps of obtaining the coordinated irrigation trigger signal are:

[0015] Based on the crop water stress index, extract the current crop water stress index value, compare the value with the collaborative threshold, and if the crop water stress index is greater than the collaborative threshold, mark it as a water stress state; otherwise, mark it as a water stress state, and generate a crop water stress judgment result;

[0016] According to the crop water stress judgment result, the latent heat flux values ​​at two adjacent moments in the current period are read, the latent heat flux value change and the change rate are calculated in units of time intervals, and the calculated latent heat flux change rate is compared item by item with a set latent heat flux change rate threshold. If the latent heat flux change rate is less than the latent heat flux change rate threshold, it is marked as an insufficient evapotranspiration state; otherwise, it is marked as a normal evapotranspiration state, and a latent heat flux rate judgment result is generated;

[0017] Based on the crop water stress judgment result and the latent heat flux rate judgment result, if both are in a water stress establishment state and an evaporation deficiency state, a coordinated irrigation trigger signal is generated.

[0018] Preferably, the steps for obtaining the target irrigation water requirement are:

[0019] Based on the collaborative irrigation trigger signal, the plot number and execution period number bound to the trigger signal are identified, the current growth period classification identifier, the previous irrigation timestamp and the previous irrigation water volume parameters, and the current soil moisture monitoring value are extracted, the time interval from the previous irrigation and the soil moisture consumption rate are calculated, and the growth period characteristic parameter set and the water consumption trend indicator are obtained;

[0020] According to the growth period characteristic parameter set and water consumption trend index, various indicators in the standard water requirement parameter library corresponding to the current growth period are retrieved, including the average water consumption per plant, the target moist layer depth and the root zone volume per unit area. Combined with the total planting area and row density parameters corresponding to the identified plot number, the regional water requirement volume is matched and calculated to obtain the target irrigation water requirement.

[0021] Preferably, the steps for obtaining the water source water intake plan are:

[0022] Based on the target irrigation water demand, read the information forms of all alternative water sources, extract the unit volume price, maximum hourly flow rate, and total water limit available in the current scheduling cycle of each water source, and organize them into alternative water source parameter sets by water source type to generate an alternative water source parameter set;

[0023] According to the set of candidate water source parameters and based on the target irrigation water demand, different water extraction combinations are traversed for each water source one by one, and the product of the volume used by each water source and the corresponding unit volume price under different water extraction scenarios is calculated respectively. The product results of each water source are cumulatively added to obtain the total irrigation cost value corresponding to each combination scenario, thereby generating an irrigation cost combination set;

[0024] Based on the irrigation cost combination set, the total irrigation cost values ​​corresponding to all combination situations are traversed, and they are compared and sorted item by item. The water source volume allocation scheme corresponding to the situation with the smallest total irrigation cost value is selected to generate a water source water intake plan.

[0025] Preferably, the steps for obtaining the economic irrigation scheduling plan are:

[0026] Based on the water source extraction plan, extract the extraction time period, hourly extraction flow value and water extraction duration of each water source, cross-compare the extraction time period of each water source with all available time periods in the current scheduling cycle, screen the compatible scheduling time node range, and generate a set of scheduling adaptable time windows;

[0027] According to the set of adaptable time windows for scheduling, the water extraction time periods of each water source are allocated to the corresponding positions in the scheduling cycle one by one. The flow of each water source is verified and screened against the maximum allowable concurrent flow limit in the scheduling cycle. All conflicting time periods that do not meet the concurrent flow limit are eliminated to obtain an economic irrigation scheduling plan.

[0028] Preferably, the steps of obtaining the device control timing list are:

[0029] Analyze the economic irrigation scheduling plan, extract the water intake, working flow, start and end time of the allowed time window, energy consumption per unit flow, electricity price function curve and pipe network pressure impact coefficient of each water source, construct a scheduling parameter structure set by sorting the water source numbers, and generate a multidimensional water source scheduling parameter matrix;

[0030] Calculating the equipment startup duration and initial startup time based on the multi-dimensional water source scheduling parameter matrix;

[0031] Generate a device control timing list based on the device startup time and initial startup time.

[0032] Preferably, the steps of acquiring the irrigation control instruction set are:

[0033] According to the device control timing list, the pump or valve device number corresponding to each device action is extracted. According to the communication protocol standard and hardware control specification of each device, the start execution timestamp and the stop execution timestamp are converted into the digital signal form of relay opening and closing, and mapped one by one according to the device number to the corresponding device control digital signal sequence to generate a water pump valve digital control signal set;

[0034] Based on the water pump and valve digital control signal set, the device control digital signal sequence corresponding to each water pump or valve is merged in sequence, and integrated into a continuous digital signal stream according to the execution order of each device control digital signal recorded in the device control action sorting sequence to generate an irrigation control instruction set.

[0035] Compared with the prior art, the advantages and positive effects of the present invention are:

[0036] In the present invention, the actual stress state of the crop is quantified by obtaining the difference between the corn canopy temperature and the ambient temperature in real time, and combined with the dynamically calculated crop water stress index, the water stress identification accuracy and response time are improved, and the problems of delayed and blind irrigation decisions are avoided; further, the actual evaporation demand of the crop is accurately judged by dynamically monitoring the change rate of the latent heat flux, avoiding the misjudgment that may be caused by single monitoring of the temperature difference, and ensuring the accuracy of irrigation demand judgment; at the same time, the prices, flow rates and available quantities of different water sources are comprehensively optimized, and the ratio of multiple water sources is configured with the lowest total irrigation cost as the standard, so that water source economic optimization becomes possible, and irrigation operation costs and resource consumption are effectively reduced; in addition, through equipment control timing arrangement and strict pressure constraint control, the pressure shock of the pipeline network and the energy cost burden are alleviated, and the safety and economy of the irrigation process are synergistically improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0039] See also Figure 1 The present invention provides a technical solution: a corn planting water-saving irrigation system based on drought risk management, comprising:

[0040] The crop stress status monitoring module obtains the corn canopy temperature and the ambient temperature, calculates the temperature difference between the canopy and the environment, and calculates the crop water stress index;

[0041] The precise irrigation demand diagnosis module compares the crop water stress index with the synergistic threshold and evaluates whether the latent heat flux change rate is lower than the rate threshold. If both are true, a synergistic irrigation trigger signal is generated to calculate the total water volume for this irrigation operation and establish the target irrigation water demand.

[0042] The multi-source irrigation cost scheduling module receives the target irrigation water demand, obtains the unit price, maximum available flow rate and total available quantity limit of multiple water sources, sums the product of the water use amount and the unit price of each water source, and forms a water source extraction plan based on the minimum sum of total irrigation cost. The water source extraction plan is then integrated into the scheduling cycle to formulate an economic irrigation scheduling plan.

