Integrated wastewater treatment irrigation method, system, and medium

Abstract

The application provides a kind of integrated sewage treatment intelligent irrigation method, system and medium, including sewage treatment device, irrigation delivery device, control hub and with each electrical element electrical connection energy module. Wherein, sewage treatment device includes water inlet, grating well, grit chamber, regulating tank, biological treatment disinfection part and drain in turn, wherein, biological treatment disinfection part includes anaerobic tank, oxygen tank, sludge tank, sedimentation tank, disinfection tank and clean water tank, wherein oxygen tank is integrated with immersed MBR membrane assembly and variable frequency aeration system;Irrigation delivery device includes multistage buried depth drip irrigation pipe network, pressure compensating dripper and solenoid valve group, wherein, multistage buried depth drip irrigation pipe network is buried according to multiple gradients.The system realizes the intelligent regulation of water quantity and water quality during sewage treatment and the real-time intelligent irrigation of farmland, green land, vegetable garden and the like, to achieve the purpose of water resource intensive and economical use and intelligent management.

Description

Technical Field

[0001] This invention relates to the field of wastewater treatment, and more particularly to an integrated wastewater treatment irrigation method, system, and medium. Background Technology

[0002] Actively explore ways to utilize domestic sewage as a resource. Through advanced treatment technologies, domestic sewage can be transformed into water resources that can be used for agricultural irrigation. This can not only reduce dependence on natural water resources, but also improve the efficiency of water resource utilization.

[0003] Because the volume of sewage discharge is small and unstable, traditional sewage treatment plants often cannot meet the needs of sewage treatment in remote urban areas, town communities, or rural areas. However, domestic sewage treatment and farmland irrigation mostly rely on manual operation or simple automated equipment, which leads to problems such as incomplete monitoring, untimely adjustment, and waste of resources. Summary of the Invention

[0004] The purpose of this invention is to provide an integrated sewage treatment irrigation method, system and medium to realize intelligent regulation of water quantity and quality during sewage treatment and real-time intelligent irrigation of farmland, green space, vegetable garden, etc., so as to achieve the purpose of intensive and economical use and intelligent management of water resources.

[0005] In a first aspect, embodiments of the present invention provide an integrated wastewater treatment and irrigation system, comprising:

[0006] Wastewater treatment equipment includes an inlet, a screen well, a grit chamber, an equalization tank, a biological treatment and disinfection unit, and an outlet connected in sequence. The biological treatment and disinfection unit includes an anaerobic tank, an aerobic tank, a sludge tank, a sedimentation tank, a disinfection tank, and a clear water tank. The aerobic tank integrates a submerged MBR membrane module and a variable frequency aeration system.

[0007] The irrigation delivery device includes a multi-level buried depth drip irrigation network, pressure-compensated drippers, and solenoid valve assembly. The multi-level buried depth drip irrigation network is laid in multiple gradients.

[0008] The monitoring module includes water quality sensors arranged in the sewage treatment device and irrigation delivery device; the soil moisture monitoring array includes multiple depth sensor nodes; and the crop growth monitor is equipped with a multispectral imaging module.

[0009] The control center includes a wastewater volume regulation calculation and analysis module based on the IUWS model, a real-time irrigation volume analysis module based on a real-time water-saving irrigation simulation model and image recognition technology, and a data transmission module that sends commands to each control element.

[0010] Energy modules that are electrically connected to various electrical components, including photovoltaic panels and energy storage systems.

[0011] In one possible implementation, the regulating tank is equipped with a liquid level adaptive baffle, which is driven by a shape memory alloy and can automatically adjust the opening degree according to the inlet water flow. The surface of the baffle is provided with a self-cleaning nano-coating.

[0012] In one possible implementation, the membrane flux control of the MBR membrane module employs a fuzzy PID algorithm based on the TMP-flux coupling model, and the membrane cleaning cycle is automatically triggered by detecting sudden changes in transmembrane pressure difference.

[0013] In one possible implementation, the real-time water-saving irrigation simulation model includes a soil moisture prediction model, a crop water requirement calculation model, a planned wetting layer depth calculation model, an effective rainfall calculation model, and a real-time irrigation volume calculation model.

[0014] In one possible implementation, the sedimentation tank includes a sludge return pump station and a sludge dewatering device to allow sludge to be returned to the anaerobic tank and dewatered, and the disinfection tank includes a chlorine dioxide disinfection device.

[0015] In a second aspect, embodiments of the present invention also provide a method applied to a system as described in any embodiment of the first aspect, comprising the following steps:

[0016] S100, multi-stage wastewater treatment steps:

[0017] The wastewater entering through the inlet is separated into solid and liquid components by a bar screen, inorganic particles are removed by a grit chamber, and the inlet flow rate is dynamically balanced by a regulating tank.

[0018] Nitrogen and phosphorus removal are carried out in the anaerobic tank of the biological treatment and disinfection section, while the aerobic tank uses MBR membrane modules and a variable frequency aeration system to achieve the biodegradation of organic matter.

[0019] The effluent after disinfection in the disinfection tank is stored in the clear water tank, and the water quality parameters are fed back to the control center in real time.

[0020] S200, Multi-dimensional Environmental Sensing Steps:

[0021] Soil moisture content matrix was obtained using a soil moisture monitoring array;

[0022] Crop canopy temperature and NDVI index were collected using the multispectral imaging module in a crop growth monitor.

[0023] Organic matter levels at each stage of wastewater treatment are monitored using water quality sensors.

[0024] S300, Intelligent Decision Generation Steps:

[0025] The reference crop water requirement ET0 is calculated based on the improved Penman-Monteith algorithm, and the theoretical crop water requirement ET is generated by combining it with the real-time Kc coefficient.c =ET0×K c ;

[0026] The irrigation demand function Q=f(ETc,Δθ,θ_min) is constructed by predicting the soil moisture change Δθ in the next N days through a real-time irrigation volume analysis module based on a real-time water-saving irrigation simulation model and image recognition technology.

