Underground pipe salt elimination and rainwater collection and recycling method and system for coastal garden

Abstract

The invention discloses an underground pipe salt elimination and rainwater collection recycling method and system for a coastal garden, and the method comprises the steps: determining underground pipe layout parameters through an underground pipe layout efficiency evaluation model, integrating multi-dimensional monitoring data through a multi-source moisture salt data fusion algorithm, formulating a rainwater collection regulation and control strategy through a rainwater storage regulation and control adaptation model, and carrying out the rainwater collection and control through a rainwater storage regulation and control adaptation model. The salt discharge, water discharge and irrigation parameters are dynamically adjusted by means of a garden water-salt collaborative management and control platform, the salt discharge frequency and the rainwater utilization intensity are optimized in combination with a water-salt state evaluation result, and closed-loop regulation and control are formed through data feedback. Wherein the key steps are further refined into a plurality of sub-steps, and coherent operation of data acquisition, parameter calculation, accurate regulation and control and effect optimization is realized. According to the method, the regulation and control accuracy and the resource utilization efficiency are improved, the method adapts to the complex water-salt environment of the coastal garden, and efficient and stable technical support is provided for ecological construction.

Description

Technical Field

[0001] This invention relates to the field of coastal garden management technology, and in particular to a method and system for underground pipe salt drainage and rainwater collection and recycling in coastal gardens. Background Technology

[0002] Coastal gardens, as an important component of ecological construction in coastal areas, have long been constrained by their unique geographical environment. Coastal areas commonly suffer from soil salinization, with shallow groundwater containing high salt content. Uneven rainfall distribution and frequent seasonal droughts further exacerbate this imbalance, directly impacting vegetation survival and growth. Meanwhile, traditional garden irrigation relies on groundwater or tap water, resulting in high water consumption, while natural rainfall, a potential water resource, is not effectively recycled, wasting water and exacerbating ecological pressure. Subsurface drainage is a common technique for improving coastal soils, and rainwater harvesting and recycling are important means of water-saving irrigation. However, achieving deep synergy between these two methods, and precisely controlling soil water and salt dynamics, is crucial for enhancing the ecological benefits and resource utilization efficiency of coastal gardens. Therefore, an integrated technical approach and systemic support are urgently needed.

[0003] Existing technologies for subsurface pipe salt removal and rainwater harvesting in coastal gardens have two prominent drawbacks: First, they lack the ability to integrate multi-dimensional technical elements. Subsurface pipe deployment is mostly based on static design using empirical parameters, without fully considering rainwater harvesting potential, vegetation water demand dynamics, and real-time changes in soil water and salt for dynamic optimization. Rainwater harvesting regulation and subsurface pipe salt removal processes are disconnected, failing to form a coordinated water and salt management mechanism, making it difficult to simultaneously improve salt removal efficiency and rainwater utilization efficiency. Second, they lack precise and closed-loop control capabilities. The integration and processing of multi-source data such as soil moisture, salinity, and rainfall are not comprehensive enough. They fail to achieve a closed-loop process of data acquisition, model calculation, execution regulation, and parameter optimization through a systematic platform. Adjustments to key operations such as subsurface pipe salt removal frequency and rainwater distribution ratio lack scientific basis, making it difficult to adapt to the complex and variable water and salt environment and vegetation growth needs of coastal gardens, thus restricting the stability and effectiveness of technology application. Summary of the Invention

[0004] In order to overcome the shortcomings and deficiencies of the existing technology, the present invention provides a method and system for salt drainage and rainwater collection and recycling in underground pipes for coastal gardens.

[0005] The technical solution adopted in this invention is a method for underground pipe desalination and rainwater collection and recycling in coastal gardens, comprising the following steps: S1, based on the distribution of soil types, groundwater depth, initial soil salinity, vegetation water requirements, and regional rainfall characteristics in coastal gardens, the spacing, burial depth, pipe diameter, and perforation rate of underground pipes are determined through an underground pipe deployment efficiency evaluation model; S2, a multi-source moisture and salinity data fusion algorithm is used to integrate real-time data obtained from soil moisture sensors, salinity sensors, meteorological monitoring stations, and groundwater monitoring points to generate a dynamic soil water and salinity monitoring dataset; S3, based on a rainwater storage regulation adaptation model, combined with rainwater runoff coefficient and storage... Based on facility capacity constraints, garden irrigation water demand, and rainfall forecast data, rainwater collection and regulation strategies are formulated; S4, the opening degree of underground pipe salt discharge valves, the water flow rate of rainwater storage facilities, and the allocation ratio of irrigation water are dynamically adjusted through the garden water and salt collaborative management platform; S5, based on the soil water and salt status assessment results output by the multi-source moisture and salt data fusion algorithm, the frequency of underground pipe salt discharge and the intensity of rainwater recycling are adjusted; S6, data on underground pipe salt discharge, rainwater utilization, soil moisture and salt changes, and vegetation growth response are continuously collected and fed back to the underground pipe deployment effectiveness assessment model, the rainwater storage regulation adaptation model, and the multi-source moisture and salt data fusion algorithm to form a closed-loop regulation mechanism.

[0006] Furthermore, the expression for the evaluation model of the effectiveness of concealed pipe installation is as follows: ,in, To determine the overall efficiency value for concealed pipe installation, Soil permeability correction factor The coefficient representing the influence of the opening ratio of the concealed pipe. The diameter of the concealed pipe. For the density of concealed pipe installation, The weighting of groundwater depth is determined by the influence of groundwater depth. To determine the spacing for concealed pipe installation, For the depth of the concealed pipe burial, The vegetation type fit coefficient. This represents the initial salinity of the soil. This is the regional rainfall intensity coefficient. These are the permeability parameters of the concealed pipe material.

[0007] Furthermore, the expression for the rainwater storage regulation adaptation model is: ,in, To adapt the output flow rate for rainwater regulation, This is the rainwater runoff correction factor. For rainfall forecast intensity, For the water catchment area of ​​the garden, For storage facility adaptability coefficient, For storage facility capacity, For the water demand intensity of garden irrigation, For the purpose of regulation cycle, The recycling efficiency coefficient. For soil moisture to reach the target threshold, These are parameters related to the effectiveness of rainwater purification treatment.

[0008] Furthermore, the expression for the multi-source moisture data fusion algorithm is as follows: ,in, The values ​​represent the water-salt state assessment values ​​after fusion. The weights for data from soil sensors, weather stations, and groundwater monitoring points are respectively... These are the salinity monitoring values ​​at three different monitoring points. The weights of soil moisture data from the three types of monitoring points are respectively. These are the soil moisture monitoring values ​​for three types of monitoring points. This is a time-dynamic correction factor. For monitoring duration, This is the data fusion cycle.

[0009] Furthermore, the regulation model expression of the garden water and salt collaborative management platform is as follows: ,in, Output values ​​for platform collaborative management, These are parameters for the salt drainage efficiency of concealed pipes. Rainwater utilization flow, For the adaptation coefficient of the control strategy, This is the water-salt balance adjustment coefficient. For the area of ​​garden soil, To coordinate and regulate weights, These are the valve opening parameters for concealed pipes. The threshold for controlling soil salinity. The length of the concealed pipe. To regulate response time, For the available capacity of the storage facility, For irrigation water utilization rate, Prioritize water demand for vegetation. The coefficient for water-salt synergy.

[0010] Furthermore, the expression for the integrated optimization model of underground pipe salt drainage and rainwater collection and recycling for coastal gardens is as follows: ,in, To comprehensively optimize the target value, These are the weighting coefficients for efficiency, traffic, integration value, and control value, respectively. To optimize the penalty coefficient, For parameters related to the construction cost of concealed pipes, Energy consumption parameters For resource recycling efficiency parameters, These are parameters related to the soil improvement effect.