[0043] The irrigation instruction generation and execution module analyzes the economic irrigation scheduling plan, generates a device control timing list based on the water intake and available flow of different water sources, and then combines the sequence and time nodes of each action in the device control timing list into an irrigation control instruction set.

[0044] The steps for obtaining the crop water stress index are as follows:

[0045] Synchronously record the corn canopy temperature and the ambient temperature, extract the temperature difference to form a temperature difference sequence, calculate and mark the current moment's canopy and ambient temperature difference, and obtain the canopy and ambient temperature difference;

[0046] Based on the temperature difference between the canopy and the environment, and referring to the lower temperature difference of sufficient water and the upper temperature difference of severe stress set in the field, the sensible heat flux, net radiation and soil heat flux were recorded simultaneously to obtain the stress-related input group;

[0047] According to the stress-related input group, the crop water stress index is calculated using the following formula:

[0048] ;

[0049] in, is the crop water stress index, is the temperature difference between the current canopy and the ambient temperature, The lower limit temperature difference for sufficient moisture, The upper temperature difference is the severe stress limit. is the sensible heat flux, is the net radiation, is the soil heat flux, It is the ratio factor of heat response and energy allocation dimension.

[0050] Specifically, the corn canopy temperature and the ambient temperature are recorded synchronously by placing a non-contact infrared thermometer above the corn planting area and a high-precision digital temperature sensor in a standard louvered box in the field. The field of view of the infrared thermometer is set to 45 degrees, vertically facing the center of the corn canopy to ensure that the measurement area covers a representative group of leaves. The digital temperature sensor is placed at a height of 2 meters from the ground. Both use a sampling period of 1 minute to continuously collect and upload temperature data. The collected canopy temperature and ambient temperature data are paired at each sampling time point, and the difference between the two, that is, the temperature difference between the canopy and the environment, is calculated. The process is carried out continuously, forming a temperature difference sequence that changes with time. For example, at 10:01 a.m., the canopy temperature is collected as 28.5°C and the ambient temperature is 27.0°C, so the temperature difference at that moment is 1.5°C. At 10:02 a.m., the canopy temperature is collected as 28.6°C and the ambient temperature is 27.1°C, so the temperature difference is 1.5°C. These continuously calculated temperature difference values ​​are stored in chronological order to form a temperature difference sequence containing hundreds of data points. The system extracts the temperature difference value at the current moment from the sequence and marks it as an immediate parameter for subsequent stress judgment, obtaining the temperature difference between the canopy and the ambient temperature.

[0051] Based on the temperature difference between the canopy and the environment obtained in the above steps, the benchmark parameters and energy balance parameters for stress judgment are further introduced. Among them, the two benchmark parameters, the lower limit temperature difference for sufficient water and the upper limit temperature difference for severe stress, need to be determined through field calibration experiments before the start of the irrigation cycle. The method for determining the lower limit temperature difference for sufficient water is to select a test field and irrigate it fully to ensure that there is no water stress during the entire sunny day. The temperature difference between the canopy and the environment is continuously measured between 12 noon and 2 pm local time, and the average value is taken as the lower limit. For example, after continuous measurement, the average temperature difference is -1.5℃, then the lower limit temperature difference for sufficient water is set to -1.5℃. The method for determining the upper limit temperature difference for severe stress is to select another test field and stop irrigation. Irrigate until the corn leaves show obvious wilting. Similarly, measure the temperature difference between the canopy and the environment at noon on a clear day, and take the average value as the upper limit. For example, if the measured average value is 5.0℃, set the upper limit temperature difference of severe stress to 5.0℃. While obtaining the current temperature difference between the canopy and the environment, measure the sensible heat flux in real time through the eddy covariance system of the field meteorological station, measure the net radiation through the net radiometer, and measure the soil heat flux through the soil heat flux plate buried 5 cm below the surface. The six data items of the current canopy and ambient temperature difference, the lower limit temperature difference of sufficient water set in the field, the upper limit temperature difference of severe stress, the sensible heat flux, the net radiation and the soil heat flux are integrated into one data record to obtain the stress-related input group.

[0052] formula: The benefit of the formula is that it constructs a more comprehensive and robust crop water stress index model by integrating information from two dimensions: heat response and energy distribution. It not only utilizes the traditional crop water stress index based on canopy temperature ( ), the core idea of , we also introduce a stress characterization based on the surface energy balance theory, namely the second term , where the sensible heat flux and effective energy (net radiation Subtract soil heat flux ) can directly reflect the distribution of energy between sensible heat and latent heat. When crop evapotranspiration weakens, the ratio will increase significantly. This dual-source judgment mechanism is determined by the ratio factor The reconciliation reduces the risk of misjudgment of a single information source (such as temperature alone) due to sudden weather changes (such as cloud cover and wind speed changes), ensures the stability and accuracy of stress diagnosis, and finally makes the change of the index smoother through square root operation.

[0053] The temperature difference between the current canopy and ambient temperatures is a direct indicator of the crop's current thermal conditions. It is obtained by measuring the corn canopy temperature with infrared thermometers deployed in the field and the ambient air temperature with a weather station. The temperature difference is then subtracted from the ambient air temperature at the same moment. This value changes dynamically, reflecting the evapotranspiration cooling effect on the crop. In this example, the value obtained through real-time monitoring in the aforementioned steps is 2.5°C.

[0054] The lower limit temperature difference of sufficient moisture represents the crop canopy cooling capacity when the soil is sufficiently moist and evapotranspiration is the strongest. It is the benchmark for defining the "no stress" state. To obtain this value, it is necessary to select a reference plot throughout the growth period of a specific corn variety to keep its soil moisture at the optimal state. Under typical meteorological conditions with clear skies and strong solar radiation, the temperature difference between the canopy and the environment is continuously measured between 12 noon and 14 noon, and the average temperature difference during this period is taken as the temperature difference. In this example, through continuous observation of the fully irrigated corn experimental field, it was found that the temperature difference was stable at around -1.5℃, so we set It is -1.5℃.

[0055] The upper temperature difference of severe stress represents the canopy temperature state when the crop is severely water-deficient, the stomata are almost closed, and the evapotranspiration is extremely weak. It is the benchmark for defining the "most severe stress" state. Its acquisition method is the same as Similarly, a reference plot was selected and water was stopped until the corn leaves showed obvious signs of permanent wilting. Under similar meteorological conditions, the temperature difference between the canopy and the environment is measured and the average value is taken. In this example, by observing the corn field with severe water shortage, the canopy temperature is much higher than the ambient temperature, and the average temperature difference is 5.0℃. Therefore, is 5.0℃.