[0027] The wastewater treatment parameter set was optimized using the wastewater volume regulation calculation and analysis module based on the IUWS model.

[0028] S400 initiates tiered irrigation based on the irrigation demand function Q.

[0029] Thirdly, embodiments of the present invention also provide an electronic device, including a memory and a processor, wherein the memory stores a program executable on the processor, and when the program is executed by the processor, the electronic device performs the method as described in any possible embodiment of the second aspect.

[0030] Fourthly, embodiments of the present invention also provide a computer-readable storage medium, the storage medium including a program that, when run on an electronic device, causes the electronic device to perform any of the possible implementations of the second aspect described above.

[0031] Fifthly, embodiments of the present invention also provide a computer program product that, when the program product is run on an electronic device, causes the electronic device to perform any of the possible implementation methods of the first aspect described above.

[0032] This invention provides an integrated wastewater treatment and irrigation system, method, procedure, and medium. The beneficial effects of the technical solution are mainly reflected in the following aspects:

[0033] The beneficial effects of the technical solution of this invention are mainly reflected in the following aspects:

[0034] I. Integrated intelligent management of sewage treatment and irrigation is achieved. Through the coordinated operation of sewage treatment devices, irrigation delivery devices, monitoring modules, and control centers, this invention can achieve intelligent regulation of water quantity and quality during sewage treatment, as well as real-time intelligent irrigation of farmland, green spaces, vegetable gardens, etc., thereby achieving the goal of intensive and economical use and intelligent management of water resources.

[0035] Second, it improves the efficiency and effectiveness of wastewater treatment. The multi-stage treatment steps in the wastewater treatment unit, including solid-liquid separation, inorganic particle removal, dynamic balancing of influent flow, nitrogen and phosphorus removal, and biodegradation of organic matter, can effectively remove pollutants from wastewater and improve effluent quality. Meanwhile, the membrane flux control of the MBR membrane module adopts a fuzzy PID algorithm based on the TMP-flux coupling model, which can optimize the membrane cleaning cycle and extend the membrane's service life.

[0036] Third, it achieves precise and intelligent irrigation. Through multi-dimensional environmental perception steps, this invention can acquire information such as soil moisture content, crop canopy temperature and NDVI index, and organic matter indicators at various stages of wastewater treatment in real time, providing data support for intelligent decision-making. In the intelligent decision generation step, the real-time irrigation volume analysis module, based on a real-time water-saving irrigation simulation model and image recognition technology, can predict future changes in soil moisture and construct an irrigation demand function, thereby achieving precise and intelligent irrigation.

[0037] Fourth, it has broad application prospects and promotional value. The integrated sewage treatment irrigation system, method, procedure, and medium of this invention are applicable to various irrigation scenarios such as farmland, green spaces, and vegetable gardens. It can effectively improve water resource utilization efficiency and reduce water waste, which is of great significance for promoting sustainable agricultural development and advancing ecological civilization. Furthermore, the technical solution of this invention is easy to promote and implement, possessing high practical value and social benefits. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 This is a schematic diagram of the composition of the integrated sewage treatment and irrigation system provided in an embodiment of the present invention;

[0040] Figure 2 This is a schematic diagram of the integrated wastewater treatment and irrigation method provided in an embodiment of the present invention;

[0041] Figure 3 This is a schematic diagram of an electronic device structure provided in an embodiment of the present invention. Detailed Implementation

[0042] In the description of embodiments of the present invention, the terminology used in the following embodiments is for the purpose of describing particular embodiments only and is not intended to be a limitation of the invention. As used in the specification and appended claims of the present invention, the singular expressions “a,” “the,” “the,” “the,” and “this” are intended to also include expressions such as “one or more,” unless the context clearly indicates otherwise. It should also be understood that in the following embodiments of the present invention, “at least one” and “one or more” refer to one or more (including two). The term “and / or” is used to describe the relationship between related objects, indicating that three relationships may exist; for example, A and / or B can indicate: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character “ / ” generally indicates that the preceding and following related objects are in an “or” relationship.

[0043] References to "one embodiment" or "some embodiments" as used in this specification mean that a particular feature, structure, or characteristic described in connection with that embodiment is included in one or more embodiments of the invention. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including, but not limited to," unless otherwise specifically emphasized. The term "connection" includes both direct and indirect connections, unless otherwise stated. "First" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features.

[0044] In embodiments of the present invention, the terms "exemplarily" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or implementation described as "exemplarily" or "for example" in embodiments of the present invention should not be construed as being more preferred or advantageous than other embodiments or implementations. Specifically, the use of the terms "exemplarily" or "for example" is intended to present the relevant concepts in a specific manner.

[0045] This invention aims to provide an integrated wastewater treatment and irrigation system that combines high technology, energy conservation, environmental protection, and intelligent control. By integrating a wastewater treatment device, an irrigation delivery device, a monitoring module, a control center, and an energy module electrically connected to each electrical component, the system achieves intelligent regulation of water quantity and quality during wastewater treatment, as well as real-time intelligent irrigation of farmland, green spaces, and vegetable gardens, thereby achieving the goals of intensive and economical use and intelligent management of water resources.

[0046] Figure 1This is a schematic diagram of the composition of an integrated sewage treatment and irrigation system provided in an embodiment of the present invention. It mainly includes: a sewage treatment device 10, an irrigation delivery device 20, a monitoring module 30, a control center 40, and an energy module 50 electrically connected to each electrical component. Wherein:

[0047] Wastewater treatment device 10 includes an inlet 101, a screen well 102, a grit chamber 103, an equalization tank 104, a biological treatment and disinfection unit 105, and an outlet 106 connected in sequence. The biological treatment and disinfection unit 105 includes an anaerobic tank 1051, an aerobic tank 1052, a sludge tank 1053, a sedimentation tank 1054, a disinfection tank 1055, and a clear water tank 1056. The aerobic tank 1052 integrates a submerged MBR membrane module 10521 and a variable frequency aeration system 10522.