[0011] Further, S3 includes the following sub-steps: S31, accessing rainfall forecast data, historical rainfall statistics, and real-time rainfall monitoring data released by the regional meteorological department through the garden water and salt collaborative management and control platform, extracting rainfall intensity, rainfall duration, and rainfall interval calibration parameters, and establishing a rainfall characteristic database; S32, based on the rainwater storage regulation and adaptation model, inputting the maximum capacity, minimum reserved capacity, and water release rate limit parameters of the storage facility, and combining the irrigation water demand intensity corresponding to different vegetation types and growth stages in different areas of the garden, determining the priority and allocation ratio of rainwater collection; S33, calculating the rainwater supplementary irrigation demand based on the difference between soil moisture monitoring data and vegetation water demand threshold, and dynamically adjusting the regulation and control strategy based on rainwater storage volume, clarifying the boundary conditions for direct rainwater utilization, storage and subsequent utilization, and emergency discharge; S34, converting the regulation and control strategy into control commands for the opening of the inlet valve and the outflow of water in the storage facility, and issuing them to the execution agency through the garden water and salt collaborative management and control platform.

[0012] Further, S4 includes the following sub-steps: S41, the garden water and salt collaborative management platform receives the soil water and salt status assessment results output by the multi-source moisture and salt data fusion algorithm in real time, and extracts the spatial location and degree parameters of areas with excessive soil salinity and areas with insufficient soil moisture; S42, based on the salt discharge priority of each area's underground pipes determined by the underground pipe layout efficiency assessment model, and combined with the current operating status data of the underground pipes, the target opening degree of each underground pipe valve is calculated to ensure that the salt discharge efficiency matches the degree of excessive soil salinity; S43, based on the real-time liquid level data of the rainwater storage facility, the water quality parameters after rainwater purification treatment, and the water quality requirements for garden irrigation water, the water discharge flow of the storage facility is adjusted to control the rate at which rainwater is transported to the irrigation area; S44, based on the water demand urgency of different vegetation areas and the soil moisture recovery target, the irrigation water volume is allocated, and water is supplied through the intelligent irrigation terminal, while simultaneously recording various operating parameters during the control process.

[0013] Further, S5 includes the following sub-steps: S51, collecting drainage flow rate and salt concentration data from the underground pipe's salt discharge outlet, combining this with soil salinity data monitored by soil sensors after salt discharge, and calculating the salt discharge effect evaluation value using a multi-source moisture and salt data fusion algorithm; S52, analyzing the correlation between irrigation water volume, irrigation duration, and soil moisture changes during rainwater utilization, and adjusting the rainwater recycling intensity and optimizing rainwater utilization efficiency by combining vegetation growth status feedback data; S53, feeding back the salt discharge effect evaluation value and rainwater utilization efficiency parameters to the underground pipe layout efficiency evaluation model, correcting the adaptability of underground pipe layout spacing and burial depth parameters, and updating the salt discharge frequency control logic; S54, based on the real-time calculation results of the rainwater storage regulation adaptation model, and combined with the dynamic changes in rainfall forecast data, adjusting the rainwater collection threshold and storage facility regulation strategy to maximize the utilization of rainwater resources and dynamically maintain water-salt balance.

[0014] This system, designed for coastal landscaping, utilizes subsurface pipes for salt drainage and rainwater harvesting and recycling. It comprises six functional units, each bidirectionally connected to a control bus via data transmission lines. Specifically: a high-precision sensing unit for multi-source water and salt parameters, using distributed soil moisture sensors, salinity sensors, meteorological monitoring modules, and groundwater monitoring probes to collect basic data on soil moisture content, salinity, rainfall intensity, and groundwater level. This data is then converted into standardized digital signals and transmitted to the data processing unit. A multi-source moisture and salinity data fusion processing unit receives the standardized data from the sensing unit and uses a multi-source moisture and salinity data fusion algorithm to perform spatiotemporal alignment, noise filtering, and feature extraction on the heterogeneous data, generating a unified-format water and salt status assessment dataset, which is then simultaneously sent to the collaborative management unit. Finally, a subsurface pipe deployment and rainwater regulation parameter calculation unit calculates parameters based on the assessment dataset using a subsurface pipe deployment effectiveness evaluation model. The system optimizes the layout parameters of underground pipes, generates rainwater collection and control strategy parameters through a rainwater storage and regulation adaptation model, and outputs both types of parameters to the collaborative management and control unit. The garden water and salt collaborative intelligent management and control unit receives the evaluation dataset from the fusion processing unit and the optimized parameters from the parameter calculation unit, generates control commands for underground pipe salt discharge valves, rainwater storage facility regulation commands, and irrigation water allocation commands, and sends them to the execution unit. The underground pipe salt discharge and rainwater circulation execution unit responds to the control commands from the management and control unit, adjusts the underground pipe salt discharge rate through electric valves, and regulates the rainwater storage and irrigation water supply flow through water pumps and flow controllers to execute salt discharge and rainwater utilization, while simultaneously collecting operational status data during the execution process and feeding it back to the management and control unit. The data storage and closed-loop optimization unit stores sensing data, fusion data, control commands, and operational status data, optimizes model parameters through historical data mining and analysis, and feeds the optimized parameters back to the parameter calculation unit and the collaborative management and control unit, improving the system's long-term adaptability and stability.

[0015] Beneficial Effects: This invention proposes a method and system for underground pipe salt drainage and rainwater collection and recycling in coastal gardens. By linking an underground pipe deployment efficiency evaluation model with a rainwater storage regulation and adaptation model, the disconnect between underground pipe salt drainage and rainwater collection is broken. By combining vegetation water demand dynamics, real-time changes in soil water and salt, and rainfall characteristics, parameters are dynamically optimized, constructing a water and salt collaborative management mechanism to simultaneously improve salt drainage efficiency and rainwater utilization efficiency. Relying on a multi-source moisture and salt data fusion algorithm, heterogeneous data such as soil, meteorology, and groundwater are comprehensively integrated and processed. In conjunction with a garden water and salt collaborative management platform, a closed-loop operation of data acquisition, model calculation, execution regulation, and parameter optimization is achieved. This provides a scientific basis for operations such as underground pipe salt drainage frequency and rainwater distribution ratio, accurately adapting to the complex and ever-changing water and salt environment and vegetation growth needs of coastal gardens. Its beneficial effects are manifested in: achieving efficient treatment of soil salinization and maximizing the recycling and utilization of rainwater resources, reducing the dependence of traditional irrigation on groundwater and tap water, reducing water consumption and ecological pressure; through the coordinated operation and closed-loop optimization of the six functional units, improving the adaptability and stability of the system in long-term operation, ensuring the survival and growth of vegetation, significantly improving the quality and sustainability of coastal garden ecological construction, and providing integrated technical support for ecological governance in coastal areas. Attached Figure Description

[0016] Figure 1 This is a flowchart of the method steps of the present invention;

[0017] Figure 2 This is a diagram showing the system unit composition of the present invention. Detailed Implementation

[0018] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0019] like Figure 1 As shown, the method for underground pipe salt drainage and rainwater collection and recycling in coastal gardens includes the following steps:

[0020] S1, based on the distribution of soil types in coastal gardens, groundwater depth, initial soil salinity, vegetation water demand characteristics and regional rainfall characteristics, the spacing, burial depth, pipe diameter and opening rate of underground pipes are determined by the underground pipe layout efficiency evaluation model.

