Long-distance water-salt dynamic regulation and control method, equipment, medium and product

Abstract

The invention discloses a long-distance water-salt dynamic regulation and control method and device, a medium and a product, and relates to the technical field of ecological management, and the method comprises the steps: periodically obtaining monitoring data through a real-time monitoring network; determining the opening degree of a flow valve based on a partial pressure technology according to the water pressure and flow data of each node of the water delivery pipe network, and dynamically adjusting the water pressure and flow of each shunt branch in the water delivery pipe network according to the opening degree of the flow valve; according to the water content of the artificial soil layer, a water supplementing strategy is determined based on a vegetation water demand model; according to the salinity value of the artificial soil layer, on the basis of a salinity accumulation risk model, salt control closed-loop control based on a high salinity water active suction band-off mechanism is carried out; according to the invention, dynamic, accurate and closed-loop management of moisture and salinity can be realized.

Description

Technical Field

[0001] This application relates to the field of ecological governance technology, and in particular to a method, equipment, medium and product for long-distance dynamic regulation of water and salt. Background Technology

[0002] Ecological restoration in extremely arid regions faces challenges such as extreme water scarcity (annual evaporation ratio as high as 4000:7), high soil salinity (up to 300 g / kg), and uneven seasonal water resource distribution. Existing water-saving ridge ecological grid technology (whose physical structure is protected by utility model patent CN202323287293.X) significantly improves water resource utilization (over 80%) by constructing a closed multi-layered structure and capillary transport channels. However, in large-scale practical applications, especially in restoration systems spanning several kilometers, the following technical challenges remain: (1) Difficulty in controlling water uniformity: During long-distance water transport, it is difficult to ensure that water is evenly distributed in the longitudinal and transverse directions due to head loss, permeability differences and terrain complexity. This may lead to uneven plant growth and affect the uniformity of the restoration effect.

[0003] (2) Lack of dynamic and precise control methods: Although the system has water storage capacity, the movement of water and salt is a dynamic process. Relying solely on static structural design makes it difficult to respond in real time to changes in water demand from extreme weather or plant growth models. In particular, when facing the problem of soil salinization, the phenomenon of salt accumulation on the surface caused by capillary rise of water requires rapid early warning and intervention based on real-time data, while traditional manual management methods have high management requirements and low efficiency (manual management requirements need to be reduced by 80%).

[0004] (3) Low management efficiency: Traditional irrigation and maintenance management still rely on manual experience, and the management needs are large.

[0005] Therefore, in order to solve the problems of difficulty in controlling the uniformity of water transport in the above-mentioned long-distance systems and the lack of dynamic feedback in traditional salt control, there is an urgent need to provide a long-distance water and salt dynamic intelligent regulation method. Summary of the Invention

[0006] The purpose of this application is to provide a method, device, medium, and product for long-distance dynamic control of water and salt, which can realize dynamic, precise, and closed-loop management of water and salt.

[0007] To achieve the above objectives, this application provides the following solution: In a first aspect, this application provides a long-distance dynamic water and salt regulation method, applied to an artificial composite soil structure including an impermeable layer, a water-conducting and air-conducting layer, a sand-barrier and water-permeable layer, and an artificial soil layer; the long-distance dynamic water and salt regulation method includes: The system periodically acquires monitoring data using a real-time monitoring network. The monitoring data includes: the water level of the water-conducting and air-conducting layer, the moisture content and salinity of the artificial soil layer, and the water pressure and flow rate data at each node of the water transmission network. The real-time monitoring network includes sensor groups installed in the water-conducting and air-conducting layer and the artificial soil layer. Based on the water pressure and flow data of each node in the water transmission network, and using pressure divider technology, the opening degree of the flow valve is determined, and the water pressure and flow of each branch in the water transmission network are dynamically adjusted according to the opening degree of the flow valve. Based on the water content of the artificial soil layer and the vegetation water demand model, a water replenishment strategy is determined. The water replenishment strategy is the water injection frequency and volume of the underground water injection system. The underground water injection system is used to directly inject water into the water-conducting and air-conducting layer through a water conveyance pipe pre-buried in the water-conducting and air-conducting layer. Based on the salinity value of the artificial soil layer, a closed-loop control mechanism for salinity control based on the active suction and removal mechanism of high salinity is implemented using a salinity accumulation risk model. The salinity accumulation risk model is used to predict the salinity accumulation risk based on the salinity value.

[0008] Optionally, the sensor group includes: a soil moisture sensor, a TDS / EC sensor, and a water pressure sensor; the TDS / EC sensor is installed at a set depth on the surface of the artificial soil layer for dynamic monitoring of salinity.