[0056] Sensible heat flux refers to the sensible heat energy exchanged between the surface and the atmosphere through turbulence. When crop evapotranspiration decreases, more energy will be dissipated in the form of sensible heat, resulting in The value increases. This parameter is directly measured by the eddy covariance instrument deployed in the field. The sensible heat flux value measured by the eddy covariance instrument at the current moment is 150W / m 2 .

[0057] Net radiation represents the net energy after deducting the reflected and emitted radiation energy from the total radiation energy received by the surface. It is the total energy source driving the surface energy balance (including evapotranspiration). This parameter is measured by a net radiation meter installed in a field weather station. The net radiation meter measures the downward shortwave and longwave radiation as well as the upward shortwave and longwave radiation at the same time. The net radiation value is calculated comprehensively in W / m 2 In this example, the net radiation value measured by the pyranometer at the current moment is 600W / m 2 .

[0058] Soil heat flux represents the amount of heat transferred into or out of the soil. It is a component of the surface energy balance and is affected by soil temperature, humidity, and solar radiation. This parameter is measured in W / m² by a soil heat flux plate buried in the soil below the canopy at a specific depth (e.g., 5 cm) below the surface. 2 In this example, the soil heat flux value measured by the soil heat flux plate at the current moment is 50W / m 2 .

[0059] is the ratio factor of the heat response and energy allocation dimensions, and is the weight coefficient used to balance the two stress evaluation dimensions in the formula. Its value range is 0 to 1. The setting of this factor is based on the actual measurement accuracy of the field sensor and the stability of the environmental conditions. When the canopy temperature measurement is greatly disturbed by factors such as wind speed, the weight of the temperature-based dimension should be reduced, that is, the The specific value can be determined by introducing an evaluation function based on measurement uncertainty, and vice versa: ,in is the relative uncertainty of the temperature measurement term, is the relative uncertainty of the energy balance term. In this example, after analyzing the historical data of the sensor, it is estimated that the comprehensive uncertainty of the temperature term is 0.15 and the comprehensive uncertainty of the energy balance term is 0.1. Then the calculation results are .

[0060] Calculation process:

[0061] Substitute the calculated values ​​of the above parameters into the crop water stress index calculation formula:

[0062] , , , , , , .

[0063] First, calculate the dimensional part of the formula based on the thermal response:

[0064] ;

[0065] Next, calculate the dimension part of the formula based on energy distribution:

[0066] ;

[0067] Then, combine the two results with the matching factor Substituting them into the complete formula:

[0068] ;

[0069] ;

[0070] ;

[0071] ;

[0072] The results show that the current crop water stress index of corn crops ( ) The calculated value is 0.4428. The theoretical value range of this index is 0 to 1. The closer the value is to 0, the better the crop moisture status is, close to the stress-free state. The closer the value is to 1, the more severe the water stress suffered by the crop. The calculated result of 0.4428 indicates that the crop is in a mild to moderate water stress state.

[0073] The steps for obtaining the cooperative irrigation trigger signal are as follows:

[0074] Based on the crop water stress index, the current crop water stress index value is extracted and compared with the collaborative threshold. If the crop water stress index is greater than the collaborative threshold, it is marked as a water stress state; otherwise, it is marked as a water stress state, and the crop water stress judgment result is generated;

[0075] According to the crop water stress judgment result, the latent heat flux values ​​at two adjacent moments in the current period are read, and the change amount and change rate of the latent heat flux value are calculated in units of time intervals. The calculated latent heat flux change rate is compared with the set latent heat flux change rate threshold item by item. If the latent heat flux change rate is less than the latent heat flux change rate threshold, it is marked as insufficient evapotranspiration state; otherwise, it is marked as normal evapotranspiration state, and the latent heat flux rate judgment result is generated;

[0076] Based on the crop water stress judgment results and the latent heat flux rate judgment results, if both are in a water stress state and evaporation deficiency state, a coordinated irrigation trigger signal is generated.

[0077] Specifically, based on the crop water stress index, the system extracts the crop water stress index value calculated at the current moment, and calculates another value of 0.55 according to the previous step. Then, the value is compared with the synergistic threshold. The threshold is not a fixed value, but is dynamically set according to the different growth stages of corn. The setting method is as follows: for a specific growth stage, such as the large bell stage, three groups of treatments are set in the experimental field, and different crop water stress indices are set as synergistic thresholds, such as 0.4, 0.5 and 0.6. During the entire growth period, when the crop water stress index of each treatment group reaches its set threshold, irrigation is carried out. After the end of the growing season, the total yield and total irrigation water volume of each treatment group are counted, and its water use efficiency is calculated. The calculation formula is: ,in is the water use efficiency (unit: kg / m3), is the total crop yield (unit: kg / hectare), is the total water consumption (unit: cubic meters / hectare). If the measured result is: when the threshold is 0.4, the yield is 9500 kg / hectare and the water consumption is 4000 cubic meters / hectare, then When the threshold is 0.5, the yield is 9200 kg / ha, and the water consumption is 3500 m3 / ha, then When the value is 2.63 and the threshold is 0.6, the yield is 8500 kg / ha and the water consumption is 3100 m3 / ha, then The value is 2.74. Considering that the yield target is to maintain above 90% of the maximum yield (i.e. not less than 8550 kg / hectare), after comprehensive comparison, the threshold of 0.5 is selected as the collaborative threshold for this growth period because it has a higher water use efficiency while meeting the yield requirements. The current crop water stress index value of 0.55 is compared with the threshold of 0.5. Since 0.55 is greater than 0.5, the current state is marked as the water stress state, and the crop water stress judgment result is generated.

[0078] According to the result of crop water stress judgment, if and only if the result is that water stress is established, the system starts further verification of the crop evapotranspiration state, and reads the latent heat flux values ​​of two adjacent moments in the current period from the time series data collected by the field eddy covariance system. The sampling interval is 1 minute. For example, the system reads the latent heat flux value of the current moment (denoted as t) as 348W / m 2 , and the latent heat flux value of the previous minute (recorded as t-1) is 350W / m 2 Then the rate of change of latent heat flux is calculated according to the time interval, that is, (348-350) / 1=-2.0W / m 2 / minute, then, the calculated latent heat flux change rate is compared with the pre-set latent heat flux change rate threshold. The threshold is set based on: analyzing the latent heat flux data of corn with sufficient water supply during the daytime (10 am to 2 pm) under historical clear weather conditions, and statistically analyzing the distribution of its 1-minute change rate. Under normal circumstances, due to stable or enhanced light, the rate is usually positive or fluctuates slightly around zero. The lower 5% quantile of the distribution is selected as the threshold to exclude the interference of normal physiological fluctuations and short-term cloud cover. For example, through analysis of historical data, it is determined that the normal change rate range is -0.5W / m 2 / min to +2.0W / m 2 / min, so the latent heat flux change rate threshold is set to -0.5W / m 2 / min, the calculated rate is -2.0W / m 2 / min with threshold -0.5W / m 2 / minute, because -2.0 is less than -0.5, the current evapotranspiration state is marked as insufficient evapotranspiration state, and the latent heat flux rate judgment result is generated.