[0021] Specifically, step S1 involves the comprehensive collection of key basic parameters for coastal gardens, including soil type distribution parameters (e.g., sandy soil accounting for 35%, loamy soil accounting for 50%, and clay soil accounting for 15%), groundwater depth data (daily average depth and fluctuation range obtained through continuous monitoring for 30 days, with data taken from 2.2 meters to 3.5 meters), initial soil salinity (50 sampling points were set up using a grid method, with stratified sampling at depths from 0 to 60 centimeters, and the average salinity range was obtained), vegetation water demand characteristics parameters (daily average water demand and critical water demand values ​​were recorded for trees, shrubs, and ground cover plants respectively during the growing season), and regional rainfall characteristics parameters (the rainfall data of the past 10 years were statistically analyzed to determine the average annual rainfall, the proportion of rainfall during the rainy season, the maximum single rainfall, and the rainfall interval cycle, etc.). During implementation, a soil type distribution map and a vegetation distribution thematic map were first drawn using a geographic information system, marking key parameters for each region. Then, all parameters were input into a subsurface pipe layout efficiency evaluation model. The model performed comprehensive calculations based on the weights of each parameter, outputting the optimal values ​​for subsurface pipe spacing, burial depth, pipe diameter, and perforation rate. Specifically, the subsurface pipe spacing was controlled between 3 and 5 meters, the burial depth was determined based on the groundwater depth to be between 1.2 and 1.8 meters, the pipe diameter was selected between 110 and 160 millimeters, and the perforation rate was set to 2% to 5%. This step, through precise parameter collection and model calculation, ensured that the subsurface pipe layout was adapted to the specific environment of the coastal garden, laying the foundation for efficient salt removal. The implementation method required strict adherence to parameter collection specifications for sample collection and data verification to ensure the accuracy of the data input into the model, thereby achieving the scientific and rational nature of the subsurface pipe layout.

[0022] S2, using a multi-source moisture and salinity data fusion algorithm to integrate real-time data obtained from soil moisture sensors, salinity sensors, meteorological monitoring stations and groundwater monitoring points, to generate a dynamic monitoring dataset of soil water and salinity;

[0023] Specifically, during step S2, the deployment and debugging of multi-source monitoring equipment are completed first. Soil moisture sensors and salinity sensors are deployed at a grid density of 2 meters × 2 meters to cover the entire coastal garden area. The sensor depth is set to three levels: 10 centimeters, 30 centimeters, and 50 centimeters, to monitor soil moisture and salinity data at different depths. The meteorological monitoring station is located in an open area of ​​the garden and is equipped with rain gauges, anemometers, temperature and humidity sensors, etc., to collect data on rainfall intensity, air humidity, and temperature every 15 minutes. Groundwater monitoring points are deployed at a density of one per 500 square meters to monitor groundwater level and salinity, and data is recorded every hour. During implementation, data collected by various monitoring devices is uploaded to the data receiving terminal in real time via a wireless transmission module. The data receiving terminal performs format conversion and preliminary screening of the raw data, removing obviously abnormal data. Subsequently, a multi-source soil moisture and salinity data fusion algorithm is activated to perform spatiotemporal alignment on heterogeneous data such as soil moisture values ​​at a depth of 10 cm and salinity values ​​at a depth of 30 cm from soil sensors, rainfall intensity data from meteorological monitoring stations, and water level data from groundwater monitoring points. The data is matched and integrated according to the same timestamp and spatial location to generate a dynamic monitoring dataset of soil water and salinity with a time resolution of 15 minutes and a spatial resolution of 2 m × 2 m. The dataset includes continuous time-series data of key indicators such as soil moisture content, salinity, rainfall intensity, and groundwater level, providing comprehensive and accurate data support for subsequent water and salinity status assessment and regulation strategy formulation. During implementation, the monitoring equipment needs to be calibrated regularly to ensure data acquisition accuracy.

[0024] S3, based on the rainwater storage and regulation adaptation model, combined with rainwater runoff coefficient, storage facility capacity constraints, garden irrigation water demand and rainfall forecast data, formulate rainwater collection and regulation strategies;

[0025] Specifically, before implementing step S3, key parameters are obtained in advance, including the rainwater runoff coefficient (by monitoring the rainfall runoff of different underlying surfaces (green areas, hardened roads, and water bodies) to determine the comprehensive rainwater runoff coefficient of the garden to be 0.4 to 0.6), storage facility capacity constraints (based on the garden area and rainfall characteristics, the total capacity of the rainwater storage tank is designed to be 500 to 1000 cubic meters, with the minimum water level warning line set at 20% of the total capacity and the maximum water level control line at 80% of the total capacity), garden irrigation water demand (calculated by vegetation type, with the average daily irrigation water demand of 30 cubic meters / hectare for the arbor area, 25 cubic meters / hectare for the shrub area, and 20 cubic meters / hectare for the ground cover plant area), and rainfall forecast data (connected to the meteorological department's high-precision forecast system to obtain the hourly rainfall intensity and duration forecast values ​​for the next 7 days). During implementation, the above parameters are first input into the rainwater storage regulation and adaptation model. The model combines historical rainfall data with real-time monitored soil moisture data to calculate and determine the start threshold (collection starts when the predicted single rainfall is greater than 5 mm) and stop threshold (collection stops when the water level of the storage facility reaches the highest control line) for rainwater collection. Then, based on the difference between irrigation water demand and soil moisture, emergency irrigation areas, general irrigation areas, and temporarily suspended irrigation areas are divided, and a rainwater allocation plan is formulated. Emergency irrigation areas are given priority in allocating stored rainwater, with an allocation ratio of no less than 40% of the total available rainwater. At the same time, rainwater regulation strategies are set. When the water level of the storage facility is below the minimum warning line, the allocation of non-essential irrigation water is reduced. When the predicted future rainfall is large and the storage facility capacity is insufficient, the emergency discharge channel is activated to control the discharge flow, ensuring that rainwater resources are fully collected and utilized while avoiding overloading of the storage facilities. During implementation, rainfall forecast data and storage facility water level data need to be updated in real time, and the regulation strategy needs to be dynamically adjusted.

[0026] S4, through the garden water and salt collaborative management and control platform, dynamically adjusts the opening of the salt discharge valve in the underground pipe, the water discharge flow of the rainwater storage facility, and the allocation ratio of irrigation water;

[0027] Specifically, step S4 is implemented using a garden water and salt collaborative management platform. This platform needs to pre-connect with the underground pipe salt drainage system, rainwater storage facilities, and irrigation system to achieve precise control command issuance and real-time feedback on execution status. During implementation, the platform first receives the dynamic monitoring dataset of soil water and salt output by a multi-source soil moisture and salt data fusion algorithm, extracts data on excessive soil salinity and insufficient soil moisture in each area, and performs comprehensive analysis by combining underground pipe layout parameters and real-time status data of rainwater storage facilities. Regarding the adjustment of the underground pipe salt drainage valve opening, five adjustment levels are set according to the degree of soil salinity exceeding the standard: 30% to 40% for salinity exceeding the standard by less than 20%; 50% to 60% for exceeding the standard by 20% to 40%; 70% to 80% for exceeding the standard by 40% to 60%; and 90% to 100% for exceeding the standard by more than 60%. The system achieves 0% accuracy in water distribution, precisely controlling valve opening via electric actuators. For rainwater storage facility flow rate regulation, the flow rate is controlled between 5 and 20 cubic meters per hour based on irrigation demand and storage facility water level. When the storage facility water level approaches the minimum warning line, the flow rate is reduced to 5 to 10 cubic meters per hour. Regarding irrigation water allocation, based on vegetation water demand priority and soil moisture conditions, the allocation ratio is 35% to 45% for tree areas, 30% to 40% for shrub areas, and 20% to 25% for ground cover areas. The platform uses an intelligent irrigation controller to allocate water to each area. During implementation, the platform collects execution data such as valve opening, flow rate, and irrigation water consumption every 5 minutes for closed-loop monitoring, ensuring accurate execution of control commands and achieving coordinated operation of underground pipe salt drainage, rainwater utilization, and irrigation regulation.

[0028] S5, based on the soil water and salt status assessment results output by the multi-source moisture and salt data fusion algorithm, adjust the frequency of salt discharge through underground pipes and the intensity of rainwater recycling.

