Integrated sewage treatment and irrigation method, system and medium

Abstract

The invention provides an integrated sewage treatment intelligent irrigation method and system and a medium. The integrated sewage treatment intelligent irrigation system comprises a sewage treatment device, an irrigation conveying device, a control center and an energy module electrically connected with all electrical elements. Wherein the sewage treatment device comprises a water inlet, a grating well, a grit chamber, an adjusting tank, a biological treatment disinfection part and a water outlet which are connected in sequence, the biological treatment disinfection part comprises an anaerobic tank, an aerobic tank, a sludge tank, a sedimentation tank, a disinfection tank and a clean water tank, and the aerobic tank is integrated with an immersed MBR membrane assembly and a variable-frequency aeration system; the irrigation conveying device comprises a multi-stage burial depth drip irrigation pipe network, a pressure compensation type water dropper and an electromagnetic valve group, and the multi-stage burial depth drip irrigation pipe network is buried according to a plurality of gradients. According to the system, intelligent adjustment of water quantity and water quality in the sewage treatment process and real-time intelligent irrigation of farmlands, greenbelts, vegetable gardens and the like are achieved, and the purposes of intensive conservation and utilization of water resources and intelligent management are achieved.

Description

Technical Field

[0001] The present invention relates to the field of sewage treatment, and particularly to an integrated sewage treatment and irrigation method, system and medium. Background Art

[0002] Actively exploring the resource utilization ways of domestic sewage, and converting domestic sewage into water resources available for agricultural irrigation through advanced treatment technologies, which can not only reduce the dependence on natural water resources, but also improve the utilization efficiency of water resources.

[0003] Due to the small and unstable sewage discharge, the traditional sewage treatment methods in sewage treatment plants often cannot meet the needs of sewage treatment in remote urban areas, urban communities or rural areas. However, the sewage treatment and farmland irrigation mostly rely on manual operation or simple automation equipment, resulting in problems such as incomplete monitoring, untimely adjustment and resource waste. Summary of the Invention

[0004] The purpose of the present invention is to provide an integrated sewage treatment and irrigation method, system and medium, so as to realize the intelligent adjustment of water quantity and water quality during the sewage treatment process and the real-time intelligent irrigation of farmland, green spaces, vegetable gardens, etc., and achieve the purpose of intensive and economical utilization of water resources and intelligent management.

[0005] In the first aspect, an embodiment of the present invention provides an integrated sewage treatment and irrigation system, including:

[0006] A sewage treatment device, including an inlet, a grille well, a grit chamber, an adjustment tank, a biological treatment and disinfection unit, and a drain port connected in sequence. Among them, 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. Among them, the aerobic tank is integrated with a submerged MBR membrane module and a variable frequency aeration system;

[0007] An irrigation and conveying device, including a multi-level buried drip irrigation pipe network, pressure-compensating drip emitters and a solenoid valve group. Among them, the multi-level buried drip irrigation pipe network is buried according to multiple gradients;

[0008] A monitoring module, including water quality sensors arranged in the sewage treatment device and the irrigation and conveying device, a soil moisture monitoring array including multiple depth sensor nodes, and a crop growth monitor equipped with a multi-spectral imaging module;

[0009] A control center, including a sewage water quantity adjustment calculation and analysis module based on the IUWS model, a real-time irrigation water quantity analysis module based on a real-time water-saving irrigation simulation model and image recognition technology, and a data transmission module that issues instructions to each control element;

[0010] An energy module electrically connected to each electrical component, including a photovoltaic panel and an energy storage system.

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

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

[0013] In a 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 water volume calculation model.

[0014] In a possible implementation, the sedimentation tank includes a sludge return pumping station and a sludge dehydrator for sludge to return to the anaerobic tank and sludge dehydration, and the disinfection tank includes a chlorine dioxide disinfection device.

[0015] In a second aspect, the embodiments of the present invention further provide a method applied to the system according to any one of the embodiments in the first aspect, including the following steps:

[0016] S100, multi-stage sewage treatment step:

[0017] The sewage input from the water inlet is subjected to solid-liquid separation through a grid well, inorganic particles are removed by a grit chamber, and the influent flow rate is dynamically balanced by a regulating tank;

[0018] Denitrification and phosphorus removal are carried out through the anaerobic tank in the biological treatment and disinfection section, and the aerobic tank uses an MBR membrane module and a variable frequency aeration system to achieve the biodegradation of organic matter;

[0019] The effluent disinfected by the disinfection tank is stored in a clean water tank, and the water quality parameters are fed back to the control center in real time;

[0020] S200, multi-dimensional environment perception step:

[0021] The soil moisture content matrix is obtained through a soil moisture monitoring array;

[0022] The crop canopy temperature and NDVI index are collected by using the multi-spectral imaging module in the crop growth monitor;

[0023] The organic matter indexes of each node of sewage treatment are monitored by a water quality sensor;

[0024] S300, intelligent decision-making generation step:

[0025] Calculate the reference crop water requirement ET based on the improved Penman-Monteith algorithm 0, generating the crop theoretical water requirement ET in combination with the real-time Kc coefficient c = ET 0 × K c ;

[0026] Predicting the change Δθ of soil moisture content in the next N days through the real-time irrigation water volume analysis module based on the real-time water-saving irrigation simulation model and image recognition technology, and constructing the irrigation demand function Q = f(ETc, Δθ, θ_min);

[0027] Optimizing the sewage treatment parameter set by using the sewage volume regulation calculation and analysis module based on the IUWS model;

[0028] S400, starting hierarchical irrigation based on the irrigation demand function Q.