[0048] The irrigation delivery device 20 includes a multi-level buried depth drip irrigation network 201-203, a pressure-compensating dripper 204, and a solenoid valve group 205. The multi-level buried depth drip irrigation network is buried in multiple gradients.

[0049] The monitoring module 30 includes a water quality sensor 301 arranged in the sewage treatment device 10 and the irrigation delivery device 20, a soil moisture monitoring array 302 including multiple depth sensor nodes, and a crop growth monitor 303 equipped with a multispectral imaging module.

[0050] The control center 40 includes a wastewater volume regulation calculation and analysis module 401 based on the IUWS model, a real-time irrigation volume analysis module 402 based on a real-time water-saving irrigation simulation model and image recognition technology, and a data transmission module 403 that sends commands to each control element.

[0051] The energy module 50, which is electrically connected to various electrical components, includes a photovoltaic panel 501 and an energy storage system 502.

[0052] In one possible embodiment, the regulating tank 104 is provided with a liquid level adaptive baffle 1041, which is driven by a shape memory alloy and can automatically adjust the opening degree according to the inlet water flow. The surface of the baffle is provided with a self-cleaning nano-coating.

[0053] In another possible embodiment, the membrane flux control of the MBR membrane module 10521 adopts a fuzzy PID algorithm based on the TMP-flux coupling model, and the membrane cleaning cycle is automatically triggered by detecting sudden changes in transmembrane pressure difference.

[0054] In one possible embodiment, the wastewater volume regulation calculation and analysis module 401 based on the IUWS model automatically regulates the inlet 101, outlet 106, and aeration pump in the variable frequency aeration system 10522 of the integrated domestic wastewater treatment device 10.

[0055] The real-time irrigation volume analysis module 402, based on a real-time irrigation simulation model and image recognition technology, couples the real-time irrigation simulation model and image recognition technology to analyze the real-time water demand of crops, enabling the system to automatically control the valves in the irrigation components.

[0056] The data transmission module 403, which sends instructions to each control element, issues instructions to the designated control element based on the decisions made by the sewage volume regulation calculation and analysis module and the real-time irrigation volume analysis module.

[0057] The real-time water-saving irrigation simulation model includes a soil moisture prediction model, a crop water requirement calculation model, a planned wetting layer depth calculation model, an effective rainfall calculation model, and a real-time irrigation volume calculation model.

[0058] In one possible embodiment, the equalization tank 104 includes a liftable adjustable baffle 1041 to regulate the influent flow to the anaerobic tank; the aerobic tank 1052 includes a submerged MBR membrane module 10521 and a variable frequency aeration system 10522; the sedimentation tank 1054 includes a sludge return pump station and a sludge dewatering device to facilitate sludge return to the anaerobic tank and sludge dewatering; and the disinfection tank 1055 includes a chlorine dioxide disinfection device.

[0059] Furthermore, the inlet 101 is connected to the bar screen 102 to remove solid waste from the sewage;

[0060] The main function of the grit chamber 103 is to remove inorganic particles from the sewage by gravity, so as to avoid these impurities from affecting the normal operation of subsequent treatment structures.

[0061] The regulating tank 104 is primarily used to regulate the influent and effluent flow rates, ensuring that the influent water volume and quality of the sewage treatment system are relatively stable, making the treatment system more stable and efficient.

[0062] The anaerobic tank 1051 degrades organic matter into simple organic matter and gas through anaerobic respiration, and is used to degrade organic matter and remove nitrogen, phosphorus, methane and other substances.

[0063] The aerobic tank 1052 effectively removes organic matter and nitrogen sources from wastewater through processes such as biological denitrification, biodegradation, and physical sedimentation.

[0064] The sludge tank 1053 stabilizes the sludge generated during the sewage treatment process through a biological treatment process, reducing the volume of sludge and harmful substances, while recovering and utilizing biogas, making the sludge easier to handle and dispose of.

[0065] Sedimentation tank 1054 separates suspended solids and other solids from wastewater through gravity settling.

[0066] Disinfection tank 1055 uses a chlorine dioxide device to eliminate pathogens and purify water.

[0067] The clear water tank 1056 is connected to the drain outlet, and an automatic solenoid valve is installed at the drain outlet. When the water quality in the clear water tank does not meet the standards, the automatic valve will automatically close.

[0068] In one embodiment, the irrigation delivery device 20 includes a water delivery hose connecting the outlet of the integrated sewage treatment device to the irrigation water storage tank, an irrigation water storage tank, an underground drip irrigation pipe, and a solenoid valve.

[0069] The regulating reservoir features an inlet equipped with an electromagnetic valve, several outlets extending from the reservoir via flexible hoses, each with its own electromagnetic valve. These valves are controlled by an intelligent control system. An overflow pipe is designed at the top of the reservoir to allow overflow into nearby water bodies when the water level exceeds the reservoir's maximum capacity.

[0070] The underground drip irrigation pipe is made of PVC or PE material. After the water outlet valve of the water storage tank, the drip irrigation pipe is divided into three branch pipes, which are buried in the soil at depths of 15-20, 35-40, and 55-60 cm respectively. Each branch pipe is equipped with a solenoid valve, which is controlled by an intelligent control system.

[0071] The automatic monitoring components include influent and effluent water quality detection probes for the integrated wastewater treatment device, oxygen content monitoring probes for the aerobic tank, soil moisture content monitoring probes, a solar power generation device for providing power, and a battery pack.

[0072] In one possible embodiment, the influent and effluent water quality real-time monitoring probes of the integrated wastewater treatment device are fixed to the walls of the equalization tank and the clear water tank, respectively. They mainly monitor indicators such as COD, turbidity, ammonia nitrogen, residual chlorine, total phosphorus, and total nitrogen in real time. The monitoring probes are equipped with LoRaWAN modules to transmit the real-time monitoring data to the cloud platform. The monitoring probes and LoRaWAN modules are powered by a solar power generation device and a battery pack.