[0009] Optionally, the vegetation water requirement model is based on the physiological parameters of drought-resistant plants and combined with ambient temperature, evaporation and real-time soil moisture content to determine the water replenishment strategy.

[0010] Optionally, the water source is treated mine drainage water or domestic sewage.

[0011] Optionally, the step of implementing closed-loop salt control based on the salinity value of the artificial soil layer and a salt accumulation risk model, using a high-salinity active suction and removal mechanism, specifically includes: Based on the salinity value of the artificial soil layer, the salinity accumulation risk is determined using a salinity accumulation risk model. When the salinity of the artificial soil layer exceeds the critical salinity value or the risk of salinity accumulation increases, dynamic salinity control early warning is implemented, and leaching and salt suppression intervention measures are carried out.

[0012] Optionally, the rinsing and salt-pressure intervention measure is to use a suction pump connected to the water supply pipeline to suction away the high-salt solution formed in the water-conducting and air-conducting layer, thereby completing the closed-loop control of salt control.

[0013] Secondly, this application provides a long-distance dynamic water and salt regulation device, applied to an artificial composite soil structure including an impermeable layer, a water-conducting and air-conducting layer, a sand-barrier and water-permeable layer, and an artificial soil layer; the long-distance dynamic water and salt regulation device includes: The monitoring data acquisition unit is used to periodically acquire monitoring data using a real-time monitoring network. The monitoring data includes: the water level of the water-conducting and air-conducting layer, the moisture content and salinity of the artificial soil layer, and the water pressure and flow rate data of each node of the water transmission pipeline network. The real-time monitoring network includes sensor groups installed in the water-conducting and air-conducting layer and the artificial soil layer. The water pressure and flow control unit is used to determine the opening degree of the flow valve based on the water pressure and flow data of each node in the water transmission network and the pressure divider technology, and to dynamically adjust the water pressure and flow of each branch in the water transmission network according to the opening degree of the flow valve. The water replenishment strategy determination unit is used to determine the water replenishment strategy based on the water content of the artificial soil layer and the vegetation water demand model; the water replenishment strategy is the water injection frequency and water volume of the underground water injection system; the underground water injection system is used to directly inject water into the water-conducting and air-conducting layer through a water conveyance pipe pre-buried in the water-conducting and air-conducting layer. The salt control closed-loop control unit is used to perform salt control closed-loop control based on the salt content of the artificial soil layer and the salt accumulation risk model, using an active high-salinity water extraction and removal mechanism; the salt accumulation risk model is used to predict the salt accumulation risk based on the salt content.

[0014] Thirdly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the long-distance water and salt dynamic control method.

[0015] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the aforementioned long-distance water and salt dynamic control method.

[0016] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the aforementioned long-distance dynamic water and salt regulation method.

[0017] According to the specific embodiments provided in this application, this application has the following technical effects: This application provides a method, device, medium, and product for long-distance dynamic water and salt regulation. It utilizes a real-time monitoring network to periodically acquire monitoring data; then, based on this data, it monitors water pressure and humidity at each node in real time, precisely controlling the diversion branches to ensure uniform water distribution in a strip-shaped system spanning several kilometers, thus solving the problem of uneven vegetation growth caused by uneven water distribution. Furthermore, it provides on-demand precise water replenishment based on monitoring data, ensuring uniform water distribution within the system, and establishes a closed-loop management system for salt control using a high-salinity water extraction and removal mechanism, significantly improving management efficiency and resistance to salinization risks. This application, based on intelligent, long-distance dynamic water and salt regulation using the Internet of Things (IoT), combined with real-time monitoring data feedback and hydraulic balance technology, effectively overcomes the limitations of controlling water transport uniformity and the lack of dynamic feedback in traditional salt control methods, achieving precise and uniform water transport and dynamic management of salinization risks. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of a long-distance water and salt dynamic control method in one embodiment of this application; Figure 2 This is a schematic diagram of an artificial composite soil structure. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0022] In one exemplary embodiment, such as Figure 1 As shown, a long-distance dynamic water and salt regulation method is provided, which is applied to an artificial composite soil structure including an impermeable layer, a water-conducting and air-conducting layer, a sand-barrier and permeable layer, and an artificial soil layer. Figure 2 As shown; the method includes the following steps S101 to S104. Wherein: S101, periodically acquire monitoring data using a real-time monitoring network; the monitoring data includes: water level of the water-conducting and air-conducting layer, moisture content and salinity of the artificial soil layer, and water pressure and flow data at each node of the water transmission network; the real-time monitoring network includes sensor groups installed in the water-conducting and air-conducting layer and the artificial soil layer. Specifically, the sensor group includes a soil moisture sensor, a TDS / EC sensor, and a water pressure sensor; the TDS / EC sensor is installed at a set depth in the surface layer (i.e., the shallow layer) of the artificial soil layer for dynamic monitoring of salinity.