[0029] In a third aspect, an electronic device is further provided in an embodiment of the present invention, including a memory and a processor. A program is stored on the memory and can run on the processor. When the program is executed by the processor, the electronic device implements the method in any possible embodiment of the second aspect.

[0030] In a fourth aspect, a computer-readable storage medium is further provided in an embodiment of the present invention. The readable storage medium includes a program. When the program runs on an electronic device, the electronic device executes the method in any possible implementation of the second aspect described above.

[0031] In a fifth aspect, a computer program product is further provided in an embodiment of the present invention. When the program product runs on an electronic device, the electronic device executes the method in any possible implementation manner of the first aspect described above.

[0032] The present invention provides an integrated sewage treatment and irrigation system, method, program 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 the present invention are mainly reflected in the following aspects:

[0034] First, the integrated intelligent management of sewage treatment and irrigation is realized. Through the collaborative work of the sewage treatment device, irrigation delivery device, monitoring module and control center, the present invention can realize the intelligent regulation of water volume and water quality in the sewage treatment process, as well as the real-time intelligent irrigation of farmland, green space, vegetable gardens, etc., thereby achieving the purpose of intensive and economical utilization and intelligent management of water resources.

[0035] II. The efficiency and effectiveness of sewage treatment are improved. The multi-stage treatment steps in the sewage treatment device, including solid-liquid separation, inorganic particle removal, dynamic balance of influent flow rate, nitrogen and phosphorus removal, and biodegradation of organic matter, can effectively remove pollutants in sewage and improve the quality of the effluent. At the same time, 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 service life of the membrane.

[0036] III. Precision and intelligence in irrigation are achieved. Through the multi-dimensional environmental perception step, the present invention can obtain information such as soil moisture content, crop canopy temperature, NDVI index, and organic matter indicators at each node of sewage treatment in real time, providing data support for intelligent decision-making. In the intelligent decision-making generation step, a real-time irrigation water volume analysis module based on a real-time water-saving irrigation simulation model and image recognition technology can predict future soil moisture changes and construct an irrigation demand function, thus achieving precision and intelligence in irrigation.

[0037] IV. It has broad application prospects and promotion value. The integrated sewage treatment and irrigation system, method, program, and medium of the present invention are applicable to various irrigation scenarios such as farmland, green spaces, and vegetable gardens, can effectively improve the water resource utilization efficiency, reduce water resource waste, and are of great significance for promoting the sustainable development of agriculture and promoting the construction of ecological civilization. At the same time, the technical solution of the present invention has the characteristics of being easy to promote and implement, and has high practical value and social benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for description in the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0039] Figure 1 It is a schematic diagram of the composition structure of the integrated sewage treatment and irrigation system provided by the embodiment of the present invention;

[0040] Figure 2 It is a schematic diagram of the process flow of the integrated sewage treatment and irrigation method provided by the embodiment of the present invention;

[0041] Figure 3 It is a schematic diagram of the structure of an electronic device provided by the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0042] In the description of the embodiments of the present invention, the terms used in the following embodiments are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification and appended claims of the present invention, the singular forms "a", "the", "above-mentioned", "this", and "such" are also intended to 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" mean one or more than two (including two). The term "and / or" is used to describe the relationship between associated objects and indicates that three relationships can exist; for example, A and / or B can mean: A exists alone, A and B exist simultaneously, or B exists alone, where A and B can be singular or plural. The character " / " generally indicates that the associated objects before and after are in an "or" relationship.

[0043] References in this specification to "one embodiment" or "some embodiments" or the like mean that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the present invention. Thus, statements such as "in one embodiment", "in some embodiments", "in other some embodiments", "in still other embodiments" and the like that appear in different places in this specification are not necessarily all referring to the same embodiment, but rather mean "one or more but not all embodiments", unless otherwise specifically emphasized in another way. The terms "comprise", "include", "have" and their variants all mean "including but not limited to", unless otherwise specifically emphasized in another way. The term "connection" includes direct connection and indirect connection, unless otherwise stated. "First" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features.

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

[0045] The present invention aims to provide an integrated sewage treatment and irrigation system that combines high technology, energy conservation and environmental protection, and intelligent control. The system integrates a sewage treatment device, an irrigation conveying device, a monitoring module, a control center, and an energy module electrically connected to each electrical component, realizing the intelligent adjustment of water volume and water quality during the sewage treatment process and the real-time intelligent irrigation of farmland, green spaces, vegetable gardens, etc., achieving the purpose of intensive and intelligent management of water resources.