[0073] In one possible embodiment, an oxygen content monitoring probe 1052 for aerobic tank 1052 is installed on the tank wall to monitor the oxygen content in the aerobic tank. The monitoring probe is equipped with a LoRaWAN module to transmit real-time monitoring data to a cloud platform. The monitoring probe and LoRaWAN module are powered by a solar power generation device and a battery pack. A crop growth monitoring module captures crop growth images in one-hour increments. The monitoring module is equipped with a LoRaWAN module to transmit real-time monitoring images to a cloud platform. The monitoring probe and LoRaWAN module are powered by a solar power generation device and a battery pack.

[0074] In addition, soil moisture monitoring probes are buried 20, 40, and 60 cm underground, mainly monitoring real-time soil moisture content. LoRaWAN modules are installed on the probes to transmit real-time monitoring data to a cloud platform. The probes and LoRaWAN modules are powered by solar power generation devices and battery packs.

[0075] The solar power generation device and battery pack are installed in an open space near the integrated device. The solar panels are supported by liftable and rotatable stainless steel pipes. The solar panels are connected to the batteries, which are then connected to various monitoring probes via wires.

[0076] In one possible embodiment, the control elements include solenoid valves for the inlet of the regulating tank and the outlet of the clear water tank of the integrated sewage treatment device, solenoid valve for the outlet of the water storage tank, inlet valve for the buried drip irrigation pipe, blower and air volume regulating valve for the aeration pump, and automatic lifting and rotation controller for the solar support rod.

[0077] In addition, the inlet and outlet regulating valves of the integrated sewage treatment device are installed in the regulating tank 104 and the clear water tank 1056, respectively. The valves are equipped with LoRaWAN modules to receive instructions sent by the cloud platform system to complete the water volume regulation. The valves and LoRaWAN modules are powered by solar power generation devices and battery packs.

[0078] The solenoid valve at the outlet of the clear water tank 1056 is connected to the water storage tank and drip irrigation pipe via a flexible hose. The valve is equipped with a LoRaWAN module, which receives instructions from the cloud platform system to regulate the water flow. The valve and the LoRaWAN module are powered by a solar power generation device and a battery pack.

[0079] In one possible embodiment, the inlet valve of the buried drip irrigation pipe is connected to the valve of the water storage tank via a flexible hose. The valve is equipped with a LoRaWAN module, which receives instructions from the cloud platform system to adjust the water volume. The valve and the LoRaWAN module are powered by a solar power generation device and a battery pack.

[0080] In one possible embodiment, the aeration pump and airflow regulating valve are used to provide oxygen to the microorganisms in the aerobic tank. The regulating valve is equipped with a LoRaWAN module to receive instructions from the cloud platform system to adjust the water flow and airflow. The valve and LoRaWAN module are powered by a solar power generation device and a battery pack.

[0081] In one possible embodiment, the solar support pole's automatic lifting and rotation control element is equipped with a LoRaWAN module, receives instructions from the cloud platform system, and adjusts the height and orientation of the solar panels according to time to ensure maximum efficiency in receiving solar energy.

[0082] In one possible embodiment, the intelligent system includes facilities for transmitting and collecting data from each monitoring element, a wastewater volume regulation calculation and analysis system based on the IUWS model, a real-time irrigation volume analysis system based on the Penman formula, and a data transmission system for issuing commands to each control element.

[0083] In one possible embodiment, the system uses a battery valve including the rear end of the hose, which is controlled by the system and controls the valve based on the water quality monitored in real time in the disinfection pool. The valve automatically closes when the water quality in the disinfection pool does not meet the standards.

[0084] Based on the above system, this embodiment provides an integrated wastewater treatment and irrigation method, such as... Figure 2 As shown, the method mainly includes the following steps:

[0085] S100, multi-stage wastewater treatment, includes the following steps:

[0086] The wastewater input from the inlet 101 is separated into solids and liquids through the bar screen 102, inorganic particles are removed by the grit chamber 103, and the influent flow rate is dynamically balanced by the equalization tank 104.

[0087] Nitrogen and phosphorus removal are carried out in the anaerobic tank 1051 of the biological treatment disinfection section 105, and the aerobic tank 1052 uses MBR membrane module 10521 and variable frequency aeration system 10522 to achieve biodegradation of organic matter.

[0088] The effluent after disinfection in disinfection tank 1055 is stored in clear water tank 1056, and water quality parameters are fed back to the control center 40 in real time.

[0089] S200, multi-dimensional environmental perception, includes the following steps:

[0090] Soil moisture content matrix was obtained using soil moisture monitoring array 302;

[0091] Crop canopy temperature and NDVI index were collected using the multispectral imaging module in the crop growth monitor 303.

[0092] Organic matter levels at each stage of wastewater treatment are monitored using water quality sensor 301.

[0093] S300, intelligent decision generation, includes the following steps:

[0094] The reference crop water requirement ET0 is calculated based on the improved Penman-Monteith algorithm, and the theoretical crop water requirement ET is generated by combining it with the real-time Kc coefficient. c =ET0×K c ;

[0095] The real-time irrigation volume analysis module 402, based on a real-time water-saving irrigation simulation model and image recognition technology, predicts the soil moisture change Δθ over the next N days, and constructs the irrigation demand function Q = f(ET). c ,Δθ,θ_min);

[0096] The wastewater treatment parameter set is optimized using the wastewater volume regulation calculation and analysis module 401 based on the IUWS model;

[0097] S400 initiates tiered irrigation based on the irrigation demand function Q.

[0098] In one feasible implementation, the improved Penman-Monteith algorithm in step S300 specifically includes:

[0099] Introducing the canopy temperature correction term ΔT_c, the calculation formula is as follows:

[0100] ET c =ET0×(1+0.02ΔT) c )

[0101] Where ΔT c = T_canopy - T_air, where T_canopy is the temperature obtained through infrared thermal imaging, and T_air is the reference temperature.