[0023] S102, based on the water pressure and flow data of each node of the water transmission pipeline network, and using pressure divider technology, determine the opening degree of the flow valve, and dynamically adjust the water pressure and flow of each branch in the water transmission pipeline network according to the opening degree of the flow valve, thereby ensuring the uniform distribution of water in the long-distance strip system. The essence of pressure divider technology is to treat the complex water supply network as a fluid resistance network, analogous to the voltage distribution principle in electronic circuits. By dynamically changing the local resistance coefficient of the nodes, the total pressure head (water pressure) of the system is controlled and distributed among the branches. When determining the specific opening degree, the node flow rate Q and the pressure difference Δp across the valve must be obtained in real time. The basic flow rate calculation formula is as follows: ; Where Q is the node flow rate, and Δp is the pressure difference across the valve. Kv(h) It is the opening degree h The function, G is the fluid density constant.

[0024] In long-distance strip-shaped systems, the specific process can be divided into the following four stages: 1. Sensing Trigger and Water Demand Identification Stage: Water pressure and flow data at each node are periodically acquired through real-time monitoring of the network. When water demand loss at the end node is detected due to frictional resistance (… h f When the pressure is too high, resulting in insufficient pressure, or when the pressure at the near-end node exceeds the limit, the pressure distribution adjustment logic is automatically triggered.

[0025] 2. Flow coefficient ( K v The iterative calculation stage of the valve opening: based on the measured pressure difference (Δ) across the valve. p Given the target traffic demand, calculate the required traffic coefficient in reverse. K v This process typically involves decoupling control logic: the total opening of the flow valve is formed by superimposing the "basic opening" that meets the target flow rate and the "incremental opening" that corrects for pressure deviation, ensuring that adjusting the pressure does not interfere with the basic flow supply.

[0026] 3. Dynamic resistance matching and action execution stage: The output command drives the actuator of the regulating valve to act; the valve core moves to change the throttling area, and by forcibly creating a local pressure drop in the near-end branch, the excess kinetic energy is converted into heat energy dissipation, thereby "pushing" the remaining water head to the far-end branch, ensuring that water permeates evenly over a distance of several kilometers.

[0027] 4. Steady-state verification and closed-loop feedback phase: After adjustment, the uniformity of moisture distribution is continuously monitored through a sensor array. If the flow rate at the remote branch still does not reach the expected level, the next round of iterative adjustment will begin until the pressure across the entire network is balanced.

[0028] The main methods of pressure divider technology, based on different control logics and levels of automation, include the following five methods in water conveyance systems: 1. Flow-modulated voltage divider method: an active method where the voltage divider setpoint is a function of the measured flow rate. P set = f ( Q )+ H min ).in, P set It is the voltage divider setting value. f ( Q () is the flow-pressure control curve; H min This is the minimum operating pressure at the critical point. When the branch flow increases, the system automatically increases the partial pressure outlet value to compensate for internal friction losses, achieving "distribution on demand".

[0029] 2. Key Point Feedback Pressure Divider Method: This method moves the control center to the "most unfavorable point" at the farthest end of the pipeline network. By transmitting the terminal pressure back in real time via long-distance wireless communication, the opening degree of the upstream pressure divider valves at each stage can be dynamically adjusted. This is the preferred solution to ensure the ultimate uniformity of long-distance systems.

[0030] 3. Fixed-point outlet pressure distribution method: the most basic method. By installing pressure regulators at the inlet of each branch, the pressure is fixed at a preset nominal value (such as 0.10MPa), eliminating pressure inconsistencies along the main pipeline.

[0031] 4. Self-optimizing node method: Based on hydraulic autonomous control. Each node's regulating valve is controlled by two pilot valves working in tandem: the inlet pilot valve protects the upstream service level, and the outlet pilot valve controls the pressure in this branch. This method does not rely on external power or complex algorithms; the system can spontaneously generate a smooth pressure gradient.

[0032] 5. Intelligent Time-Sharing / Pressure Dividing Technology: Integrated frequency converter cabinet identifies the existing residual pressure in municipal or main pipelines. During periods of low water usage, pressure is reduced to minimize leakage; during peak periods, the frequency converter is activated to provide "pressure relay" water supply.