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

[0047] The sewage treatment device 10 includes a water inlet 101, a grille well 102, a grit chamber 103, an adjustment tank 104, a biological treatment and disinfection unit 105, and a drain outlet 106 connected in sequence. Among them, 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. Among them, the aerobic tank 1052 is integrated with a submerged MBR membrane module 10521 and a variable frequency aeration system 10522;

[0048] The irrigation conveying device 20 includes a multi-stage buried drip irrigation pipe network 201 - 203, pressure-compensating drip emitters 204, and a solenoid valve group 205. Among them, the multi-stage buried drip irrigation pipe network is buried according to multiple gradients;

[0049] The monitoring module 30 includes water quality sensors 301 arranged in the sewage treatment device 10 and the irrigation conveying device 20. The soil moisture monitoring array 302 includes multiple depth sensor nodes, and the crop growth monitor 303 is equipped with a multi-spectral imaging module;

[0050] The control center 40 includes a sewage volume adjustment calculation and analysis module 401 based on the IUWS model, a real-time irrigation water 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 issues instructions to each control element;

[0051] The energy module 50 electrically connected to each electrical component includes a photovoltaic panel 501 and an energy storage system 502.

[0052] In a possible embodiment, the adjustment tank 104 is provided 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 according to the influent flow rate. 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 the sudden change of the transmembrane pressure difference.

[0054] In a possible embodiment, the sewage volume adjustment calculation and analysis module 401 based on the IUWS model automatically adjusts the water inlet 101, the drain outlet 106, the aeration pump in the variable frequency aeration system 10522, etc. in the integrated domestic sewage treatment device 10.

[0055] The real-time irrigation water volume analysis module 402 based on the 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, providing the system with the basis for automatically controlling the valves in the irrigation components.

[0056] The data transmission module 403 that issues commands to each control component issues commands to the specified control components according to the decisions made by the sewage volume adjustment calculation and analysis module and the real-time irrigation water volume analysis module.

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

[0058] In a possible embodiment, the regulating tank 104 includes a liftable regulating baffle 1041 to adjust the water inflow into the anaerobic tank. The aerobic tank 1052 includes an immersed MBR membrane module 10521 and a variable-frequency aeration system 10522. The sedimentation tank 1054 includes a sludge return pumping station and a sludge dehydrator for sludge return to the anaerobic tank and sludge dehydration. The disinfection tank 1055 includes a chlorine dioxide disinfection device. The sedimentation tank 1054 includes a sludge return pumping station and a sludge dehydrator for sludge return to the anaerobic tank and sludge dehydration. The disinfection tank 1055 includes a chlorine dioxide disinfection device.

[0059] Further, the water inlet 101 is connected to the grille well 102 to remove solid waste in the sewage;

[0060] The main function of the grit chamber 103 is to remove inorganic particles in the sewage by gravity to prevent these impurities from affecting the normal operation of subsequent treatment structures;

[0061] The regulating tank 104 is primarily used to regulate the inflow and outflow of water, ensuring relatively stable water volume and quality of the influent to the sewage treatment system, making the treatment system more stable and efficient;

[0062] The anaerobic tank 1051 degrades organic substances into simple organic substances and gases through anaerobic respiration, which is used to degrade organic substances, remove nitrogen, phosphorus, methane, etc.;

[0063] The aerobic tank 1052 effectively removes organic substances and nitrogen sources in the wastewater through processes such as biological denitrification, biodegradation, and physical precipitation;

[0064] The sludge tank 1053 stabilizes the sludge generated during the sewage treatment process through biological treatment, reducing the volume and harmful substances of the sludge. At the same time, biogas is recycled, making the sludge easier to handle and dispose of;

[0065] The sedimentation tank 1054 separates suspended solids and other solids in the wastewater through gravitational sedimentation;

[0066] The disinfection tank 1055 eliminates pathogens and purifies the water quality through a chlorine dioxide device;

[0067] The clear water tank 1056 is connected to the drain outlet, and an automatic electromagnetic valve is installed at the drain outlet. When the water quality in the clear water tank does not meet the standard, the automatic valve closes automatically;

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

[0069] Among them, an electromagnetic valve is installed at the inlet of the regulating storage tank, several outlets are provided, the outlets extend out of the storage tank through a hose and an electromagnetic valve is installed at the hose. The electromagnetic valve is controlled by an intelligent control system. An overflow pipe is designed at the top of the regulating storage tank. When the water storage volume exceeds the maximum water storage volume of the storage tank, it overflows to the nearby water area

[0070] The buried drip irrigation pipe is made of PVC or PE material. After the water outlet valve of the storage tank, the drip irrigation pipe is divided into three branch pipes, which are respectively buried at 15 - 20 cm, 35 - 40 cm, and 55 - 60 cm in the soil. Electromagnetic valves are installed on each branch pipe, and the electromagnetic valves are controlled by an intelligent control system.

[0071] The automatic monitoring components include water quality detection probes for the inlet and outlet of the integrated sewage treatment device, oxygen content monitoring probes in the aerobic tank, soil moisture content monitoring probes, a solar power generation device for providing electricity, and a battery pack.

[0072] In a possible embodiment, the real-time monitoring probes for the inlet and outlet water quality of the integrated sewage treatment device are respectively fixed on the pool walls of the regulating tank and the clear water tank, mainly for real-time monitoring of indicators such as COD, turbidity, ammonia nitrogen, residual chlorine, total phosphorus, and total nitrogen. The monitoring probes are installed with LoRaWAN modules to transmit the real-time monitoring data to the cloud platform. The monitoring probes and LoRaWAN modules are powered by the solar power generation device and the battery pack.