[0102] In one possible embodiment, initiating tiered irrigation includes:

[0103] First priority: Open the 55-60cm deep drip irrigation tube 203, with a flow rate Q1 = K1 × Q_total;

[0104] The second priority is to open the 35-40cm deep drip irrigation tube 202, with a flow rate of Q2 = K2 × Q_total;

[0105] The third priority is to open the 15-20cm deep drip irrigation tube 201, with a flow rate of Q3 = K3 × Q_total;

[0106] Where K1+K2+K3=1 and K1>K2>K3;

[0107] The MBR membrane flux is adjusted synchronously as follows: γ = γ0 × (1 + λ × ΔCOD), where λ is the water quality feedback coefficient, γ0 is the reference MBR membrane flux, and ΔCOD is the change in chemical oxygen demand (COD).

[0108] The method for dynamically determining the weighting coefficients of the tiered irrigation system includes:

[0109] K1 = 0.5 + 0.3 × sin(2πt / 24)

[0110] K2 = 0.3 - 0.1 × sin(2πt / 24)

[0111] K3 = 0.2 - 0.2 × sin(2πt / 24)

[0112] Where t represents the cumulative sunshine hours of the day.

[0113] It should be understood that soil moisture refers to the moisture content in the soil at a certain depth. Soil moisture forecasting is the basis for crop irrigation forecasting. In areas with scarce agricultural water resources, soil moisture forecasting is of guiding significance for the dynamic and rational regulation of farmland water.

[0114] Common methods for predicting soil moisture include empirical formulas, soil hydrodynamics, recession index, and water balance. This application uses the soil water balance method for soil moisture forecasting. This method comprehensively considers the factors affecting soil moisture changes and can be used to analyze different soil types, research objectives, time periods, and spatial locations within farmland, making it widely applicable. The water balance model for the crop planning wetting layer on a daily basis is as follows:

[0115] W i =W i-1 +P 0i +W Ti -ET i +M i +K i (5-1)

[0116] In the formula, Wi-1 is the initial planned soil moisture content of the wetting layer on day i, mm; Wi is the planned soil moisture content of the wetting layer at the end of day i, mm; P0i is the effective rainfall on day i, mm; WTi is the increase in water volume due to the increase in the planned wetting layer on day i, mm; ETi is the crop water requirement on day i, mm; Mi is the irrigation volume on day i, mm; Ki is the groundwater recharge on day i, mm.

[0117] Since the groundwater depth in the experimental area is about 4m, the replenishment of crops by groundwater can be ignored. Therefore, equation (5-1) can be transformed into:

[0118] W i =W i-1 +P 0i +W n -ET i +M i (5-2)

[0119] The planned soil moisture content of the wetting layer, crop water requirement, irrigation amount, and the increase in water due to the increase in the planned wetting layer at the beginning and end of day i can be calculated by the following formulas:

[0120] W i-1 =1000·n·Hi-1 ·θ i-1 (5-3)

[0121] W i =1000·n·H i ·θ i (5-4)

[0122] ET i =K ci ·K wi ·ET 0i (5-5)

[0123] M i =1000·n·H i ·(θ c1 -θ) (5-6)

[0124] W π =1000·n·(H i -H i-1 )·θ deep (5-7)

[0125] In the formula, H i-1 Hi is the initial planned wetting depth on day i, in mm; Hi is the planned wetting depth at the end of day i, in mm; θi-1 is the initial soil moisture content on day i, as a percentage of soil volume; θi is the soil moisture content at the end of day i, as a percentage of soil volume; n is the soil porosity, as a percentage of soil volume; Kci is the crop coefficient on day i; Kwi is the soil moisture correction coefficient on day i; ET 0i θc1 represents the reference crop evapotranspiration on day i, in mm; θc1 represents the soil moisture content to be achieved after irrigation, expressed as a percentage of soil volume; θdeep represents the deep soil moisture content, expressed as a percentage of soil volume.

[0126] Equation (5-7) yields a daily recursive prediction model for the planned moisture content of the crop wetting layer:

[0127]

[0128] Starting from the crop sowing date, the soil moisture in the planned wet layer of the crop can be predicted daily by formula (5-8) and compared, analyzed and corrected with the measured values.

[0129] Regarding crop water requirement calculation models:

[0130] Irrigation district water demand is one of the most fundamental aspects of irrigation water use decisions and allocation. Only by forecasting irrigation district water demand and considering factors such as precipitation, groundwater, and external water supply can the rational and optimized allocation of water resources in the irrigation district be achieved. Irrigation district water demand is primarily calculated based on the water requirements of various crops within the irrigation district, i.e., crop evapotranspiration.

[0131] Based on the analysis of actual data and the specific conditions of the study area, this book uses a modified Penman formula to calculate the reference crop evapotranspiration in the irrigation area, taking into account the basic model of crop water demand. The calculation is then modified and adjusted by various factor function terms to obtain the predicted crop water demand in the irrigation area.

[0132] According to relevant research, the formula for calculating real-time crop water requirement is as follows:

[0133] ET i =K ci ·K wi ·ET 0i (5-9)

[0134] In the formula, ET i Let K be the crop water requirement for day i, in mm; ci K represents the crop coefficient for day i; wi ET is the soil moisture correction factor for day i under real-time under-sufficient irrigation conditions. 0i The reference crop water requirement for day i is in mm.