[0033] In long-distance strip systems, due to the power function coupling relationship between branch flow and pressure, even a tiny pressure fluctuation can lead to a severe imbalance in flow.

[0034] (1) Overcoming length limitations: When the laying length exceeds 90 meters, the moisture uniformity will drop sharply. Dynamic adjustment based on pressure distribution technology can achieve "segmented independent pressure control", transforming an uncontrollable long-distance system into multiple controllable short-distance subsystems, so that the CU uniformity coefficient is stabilized above 95%.

[0035] (2) Suppressing chain reaction: The pressure-splitting technology establishes a local "buffer zone" at each branch node to prevent the flow fluctuation of a single branch from causing a "domino effect" of hydraulic interference to the downstream nodes; S103, Based on the moisture content of the artificial soil layer and the vegetation water demand model, a water replenishment strategy is determined; the water replenishment strategy is the water injection frequency and water volume of the underground water injection system; the underground water injection system is used to directly inject water into the water-conducting and air-conducting layer through water delivery pipes pre-buried in the water-conducting and air-conducting layer; the vegetation water demand model is based on the physiological parameters of drought-resistant plants, combined with ambient temperature, evaporation, and real-time soil moisture content, to determine the water replenishment strategy.

[0036] In order to improve water resource utilization and water loss rate, the water source is treated mine drainage water or domestic sewage. After the above water treatment operation, the water resource utilization rate can be increased to more than 80% and the water loss rate can be controlled below 5%.

[0037] The vegetation water requirement model is primarily constructed based on the internationally recognized FAO Penman-Monteith equation, with localized modifications made to account for the physiological characteristics of artificial soil layers and drought-resistant vegetation. The core idea behind this model is to calculate plant evaporation using meteorological data, determine the water requirement of "plants" at specific stages using plant coefficients, and finally measure the remaining water volume in the artificial soil layer using sensors, thereby accurately calculating how much water the "underground water injection system" needs to inject.

[0038] The construction of a vegetation water requirement model is a closed-loop process that integrates meteorological factors, plant physiological characteristics, and soil moisture status, and consists of three main levels: 1. Basic evapotranspiration calculation layer: Reference evapotranspiration is calculated using the Penman-Monteith equation ( AND 0 ), quantifying the driving force of environmental factors (such as radiation, wind speed, and humidity) on water loss.

[0039] 2. Physiological parameter correction layer: Introducing crop coefficient ( K c ) and stress coefficient ( Ks The study highlights the unique stomatal regulation mechanisms and water use strategies of drought-resistant plants (such as Haloxylon ammodendron and Tamarix chinensis).

[0040] 3. Water injection decision-making level: Based on the real-time collected moisture content data, calculate the current water deficit and determine the water replenishment frequency and single water injection volume in combination with the "winter storage and summer use" mode.

[0041] The latent heat flux formula for vegetation transpiration is used to calculate the evaporation and transpiration demand of vegetation in artificial soil systems: ; in, λET The latent heat flux generated by evaporation ( MJ • m −2 • d −1 Δ represents the slope of the saturated vapor pressure-temperature curve, reflecting the effect of temperature on evaporation. R n Net radiation is the primary energy source for water loss; the effects of slope and aspect must be considered in artificial slopes. G This refers to soil heat flux. Artificial soil layers are thinner, and their heat conduction characteristics differ from those of natural deep soil layers. ρ a air density ( kg•m −3 ); c p Specific heat of air at constant pressure ( MJ•kg −1 ℃ −1 ); e s −e a The saturated vapor pressure deficit reflects the dryness of the air; γ This is the hygrometer constant; r a Aerodynamic drag is affected by the wind speed and vegetation height in the injection layer; r s Surface resistance (or canopy resistance) is a concentrated manifestation of the physiological characteristics of drought-resistant plants.

[0042] The formula for correcting actual vegetation water requirements is: ; in, AND c This represents the actual water requirement for vegetation. K c This is the crop coefficient, reflecting the water consumption potential of plants at different developmental stages; K sThe stress coefficient reflects the degree to which real-time soil moisture content inhibits transpiration; when moisture drops to a threshold, plants will reduce water loss by increasing stomatal resistance. AND 0 Evaporation and transpiration; The single injection volume (replenishment volume determination) is used to determine the final replenishment volume of the underground water injection system. V : ; in, V This represents the total water replenishment volume; θ target,i For the first i The target volumetric moisture content of the artificial soil layer is usually set at around 85% of field capacity. θ real,i The first sensor acquired i Real-time volumetric moisture content of the artificial soil layer; Δ Z i For the first i The thickness of the artificial soil layer; A The effective coverage area of ​​the water replenishment system; the This is the system efficiency coefficient, typically taken as 0.85-0.95; S104. Based on the salinity value of the artificial soil layer and the salinity accumulation risk model, a closed-loop control of salinity is implemented based on the active suction and removal mechanism of high salinity. The salinity accumulation risk model is used to predict the salinity accumulation risk based on the salinity value.