[0029] Specifically, in step S5, the latest collected data on soil moisture, salinity, rainfall, and groundwater are first processed using a multi-source soil moisture and salinity data fusion algorithm. The results of the soil water and salinity assessment are then output to determine whether the soil salinity in each area meets the standard (the standard is that the surface soil salinity is less than 0.3%) and whether the soil moisture content is within the appropriate range (the appropriate moisture content for tree areas is 60% to 80% of the soil field capacity, for shrub areas it is 55% to 75%, and for ground cover plant areas it is 50% to 70%). During implementation, the frequency of underground drainage was adjusted based on the assessment results. When the soil salinity in a certain area exceeded the standard for three consecutive monitoring tests, and the exceedance was within 20%, the drainage frequency was adjusted to once every two days, with each drainage session lasting two hours. When the exceedance was between 20% and 40%, the drainage frequency was adjusted to once a day, with each drainage session lasting three hours. When the exceedance was above 40%, the drainage frequency was adjusted to twice a day, with each drainage session lasting 2.5 hours. Regarding the adjustment of rainwater recycling intensity, when the soil moisture content was within 10% of the lower limit of the suitable range, the rainwater utilization intensity was increased by 20%, increasing irrigation duration and frequency. When the soil moisture content was within the suitable range, the original rainwater utilization intensity was maintained. When the soil moisture content was within 10% of the upper limit of the suitable range, the rainwater utilization intensity was reduced by 30%, reducing irrigation water consumption. When the soil moisture content was more than 10% of the upper limit of the suitable range, rainwater irrigation was suspended, and only underground drainage was carried out. Meanwhile, the relationship between the adjusted salt discharge frequency, rainwater utilization intensity and soil water and salt status changes is recorded in real time to provide data support for further optimization of control strategies. During implementation, it is necessary to ensure the timeliness and accuracy of the assessment results and to ensure the pertinence of the adjustment measures.

[0030] S6 continuously collects data on salt discharge from underground pipes, rainwater utilization, soil moisture and salinity changes, and vegetation growth response. This data is then fed back to the underground pipe deployment effectiveness assessment model, the rainwater storage regulation and adaptation model, and the multi-source moisture and salinity data fusion algorithm to form a closed-loop regulation mechanism.

[0031] Specifically, during step S6, a full-process data acquisition system needs to be constructed. Flow sensors installed at the underground pipe drainage outlets will collect the amount of salt discharged in real time, recording the cumulative amount of salt discharged every hour. By combining the level sensor and flow sensor of the rainwater storage facility, rainwater utilization will be calculated, including irrigation water consumption and landscape water replenishment, and the total amount of rainwater utilized daily, weekly, and monthly will be statistically analyzed. Soil sensors will continuously monitor changes in soil moisture and salinity, recording soil moisture and salinity data at each depth every 15 minutes, and calculating the difference between the current and adjusted values. Vegetation growth monitoring equipment (such as high-definition cameras and plant physiological sensors) will collect growth response data such as plant height, crown width, and leaf chlorophyll content weekly. During implementation, all collected data are organized in a unified format and stored and managed in a database. The data is then fed back to the underground pipe deployment efficiency evaluation model, the rainwater storage and regulation adaptation model, and the multi-source moisture and salinity data fusion algorithm via a data transmission channel. The underground pipe deployment efficiency evaluation model receives data on underground pipe salt discharge and soil salinity changes, corrects the weighting coefficients of the underground pipe deployment parameters, and optimizes the calculation logic for parameters such as underground pipe spacing and burial depth. The rainwater storage and regulation adaptation model adjusts the calculation rules for rainwater collection thresholds and distribution ratios based on rainwater utilization, rainfall data, and soil moisture change data. The multi-source moisture and salinity data fusion algorithm combines newly collected soil moisture and salinity data with vegetation growth response data to optimize the weighting allocation and noise filtering algorithms for data fusion, improving the accuracy of the fusion results. Through continuous data feedback and model optimization, a closed-loop control mechanism is formed, enabling the implementation of the entire method to dynamically adapt to changes in the coastal garden environment, continuously improve the salt drainage effect of underground pipes and the efficiency of rainwater utilization. During implementation, it is necessary to ensure the stability of data transmission and the timeliness of model optimization to guarantee the effectiveness of closed-loop control.

[0032] Preferably, the expression for the performance evaluation model of concealed pipe installation is: ,in, To determine the overall efficiency value for concealed pipe installation, Soil permeability correction factor The coefficient representing the influence of the opening ratio of the concealed pipe. The diameter of the concealed pipe. For the density of concealed pipe installation, The weighting of groundwater depth is determined by the influence of groundwater depth. To determine the spacing for concealed pipe installation, For the depth of the concealed pipe burial, The vegetation type fit coefficient. This represents the initial salinity of the soil. This is the regional rainfall intensity coefficient. These are the permeability parameters of the concealed pipe material.

[0033] Specifically, the implementation of the underground pipe deployment effectiveness evaluation model involves several key aspects. The soil permeability coefficient correction factor is determined based on soil particle composition, porosity, and other physical properties. The underground pipe opening rate influence coefficient is related to the shape and distribution density of the pipe openings. The pipe diameter and deployment density directly correlate with the salt drainage channel's transport capacity. The groundwater depth influence weight is set based on the intensity of the groundwater level's effect on soil salt transport. The underground pipe deployment spacing and burial depth determine the salt drainage range and depth. The vegetation type suitability coefficient is determined by the tolerance of different vegetation types to soil salinity. The initial soil salinity is obtained through multi-point sampling and testing. The regional rainfall intensity coefficient is calculated based on long-term rainfall monitoring data. The underground pipe material permeability parameters are determined by the porosity and permeability of the pipe manufacturing material. During implementation, the actual values ​​of all parameters are collected according to standardized procedures to ensure their authenticity and accuracy. These parameters are then substituted into the model for comprehensive calculation. Through the model's synergistic analysis of various parameters, the overall effectiveness of the underground pipe deployment scheme is quantified. This effectiveness includes multiple indicators such as salt drainage efficiency, material utilization rate, and environmental adaptability. The core of the model implementation lies in overcoming the limitations of single-parameter decision-making through weighted calculation and dynamic correlation of multiple parameters. This ensures that the output parameters for underground pipe layout not only meet the desalination requirements of different soil types and groundwater conditions, but also adapt to the water and salt environment for vegetation growth. At the same time, it takes into account the economy and feasibility of underground pipe layout, providing a scientific and comprehensive quantitative basis for determining the underground pipe layout scheme in step S1, and ensuring the rationality and efficiency of the initial design of the underground pipe desalination system.

[0034] Preferably, the expression for the rainwater storage regulation adaptation model is: ,in, To adapt the output flow rate for rainwater regulation, This is the rainwater runoff correction factor. For rainfall forecast intensity, For the water catchment area of ​​the garden, For storage facility adaptability coefficient, For storage facility capacity, For the water demand intensity of garden irrigation, For the purpose of regulation cycle, The recycling efficiency coefficient. For soil moisture to reach the target threshold, These are parameters related to the effectiveness of rainwater purification treatment.

[0035] Specifically, the implementation of the rainwater storage regulation adaptation model involves considering factors such as underlying surface type, slope, and vegetation cover on rainwater runoff correction coefficients. Rainfall prediction intensity is derived from high-precision short-term forecast data from meteorological departments. The garden catchment area is calculated based on the actual catchment area determined by geographic mapping. The storage facility adaptation coefficient is related to the type, structure, and impermeability of the rainwater storage facilities. The storage facility capacity is the maximum water storage volume determined during the design phase. The garden irrigation water demand intensity is divided according to the water demand characteristics of different vegetation types and growth stages. The regulation cycle is set in conjunction with rainfall frequency and vegetation water demand cycle. The recycling efficiency coefficient reflects the loss during rainwater purification and transportation. The soil moisture threshold is the critical value of soil moisture content for maintaining normal vegetation growth. Rainwater purification effect parameters are determined by detecting indicators such as turbidity and pollutant content of purified rainwater. During implementation, the system first collects measured and design data of the above parameters to ensure that the parameters match the actual situation of the coastal garden. Then, the parameters are input into the model for calculation. The model dynamically balances the relationship between rainwater collection, storage capacity, and irrigation demand through a combination of exponential and fractional operations. The key to implementing this model is to accurately output the appropriate rainwater flow rate for regulation based on rainfall forecasts and actual soil moisture, and to clarify the dynamic ratio of rainwater collection, storage, utilization, and discharge. This ensures that rainwater resources are recycled and utilized to the maximum extent, avoiding water waste, while also preventing storage facilities from being overloaded due to excessive rainfall. At the same time, it ensures that the output rainwater flow rate can meet the real-time needs of garden irrigation, providing quantitative support for the formulation of rainwater collection and regulation strategies in step S3, and achieving precise matching between rainwater resource utilization and garden irrigation needs.