[0079] Based on the crop water stress judgment result and the latent heat flux rate judgment result, the system executes a collaborative judgment logic to retrieve the latest crop water stress judgment result status flag and the latent heat flux rate judgment result status flag in the internal storage. Taking the above process as an example, the crop water stress judgment result obtained by the system is "water stress established state", and the latent heat flux rate judgment result obtained at the same time is "evaporation insufficient state". The system performs a logical AND operation on these two status flags to determine whether both are established at the same time. This double verification mechanism is used to confirm the urgency and authenticity of irrigation needs. Only when based on the canopy The irrigation demand is finally confirmed only when both the temperature stress index and the evapotranspiration dynamic index based on energy balance point to water deficit. In this case, since both the "water stress state" and the "evapotranspiration deficiency state" conditions are met, the result of the logical AND operation is true. The system determines that the coordinated irrigation condition has been triggered and then generates a structured coordinated irrigation trigger signal. This signal is a data packet that contains the trigger timestamp, the plot number where the stress occurs (for example, A-02), the current crop water stress index value (0.55), and the latent heat flux change rate at the time of triggering (-2.0W / m 2 / minute), a coordinated irrigation trigger signal is generated.

[0080] The steps to obtain the target irrigation water requirement are:

[0081] Based on the coordinated irrigation trigger signal, the plot number and execution period number bound to the trigger signal are identified, the current growth period classification identifier, the previous irrigation timestamp and the previous irrigation water volume parameters, as well as the current soil moisture monitoring value are extracted, the time interval since the previous irrigation and the soil moisture consumption rate are calculated, and the growth period characteristic parameter set and water consumption trend indicator are obtained;

[0082] According to the characteristic parameter set of the growth period and the water consumption trend index, various indicators in the standard water requirement parameter library corresponding to the current growth period are retrieved, including the average water consumption per plant, the target moist layer depth and the root zone volume per unit area. Combined with the total planting area and row density parameters corresponding to the identified plot number, the regional water requirement volume is matched and calculated to obtain the target irrigation water requirement.

[0083] Specifically, based on the collaborative irrigation trigger signal, the system first parses the data contained in the signal, identifies the bound plot number as "A-02" and the execution period number as "2023071514", then queries the preset crop growth calendar based on the current date, determines that the corn in the plot is in the large bell stage, and uses this as the growth period classification identifier. At the same time, the system accesses the historical irrigation record database of the plot and finds that the last irrigation timestamp is "2023-07-10 08:00:00" and the last irrigation water volume is 500 cubic meters. In addition, the system reads the real-time volume moisture content monitoring value of each sensor (for example, deployed at a depth of 20 cm, 40 cm, and 60 cm) from the soil moisture sensor network deployed in the plot "A-02", and calculates its weighted average to obtain the current soil moisture content monitoring value of 18%. The system then calculates the current time point (2023-07-15 The interval from the last irrigation time to the last irrigation time is 5.27 days. Combining the soil moisture content after the last irrigation (for example, 28%) with the current value, the soil moisture consumption rate is calculated to be (28%-18%) / 5.27 days, or approximately 1.9% / day. This rate is the soil moisture consumption trend. Finally, the system combines the growth period classification mark "large bell mouth period", the irrigation interval "5.27 days", and the last irrigation water volume "500 cubic meters" to obtain the growth period characteristic parameter set, and uses the soil moisture consumption rate "1.9% / day" as the moisture consumption trend indicator.

[0084] According to the growth period characteristic parameter set and water consumption trend index obtained in the previous step, the system accesses an internally stored standard water requirement parameter library, which is established based on many years of field test data and crop model simulation results, and contains detailed water requirement characteristics of different corn varieties in each growth period. The system uses the growth period classification identifier "large bell period" as the search key to retrieve the corresponding parameters from the library, including the average water consumption per plant, which is 0.4 liters per plant per day, the target wet layer depth, which is 60 cm, and the root zone volume per unit area, which is 0.6 cubic meters per square meter. At the same time, the system queries the farmland geographic information system according to the plot number "A-02" in the collaborative irrigation trigger signal to obtain the data of the plot. The total planting area of ​​the plot is 20,000 square meters, and the planting row density parameters are 0.6 meters for row spacing and 0.25 meters for plant spacing. The planting density is calculated to be 6.67 plants per square meter. Subsequently, the system performs a matching calculation for the regional water demand volume. First, the total number of plants in the plot is calculated, that is, 20,000 square meters multiplied by 6.67 plants / square meter, which is 133,400 plants. The total number of plants is then multiplied by the average water consumption per plant, resulting in a total daily water consumption of 53.36 cubic meters. Taking into account the irrigation interval and the current soil moisture deficit, the system sets the planned irrigation amount to restore the soil moisture content from the current 18% to 85% of the field water holding capacity (for example, the target value is 26%). The required supplementary water volume is calculated as follows: ,in is the water volume required, is the plot area, is the target wetted layer depth, is the target soil volume moisture content, is the current soil volume moisture content, substitute the value for calculation: Cubic meters to obtain the target irrigation water requirement.

[0085] The steps for obtaining a water source intake plan are as follows:

[0086] Based on the target irrigation water demand, read the information forms of all alternative water sources, extract the unit volume price, maximum hourly flow rate, and total water volume limit of each water source in the current scheduling cycle, and organize them into alternative water source parameter sets by water source type to generate an alternative water source parameter set;

[0087] Based on the set of alternative water source parameters and the target irrigation water demand, the different water withdrawal combinations are traversed for each water source one by one. The product of the volume of water used by each source and the corresponding unit volume price is calculated under different water withdrawal scenarios. The product results of each water source are cumulatively added together to obtain the total irrigation cost value corresponding to each combination scenario, thus generating an irrigation cost combination set.

[0088] Based on the irrigation cost combination set, the total irrigation cost values ​​corresponding to all combination situations are traversed, and they are compared and sorted item by item. The water source volume allocation plan corresponding to the situation with the smallest total irrigation cost value is selected to generate a water source water intake plan.