[0043] S104 specifically includes: S41. Based on the salinity value of the artificial soil layer, the salinity accumulation risk is determined using a salinity accumulation risk model. S42. When the salinity of the artificial soil layer is higher than the critical salinity value or the risk of salinity accumulation increases, dynamic salinity control early warning will be implemented, and leaching and salt suppression intervention measures will be carried out.

[0044] Among them, the salt accumulation risk model is the core decision-making tool for quantitatively assessing the probability of functional degradation of artificial soil layers under specific environments. By identifying external hazards, system vulnerabilities, and exposure levels, the salt accumulation risk model enables dynamic prediction and control of salinization risks. The model's advancement lies in its "self-evolution" capability; that is, by periodically analyzing the infiltration rate fed back by sensors, it automatically corrects the performance degradation parameters of the "siltation layer" caused by long-term operation, thereby ensuring the system's continued effectiveness throughout its entire restoration lifecycle.

[0045] The salt accumulation risk model aims to quantify the mass balance process of salt transport in artificial soil layers. Its core logic lies in distinguishing between "hazards" (external threats, such as highly mineralized irrigation water and groundwater level fluctuations) and "vulnerabilities" (system resistance, such as soil texture and crop salt tolerance threshold).

[0046] (1) Salt accumulation kinetics: Identifying capillary action, evaporation and transpiration ( AND As the main driver of risk growth, rinsing flux serves as a key negative weight for risk reduction.

[0047] (2) Degradation criteria: The model focuses on salt concentration and monitors the saturated permeability coefficient. K s ) decay. When predicted K s When the decline exceeds 20%, it is judged as having a high risk of irreversible degradation.

[0048] The salt balance equation (based on physical kinetics) is used to describe the total change in salt content within an artificial soil unit: ; Where Δ S This refers to the change in salinity over a given time period. F up This refers to the upward salt flux caused by strong surface evaporation; F down This refers to the downward rinsing flux caused by rainfall or artificial irrigation.

[0049] Risk Index ( RI The weighted model is used to determine specific risk values ​​and whether the S42 warning is triggered. ; in, RI The risk index (usually normalized to 0-1) is considered to be close to or exceed 0.7, indicating increased risk. EC t The measured electrical conductivity (salt load) of the artificial soil layer is shown. EC max The maximum salt threshold that vegetation can tolerate; d(EC) / dt This represents the real-time salt accumulation rate; d(EC ) / dt ) crit This is the critical salt deposition rate threshold. AND 0 represents evaporation and transpiration. P This refers to precipitation. AND 0,avg This represents the historical average potential evaporation and transpiration for the same period. α , β , γ The weight coefficients for each factor are determined through regression analysis using historical long-term monitoring data.

[0050] The construction of a salt accumulation risk model is a multi-stage, cyclical process that integrates data and mechanisms: 1. Multi-source heterogeneous data acquisition: IoT monitoring: In-situ data is collected using a four-pin conductivity sensor and an FDR / TDR moisture sensor.

[0051] Remote sensing inversion: Salt sensitivity indices (such as SI1, SI5, SI8) are extracted using Landsat8 / Sentinel-2 images.

[0052] 2. Feature selection and dimensionality reduction: The “filtering method” (Pearson correlation coefficient) and the “exhaustive search method” are used to select the feature combination with the highest explanatory power (such as terrain curvature, meteorological factors, etc.).

[0053] Machine learning algorithms (such as AdaBoost and Random Forest) are introduced into the salt accumulation risk model to handle nonlinear relationships. Stacking technology is used to fuse the prediction results of multiple base models to improve prediction accuracy.

[0054] The salt accumulation risk model is cross-validated and compared with physical models (such as HYDRUS-1D) to correct the permeability and diffusion coefficient parameters in the model, ensuring its reliability in extreme environments.