[0135] The reference crop evapotranspiration rate is a hypothetical reference crop canopy evapotranspiration rate. The hypothetical crop height is 0.12 m, with a fixed leaf surface resistance of 70 s / m and a reflectance of 0.23. It closely resembles the evapotranspiration rate of a wide-open, uniformly tall, vigorously growing, fully covered green grassland that does not suffer from water shortage. It is commonly used as a reference for calculating the water requirements of various specific crops. This book uses the modified Penman formula to calculate the reference crop water requirement ET0. The specific calculation formula is as follows:

[0136]

[0137] In the formula, ET0 is the reference crop evapotranspiration, in mm·d. -1 ;P 0 P is the standard atmospheric pressure at sea level. 0 =1013.25 hPa; P is the actual air pressure at the calculation location; Rn is the net radiation received by the surface of the reference crop canopy. denoted as a temperature function under standard atmospheric pressure; Δ represents the slope of the curve of saturated water vapor pressure versus temperature at average air temperature. γ is the hygrometer constant; e b saturated vapor pressure, in kPa; t is the average temperature; Ea For drying power, E a =0.26(1+0.54u)(e a -e d );e d The actual local water vapor pressure is denoted as ν; the wind speed at a height of 2m above the ground is ν.

[0138] Taking into account the climate conditions and requirements of the study area, K ci The calculation adopts a method that varies daily with the cumulative number of days in the crop's growth period:

[0139]

[0140] In the formula, i represents the cumulative number of days in the maternity period; I represents the total number of days in the maternity period.

[0141] When there is sufficient moisture in the field, the soil moisture correction factor K is generally not considered in the calculation of crop evapotranspiration. wi The influence of K. Under conditions of insufficient irrigation or water shortage, the capillary conductivity in the soil decreases, the root water absorption rate decreases, and the influence of the soil factor function term is mainly manifested as soil water stress. Therefore, K wi It mainly reflects the impact of soil moisture conditions on crop evapotranspiration.

[0142] The calculation formula is as follows:

[0143]

[0144] In the formula, θi is the soil moisture content on day i, expressed as a percentage of soil volume. θ max Field water holding capacity, expressed as a percentage of soil volume. θ c1 The upper limit of suitable soil moisture for non-fully irrigated soil is defined as the percentage of field capacity θ. max The percentage is expressed as a percentage and is determined according to different experimental protocols in the study; θ c2 The lower limit of suitable soil moisture for non-fully irrigated soil is defined as the percentage of θ. max The percentage is expressed as a percentage; it is determined according to different experimental schemes in the study; α is an empirical coefficient, which can be taken as 0.89 for dryland crops.

[0145] Determination of planned wetting layer depth: For dryland crops, the planned wetting layer depth usually refers to the main root water absorption layer of the crop. It mainly depends on the crop growth status and the depth of the crop root activity layer, and is also related to factors such as crop variety, growth stage, field soil properties, groundwater depth and soil microbial activity.

[0146] In the early stages of crop growth, the root system is relatively shallow and water consumption is low. However, in order to maintain soil microbial activity and create conditions for future root growth, the planned wetting layer depth is generally slightly larger than the root activity layer depth. As the crop grows and the root system develops, water demand increases, and the planned wetting layer gradually deepens. Towards the end of the growth period, as the crop root system stops developing and water demand decreases, the planned wetting layer depth should not be increased further.

[0147] The planned wetting layer depth should increase as the crop grows and its root system deepens. In different climate zones, hydrological years, and different growth stages of the crop, the planned soil wetting layer depth can be flexibly adjusted based on local water resources and weather conditions. Therefore, the planned soil wetting layer depth during irrigation should be determined comprehensively based on specific circumstances.

[0148] This book assumes that the planned wetting layer increases linearly and uniformly each day throughout the crop's entire growth period. Therefore, the planned wetting layer depth for any given day can be simulated using a linear, day-by-day recursive model. To this end, a calculation model for the planned wetting layer depth of crops is established:

[0149]

[0150] In the formula, H i h is the planned wetting layer depth for the crop on day i. n-1 h is the initial value of the planned wetting layer depth for the (n-1)th reproductive period; n Let be the initial value of the planned wetting layer depth for the nth growth stage; n is the number of crop growth stages; i is the cumulative number of days of crop growth after sowing. The number of growth days in the nth reproductive period; Let j be the number of days of growth in the j-th reproductive period. Let j be the number of days of growth in the (j-1)th reproductive period, where j = 1, 2, ..., n.

[0151] Regarding the calculation of effective rainfall:

[0152] Effective rainfall refers to the portion of rainfall available to meet crop transpiration and soil evaporation. For areas with scarce agricultural water resources, fully utilizing limited rainfall can effectively alleviate the shortage of agricultural water. For under-irrigated areas, the full and efficient use of rainfall is crucial for developing rational irrigation systems and managing agricultural water resources. Many factors influence effective rainfall. Due to different calculation purposes and variations in regional climate conditions and geographical location, the methods for estimating effective rainfall also differ. Appropriate calculation methods must be selected based on the specific conditions of the region.

[0153] Currently, commonly used methods for calculating effective rainfall include direct monitoring techniques and indirect calculation methods. Indirect calculation methods include empirical methods such as formulas and charts, as well as the soil water balance method. Through comparative analysis of the reliability and adaptability of the calculation results, significant differences were found in the simulation results of different models under the same conditions.

[0154] Many factors influence effective rainfall, and the estimation methods for effective rainfall vary depending on the calculation purpose. For a specific region, a calculation method suitable for that region's characteristics must be selected. Considering the actual conditions of the study area, this model uses the empirical rainfall utilization coefficient method to calculate effective rainfall. The calculation formula is as follows:

[0155] P 0i =α·P i (5-14)

[0156] In the formula, P 0i P represents the effective rainfall in stage i; i α represents the rainfall in stage i; α is the effective utilization coefficient of rainfall, and the values ​​of α are shown in Table 5-1.