[0036] Preferably, the expression for the multi-source moisture data fusion algorithm is: ,in, The values ​​represent the water-salt state assessment values ​​after fusion. The weights for data from soil sensors, weather stations, and groundwater monitoring points are respectively... These are the salinity monitoring values ​​at three different monitoring points. The weights of soil moisture data from the three types of monitoring points are respectively. These are the soil moisture monitoring values ​​for three types of monitoring points. This is a time-dynamic correction factor. For monitoring duration, This is the data fusion cycle.

[0037] Specifically, in implementing the multi-source soil moisture and salinity data fusion algorithm, the weights of the three types of monitoring points are determined based on the accuracy, deployment density, and data reliability of different monitoring equipment. Soil sensor data focuses on the direct monitoring of soil moisture and salinity; meteorological station data provides information on external environmental factors such as rainfall, temperature, and humidity; and groundwater monitoring point data reflects the indirect effects of groundwater level and salinity on soil water and salinity. A time-dynamic correction coefficient is used to compensate for the timeliness differences of data from different monitoring periods. The monitoring duration is the continuous time span of data collection, and the data fusion cycle is the time interval for the algorithm to perform one complete data fusion. During implementation, the raw data collected from the three types of monitoring points are first preprocessed to remove abnormal data caused by equipment failure or environmental interference. Then, the data of the same type are weighted and summed according to the set weight coefficients. The discrete characteristics of soil moisture data are integrated through square root operation, and the time differences of the data are dynamically corrected by combining a sine function to finally generate a water and salinity status assessment value in a unified format. The core of this algorithm lies in solving the problem of the one-sidedness and limitations of single monitoring data by aligning and fusing multi-source data in a spatiotemporal manner. It transforms heterogeneous data such as soil, meteorology, and groundwater into comprehensive assessment results that can fully reflect the dynamic changes of soil water and salt in coastal gardens. The data fusion process strictly follows the principle of spatiotemporal matching to ensure that data from different sources and dimensions can effectively complement each other. This provides a precise and comprehensive data processing method for generating the soil water and salt dynamic monitoring dataset in step S2 and assessing the soil water and salt status in step S5, thereby improving the scientific nature and accuracy of subsequent regulatory decisions.

[0038] Preferably, the regulation model expression of the garden water and salt collaborative management platform is: ,in, Output values ​​for platform collaborative management, These are parameters for the salt drainage efficiency of concealed pipes. Rainwater utilization flow, For the adaptation coefficient of the control strategy, This is the water-salt balance adjustment coefficient. For the area of ​​garden soil, To coordinate and regulate weights, These are the valve opening parameters for concealed pipes. The threshold for controlling soil salinity. The length of the concealed pipe. To regulate response time, For the available capacity of the storage facility, For irrigation water utilization rate, Prioritize water demand for vegetation. The coefficient for water-salt synergy.

[0039] Specifically, the implementation of the water and salt synergistic management platform control model for gardens involves determining the efficiency parameters of subsurface pipe salt discharge by monitoring the discharge flow rate and changes in soil salinity after discharge. Rainwater utilization flow rate refers to the actual amount of rainwater delivered from storage facilities to the irrigation system. The control strategy adaptation coefficient is set based on the degree of matching between the platform's control logic and the actual environment. The water and salt balance regulation coefficient reflects the platform's control strength in maintaining soil water and salt balance. The garden soil area refers to the actual green area of ​​the coastal garden. The synergistic control weight is used to balance the control priorities of subsurface pipe salt discharge and rainwater utilization. The valve opening parameter is the actual degree to which the valve is opened; the soil salinity control threshold is the upper limit of soil salinity to ensure vegetation growth; the underground pipe length is the total length of the underground pipes actually laid; the control response time is the interval between the platform receiving data and issuing instructions; the available capacity of the storage facility is the remaining water volume of the storage facility monitored in real time; the irrigation water utilization rate is the ratio of the actual water used for vegetation irrigation to the water transported; the vegetation water demand priority is divided according to vegetation type, growth stage, and landscape importance; and the water-salt synergy coefficient is used to quantify the synergistic effect of salt removal and water replenishment. During implementation, the platform collects dynamic data of the above parameters in real time, and through fractional and square root calculations of the model, comprehensively balances multiple objectives such as salt removal efficiency, rainwater utilization efficiency, and water-salt balance, outputting precise synergistic control values. The key to implementing this model is to integrate the control parameters of the underground pipe desalination system and the rainwater utilization system. Through the collaborative calculation of multiple parameters, it achieves precise control over the opening of underground pipe valves, rainwater discharge flow, and irrigation water allocation. This breaks the limitations of the independent operation of each system in traditional management and control, provides a quantitative basis for the dynamic control of the platform in step S4, ensures the synergy and scientific nature of desalination, rainwater utilization, and irrigation control, and maintains the water and salt balance of coastal garden soil.

[0040] Preferably, the expression for the integrated optimization model of underground pipe salt drainage and rainwater collection and recycling for coastal gardens is: ,in, To comprehensively optimize the target value, These are the weighting coefficients for efficiency, traffic, integration value, and control value, respectively. To optimize the penalty coefficient, For parameters related to the construction cost of concealed pipes, Energy consumption parameters For resource recycling efficiency parameters, These are parameters related to the soil improvement effect.

[0041] Specifically, in implementing the comprehensive optimization model, four weighting coefficients are determined based on the core objectives of coastal garden ecological construction. These coefficients quantify the importance of underground pipe deployment efficiency, rainwater regulation flow, water-salt data fusion value, and platform control value in the comprehensive optimization. An optimization penalty coefficient is used to constrain the impact of negative indicators such as underground pipe construction costs and energy consumption. The underground pipe construction cost parameter is the comprehensive cost accounting value of underground pipe materials, construction, and installation. The energy consumption parameter reflects the energy consumption during the operation of the underground pipe desalination system, rainwater storage facilities, and control platform. The resource recovery efficiency parameter is the ratio of rainwater recovery and utilization to total rainfall. The soil improvement effect parameter is determined by comparing changes in soil salinity, fertility, and other indicators before and after desalination. During implementation, the output results of each sub-model (underground pipe deployment comprehensive efficiency value, rainwater regulation adaptation flow, water-salt status assessment value, and platform collaborative control value) and related cost, energy consumption, and efficiency parameters are first collected. These are then substituted into the model according to the set weighting and penalty coefficients for calculation. The model outputs the comprehensive optimization target value through a combination of weighted summation and penalty term correction. The core of this model lies in comprehensively considering technical efficiency with economic and ecological benefits. While ensuring the effectiveness of underground pipe salt drainage, rainwater utilization efficiency, and water and salt control accuracy, it minimizes construction costs and energy consumption, improves resource recycling efficiency and soil improvement effects, and provides a global quantitative basis for the parameter optimization of the entire method and system. This achieves a comprehensive balance between technical performance, economic benefits, and ecological benefits, ensuring the long-term sustainability and optimization of underground pipe salt drainage and rainwater collection and recycling systems used in coastal gardens.