[0055] Among them, the dynamic salt control intervention based on the salt accumulation risk model is as follows: when RI Increase or EC When the value exceeds the dynamic threshold, the system triggers the following intervention measures: (1) Precise rinsing and salt suppression: Based on the water replenishment calculation model, the optimal rinsing water volume is determined to dissolve the surface salt and press it into the lower water and air guiding layer.

[0056] (2) Active suction and removal: Immediately start the suction pump to suction and remove the high-salt solution collected in the water and air guiding layer from the system, thus completing the salt control closed loop.

[0057] Specifically, the salt-controlling intervention measure involves using a suction pump connected to the water pipeline to draw away the high-salt solution formed in the water-conducting and air-conducting layer, thereby completing the closed-loop control of salt control. The automated regulation of this application achieves precise irrigation and intelligent management, reducing the need for manual management by 80%.

[0058] As a specific embodiment, the salt-pressing intervention measure involves driving deep water injection or activating the leaching facility to dissolve the surface salt and press it into the lower water-conducting and air-conducting layer, forming a high-salt water layer. Then, the suction pump connected to the water supply pipeline (water distribution pipeline) is immediately activated to extract the high-salt solution collected in the water-conducting and air-conducting layer and remove it from the system. Finally, through the closed-loop operation of leaching and suction removal, the high-salt solution is removed, leaving cleaned low-salt soil in the artificial soil layer, providing a suitable growth environment for plants.

[0059] As a specific example, during the design and operation phases, numerical simulation software (such as HYDRUS-1D) is developed or referenced, and the collected environmental and operational data are input to optimize the water delivery path, water pressure control parameters, and water injection strategy, thereby improving the reliability of system operation.

[0060] The water source, water treatment, main water supply network, pressure / flow control, suction pump, and water supply pipeline (or water distribution pipeline) pre-installed inside the water-conducting and air-conducting layer (i.e., gravel aquifer) in this application can be constructed as a water circulation and regulation system; utilizing the bidirectional function of the water supply pipeline (or water distribution pipeline), it can be used to directly inject water into the underground aquifer (avoiding surface water evaporation loss from the source), and also serve as a high-salinity water suction pipeline during salinity control operations; The following specific embodiment illustrates the real-time monitoring network and hydraulic balance control in this application: (1) Construction of the real-time monitoring network: In a strip-shaped ecological grid exceeding 500 meters in length, multiple intelligent sensors are deployed at longitudinal and transverse intervals within the water-conducting and air-conducting layer (gravel water storage layer) and the artificial soil layer. The sensor types include: 1) Water pressure sensor: installed in the main water supply pipeline and key diversion nodes to monitor the hydraulic balance in real time.

[0061] 2) Soil moisture sensor and TDS / EC sensor: Deployed in the main activity area of ​​plant roots (e.g., 0-60cm deep) and the shallow surface layer (e.g., 5-10cm) where salt accumulation is likely to occur in the artificial soil layer to monitor the dynamics of moisture and salt in real time.

[0062] 3) Water level observation pipe: installed in the water and air guiding layer, used to check the water storage and groundwater level.

[0063] (2) Long-distance uniformity assurance (intelligent pressure regulation): Intelligent pressure regulation technology and a water pressure control system (including regulating valves, flow meters, and data acquisition modules) are installed at the water source end. This system receives water pressure and humidity data from each node in real time from the monitoring network through integrated high-precision electric regulating valves and flow meters. The control logic is as follows: The intelligent management platform calculates the head loss along the pipeline during long-distance water transmission according to the preset hydraulic balance model, and dynamically adjusts the opening of the diversion valves according to the real-time humidity differences at different nodes to ensure that the gravel reservoir area far from the water source end can also obtain water pressure and injection rate that are basically the same as those near the water source end.

[0064] By precisely controlling water pressure, a uniform distribution of water is achieved in a long-distance strip system, solving the problem of uneven vegetation growth caused by uneven water distribution.

[0065] The following examples, using data, illustrate the dynamic salt control and precise hydration provided in this application: 1. Dynamic early warning and intervention for salinization: 1) Early warning mechanism: The platform continuously receives salinity values ​​from the shallow layer (5-10cm) of the artificial soil. When the salinity value rises for three consecutive days and reaches the preset critical value (e.g., exceeding 20g / kg), or when the risk of salt accumulation is predicted during the warming period (e.g., February), a high salinity risk warning is automatically triggered.