[0073] In a possible embodiment, the oxygen content monitoring probe in the aerobic tank 1052 is installed on the pool wall of the aerobic tank to monitor the oxygen content in the aerobic tank. The monitoring probe is installed with a LoRaWAN module to transmit the real-time monitoring data to the cloud platform. The monitoring probe and LoRaWAN module are powered by the solar power generation device and the battery pack. The crop growth monitoring module captures images of crop growth in units of 1 hour. The monitoring module is installed with a LoRaWAN module to transmit the real-time monitoring images to the cloud platform. The monitoring probe and LoRaWAN module are powered by the solar power generation device and the battery pack.

[0074] In addition, soil moisture monitoring probes are buried 20, 40, and 60 cm underground to mainly monitor the real-time soil moisture content. The monitoring probes are installed with LoRaWAN modules to transmit 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.

[0075] Among them, the solar power generation device and the battery pack are installed in the open space near the integrated device. A liftable and rotatable stainless steel pipe supports the solar panel. The solar panel is connected to the battery, and the battery is connected to each monitoring probe through wires.

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

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

[0078] Among them, the electromagnetic valve at the outlet of the clear water tank 1056 is connected to the reservoir and the drip irrigation pipe through a hose. The valve is installed with a LoRaWAN module to receive instructions sent by the cloud platform system to complete water volume regulation. The valve and LoRaWAN module are powered by a solar power generation device and a battery pack.

[0079] In a possible embodiment, the inlet valve of the buried drip irrigation pipe is connected to the reservoir valve through a hose. The valve is installed with a LoRaWAN module to receive instructions sent by the cloud platform system to complete water volume regulation. The valve and LoRaWAN module are powered by a solar power generation device and a battery pack.

[0080] In a possible embodiment, the aeration pump and the air volume regulating valve are used to provide oxygen to the microorganisms in the aerobic tank. The regulating valve is installed with a LoRaWAN module to receive instructions sent by the cloud platform system to complete air volume regulation. The valve and LoRaWAN module are powered by a solar power generation device and a battery pack.

[0081] In a possible embodiment, the automatic lifting and rotation control element of the solar support rod is installed with a LoRaWAN module to receive instructions sent by the cloud platform system and adjust the height and direction of the solar panel according to time to ensure maximum efficiency in receiving solar energy.

[0082] In a possible embodiment, the intelligent system includes a transmission and collection facility for data of each monitoring element, a sewage volume regulation calculation and analysis system based on the IUWS model, a real-time irrigation water volume analysis system based on the Penman formula, and a data transmission system for sending instructions to each control element.

[0083] In a possible embodiment, a battery valve including the rear end of a hose is controlled by the system, and the valve is controlled according to the water quality condition monitored in real time in the disinfection tank. When the water quality in the disinfection tank does not meet the standard, the valve automatically closes.

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

[0085] S100, multi-stage sewage treatment, including the following steps:

[0086] The sewage input from the water inlet 101 is subjected to solid-liquid separation through the grid well 102, the inorganic particles are removed by using the grit chamber 103, and the inlet flow rate is dynamically balanced by using the regulating tank 104;

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

[0088] The effluent disinfected by 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;

[0089] S200, multi-dimensional environment perception, including the following steps:

[0090] The soil moisture content matrix is obtained through the soil moisture monitoring array 302;

[0091] The canopy temperature of the crop and the NDVI index are collected by using the multi-spectral imaging module in the crop growth monitor 303;

[0092] The organic matter indexes at each node of sewage treatment are monitored by the water quality sensor 301;

[0093] S300, intelligent decision-making generation, including the steps:

[0094] Calculating the reference crop water requirement ET based on the improved Penman-Monteith algorithm 0 , and generating the theoretical crop water requirement ET by combining the real-time Kc coefficient c =ET 0 ×K c ;

[0095] Predict the change of soil moisture Δθ in the next N days through the real-time irrigation water volume analysis module 402 based on the real-time water-saving irrigation simulation model and image recognition technology, and construct the irrigation demand function Q = f(ET c , Δθ, θ_min);

[0096] Optimize the sewage treatment parameter set by using the sewage volume regulation calculation and analysis module 401 based on the IUWS model;

[0097] S400, start hierarchical irrigation based on the irrigation demand function Q.

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

[0099] Introduce the canopy temperature correction term ΔT_c, and the calculation formula is:

[0100] ET c = ET 0 ×(1 + 0.02ΔT c )

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

[0102] In a possible embodiment, starting hierarchical irrigation includes:

[0103] Open the drip irrigation pipe 203 with a depth of 55 - 60 cm at the first priority, and the flow rate Q1 = K1 × Q_total;

[0104] Open the drip irrigation pipe 202 with a depth of 35 - 40 cm at the second priority, and the flow rate Q2 = K2 × Q_total;

[0105] Open the drip irrigation pipe 201 with a depth of 15 - 20 cm at the third priority, and the flow rate Q3 = K3 × Q_total;

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

[0107] Synchronously adjust the MBR membrane flux γ = γ0 × (1 + λ × ΔCOD), 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 weight coefficient of the hierarchical irrigation 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 is the cumulative sunlight hours of the day.