[0157] Table 5-1 Values ​​of Rainfall Effective Utilization Coefficient α

[0158]

[0159] Regarding the determination of real-time irrigation volume:

[0160] The basic principle of real-time irrigation forecasting is to establish a daily recursive simulation model of soil moisture in the field based on measured meteorological data and the principle of water balance. This model accurately forecasts the short-term and even daily changes in soil moisture for crops. When the soil moisture content is close to the minimum allowable moisture content for the crop's growth stage, an irrigation decision is made, determining the irrigation amount and timing. If precipitation or irrigation replenishment occurs during the forecast period, irrigation is postponed, and the forecast results are adjusted and corrected in a timely manner based on the actual situation. Simultaneously, the simulation results, such as soil moisture, are corrected based on actual monitoring values.

[0161] The irrigation quota is calculated as follows:

[0162] (1) Crop irrigation amount when water supply is sufficient:

[0163] When the incoming water volume is large enough to meet irrigation needs, the irrigation volume M1 is:

[0164] M i =1000·n·H i (1-θ i )·θ max (5-15)

[0165] In the formula, θi H represents the initial soil moisture content on day i; i θmax is the planned wetting layer depth for crop growth on day i; θmax is the field water holding capacity as a percentage of soil volume; n is the porosity of the soil within the planned wetting layer as a percentage of soil volume.

[0166] (2) Irrigation amount for crops when water supply is insufficient:

[0167] When water supply is insufficient or water resources are scarce, crops are irrigated using their inherent physiological water-saving and drought-resistant properties. The irrigation volume Mi is:

[0168] M i =1000·n·H i (θ c1 -θ i )·θ max (5-16)

[0169] In the formula, θc1 is the soil moisture content to be achieved after irrigation. When irrigation is not fully completed, θc1 is generally taken as 90%. max In this study, values ​​were selected based on different design values ​​from the irrigation experiment.

[0170] The aforementioned devices may be executed by chips or chip modules. The modules / units included in the various devices and products described in the above embodiments may be software modules / units, hardware modules / units, or a combination of both.

[0171] The following describes an electronic device provided by an embodiment of this application. Please refer to [link / reference]. Figure 3 , Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application, wherein the electronic device 3100 implements... Figure 1 The corresponding method embodiment's function. Specifically, the electronic device 3100 includes: a receiver 3101, for example, which can be... Figure 1 The water quality sensor 301 and transmitter 3102, for example, can be... Figure 1 Soil entropy monitoring array 302; processor 3103, for example, can be... Figure 1 The device includes a crop growth monitor 303, or a control center 40, and a memory 3104 (where the number of processors 3103 in the electronic device 3100 can be one or more), wherein the processor 3103 may include an application processor 31031 and a communication processor 31032. In some embodiments of this application, the receiver 3101, transmitter 3102, processor 3103, and memory 3104 may be connected via a bus or other means.

[0172] Memory 3104 may include read-only memory and random access memory, and provides instructions and data to processor 3103. A portion of memory 3104 may also include non-volatile random access memory (NVRAM). Memory 3104 stores processor and operation instructions, executable modules or data structures, or subsets thereof, or extended sets thereof, wherein the operation instructions may include various operation instructions for implementing various operations.

[0173] Processor 3103 controls the operation of electronic devices. In specific applications, the various components of electronic devices are coupled together through a bus system, which may include not only data buses but also power buses, control buses, and status signal buses. However, for clarity, all buses in the diagram are referred to as a bus system.

[0174] The methods disclosed in the embodiments of this application can be applied to or implemented by processor 3103. Processor 3103 can be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above methods can be completed by integrated logic circuits in the hardware or by instructions in software form within processor 3103. Processor 3103 can be a general-purpose processor, digital signal processor (DSP), microprocessor or microcontroller, as well as a vision processing unit (VPU), tensor processing unit (TPU), or other processors suitable for AI computation. It may further include application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. Processor 3103 can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiments of this application can be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory 3104, and processor 3103 reads information from memory 3104 and, in conjunction with its hardware, completes the steps in the above method embodiments.

[0175] Receiver 3101 can be used to receive input digital or character information, and to generate signal inputs related to the settings and function control of electronic devices. Transmitter 3102 can be used to output digital or character information through the first interface; transmitter 3102 can also be used to send instructions to the disk group through the first interface to modify the data in the disk group; transmitter 3102 may also include a display device such as a display screen.

[0176] This application also provides a computer program product that, when run on a computer, causes the computer to perform the steps performed by the aforementioned device, or causes the computer to perform the steps performed by the aforementioned device.

[0177] This application also provides a computer-readable storage medium storing a program for signal processing, which, when run on a computer, causes the computer to perform the steps performed by the aforementioned device, or causes the computer to perform the steps performed by the aforementioned device.

[0178] The execution device, training device, or electronic device provided in this application embodiment can specifically be a chip. The chip includes a processing unit and a communication unit. The processing unit can be, for example, a processor, and the communication unit can be, for example, an input / output interface, pins, or circuits. The processing unit can execute computer execution instructions stored in the storage unit to cause the chip within the execution device to execute the data processing method described in the above embodiments, or to cause the chip within the training device to execute the data processing method described in the above embodiments. Optionally, the storage unit is a storage unit within the chip, such as a register or cache. Alternatively, the storage unit can be a storage unit located outside the chip within the wireless access device, such as a read-only memory (ROM) or other types of static storage devices capable of storing static information and instructions, such as random access memory (RAM).

[0179] It should also be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. In addition, in the device embodiment drawings provided in this application, the connection relationship between modules indicates that they have a communication connection, which can be implemented as one or more communication buses or signal lines.

[0180] Through the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware, or it can be implemented by special-purpose hardware including application-specific integrated circuits, special-purpose CPUs, special-purpose memory, special-purpose components, etc. Generally, any function performed by a computer program can be easily implemented by corresponding hardware, and the specific hardware structure used to implement the same function can also be diverse, such as analog circuits, digital circuits, or special-purpose circuits. However, for this application, software program implementation is more often the preferred implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a readable storage medium, such as a computer floppy disk, USB flash drive, mobile hard disk, ROM, RAM, magnetic disk, or optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, training equipment, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0181] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product.