[0089] Specifically, based on the target irrigation water demand calculated in the above steps, for example, 960 cubic meters, the system automatically reads the pre-configured information form of all alternative water sources. The form is a structured data file that records the details of all water sources available to the farm. The system extracts the key parameters of each water source from the information form. For example, water source 1 is "reservoir water", the unit volume price is 0.8 yuan / cubic meter, it is transported through pipelines, and the maximum pumping flow of the pump station is 100 cubic meters per hour. In this scheduling cycle (for example, the next 24 hours), according to the quota of the reservoir management department, the total available volume is limited to 600 cubic meters. Water source The second is "underground well water", with a unit volume price (mainly converted from electricity costs) of 1.2 yuan / cubic meter, a maximum output flow of 80 cubic meters per hour, and no total available quantity limit. The third water source is "recycled water", with a unit volume price of 0.5 yuan / cubic meter, supplied through a dedicated pipeline, a maximum available flow of 50 cubic meters per hour, and a total available quantity limit of 400 cubic meters during this scheduling cycle. The system organizes this information into an alternative water source parameter set containing three entries according to the water source type. Each entry contains four fields: water source name, unit price, maximum flow, and total available quantity, to generate an alternative water source parameter set.

[0090] According to the set of alternative water source parameters generated in the previous step and based on the target irrigation water demand of 960 cubic meters, the system uses a constrained optimization algorithm to traverse all possible water extraction combinations. The algorithm first sorts the three water sources by unit price from low to high, namely recycled water (0.5 yuan / cubic meter), reservoir water (0.8 yuan / cubic meter), and underground well water (1.2 yuan / cubic meter). Then, with the goal of meeting the total water volume of 960 cubic meters, water is taken from the water source with the lowest cost first until its total available volume limit is reached, and then water is requested from water sources with higher costs in turn. The specific process is: first, consider taking water from recycled water, whose maximum available volume is 400 cubic meters, which is less than 960 cubic meters, so all of it is taken, and the remaining water demand is 960-400=560 cubic meters. Next, consider taking water from reservoir water, whose maximum available volume is 200 cubic meters. The total water volume is 600 cubic meters, which is greater than the remaining 560 cubic meters. Therefore, 560 cubic meters of water from the reservoir can meet the total demand. At this time, the underground well water withdrawal is 0, forming the first combination plan: 400 cubic meters of recycled water, 560 cubic meters of reservoir water, and 0 cubic meters of underground well water. The total cost is 400×0.5+560×0.8+0×1.2=200+448=648 yuan. The system will also generate other combinations that meet the total water volume and the available amount constraints of each water source. For example, reducing the use of reservoir water and increasing the use of well water, but because the cost of well water is higher, its total cost must be higher than 648 yuan. The system records each valid combination plan (that is, the sum of the water withdrawal of each water source is equal to 960 cubic meters, and the water withdrawal of each water source does not exceed its total available amount limit) and its corresponding total cost value to generate an irrigation cost combination set.

[0091] Based on the irrigation cost combination set generated in the previous step, the system traverses and compares and sorts the total irrigation cost values ​​corresponding to all combination situations in the set. For example, the set includes combination 1: 400 cubic meters of recycled water, 560 cubic meters of reservoir water, and 0 cubic meters of underground well water, with a total cost of 648 yuan; combination 2: 300 cubic meters of recycled water, 600 cubic meters of reservoir water, and 60 cubic meters of underground well water, with a total cost of 300×0.5+600×0.8+60×1.2=150+480+72=702 yuan; combination 3: 400 cubic meters of recycled water, 500 cubic meters of reservoir water, and 60 cubic meters of underground well water. meters, the total cost is 400×0.5+500×0.8+60×1.2=200+400+72=672 yuan. The system arranges all these combinations in ascending order according to the total cost value. After sorting, the combination with the lowest cost will be at the top of the list. The system automatically selects the case with the smallest total irrigation cost, that is, combination 1, with a total cost of 648 yuan, and then extracts the volume distribution plan of each water source corresponding to this case, that is, 400 cubic meters of recycled water, 560 cubic meters of reservoir water, and 0 cubic meters of underground well water. This plan is the final economically optimal water extraction plan, and a water source extraction plan is generated.

[0092] The steps to obtain the economic irrigation scheduling plan are:

[0093] Based on the water source extraction plan, extract the extraction time period, hourly extraction flow value and water extraction duration of each water source, cross-compare the extraction time period of each water source with all available time periods in the current scheduling cycle, screen the compatible scheduling time node range, and generate a set of scheduling adaptable time windows;

[0094] According to the set of adaptable time windows for scheduling, the water extraction time periods of each water source are allocated to the corresponding positions in the scheduling cycle one by one. The flow of each water source is verified and screened against the maximum allowable concurrent flow limit in the scheduling cycle. All conflicting time periods that do not meet the concurrent flow limit are eliminated to obtain an economic irrigation scheduling plan.

[0095] Specifically, based on the water source extraction plan generated in the above steps, that is, 400 cubic meters of recycled water and 560 cubic meters of reservoir water, the system first calculates the execution parameters for each water source task. For recycled water, the water intake is 400 cubic meters, and its maximum available flow rate is 50 cubic meters per hour. Therefore, the water extraction duration is calculated as 400 / 50=8 hours. For reservoir water, the water intake is 560 cubic meters, and its maximum available flow rate is 100 cubic meters per hour. Therefore, the water extraction duration is 560 / 100=5.6 hours. Then, the system cross-compares these water extraction tasks with the available time periods in the current scheduling cycle (the next 24 hours). The available time periods are determined by external conditions, for example For example, the water supply time of the recycled water plant is from 8 am to 6 pm (18:00) every day, and the off-peak electricity price period of the power grid is from 10 pm to 6 am the next day. The system matches the duration requirements of these two water-taking tasks with these available time windows. For example, the 8-hour water-taking task of recycled water must be completed within the 10-hour window from 8 am to 6 pm, while the 5.6-hour water-taking task of reservoir water can be arranged at any time period. The system will give priority to arranging the water-taking task of reservoir water during the off-peak electricity price period. Through this cross-comparison, all compatible scheduling time node ranges for each water-taking task are screened out, and a set of feasible start-up time windows for each water source is generated, that is, the scheduling adaptable time window set.

[0096] According to the set of adaptive time windows generated in the previous step, the system adopts a scheduling algorithm based on priority and constraints to allocate the water extraction tasks of each water source to specific locations within the scheduling cycle (the next 24 hours timeline) one by one. The lowest cost principle is followed during allocation, and the task of using recycled water is given priority. The extraction period is 8 hours, and the feasible start time window is from 8 am to 10 am (to ensure completion before 6 pm). The system chooses to start at 8 am, then its working period is 8:00-16:00, and the flow rate is 50 cubic meters / hour. Then the water extraction task of reservoir water is arranged, which lasts for 5.6 hours and can be arranged at any time. However, the system will check the maximum allowable concurrent flow limit of the pipeline network, which is set according to the design delivery capacity of the main pipeline of the pipeline network, for example, 120 cubic meters / hour. , in the period of 8:00-16:00, recycled water has occupied a flow of 50 cubic meters / hour, and the remaining available flow is 120-50=70 cubic meters / hour, which is less than the 100 cubic meters / hour flow required by reservoir water. Therefore, reservoir water and recycled water cannot work concurrently during the period of 8:00-16:00. The system schedules the reservoir water task after the recycled water task is completed, that is, starting from 16:00 and lasting 5.6 hours to 21:36. This arrangement meets the concurrent flow limit (only reservoir water works in this period, with a flow of 100 cubic meters / hour, which is less than 120 cubic meters / hour) and does not conflict with other constraints. Through such a verification and screening process, the system eliminates all conflicting time periods that do not meet the concurrent flow limit, and finally forms a conflict-free and executable schedule to obtain an economic irrigation scheduling plan.