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

[0114] Common methods for soil moisture prediction include empirical formula method, soil hydrodynamics method, recession index method, water balance method, etc. This application uses the soil water balance method for soil moisture forecasting. This method comprehensively considers the factors affecting soil water change, can analyze different time periods and farmland spatial positions for different soil types or research purposes, and has a wide application range. The water balance model of the planned wetting layer of crops with a daily time period 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 soil water content of the initial planned wetting layer on the i-th day, in mm; Wi is the soil water content of the planned wetting layer at the end of the i-th day, in mm; P0i is the effective rainfall on the i-th day, in mm; WTi is the water volume increased due to the increase of the planned wetting layer on the i-th day, in mm; ETi is the crop water requirement on the i-th day, in mm; Mi is the irrigation water volume on the i-th day, in mm; Ki is the groundwater recharge on the i-th day, in mm.

[0117] Since the groundwater depth in the test area is about 4m, the groundwater recharge to crops can be ignored. Therefore, formula (5 - 1) can be changed to:

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

[0119] Among them, the soil water content of the initial and end planned wetting layers, crop water requirement, irrigation water volume, and water volume increased due to the increase of the planned wetting layer on the i-th day can be obtained by the following formulas respectively:

[0120] Wi-1 = 1000·n·H i-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] Wherein, H i-1 is the initial planned wetting layer depth on the i-th day, in mm; Hi is the planned wetting layer depth at the end of the i-th day, in mm; θi-1 is the initial soil water content on the i-th day, expressed as a percentage of the soil volume; θi is the soil water content at the end of the i-th day, expressed as a percentage of the soil volume; n is the soil porosity, expressed as a percentage of the soil volume; Kci is the crop coefficient on the i-th day; Kwi is the soil water correction coefficient on the i-th day; ET 0i is the reference crop evapotranspiration on the i-th day, in mm; θc1 is the soil water content to be achieved after irrigation, expressed as a percentage of the soil volume; θdeep is the deep soil water content, expressed as a percentage of the soil volume.

[0126] From Equation (5 - 7), a daily recursive prediction model for the water content of the crop planned wetting layer can be obtained:

[0127]

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

[0129] Regarding the crop water requirement calculation model:

[0130] The water demand of the irrigation district is one of the most basic contents in making irrigation water decisions and water volume allocation. Based on the prediction of the water demand of the irrigation district and combined with precipitation factors and recharge factors such as groundwater and diverted water, the reasonable and optimal scheduling of water resources in the irrigation district can be carried out. The water demand of the irrigation district is mainly calculated based on the water demands of various crops in the irrigation district, that is, the crop evapotranspiration.

[0131] Combined with the situation of the study area and based on the analysis of actual data, this book calculates the reference crop evapotranspiration of the irrigation district using the modified Penman formula according to the basic model of crop water demand, and makes corrections and calculations in combination with various factor function terms to obtain the prediction results of the crop water demand in the irrigation district.

[0132] According to relevant research, the calculation formula for the real-time water demand of crops is as follows:

[0133] ET i =K ci ·K wi ·ET 0i (5-9)

[0134] In the formula, ET i is the water demand of the crop on the i-th day, in mm; K ci is the crop coefficient on the i-th day; K wi is the soil moisture correction coefficient on the i-th day under real-time deficit irrigation; ET 0i is the reference crop water demand on the i-th day, in mm.

[0135] The reference crop evapotranspiration is the evapotranspiration rate of a hypothetical reference crop canopy. The height of the hypothetical crop is 0.12 m, the fixed leaf surface resistance is 70 s / m, and the albedo is 0.23, which is very similar to the evapotranspiration of a green grassland with an open surface, uniform height, vigorous growth, completely covering the ground and not lacking water. It is usually used as a reference for calculating the water demands of various specific crops. This book uses the modified Penman formula to calculate the reference crop water demand ET 0 The specific calculation formula is:

[0136]

[0137] In the formula, ET 0 is the reference crop evapotranspiration, with the unit of mm·d -1 ; P 0 is the standard atmospheric pressure at sea level, P 0 =1013.25 hPa; P is the actual atmospheric pressure at the calculation location; Rn is the net radiation received by the reference crop canopy surface, is the temperature function under standard atmospheric pressure; △ is the slope of the saturated water vapor pressure and temperature curve at the average temperature, γ is the psychrometer constant; e bis the saturated water vapor pressure, with the unit of kPa; t is the average temperature; E a is the drying power, E a = 0.26(1 + 0.54u)(e a - e d ); e d is the actual water vapor pressure at the local area; u is the wind speed at a height of 2 m above the ground.