[0042] Preferably, step S3 includes the following sub-steps: S31, accessing rainfall forecast data, historical rainfall statistics, and real-time rainfall monitoring data released by the regional meteorological department through the garden water and salt collaborative management and control platform, extracting rainfall intensity, rainfall duration, and rainfall interval calibration parameters, and establishing a rainfall characteristic database; S32, based on the rainwater storage regulation and adaptation model, inputting the maximum capacity, minimum reserved capacity, and water release rate limit parameters of the storage facility, and combining the irrigation water demand intensity corresponding to different vegetation types and growth stages in different areas of the garden, determining the priority and allocation ratio of rainwater collection; S33, calculating the rainwater supplementary irrigation demand based on the difference between soil moisture monitoring data and vegetation water demand threshold, and dynamically adjusting the regulation and control strategy based on rainwater storage volume, clarifying the boundary conditions for direct rainwater utilization, storage and subsequent utilization, and emergency discharge; S34, converting the regulation and control strategy into control commands for the opening of the inlet valve and the outflow of water in the storage facility, and issuing them to the execution agency through the garden water and salt collaborative management and control platform.

[0043] Specifically, step S3 includes four sub-steps: S31: Through the garden water and salt collaborative management platform, access rainfall forecast data released by the regional meteorological department, historical rainfall statistics for the past 10 years, and data from 12 real-time rainfall monitoring points deployed within the garden. Extract key parameters such as rainfall intensity, duration, and interval, and organize them into a rainfall characteristic database with a resolution of 15 minutes according to time series. The database covers rainfall-related information for the entire garden area and a surrounding 5-kilometer radius, providing basic data support for subsequent strategy formulation; S32: Based on the rainwater storage regulation and adaptation model, input parameters such as the maximum capacity, minimum reserved capacity, and water release rate limit of three rainwater storage tanks. Combined with the irrigation water demand intensity corresponding to different growth stages of the three types of areas in the garden—tree area, shrub area, and ground cover plant area—the platform calculates and determines the rainwater collection priority, with the tree area having the highest priority and an allocation ratio of no less than 40% of the total available rainwater. Shrub areas are prioritized, with an allocation ratio of 30% to 35%, while ground cover areas have the lowest priority, with an allocation ratio of 25% to 30%. S33 calculates the difference between real-time data from 80 soil moisture monitoring points distributed throughout the garden and the water demand thresholds for various vegetation types to determine the supplementary irrigation needs for each area. Combined with real-time liquid level data from rainwater storage facilities, the control strategy is dynamically adjusted to clarify the specific boundary conditions for direct use of rainwater for irrigation, delayed use after storage, and emergency discharge when storage capacity is exceeded. When the storage liquid level is below 20% of the total capacity, only the irrigation needs of the tree area are guaranteed. S34 transforms the established control strategy into specific control instructions through the garden water and salt collaborative management platform, including the opening degree of the inlet valve of the storage facility and the control parameters for the outflow rate. These instructions are transmitted to each actuator via wired transmission, ensuring that the instruction transmission delay does not exceed 2 seconds. Simultaneously, the instruction issuance time and the response status of the actuators are recorded to form a complete operation log.

[0044] Preferably, step S4 includes the following sub-steps: S41, the garden water and salt collaborative management platform receives the soil water and salt status assessment results output by the multi-source soil moisture and salt data fusion algorithm in real time, and extracts the spatial location and degree parameters of areas with excessive soil salinity and areas with insufficient soil moisture; S42, based on the salt discharge priority of each area's underground pipes determined by the underground pipe layout efficiency assessment model, and combined with the current operating status data of the underground pipes, the target opening degree of each underground pipe valve is calculated to ensure that the salt discharge efficiency matches the degree of excessive soil salinity; S43, based on the real-time liquid level data of the rainwater storage facility, the water quality parameters after rainwater purification treatment, and the water quality requirements for garden irrigation water, the water discharge flow of the storage facility is adjusted to control the rate at which rainwater is transported to the irrigation area; S44, based on the water demand urgency of different vegetation areas and the soil moisture recovery target, the irrigation water volume is allocated, and water is supplied through the intelligent irrigation terminal, while simultaneously recording various operating parameters during the control process.

[0045] Specifically, step S4 includes four sub-steps: S41 The garden water and salt collaborative management platform receives the soil water and salt status assessment results output by the multi-source soil moisture and salt data fusion algorithm in real time. This result comes from the integrated data of 100 distributed soil sensors, 6 meteorological monitoring stations, and 4 groundwater monitoring points within the garden. The platform extracts the spatial coordinates and parameters of the degree of exceedance and deficiency of soil salinity in areas with excessive soil salinity and insufficient soil moisture, classifies them into three regional levels according to severity, and marks them on the electronic map; S42 Based on the salt drainage priority of underground pipes in each region determined by the underground pipe deployment efficiency assessment model, and combined with the current operating status data of 3000 meters of underground pipes in the entire area, the target opening degree of the valves in each section of underground pipes is calculated. The valve opening degree of the underground pipes corresponding to the most severely excessive salinity is set to 90% to 100%, the moderately excessive area is 60% to 80%, and the slightly excessive area is 30% to 50%. The system precisely controls the valve opening using an electric actuator, with a control accuracy error not exceeding 2%. S43 adjusts the water flow rate of the storage facility based on real-time liquid level data, turbidity after rainwater purification, and pollutant content, combined with the water quality requirements for garden irrigation. The flow rate ranges from 5 cubic meters per hour to 20 cubic meters per hour. If the water quality parameters do not meet the standards, a secondary purification process is automatically initiated. Once the water quality meets the standards, the flow rate is adjusted to deliver water to the irrigation area. S44 allocates irrigation water to each area based on the urgency of water demand and soil moisture recovery targets for different vegetation areas. It simultaneously records various operating parameters during the control process, including valve opening, water flow rate, irrigation duration, and water quality parameters. An operating status report is generated every 5 minutes and stored in the platform database for subsequent querying and analysis, ensuring the control process is traceable and optimizable.

[0046] Preferably, step S5 includes the following sub-steps: S51, collecting drainage flow rate and salt concentration data from the underground pipe's salt discharge outlet, combining this with soil salinity data monitored by soil sensors after salt discharge, and calculating the salt discharge effect evaluation value using a multi-source moisture and salt data fusion algorithm; S52, analyzing the correlation between irrigation water volume, irrigation duration, and soil moisture changes during rainwater utilization, and adjusting the rainwater recycling intensity and optimizing rainwater utilization efficiency by combining vegetation growth status feedback data; S53, feeding back the salt discharge effect evaluation value and rainwater utilization efficiency parameters to the underground pipe layout efficiency evaluation model, correcting the adaptability of underground pipe layout spacing and burial depth parameters, and updating the salt discharge frequency control logic; S54, based on the real-time calculation results of the rainwater storage regulation adaptation model, and combined with the dynamic changes in rainfall forecast data, adjusting the rainwater collection threshold and storage facility regulation strategy to maximize the utilization of rainwater resources and dynamically maintain water-salt balance.