[0097] The steps to obtain the device control timing list are:

[0098] Analyze the economic irrigation scheduling plan, extract the water intake, working flow, start and end time of the allowed time window, energy consumption per unit flow, electricity price function curve and pipe network pressure impact coefficient of each water source, construct the scheduling parameter structure set by sorting the water source numbers, and generate a multidimensional water source scheduling parameter matrix;

[0099] Based on the multi-dimensional water source scheduling parameter matrix, the equipment startup duration and initial startup time are calculated using the following formula:

[0100] ,

[0101] ,

[0102] ,

[0103] in, For the How long does the equipment of each water source last when it is turned on? For the The volume of water required during a water source scheduling period is: For the The actual working flow of each water source, To meet the pressure constraint Initial start-up time of each water source, It is the next available start time pointer of the system after the last water source stops. For the The starting boundary of the water source available start time window, Scheduling time point The following is the collection of all water source numbers currently in operation. For the The unit time pressure impact value of a water source, is the maximum total pressure shock value allowed by the pipe network, For the electricity price function The length of translation time that minimizes the total electricity cost is: For the moment The unit electricity value, is the candidate time shift for traversal;

[0104] Generate a device control timing list based on the device startup time and initial startup time.

[0105] Specifically, to parse the economic irrigation scheduling plan, the system first reads the working hours of each water source determined in the plan, for example, the working hours of recycled water are from 8:00 to 16:00, and the working hours of reservoir water are from 16:00 to 21:36. Then, the system extracts detailed parameters associated with each water source task from the relevant database and configuration file, including the water intake volume extracted from the water source intake plan, such as 400 cubic meters of recycled water and 560 cubic meters of reservoir water, the working flow rate extracted from the alternative water source parameter set, such as 50 cubic meters / hour of recycled water and 100 cubic meters / hour of reservoir water, and the start and end time of the allowed time window, such as 8:00 to 18:00 for recycled water. In addition, the system also needs to extract parameters related to operating costs and safety, including the unit flow energy consumption value calibrated according to the water pump equipment manual and historical operating data. For example, the regeneration water pump is 0.05 kWh / m3, and the reservoir water pump is 0.08 kWh / m3. The local time-of-use electricity price function curve obtained from the power grid company defines the electricity prices during peak hours (8:00-22:00, electricity price 1.2 yuan / kWh) and valley hours (22:00-8:00 the next day, electricity price 0.4 yuan / kWh). The pressure impact coefficient generated by the startup of each water source pump on the pipeline network is calculated through hydraulic model simulation. For example, the regeneration water pump is 0.05 MPa and the reservoir water pump is 0.1 MPa. Finally, these extracted parameters (water intake, working flow, time window, energy consumption value, electricity price curve, pressure coefficient) are sorted and organized according to the water source number (for example, regeneration water is No. 1 and reservoir water is No. 2) to construct a structured scheduling parameter set and generate a multidimensional water source scheduling parameter matrix.

[0106] formula:

[0107] ;

[0108] ;

[0109] ;

[0110] Through a three-step scheduling optimization process, the cost of irrigation task execution is minimized under physical constraints. The first step formula is It is the basis, which converts the abstract irrigation water demand into the specific time execution length. The second step formula It is a constraint solving process, which not only considers the temporal dependencies between tasks, but also introduces the key safety constraint of pipeline pressure shock (given by and The comparison shows that the physical feasibility and safety of the scheduling scheme are ensured. The third step formula is It is the core economic optimization, which is to optimize the electricity price function within the determined feasible time window. Perform integral operations to find the optimal time shift by exhaustive or optimized search , and push high-energy-consuming irrigation tasks to the electricity price valley as much as possible, thereby reducing the operating electricity cost of irrigation without affecting the irrigation effect and system safety.

[0111] For the The volume of water required for each water source scheduling period is directly derived from the water source intake plan formulated in the previous step. It is the final output of the multi-source irrigation cost scheduling module. It clarifies the specific amount of water that needs to be obtained from each water source to meet the target irrigation water demand. In this example, the second water source "reservoir water" (i.e. ) as an example, the required water supply volume is 560 cubic meters.

[0112] For the The actual working flow rate of each water source is an inherent property of the water source itself, which is determined by the pump model, pipeline design and working head. During the system initialization phase, it is obtained by reading the maximum available flow rate of each water source recorded in the alternative water source parameter set. In this example, the reservoir water ( )’s actual working flow is 100 cubic meters per hour.

[0113] The next available start time pointer of the system after the last water source stops. It is a dynamically updated variable used to ensure that irrigation tasks are executed in sequence to avoid time overlap conflicts. Its value is equal to the end time of the previous scheduled task. In this example, for example, the task of "recycled water" of water source No. 1 has been scheduled to be executed from 8:00 to 16:00, then the current The value of is 16.0 (hours).

[0114] For the The starting boundary of the available start time window of each water source is determined by the external supply conditions of the water source or specific operating regulations, such as the fixed water supply time of the recycled water plant. For reservoir water, since it can be taken 24 hours a day, the starting boundary of its available start time window is 0:00, that is, .

[0115] For the The unit time pressure shock value of a water source represents the instantaneous pressure increment caused by the water pump starting up on the pipe network system. Its value is obtained by simulating the water hammer effect of a specific type of water pump or by installing a high-frequency pressure sensor in the actual pipe network for on-site calibration. In this example, the reservoir water pump ( ) has a pressure shock value of 0.1 MPa.

[0116] The maximum total pressure shock value allowed by the pipe network is a critical parameter related to the safe operation of the entire irrigation system. Its setting basis is the rated pressure capacity of the weakest link in the pipe network (such as PVC pipes, valves, joints, etc.), and a certain safety margin is considered. For example, if the rated pressure of the pipe is 0.6 MPa, it can be set is 0.4 MPa. In this example, It is 0.2 MPa.

[0117] Scheduling time point The set of all running water source numbers is a time-varying set. When calculating the start time of a specific task, it is necessary to check whether the sum of the pressure shocks of all concurrently running water sources exceeds the limit after the task is started at that moment. In this example, when considering starting the reservoir water task at 16:00, It will only contain reservoir water number {2}.