[0138] Taking into account the climate conditions and requirements of the study area comprehensively, where K ci is calculated using a calculation method that varies day by day with the cumulative number of days in the crop growth period:

[0139]

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

[0141] When the soil moisture in the field is sufficient, the calculation of crop evapotranspiration generally does not consider the influence of the soil moisture correction coefficient K wi . Under non - sufficient irrigation conditions or when the water is insufficient, 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 mainly reflects the influence 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 the i - th day, expressed as a percentage of the soil volume, θ max is the field water holding capacity, expressed as a percentage of the soil volume, θ c1 is the upper limit index of suitable soil moisture for non - sufficient irrigation, expressed as a percentage of the field water holding capacity θ max , and is determined according to different experimental schemes in the study; θ c2 is the lower limit index of suitable soil moisture for non - sufficient irrigation, expressed as a percentage of θ max , and is determined according to different experimental schemes in the study; α is an empirical coefficient, and for dry crops, it can be taken as 0.89.

[0145] Determination of the planned wetting layer depth: For dry crops, the planned wetting layer depth of the soil usually refers to the main root water absorption layer of the crop, which 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 activities.

[0146] In the initial stage of crop growth, the crop roots are relatively shallow and the water consumption is also relatively small. However, in order to maintain the activities of soil microorganisms and create conditions for the subsequent growth of the roots, the depth of the planned moist soil layer is generally taken to be slightly larger than the depth of the root activity layer. As the crop grows and the roots develop, the water demand increases and the planned moist soil layer gradually deepens. At the end of the growth period, since the crop roots stop developing and the water demand decreases, the depth of the planned moist soil layer should not continue to increase.

[0147] The depth of the planned moist soil layer should increase with the growth and development of the crop and the continuous deepening of the roots. In different types of climate zones, different hydrological years, and different growth and development stages of the crop, the depth of the planned moist soil layer can be flexibly controlled according to the local water source and weather conditions at that time. Therefore, the depth of the planned moist soil layer during irrigation should be determined comprehensively according to specific circumstances.

[0148] This book assumes that the planned moist soil layer increases linearly and uniformly every day during the entire growth period of the crop. Then, the depth of the planned moist soil layer on any day of the crop can be simulated using a linear daily recursive model. For this purpose, a calculation model for the depth of the planned moist soil layer of the crop is established:

[0149]

[0150] In the formula, H i is the depth of the planned moist soil layer on the i-th day of the crop; h n-1 is the initial value of the depth of the planned moist soil layer in the (n - 1)-th growth period; h n is the initial value of the depth of the planned moist soil layer in the n-th growth period; n is the number of growth periods of the crop; i is the cumulative number of days of growth after the crop is sown; is the number of days of growth in the n-th growth period; is the number of days of growth in the j-th growth period, is the number of days of growth in the (j - 1)-th growth period, and j = 1, 2,..., n.

[0151] Regarding the calculation of effective rainfall:

[0152] Effective rainfall refers to the part of the rainfall that can be used to meet the transpiration of crop plants and the evaporation of the soil between plants. For areas with shortages of agricultural water resources, making full use of limited rainfall can effectively alleviate the shortage of agricultural water. For deficit irrigation, making full and efficient use of rainfall is of great significance for formulating a reasonable irrigation system and agricultural water resource management. There are many factors affecting effective rainfall. Due to different calculation purposes, differences in the climate conditions and geographical locations of the research areas, the estimation methods of effective rainfall are not the same. For the specific conditions of the region, a reasonable calculation method needs to be selected.

[0153] At present, the commonly used methods for calculating effective rainfall include direct monitoring technology and indirect calculation methods. Indirect calculation methods include empirical methods such as formulas and charts, as well as the soil water balance method, etc. Through the comparative analysis of the reliability and adaptability of the calculation results, it is found that there are obvious differences in the simulation calculation results of different models under the same conditions.

[0154] There are many factors affecting effective rainfall. Due to different calculation purposes, the estimation methods of effective rainfall are not the same. For the characteristics of a certain region, a calculation method that conforms to the effective rainfall in that region needs to be selected. According to the actual situation of the research area, the empirical rainfall effective utilization coefficient method is used to calculate the effective rainfall in this model. The calculation formula is as follows:

[0155] P 0i = α·P i (5-14)

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

[0157] Table 5-1 Values of the rainfall effective utilization coefficient α

[0158]

[0159] Regarding the determination of real-time irrigation water 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 according to the principle of water balance, make an accurate forecast of the short-term and even daily soil moisture changes of crops. When the soil moisture content is close to the lowest allowable moisture content at the growth stage of the crop, an irrigation decision is made to determine the irrigation volume and irrigation time; if there is precipitation or irrigation water replenishment during the forecasting period, the irrigation is postponed and the forecasting results are adjusted and corrected in a timely manner according to the actual specific situation. At the same time, the simulation results such as soil moisture are corrected based on the actual monitoring values.

[0161] The calculation of irrigation quota is as follows:

[0162] (1) Crop irrigation water volume when water inflow is sufficient:

[0163] When the water inflow is very large and sufficient to meet the irrigation demand, the irrigation water volume M 1 is:

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

[0165] In the formula, θ i is the initial soil moisture content on the i-th day; H i is the planned wetting layer depth of the crop on the i-th day; θmax is the field water holding capacity, expressed as a percentage of the soil volume; n is the porosity of the soil in the planned wetting layer, expressed as a percentage of the soil volume.

[0166] (2) Amount of water for crops when water supply is insufficient:

[0167] When water is insufficient or water resources are scarce, crops can be irrigated incompletely by taking advantage of their physiological water-saving and drought-resistance capabilities. 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 sufficient, θc1 is generally taken as 90%θ max In this study, the values ​​were taken based on different design values ​​of irrigation experiments.