[0182] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this application are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, training device, or data center to another website, computer, training device, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a training device or data center that integrates one or more available media. The available media may be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state drives (SSDs)).

Claims

1. A method applied to an integrated wastewater treatment and irrigation system, characterized in that, include: S100, multi-stage wastewater treatment steps: The wastewater input from the inlet (101) is separated into solid and liquid components by a grit chamber (102), inorganic particles are removed by a grit chamber (103), and the influent flow rate is dynamically balanced by an equalization tank (104). Nitrogen and phosphorus removal are carried out in the anaerobic tank (1051) of the biological treatment disinfection unit (105), and the aerobic tank (1052) uses MBR membrane module (10521) and variable frequency aeration system (10522) to achieve biodegradation of organic matter; The effluent after disinfection in the disinfection tank (1055) is stored in the clear water tank (1056), and the water quality parameters are fed back to the control center (40) in real time. S200, Multi-dimensional Environmental Sensing Steps: Soil moisture content matrix was obtained using a soil moisture monitoring array (302); Crop canopy temperature and NDVI index were collected using the multispectral imaging module in the crop growth monitor (303); Organic matter levels at each stage of wastewater treatment are monitored using a water quality sensor (301). S300, Intelligent Decision Generation Steps: Reference crop water requirement calculated based on the improved Penman-Monteith algorithm. Combined with real time The coefficient generates the theoretical water requirement of crops. ; The real-time irrigation volume analysis module (402) based on a real-time water-saving irrigation simulation model and image recognition technology predicts the soil moisture change Δθ over the next N days, and constructs the irrigation demand function Q=f( ,Δθ,θ_min); The wastewater treatment parameter set is optimized using the wastewater volume regulation calculation and analysis module (401) based on the IUWS model; S400 initiates tiered irrigation based on the irrigation demand function Q.

2. The method according to claim 1, characterized in that, The improved Penman-Monteith algorithm in S300 specifically includes: Introducing a canopy temperature correction term The calculation formula is: ； in =T_canopy-T_air, where T_canopy is the temperature obtained through infrared thermal imaging, and T_air is the reference temperature.

3. The method according to claim 1, characterized in that, Initiating tiered irrigation includes: First priority: Open the 55-60cm deep drip irrigation line (203), flow rate Q1=K1×Q_total; The second priority is to open the 35-40cm deep drip irrigation tube (202), with a flow rate Q2=K2×Q_total; The third priority is to open the 15-20cm deep drip irrigation tube (201), with a flow rate Q3 = K3 × Q_total; Where K1+K2+K3=1 and K1>K2>K3; The MBR membrane flux is adjusted synchronously as follows: γ = γ0 × (1 + λ × ΔCOD), where λ is the water quality feedback coefficient, γ0 is the reference MBR membrane flux, and ΔCOD is the change in chemical oxygen demand (COD). The method for dynamically determining the weighting coefficients of the tiered irrigation system includes: K1 = 0.5 + 0.3 × sin(2πt / 24) K2 = 0.3 - 0.1 × sin(2πt / 24) K3 = 0.2 - 0.2 × sin(2πt / 24) Where t represents the cumulative sunshine hours of the day.

4. The method according to claim 1, characterized in that, The integrated wastewater treatment and irrigation system includes: Wastewater treatment device (10) includes an inlet (101), a screen well (102), a grit chamber (103), an equalization tank (104), a biological treatment and disinfection section (105), and an outlet (106) connected in sequence. The biological treatment and disinfection section (105) includes an anaerobic tank (1051), an aerobic tank (1052), a sludge tank (1053), a sedimentation tank (1054), a disinfection tank (1055), and a clear water tank (1056). The aerobic tank (1052) integrates a submerged MBR membrane module (10521) and a variable frequency aeration system (10522). The irrigation delivery device (20) includes a multi-level buried depth drip irrigation network (201-203), a pressure-compensated dripper (204), and a solenoid valve assembly (205), wherein the multi-level buried depth drip irrigation network is buried in multiple gradients; The monitoring module (30) includes a water quality sensor (301) arranged in the sewage treatment device (10) and the irrigation delivery device (20), the soil moisture monitoring array (302) includes multiple depth sensor nodes, and the crop growth monitor (303) is equipped with a multispectral imaging module; The control center (40) includes a wastewater volume regulation calculation and analysis module (401) based on the IUWS model, a real-time irrigation volume analysis module (402) based on a real-time water-saving irrigation simulation model and image recognition technology, and a data transmission module (403) that sends commands to each control element. An energy module (50) electrically connected to various electrical components includes a photovoltaic panel (501) and an energy storage system (502).

5. The method according to claim 4, characterized in that, The regulating tank (104) is equipped with a liquid level adaptive baffle (1041). The liquid level adaptive baffle (1041) is driven by a shape memory alloy and can automatically adjust the opening degree according to the inlet water flow. The surface of the baffle is equipped with a self-cleaning nano-coating.

6. The method according to claim 4 or 5, characterized in that, The membrane flux control of the MBR membrane module (10521) adopts a fuzzy PID algorithm based on the TMP-flux coupling model, and the membrane cleaning cycle is automatically triggered by the detection of sudden changes in transmembrane pressure difference.

7. The method according to claim 4 or 5, characterized in that, The real-time water-saving irrigation simulation model includes a soil moisture prediction model, a crop water requirement calculation model, a planned wetting layer depth calculation model, an effective rainfall calculation model, and a real-time irrigation volume calculation model.

8. The method according to claim 4 or 5, characterized in that, The sedimentation tank (1054) includes a sludge return pump station and a sludge dewatering device to allow sludge to return to the anaerobic tank and for sludge dewatering. The disinfection tank (1055) includes a chlorine dioxide disinfection device.

9. A computer program product, when run on an electronic device, causes the electronic device to perform the method described in any one of claims 1 to 3.

10. A computer-readable storage medium storing a program therein, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1 to 3.

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