[0066] 2) Salt Control Intervention (Leaching, Salt Pressure, and Desalination via Suction): After the warning is activated, salt control intervention measures are automatically implemented. The platform drives the water injection system to leach and pressure salt into the water-conducting and aeration layer in a low-speed, high-volume mode. This operation dissolves the surface salt and presses it into the lower water-conducting and aeration layer, forming a high-salt solution. After the leaching and salt pressure operation is completed, the intelligent management platform sends a command to the suction pump based on the high-salt solution level indication in the lower water-conducting and aeration layer, initiating the high-salt water suction and removal (active desalination) operation: the water supply pipe (water distribution pipe) connected inside the water-conducting and aeration layer switches to suction mode, and the suction pump extracts the high-salt solution collected in the water-conducting and aeration layer, collects it, and transfers it to a designated high-salt treatment area or evaporation tank outside the system. The above steps avoid salt residue and repeated circulation, thereby efficiently removing salt and ensuring that the artificial soil layer is restored to a low-salt state, suitable for the growth of salt-tolerant plants (such as Haloxylon ammodendron and Tamarix chinensis).

[0067] (2) Precise water replenishment on demand (reducing the need for manual management): 1) Vegetation water requirement model analysis: Integrate the vegetation water requirement model (based on the physiological parameters of drought-resistant plants such as Haloxylon ammodendron and Tamarix chinensis) and combine it with real-time soil moisture, ambient temperature and evaporation data.

[0068] 2) Automatic water replenishment decision: When the moisture content of the artificial soil layer is lower than the warning value (e.g., lower than the plant wilting coefficient), the platform automatically triggers the on-demand water replenishment command, accurately calculates the required water replenishment amount, and replenishes water to the gravel water storage layer through underground water pipelines according to the water injection strategy of "winter storage and summer use" mode (avoiding surface evaporation).

[0069] The above steps enable automated and precise management of the entire irrigation process, reducing the need for manual management by approximately 80%.

[0070] (3) Numerical simulation optimization: In the initial stage of operation, measured hydrological and meteorological parameters from the Shaerhu mining area were input using numerical simulation software such as HYDRUS-1D to simulate the transport patterns of water and salt in the structure under different water injection strategies. The simulation results were used to calibrate valve parameters and salinity risk thresholds in the hydraulic balance control system, further improving the reliability of system operation.

[0071] Based on the same inventive concept, this application also provides a long-distance water and salt dynamic control device for implementing the aforementioned long-distance water and salt dynamic control method. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations of one or more long-distance water and salt dynamic control device embodiments provided below can be found in the limitations of the long-distance water and salt dynamic control method described above, and will not be repeated here.

[0072] In one exemplary embodiment, a long-distance dynamic water and salt regulation device is provided, applied to an artificial composite soil structure including an impermeable layer, a water-conducting and air-conducting layer, a sand-barrier and water-permeable layer, and an artificial soil layer; the long-distance dynamic water and salt regulation device includes: The monitoring data acquisition unit is used to periodically acquire monitoring data using a real-time monitoring network. The monitoring data includes: the water level of the water-conducting and air-conducting layer, the moisture content and salinity of the artificial soil layer, and the water pressure and flow rate data of each node of the water transmission pipeline network. The real-time monitoring network includes sensor groups installed in the water-conducting and air-conducting layer and the artificial soil layer. The water pressure and flow control unit is used to determine the opening degree of the flow valve based on the water pressure and flow data of each node in the water transmission network and the pressure divider technology, and to dynamically adjust the water pressure and flow of each branch in the water transmission network according to the opening degree of the flow valve. The water replenishment strategy determination unit is used to determine the water replenishment strategy based on the water content of the artificial soil layer and the vegetation water demand model; the water replenishment strategy is the water injection frequency and water volume of the underground water injection system; the underground water injection system is used to directly inject water into the water-conducting and air-conducting layer through a water conveyance pipe pre-buried in the water-conducting and air-conducting layer. The salt control closed-loop control unit is used to perform salt control closed-loop control based on the salt content of the artificial soil layer and the salt accumulation risk model, using an active high-salinity water extraction and removal mechanism; the salt accumulation risk model is used to predict the salt accumulation risk based on the salt content.

[0073] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal. The computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is connected to the system bus via the I / O interfaces. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The I / O interfaces of the computer device are used for exchanging information between the processor and external devices. The communication interface of the computer device is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements a long-distance dynamic water-salt regulation method.

[0074] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0075] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0076] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0077] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0078] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0079] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0080] In this application, all actions to acquire signals, information, or data are carried out in compliance with the relevant data protection laws and policies of the country where the location is situated, and with the authorization granted by the owner of the relevant device.