[0047] Specifically, step S5 includes four sub-steps, and the specific implementation process is as follows: S51: Install 20 flow sensors and 15 salt concentration sensors at the underground drainage outlet to collect drainage flow and salt concentration data in real time. Simultaneously, combine this with soil salinity data from 0 to 60 cm depth monitored by soil sensors. Use a multi-source soil moisture and salt data fusion algorithm to integrate and calculate the salt drainage effect evaluation value. The evaluation value includes three core indicators: salt drainage efficiency, total salt removal, and the decrease in soil salinity. Data collection intervals are 10 minutes to ensure the timeliness and accuracy of the evaluation results. S52: Analyze the correlation between irrigation water volume, irrigation duration, and soil moisture changes during rainwater utilization. Combine this with feedback data such as plant height, crown width, and leaf chlorophyll content obtained from 50 vegetation growth monitoring points set up in the garden to adjust the intensity of rainwater recycling. When vegetation growth data does not meet expectations, increase rainwater utilization intensity by 20% to 30% to optimize rainwater utilization. Efficiency is assessed by recording changes in various data before and after adjustments and establishing a correlation analysis archive. S53 feeds back the salt drainage effect assessment value and rainwater utilization efficiency parameters to the underground pipe layout efficiency assessment model through the data transmission channel. The model combines the feedback data to correct the adaptability of parameters such as underground pipe layout spacing and burial depth, and updates the salt drainage frequency control logic. When the salt drainage effect assessment value is more than 30% lower than the set standard, the salt drainage frequency is adjusted from once a day to twice a day, and the duration of each salt drainage is extended by 30 minutes. S54 Based on the real-time calculation results of the rainwater storage regulation adaptation model and combined with the dynamic changes of the 7-day rainfall forecast data updated by the meteorological department, the rainwater collection threshold and storage facility regulation strategy are adjusted. When the predicted cumulative rainfall in the next 3 days exceeds 50 mm, the current liquid level of the storage facility is reduced to 50% of the total capacity in advance to reserve sufficient storage space, so as to maximize the utilization of rainwater resources and dynamically maintain the water and salt balance, and ensure that the soil water and salt state is always within the suitable range for vegetation growth.

[0048] like Figure 2As shown, this is a subsurface pipe salt drainage and rainwater collection and recycling system for coastal gardens. This system, applied to subsurface pipe salt drainage and rainwater collection and recycling methods in coastal gardens, includes six functional units. Each unit is bidirectionally connected to a control bus via data transmission lines. Specifically: a high-precision sensing unit for multi-source water and salt parameters in coastal gardens, used to collect basic data on soil moisture content, salinity, rainfall intensity, and groundwater level through distributed soil moisture sensors, salinity sensors, meteorological monitoring modules, and groundwater monitoring probes. The data is converted into standardized digital signals and transmitted to the data processing unit. A multi-source moisture and salinity data fusion processing unit receives the standardized data transmitted from the sensing unit, performs spatiotemporal alignment, noise filtering, and feature extraction on the heterogeneous data using a multi-source moisture and salinity data fusion algorithm, generates a unified format water and salt status assessment dataset, and simultaneously sends the dataset to the collaborative management unit. A subsurface pipe deployment and rainwater regulation parameter calculation unit is used to calculate the subsurface pipe deployment effectiveness evaluation model based on the assessment dataset. The system calculates optimized parameters for underground pipe layout and generates rainwater collection and control strategy parameters through a rainwater storage and regulation adaptation model. These two types of parameters are then output to the collaborative management and control unit. The garden water and salt collaborative intelligent management and control unit receives the evaluation dataset from the fusion processing unit and the optimized parameters from the parameter calculation unit. It generates control commands for underground pipe desalination valves, rainwater storage facility regulation commands, and irrigation water allocation commands, which are then sent to the execution unit. The underground pipe desalination and rainwater circulation execution unit responds to the control commands from the management and control unit. It adjusts the desalination rate of the underground pipes through electric valves and regulates the rainwater storage and irrigation water supply flow through water pumps and flow controllers, executing desalination and rainwater utilization. Simultaneously, it collects operational status data during the execution process and feeds it back to the management and control unit. The data storage and closed-loop optimization unit stores sensing data, fusion data, control commands, and operational status data. It optimizes model parameters through historical data mining and analysis, and feeds the optimized parameters back to the parameter calculation unit and the collaborative management and control unit, improving the system's long-term adaptability and stability.

[0049] This invention relates to a method and system for underground pipe salt drainage and rainwater harvesting and recycling in coastal gardens. Addressing the issues of fragmentation and insufficient coordination between underground pipe salt drainage and rainwater harvesting, it integrates parameters such as soil water and salt dynamics, vegetation water requirements, and rainfall characteristics into a unified control system through the linkage of an underground pipe deployment efficiency evaluation model and a rainwater storage and regulation adaptation model. This achieves dynamic adaptation between underground pipe deployment parameters and rainwater regulation strategies, establishing a water and salt collaborative management mechanism and overcoming the limitations of independent operation in traditional technologies. Furthermore, addressing the lack of precise control and scientific basis, it integrates multi-dimensional data from soil, meteorology, and groundwater using a multi-source moisture and salt data fusion algorithm. This, combined with a garden water and salt collaborative management platform, creates a closed-loop operation system covering the entire process from data collection and fusion processing to command issuance and effect feedback. This provides comprehensive data support for operations such as salt drainage frequency and rainwater allocation ratios, adapting to the complex and ever-changing environmental needs of coastal gardens.

[0050] This method and system achieve integrated operation of salt removal, rainwater collection, and irrigation regulation through the connection between steps and the synergy of system units, avoiding technological fragmentation. It exhibits outstanding dynamic adaptability, continuously receiving operational data feedback through a closed-loop control mechanism to constantly optimize model parameters and control strategies, adapting to dynamic changes in environmental factors such as soil water and salinity, and rainfall. It is highly efficient in resource utilization, maximizing the recycling and utilization of rainwater resources and reducing reliance on traditional water resources. Simultaneously, precise salt removal reduces the impact of soil salinization, achieving simultaneous improvement in ecological and resource benefits. Operation is stable and reliable, with the division of labor and collaboration among six functional units and data support ensuring the continuity of technology implementation and the stability of its effects, providing long-term technical support for coastal garden ecological construction.

[0051] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," "link," and "fix" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal communication between two components. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0052] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various equivalent changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for underground pipe salt drainage and rainwater collection and recycling in coastal gardens, characterized in that, Includes the following steps: S1. Based on parameters such as the distribution of soil types in coastal gardens, groundwater depth, initial soil salinity, vegetation water requirements, and regional rainfall characteristics, a subsurface pipe layout efficiency evaluation model is used to determine the spacing, burial depth, pipe diameter, and perforation rate of subsurface pipes. S2. A multi-source moisture and salinity data fusion algorithm is used to integrate real-time data from soil moisture sensors, salinity sensors, meteorological monitoring stations, and groundwater monitoring points to generate a dynamic soil water and salinity monitoring dataset. S3. Based on a rainwater storage and regulation adaptation model, combined with rainwater runoff coefficient, storage facility capacity constraints, garden irrigation water requirements, and rainfall forecast data, [further details on rainfall prediction are needed]. S4. Develop rainwater harvesting and regulation strategies; S5. Dynamically adjust the opening degree of the underground pipe salt discharge valve, the water flow rate of the rainwater storage facility, and the allocation ratio of irrigation water through the garden water and salt collaborative management platform; S6. Adjust the frequency of underground pipe salt discharge and the intensity of rainwater recycling based on the soil water and salt status assessment results output by the multi-source moisture and salt data fusion algorithm; S7. Continuously collect data on underground pipe salt discharge, rainwater utilization, soil moisture and salt change values, and vegetation growth response, and feed them back to the underground pipe deployment effectiveness assessment model, the rainwater storage regulation adaptation model, and the multi-source moisture and salt data fusion algorithm to form a closed-loop regulation mechanism.

2. The method for underground pipe salt drainage and rainwater collection and recycling in coastal gardens according to claim 1, characterized in that, The expression for the evaluation model of the effectiveness of concealed pipe installation is as follows: ,in, To determine the overall efficiency value for concealed pipe installation, Soil permeability correction factor The coefficient representing the influence of the opening ratio of the concealed pipe. The diameter of the concealed pipe. For the density of concealed pipe installation, The weighting of groundwater depth is determined by the influence of groundwater depth. To determine the spacing for concealed pipe installation, For the depth of the concealed pipe burial, The vegetation type fit coefficient. This represents the initial salinity of the soil. This is the regional rainfall intensity coefficient. These are the permeability parameters of the concealed pipe material.