[0118] For the moment The unit electricity value is a piecewise function that reflects the time-of-use electricity price strategy. Its specific value is obtained from the power supply department and is converted into the unit flow energy consumption value of the water pump to obtain the operating cost per unit time. In this example, the water pump power is , then the electricity price function is: (peak time), ;when (Valley Time), .

[0119] The candidate time shift for traversal is a variable used for search during the optimization process, representing the time to shift the task backward from its initial start time.

[0120] Calculation process:

[0121] Reservoir water ( ) as an example to calculate:

[0122] 1. Calculate device power-on time and initial startup time :

[0123] ;

[0124] 2. Calculate the initial startup time :

[0125] First determine the starting point for the search: .

[0126] from Start checking the pressure constraint. At this time, if the reservoir water is started, the concurrently running water source set is .

[0127] The total pressure is .

[0128] because , the constraints are satisfied.

[0129] Therefore, the minimum satisfying condition is found This is the initial startup time: (i.e. 4 p.m.).

[0130] 3. Calculate the optimal translation time :

[0131] The goal is to minimize the cost function The task duration is 5.6 hours and is initially scheduled for the [16.0, 21.6] time period.

[0132] The system needs to search within a feasible range The upper limit of this range is determined by the end time of the scheduling cycle (24:00), and the latest start time is , so the largest for Hour.

[0133] The system will traverse From 0 to 2.4, calculate each The corresponding total electricity bill, since the electricity price is segmented, the key node is 22:00.

[0134] when When the task starts, (18:24), the end time is (24:00).

[0135] The costs for this period are:

[0136] ;

[0137] ;

[0138] ;

[0139] By comparing all candidates The cost of The cost is lowest when Hour.

[0140] The results show that the irrigation task duration of reservoir water is 5.6 hours, and its optimal start-up time should be shifted back 2.4 hours from the initially determined 4 pm, that is, to start at 6:24 pm (18:4). This can maximize the use of night-time off-peak electricity prices and achieve the lowest operating cost while meeting all operating constraints. The final start-up duration (5.6 hours) and optimized start-up time (18:24) will be used to generate the final device control timing.

[0141] Based on the equipment startup duration and optimized initial startup time of each water source task calculated in the previous step, the system begins to specifically arrange the equipment action sequence. For each scheduling task, for example, water source No. 1 "recycled water", its equipment startup duration is 8 hours, and the optimized startup time is 8:00 am. Based on this, the system calculates its stop time as 16:00 pm. Subsequently, the system generates two core control records for the task: one is a startup record, containing {equipment number: "recycled water pump", action: "start", execution timestamp: "08:00:00"}, and the other is a stop record, containing {equipment number: "recycled water pump", action: "stop", execution timestamp: "16:00:00"}. Similarly, for water source No. 2 "reservoir water", its equipment startup duration is 5.6 hours, and the optimized startup time is 6:24 pm. The system calculates its stop time as midnight and generates corresponding start and stop records. The system summarizes all control records generated by all water source tasks.

[0142] The steps to obtain the irrigation control instruction set are:

[0143] According to the equipment control timing list, the pump or valve equipment number corresponding to each equipment action is extracted. According to the communication protocol standard and hardware control specification of each equipment, the start execution timestamp and stop execution timestamp are converted into the digital signal form of relay opening and closing. Then, they are mapped one by one into the corresponding equipment control digital signal sequence according to the equipment number to generate the water pump and valve digital control signal set;

[0144] Based on the digital control signal set of water pumps and valves, the device control digital signal sequence corresponding to each water pump or valve is merged in turn, and then integrated into a continuous digital signal stream according to the execution order of each device control digital signal recorded in the device control action sorting sequence to generate an irrigation control instruction set.

[0145] Specifically, according to the device control timing list, the system reads the device action items in the list one by one. For example, the first item read is {Device number: "Regeneration water pump", action: "Open", execution timestamp: "08:00:00"}. The system queries the preset hardware configuration file based on the device number "Regeneration water pump" and determines that the pump is controlled by a No. 3 relay connected to a programmable logic controller (PLC). Its communication protocol is Modbus RTU. The hardware control specification requires writing "1" to the coil address of the relay (for example, address 00003) to indicate closing (opening) and writing "0" to indicate disconnection (closing). The system converts the "Open" action and the "08:00:00" execution start timestamp into a specific Modbus instruction frame. The data field of the frame contains the target relay address and operation code. For example, the instruction is "01 05 00 03 FF 00", where "01" is the device address, "05" is the write single coil function code, "00 03" is the coil address, and "FF "00" represents forced setting (opening). For the stop action, an instruction with a data field of "00 00" is generated. The system performs this conversion process for each action in the list, generating a series of digital signal instructions with timestamps for each device (such as the regeneration water pump, reservoir water pump, and related valves). These instructions together constitute the control digital signal sequence of the device. Finally, the sequences of all devices are summarized to generate a set of digital control signals for pumps and valves.

[0146] Based on the water pump and valve digital control signal set, the system starts the final instruction set generation program. The program first accesses the device control sequence list generated in the previous step. The list has been globally sorted according to the execution timestamp of each device action. For example, the sorted sequence may be: 8:00 regeneration water pump turns on, 8:01 valve No. 1 turns on, 16:00 regeneration water pump turns off, 16:01 valve No. 1 turns off, 18:24 reservoir water pump turns on, and so on. The program extracts the specific device control digital signal sequence corresponding to each action from the water pump and valve digital control signal set in turn according to this sorted action sequence. For example, at the time point 8:00, the opening instruction frame of the regeneration water pump is extracted, and at 8:01, the opening instruction frame of valve No. 1 is extracted. Then, these single instruction frames extracted in chronological order are connected in series to form a continuous, chronologically arranged digital signal stream. Each byte of this signal stream strictly corresponds to a specific hardware operation, and its position in the stream determines the order in which it is sent. This complete, time-accurate digital signal stream that includes all irrigation actions within the scheduling cycle is what is ultimately sent to the underlying PLC or field bus controller to generate the irrigation control instruction set.