[0081] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0082] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A long-distance dynamic water and salt regulation method, applied to an artificial composite soil structure comprising an impermeable layer, a water-conducting and air-conducting layer, a sand-barrier and permeable layer, and an artificial soil layer; characterized in that, The long-distance dynamic water and salt regulation method includes: The system periodically acquires monitoring data using a real-time monitoring network. The monitoring data includes: the water level of the water-conducting and air-conducting layer, the moisture content and salinity of the artificial soil layer, and the water pressure and flow rate data at each node of the water transmission network. The real-time monitoring network includes sensor groups installed in the water-conducting and air-conducting layer and the artificial soil layer. Based on the water pressure and flow data of each node in the water transmission network, and using pressure divider technology, the opening degree of the flow valve is determined, and the water pressure and flow of each branch in the water transmission network are dynamically adjusted according to the opening degree of the flow valve. Based on the water content of the artificial soil layer and the vegetation water demand model, a water replenishment strategy is determined. The water replenishment strategy is the water injection frequency and volume of the underground water injection system. The underground water injection system is used to directly inject water into the water-conducting and air-conducting layer through a water conveyance pipe pre-buried in the water-conducting and air-conducting layer. Based on the salinity value of the artificial soil layer, a closed-loop control mechanism for salinity control based on the active suction and removal mechanism of high salinity is implemented using a salinity accumulation risk model. The salinity accumulation risk model is used to predict the salinity accumulation risk based on the salinity value.

2. The long-distance water and salt dynamic control method according to claim 1, characterized in that, The sensor group includes a soil moisture sensor, a TDS / EC sensor, and a water pressure sensor; the TDS / EC sensor is installed at a set depth on the surface of the artificial soil layer for dynamic monitoring of salinity.

3. The long-distance dynamic water and salt regulation method according to claim 1, characterized in that, The vegetation water requirement model is based on the physiological parameters of drought-resistant plants and combines environmental temperature, evaporation rate and real-time soil moisture content to determine water replenishment strategies.

4. The long-distance dynamic water and salt regulation method according to claim 1, characterized in that, The water source is treated mine drainage water or domestic sewage.

5. The long-distance dynamic water and salt regulation method according to claim 1, characterized in that, The aforementioned closed-loop salt control, based on the salinity value of the artificial soil layer and a salt accumulation risk model, and employing an active high-salinity water extraction and removal mechanism, specifically includes: Based on the salinity value of the artificial soil layer, the salinity accumulation risk is determined using a salinity accumulation risk model. When the salinity of the artificial soil layer exceeds the critical salinity value or the risk of salinity accumulation increases, dynamic salinity control early warning is implemented, and leaching and salt suppression intervention measures are carried out.

6. The long-distance dynamic water and salt regulation method according to claim 5, characterized in that, The salt-pressure intervention measure involves using a suction pump connected to the water pipeline to draw away the high-salt solution formed in the water-conducting and air-conducting layer, thereby completing the closed-loop control of salt control.

7. A long-distance dynamic water and salt regulation device, applied to an artificial composite soil structure comprising an impermeable layer, a water-conducting and air-conducting layer, a sand-barrier and permeable layer, and an artificial soil layer; characterized in that, The long-distance water and salinity dynamic control device includes: The monitoring data acquisition unit is used to periodically acquire monitoring data using a real-time monitoring network. The monitoring data includes: the water level of the water-conducting and air-conducting layer, the moisture content and salinity of the artificial soil layer, and the water pressure and flow rate data of each node of the water transmission pipeline network. The real-time monitoring network includes sensor groups installed in the water-conducting and air-conducting layer and the artificial soil layer. The water pressure and flow control unit is used to determine the opening degree of the flow valve based on the water pressure and flow data of each node in the water transmission network and the pressure divider technology, and to dynamically adjust the water pressure and flow of each branch in the water transmission network according to the opening degree of the flow valve. The water replenishment strategy determination unit is used to determine the water replenishment strategy based on the water content of the artificial soil layer and the vegetation water demand model; the water replenishment strategy is the water injection frequency and water volume of the underground water injection system; the underground water injection system is used to directly inject water into the water-conducting and air-conducting layer through a water conveyance pipe pre-buried in the water-conducting and air-conducting layer. The salt control closed-loop control unit is used to perform salt control closed-loop control based on the salt content of the artificial soil layer and the salt accumulation risk model, using an active high-salinity water extraction and removal mechanism; the salt accumulation risk model is used to predict the salt accumulation risk based on the salt content.

8. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the long-distance water and salt dynamic control method according to any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the long-distance dynamic water and salt regulation method according to any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the long-distance dynamic water and salt regulation method according to any one of claims 1-6.

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