[0170] The above device may be executed by a chip or a chip module. The various modules / units included in the various devices and products described in the above embodiments may be software modules / units or hardware modules / units, or may be partially software modules / units and partially hardware modules / units.

[0171] Next, an electronic device provided by an embodiment of the present application is introduced. Figure 3 , Figure 3 A schematic diagram of a structure of an electronic device provided in an embodiment of the present application, wherein the electronic device 3100 implements Figure 1 Specifically, the electronic device 3100 includes: a receiver 3101, which can be Figure 1 The water quality sensor 301 in the embodiment; the transmitter 3102, for example, can be Figure 1 The soil entropy monitoring array 302; the processor 3103, for example, can be Figure 1 The crop growth monitor 303 in the electronic device 3100, or the control center 40, and the memory 3104 (wherein the number of processors 3103 in the electronic device 3100 may be one or more), wherein the processor 3103 may include an application processor 31031 and a communication processor 31032. In some embodiments of the present application, the receiver 3101, the transmitter 3102, the processor 3103 and the memory 3104 may be connected via a bus or other means.

[0172] The memory 3104 may include a read-only memory and a random access memory, and provide instructions and data to the processor 3103. A part of the memory 3104 may also include a non-volatile random access memory (NVRAM). The 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] The processor 3103 controls the operation of the electronic device. In a specific application, the various components of the electronic device are coupled together through a bus system, which may include a power bus, a control bus, a status signal bus, etc. in addition to the data bus. However, for the sake of clarity, all kinds of buses are referred to as the bus system in the figure.

[0174] The method disclosed in the embodiments of the present application can be applied to or implemented by the processor 3103. The processor 3103 can be an integrated circuit chip with signal processing capabilities. During implementation, the steps of the above method can be completed by the integrated logic circuit in the hardware of the processor 3103 or instructions in software form. The above-mentioned processor 3103 can be a general-purpose processor, a digital signal processor (DSP), a microprocessor or a microcontroller, and a vision processing unit (VPU), a tensor processing unit (TPU), etc., which are processors suitable for AI operations. It can further include an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The processor 3103 can implement or execute the various methods, steps and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiments of the present application can be directly embodied as being executed and completed by a hardware decoding processor, or executed and completed by a combination of hardware and software modules in the decoding processor. The software module can be located in a mature storage medium in the art such as random access memory, flash memory, read-only memory, programmable read-only memory or electrically erasable programmable memory, registers, etc. This storage medium is located in the memory 3104, and the processor 3103 reads the information in the memory 3104 and combines its hardware to complete the steps in the above method embodiments.

[0175] The receiver 3101 can be used to receive input digital or character information and generate signal inputs related to the relevant settings and function controls of the electronic device. The transmitter 3102 can be used to output digital or character information through the first interface; the 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; the transmitter 3102 can also include a display device such as a display screen.

[0176] In the embodiments of the present application, a computer program product is also provided. When it runs on a computer, it causes the computer to execute the steps performed by the foregoing device, or causes the computer to execute the steps performed by the foregoing device.

[0177] In an embodiment of the present application, a computer-readable storage medium is further provided. A program for signal processing is stored in the computer-readable storage medium. When it runs on a computer, it causes the computer to execute the steps performed by the aforementioned device, or causes the computer to execute the steps performed by the aforementioned device.

[0178] The execution device, training device or electronic device provided in the embodiment of the present application may specifically be a chip. The chip includes a processing unit and a communication unit. The processing unit may be a processor, for example, and the communication unit may be an input / output interface, a pin or a circuit, etc. The processing unit may execute the computer execution instructions stored in the storage unit to cause the chip in the execution device to execute the data processing method described in the above embodiment, or to cause the chip in the training device to execute the data processing method described in the above embodiment. Optionally, the storage unit is a storage unit inside the chip, such as a register, a cache, etc. The storage unit may also be a storage unit outside the chip in the radio access device, such as a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM), etc.

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

[0180] Through the description of the above embodiments, those skilled in the art can clearly understand that the present application can be implemented by means of software plus necessary general hardware. Of course, it can also be implemented by dedicated hardware including application-specific integrated circuits, dedicated CPUs, dedicated memories, dedicated components, etc. Generally, functions completed by computer programs can be easily implemented by corresponding hardware, and the specific hardware structures for implementing the same function can also be diverse, such as analog circuits, digital circuits, or dedicated circuits, etc. However, for the present application, software program implementation is a better embodiment in more cases. Based on such an understanding, the technical solution of the present 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 floppy disk, USB flash drive, mobile hard disk, ROM, RAM, magnetic disk, or optical disc of a computer, etc., and includes several instructions to enable a computer device (which can be a personal computer, training device, or network device, etc.) to execute the methods described in various embodiments of the present application.

[0181] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of 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, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a dedicated computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website, computer, training device, or data center to another website, computer, training device, or data center by wire (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can store, or a data storage device such as a training device or data center that includes one or more integrated available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a DVD), or a semiconductor medium (such as a solid-state drive (SSD)), etc.