Claims

1. A corn planting water-saving irrigation system based on drought risk management, characterized in that: The system comprises: The crop stress status monitoring module synchronously records the corn canopy temperature and the ambient temperature, extracts the temperature difference to form a temperature difference sequence, calculates and marks the current canopy and ambient temperature difference, and obtains the canopy and ambient temperature difference. Based on the canopy and ambient temperature difference, and referring to the field-set lower limit temperature difference for sufficient water and upper limit temperature difference for severe stress, the module synchronously records the sensible heat flux, net radiation, and soil heat flux to obtain a stress-related input group. Based on the stress-related input group, the crop water stress index is calculated using the following formula: ； in, is the crop water stress index, is the temperature difference between the current canopy and the ambient temperature, The lower limit temperature difference for sufficient moisture, The upper temperature difference is the severe stress limit. is the sensible heat flux, is the net radiation, is the soil heat flux, is the ratio factor between the heat response and energy allocation dimensions; The precise irrigation demand diagnosis module compares the crop water stress index with the synergistic threshold to determine whether the crop water stress index is greater than the synergistic threshold and evaluates whether the latent heat flux change rate is lower than the rate threshold. If both conditions are met, a synergistic irrigation trigger signal is generated to calculate the total water volume of the current irrigation operation and establish the target irrigation water demand. The multi-source irrigation cost scheduling module receives the target irrigation water demand, obtains the unit price, maximum available flow rate, and total available quantity limit of multiple water sources, sums the product of the water use amount and the unit price of each water source, and forms a water source extraction plan based on the minimum sum of the total irrigation cost. The water source extraction plan is then integrated into the scheduling cycle to formulate an economic irrigation scheduling plan. The irrigation instruction generation and execution module analyzes the economic irrigation scheduling plan, generates a device control timing list based on the water intake and available flow of different water sources, and then combines the sequence and time nodes of each action in the device control timing list into an irrigation control instruction set.

2. The corn planting water-saving irrigation system based on drought risk management according to claim 1, characterized in that: The steps for obtaining the coordinated irrigation trigger signal are: Based on the crop water stress index, extract the current crop water stress index value, compare the value with the collaborative threshold, and if the crop water stress index is greater than the collaborative threshold, mark it as a water stress state; otherwise, mark it as a water stress state, and generate a crop water stress judgment result; According to the crop water stress judgment result, the latent heat flux values ​​at two adjacent moments in the current period are read, the latent heat flux value change and the change rate are calculated in units of time intervals, and the calculated latent heat flux change rate is compared item by item with a set latent heat flux change rate threshold. If the latent heat flux change rate is less than the latent heat flux change rate threshold, it is marked as an insufficient evapotranspiration state; otherwise, it is marked as a normal evapotranspiration state, and a latent heat flux rate judgment result is generated; Based on the crop water stress judgment result and the latent heat flux rate judgment result, if both are in a water stress establishment state and an evaporation deficiency state, a coordinated irrigation trigger signal is generated.

3. The corn planting water-saving irrigation system based on drought risk management according to claim 1, characterized in that: The steps for obtaining the target irrigation water requirement are: Based on the collaborative irrigation trigger signal, the plot number and execution period number bound to the trigger signal are identified, the current growth period classification identifier, the previous irrigation timestamp and the previous irrigation water volume parameters, and the current soil moisture monitoring value are extracted, the time interval from the previous irrigation and the soil moisture consumption rate are calculated, and the growth period characteristic parameter set and the water consumption trend indicator are obtained; According to the growth period characteristic parameter set and water consumption trend index, various indicators in the standard water requirement parameter library corresponding to the current growth period are retrieved, including the average water consumption per plant, the target moist layer depth and the root zone volume per unit area. Combined with the total planting area and row density parameters corresponding to the identified plot number, the regional water requirement volume is matched and calculated to obtain the target irrigation water requirement.

4. The corn planting water-saving irrigation system based on drought risk management according to claim 1, characterized in that: The steps for obtaining the water source water intake plan are as follows: Based on the target irrigation water demand, read the information forms of all alternative water sources, extract the unit volume price, maximum hourly flow rate, and total water limit available in the current scheduling cycle of each water source, and organize them into alternative water source parameter sets by water source type to generate an alternative water source parameter set; According to the set of candidate water source parameters and based on the target irrigation water demand, different water extraction combinations are traversed for each water source one by one, and the product of the volume used by each water source and the corresponding unit volume price under different water extraction scenarios is calculated respectively. The product results of each water source are cumulatively added to obtain the total irrigation cost value corresponding to each combination scenario, thereby generating an irrigation cost combination set; Based on the irrigation cost combination set, the total irrigation cost values ​​corresponding to all combination situations are traversed, and they are compared and sorted item by item. The water source volume allocation scheme corresponding to the situation with the smallest total irrigation cost value is selected to generate a water source water intake plan.

5. The corn planting water-saving irrigation system based on drought risk management according to claim 1, characterized in that: The steps for obtaining the economic irrigation scheduling plan are as follows: Based on the water source extraction plan, extract the extraction time period, hourly extraction flow value and water extraction duration of each water source, cross-compare the extraction time period of each water source with all available time periods in the current scheduling cycle, screen the compatible scheduling time node range, and generate a set of scheduling adaptable time windows; According to the set of adaptable time windows for scheduling, the water extraction time periods of each water source are allocated to the corresponding positions in the scheduling cycle one by one. The flow of each water source is verified and screened against the maximum allowable concurrent flow limit in the scheduling cycle. All conflicting time periods that do not meet the concurrent flow limit are eliminated to obtain an economic irrigation scheduling plan.

6. The corn planting water-saving irrigation system based on drought risk management according to claim 1, characterized in that: The steps for obtaining the device control timing list are: Analyze the economic irrigation scheduling plan, extract the water intake, working flow, start and end time of the allowed time window, energy consumption per unit flow, electricity price function curve and pipe network pressure impact coefficient of each water source, construct a scheduling parameter structure set by sorting the water source numbers, and generate a multidimensional water source scheduling parameter matrix; Based on the multi-dimensional water source scheduling parameter matrix, the equipment startup duration and initial startup time are calculated using the following formula: ， ， ， in, For the How long does the equipment of each water source last when it is turned on? For the The volume of water required during a water source scheduling period is: For the The actual working flow of a water source, To meet the pressure constraint Initial start-up time of each water source, It is the next available start time pointer of the system after the last water source stops. For the The starting boundary of the water source available start time window, Scheduling time point The following is the collection of all water source numbers currently in operation. For the The unit time pressure impact value of a water source, is the maximum total pressure shock value allowed by the pipe network, For the electricity price function The length of translation time that minimizes the total electricity cost is: For the moment The unit value of electricity, is the candidate time shift for traversal; Generate a device control timing list based on the device startup time and initial startup time.

7. The corn planting water-saving irrigation system based on drought risk management according to claim 1, characterized in that: The steps for obtaining the irrigation control instruction set are: According to the device control timing list, the pump or valve device number corresponding to each device action is extracted. According to the communication protocol standard and hardware control specification of each device, the start execution timestamp and the stop execution timestamp are converted into the digital signal form of relay opening and closing, and mapped one by one according to the device number to the corresponding device control digital signal sequence to generate a water pump valve digital control signal set; Based on the water pump and valve digital control signal set, the device control digital signal sequence corresponding to each water pump or valve is merged in sequence, and integrated into a continuous digital signal stream according to the execution order of each device control digital signal recorded in the device control action sorting sequence to generate an irrigation control instruction set.

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