3. The method for underground pipe salt drainage and rainwater collection and recycling in coastal gardens according to claim 1, characterized in that, The expression for the rainwater storage regulation and adaptation model is: ,in, To adapt the output flow rate for rainwater regulation, This is the rainwater runoff correction factor. For rainfall forecast intensity, For the water catchment area of ​​the garden, For storage facility adaptability coefficient, For storage facility capacity, For the water demand intensity of garden irrigation, For the purpose of regulation cycle, The recycling efficiency coefficient. For soil moisture to reach the target threshold, These are parameters related to the effectiveness of rainwater purification treatment.

4. The method for underground pipe salt drainage and rainwater collection and recycling in coastal gardens according to claim 1, characterized in that, The expression for the multi-source moisture salt data fusion algorithm is as follows: ,in, The values ​​represent the water-salt state assessment values ​​after fusion. The weights for data from soil sensors, weather stations, and groundwater monitoring points are respectively... These are the salinity monitoring values ​​at three different monitoring points. The weights of soil moisture data from the three types of monitoring points are respectively. These are the soil moisture monitoring values ​​for three types of monitoring points. This is a time-dynamic correction factor. For monitoring duration, This is the data fusion cycle.

5. The method for underground pipe salt drainage and rainwater collection and recycling in coastal gardens according to claim 1, characterized in that, The regulation model expression of the garden water and salt collaborative management platform is as follows: ,in, Output values ​​for platform collaborative management, These are parameters for the salt drainage efficiency of concealed pipes. Rainwater utilization flow, For the adaptation coefficient of the control strategy, This is the water-salt balance adjustment coefficient. For the area of ​​garden soil, To coordinate and regulate weights, These are the valve opening parameters for concealed pipes. The threshold for controlling soil salinity. The length of the concealed pipe. To regulate response time, For the available capacity of the storage facility, For irrigation water utilization rate, Prioritize water demand for vegetation. The coefficient for water-salt synergy.

6. The method for underground pipe salt drainage and rainwater collection and recycling in coastal gardens according to claim 1, characterized in that, The expression for the integrated optimization model of underground pipe salt drainage and rainwater collection and recycling for coastal gardens is as follows: ,in, To comprehensively optimize the target value, These are the weighting coefficients for efficiency, traffic, integration value, and control value, respectively. To optimize the penalty coefficient, For parameters related to the construction cost of concealed pipes, Energy consumption parameters For resource recycling efficiency parameters, These are parameters related to the soil improvement effect.

7. The method for underground pipe salt drainage and rainwater collection and recycling in coastal gardens according to claim 1, characterized in that, S3 includes the following steps: S31, accessing rainfall forecast data, historical rainfall statistics data and real-time rainfall monitoring data released by the regional meteorological department through the garden water and salt collaborative management and control platform, extracting rainfall intensity, rainfall duration and rainfall interval calibration parameters, and establishing a rainfall characteristic database; S32, based on the rainwater storage regulation and adaptation model, input the maximum capacity, minimum reserved capacity, and water release rate limit parameters of the storage facility, and combine them with the irrigation water demand intensity corresponding to different vegetation types and growth stages in different areas of the garden to determine the priority and allocation ratio of rainwater collection; S33, based on the difference between soil moisture monitoring data and vegetation water demand threshold, calculate the rainwater supplementary irrigation demand, and combine the dynamic adjustment and regulation strategy of rainwater storage to clarify the boundary conditions for direct rainwater utilization, storage and subsequent utilization, and emergency discharge; S34, convert the regulation strategy into control instructions for the opening of the inlet valve and the outflow of water in the storage facility, and issue them to the implementing agency through the garden water and salt collaborative management and control platform.

8. The method for underground pipe salt drainage and rainwater collection and recycling in coastal gardens according to claim 1, characterized in that, S4 includes the following sub-steps: S41, the garden water and salt collaborative management platform receives the soil water and salt status assessment results output by the multi-source moisture and salt data fusion algorithm in real time, and extracts the spatial location and degree parameters of areas with excessive soil salinity and areas with insufficient soil moisture; S42, based on the salt discharge priority of each area determined by the underground pipe deployment efficiency assessment model, and combined with the current operating status data of the underground pipes, the target opening degree of each underground pipe valve is calculated to ensure that the salt discharge efficiency matches the degree of excessive soil salinity; S43, based on the real-time liquid level data of the rainwater storage facility, the water quality parameters after rainwater purification treatment, and the water quality requirements for garden irrigation water, the water discharge flow of the storage facility is adjusted to control the rate at which rainwater is transported to the irrigation area; S44, based on the water demand urgency of different vegetation areas and the soil moisture recovery target, the irrigation water volume is allocated, and water is supplied through the intelligent irrigation terminal, while simultaneously recording various operating parameters during the control process.

9. The method for underground pipe salt drainage and rainwater collection and recycling in coastal gardens according to claim 1, characterized in that, S5 includes the following sub-steps: S51, collecting drainage flow rate and salt concentration data from the underground pipe's salt discharge outlet, combining this with soil salinity data from soil sensors after salt discharge, and calculating the salt discharge effect evaluation value using a multi-source soil moisture and salt data fusion algorithm; S52, analyzing the correlation between irrigation water volume, irrigation duration, and soil moisture changes during rainwater utilization, and adjusting the rainwater recycling intensity and optimizing rainwater utilization efficiency based on vegetation growth status feedback data; S53, feeding back the salt discharge effect evaluation value and rainwater utilization efficiency parameters to the underground pipe layout efficiency evaluation model, correcting the adaptability of underground pipe layout spacing and burial depth parameters, and updating the salt discharge frequency control logic; S54, based on the real-time calculation results of the rainwater storage regulation adaptation model, and combined with the dynamic changes in rainfall forecast data, adjusting the rainwater collection threshold and storage facility regulation strategy to maximize the utilization of rainwater resources and dynamically maintain water-salt balance.

10. A submerged pipe system for salt drainage and rainwater collection and recycling in coastal gardens, characterized in that, This system is applied to the method for underground pipe salt drainage and rainwater collection and recycling in coastal gardens as described in claim 1. It comprises six functional units, each connected bidirectionally via a data transmission line and a control bus. Specifically: a high-precision sensing unit for multi-source water and salt parameters in coastal gardens, used to collect basic data on soil moisture content, salinity, rainfall intensity, and groundwater level through distributed soil moisture sensors, salinity sensors, meteorological monitoring modules, and groundwater monitoring probes; converting the data into standardized digital signals and transmitting them to the data processing unit; and a multi-source moisture and salt data fusion processing unit, used to receive the standardized data transmitted by the sensing unit, perform spatiotemporal alignment, noise filtering, and feature extraction on the heterogeneous data using a multi-source moisture and salt data fusion algorithm, generating a unified format water and salt state assessment dataset, and simultaneously sending the dataset to the collaborative management unit. The underground pipe layout and rainwater regulation parameter calculation unit is used to calculate the underground pipe layout optimization parameters based on the evaluation dataset and through the underground pipe layout effectiveness evaluation model, and to generate rainwater collection and regulation strategy parameters through the rainwater storage regulation adaptation model, and output the two types of parameters to the collaborative management and control unit. The garden water and salt collaborative intelligent control unit is used to receive the evaluation dataset from the fusion processing unit and the optimization parameters from the parameter calculation unit, generate control commands for the underground pipe salt discharge valve, control commands for the rainwater storage facility, and irrigation water allocation commands, and send them to the execution unit; the underground pipe salt discharge and rainwater circulation execution unit is used to respond to the control commands of the control unit, adjust the underground pipe salt discharge rate through electric valves, and adjust the rainwater storage and irrigation water supply flow through water pumps and flow controllers to execute salt discharge and rainwater utilization, while collecting the operation status data during the execution process and feeding it back to the control unit; The data storage and closed-loop optimization unit is used to store sensing data, fused data, control commands and operating status data. It optimizes model parameters through historical data mining and analysis, and feeds the optimized parameters back to the parameter calculation unit and collaborative management and control unit to improve the adaptability and stability of the system in long-term operation.

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