Claims

1. An integrated sewage treatment irrigation system, characterized in that: include: A sewage treatment device (10) comprises a water inlet (101), a screen well (102), a grit chamber (103), a regulating tank (104), a biological treatment and disinfection section (105) and a drain (106) connected in sequence, wherein the biological treatment and disinfection section (105) comprises 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), wherein the aerobic tank (1052) is integrated with an immersed MBR membrane module (10521) and a variable frequency aeration system (10522); An irrigation delivery device (20) comprises a multi-level buried depth drip irrigation pipe network (201-203), a pressure compensation dripper (204) and a solenoid valve group (205), wherein the multi-level buried depth drip irrigation pipe network is buried according to multiple gradients; A monitoring module (30), comprising a water quality sensor (301) arranged in a sewage treatment device (10) and an irrigation delivery device (20), a soil moisture monitoring array (302) comprising a plurality of depth sensor nodes, and a crop growth monitor (303) equipped with a multi-spectral imaging module; The control center (40) includes a sewage water volume adjustment 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) for issuing instructions to each control element; An energy module (50) electrically connected to each electrical component includes a photovoltaic panel (501) and an energy storage system (502).

2. The system according to claim 1, characterized in that The regulating tank (104) is provided 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 according to the water inflow flow rate, and the surface of the baffle is provided with a self-cleaning nano coating.

3. The system according to claim 1 or 2, characterized in that: The membrane flux control of the MBR membrane assembly (10521) adopts a fuzzy PID algorithm based on a TMP-flux coupling model, and the membrane cleaning cycle is automatically triggered by detecting a sudden change in the transmembrane pressure difference.

4. The system according to claim 1 or 2, 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 wet layer depth calculation model, an effective rainfall calculation model, and a real-time irrigation volume calculation model.

5. The system according to claim 1 or 2, characterized in that: The sedimentation tank (1054) includes a sludge return pump station and a sludge dewaterer so that the sludge can be returned to the anaerobic tank and dewatered. The disinfection tank (1055) includes a chlorine dioxide disinfection device.

6. A method applied to the system according to any one of claims 1 to 5, characterized in that: include: S100, multi-stage sewage treatment steps: The sewage inputted from the water inlet (101) is separated into solid and liquid through the grid well (102), inorganic particles are removed by using the grit chamber (103), and the inlet flow rate is dynamically balanced by using the regulating tank (104); The anaerobic tank (1051) in the biological treatment and disinfection section (105) is used to remove nitrogen and phosphorus, and the aerobic tank (1052) uses an MBR membrane module (10521) and a variable frequency aeration system (10522) to achieve biological degradation of organic matter; The effluent after disinfection in the disinfection tank (1055) is stored in the clean water tank (1056), and the water quality parameters are fed back to the control center (40) in real time; S200, multi-dimensional environment perception steps: Obtaining a soil moisture matrix through a soil moisture monitoring array (302); The multispectral imaging module in the crop growth monitor (303) is used to collect the crop canopy temperature and NDVI index; Monitoring the organic matter index at each node of the sewage treatment through a water quality sensor (301); S300, intelligent decision making steps: The reference crop water requirement ET0 is calculated based on the improved Penman-Monteith algorithm and combined with the real-time K c Coefficient to generate theoretical crop water requirement ET c =ET0×K c ; The real-time irrigation volume analysis module (402) based on the real-time water-saving irrigation simulation model and image recognition technology predicts the soil moisture change Δθ in the next N days, and constructs an irrigation demand function Q=f(ET c ,Δθ,θ_min); Optimizing the sewage treatment parameter set by using the sewage water volume regulation calculation and analysis module (401) based on the IUWS model; S400: Starting graded irrigation based on the irrigation demand function Q.

7. The method according to claim 6, characterized in that The improved Penman-Monteith algorithm in S300 specifically includes: Introducing the canopy temperature correction term ΔT c , the calculation formula is: AND c =ET0×(1+0.02ΔT c ) Where ΔT c =T_canopy-T_air, T_canopy is the temperature obtained by infrared thermal imaging, and T_air is the reference temperature.

8. The method according to claim 6, characterized in that Starting staged irrigation includes: The first priority is to open the 55-60 cm deep drip irrigation pipe (203), with a flow rate of Q1 = K1 × Q_total; The second priority is to open the 35-40 cm deep drip irrigation pipe (202), with a flow rate of Q2 = K2 × Q_total; The third priority is to open the 15-20 cm deep drip irrigation pipe (201), with a flow rate of Q3 = K3 × Q_total; Where K1+K2+K3=1 and K1>K2>K3; Synchronously adjust the MBR membrane flux γ = γ0 × (1 + λ × ΔCOD), λ is the water quality feedback coefficient, γ0 is the reference MBR membrane flux, ΔCOD is the change in chemical oxygen demand (COD); The method for dynamically determining the weight coefficient of the hierarchical irrigation 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 is the cumulative number of hours of sunlight per day.

9. A computer program product, when the program product is run on an electronic device, enables the electronic device to execute the method as claimed in any one of claims 6 to 8.

10. A computer-readable storage medium, wherein a program is stored in the computer-readable storage medium, characterized in that: When the program is executed by a processor, the method according to any one of claims 6 to 8 is implemented.

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