An aquatic plant parameterization configuration design method and system

Abstract

The present application relates to the technical field of plant ecological configuration, and particularly relates to an aquatic plant ecological configuration parameterization design method and system. The design method can provide quantitative basis for the design and optimization of the scheme based on the dual targets of aquatic plant ecological function and landscape benefit by constructing a parameterization standard module including ecological index standards and landscape index standards, realize precise design of the aquatic plant configuration scheme, and reduce the dependence on artificial experience. Meanwhile, by constructing a multi-dimensional database and adopting a multi-database linkage data fusion mechanism, the design recommendation and optimization can be provided with data support, and the quantitative linkage of plant variety-planting amount-purification effect-landscape score-cost can be realized. Meanwhile, by automatically matching plant varieties through an algorithm design process, an optimized combination structure can be obtained, the aquatic plant configuration scheme considering ecological efficiency and landscape value can be quickly obtained, and the precise design of aquatic plant configuration from 'experience-driven' to 'data-driven' is realized.

Description

Technical Field

[0001] This invention relates to the field of ecological configuration design technology for garden plants, specifically to a parametric configuration design method and system for aquatic plants. Background Technology

[0002] In the field of aquatic plant ecological landscape design and aquatic ecological restoration engineering, the scientific configuration of aquatic plants directly determines the ecological purification efficiency of the water body, the landscape presentation effect, and the feasibility and stability of the project implementation. However, the current aquatic plant design methods used in the industry have many key technical defects, resulting in a serious disconnect between the design scheme and the actual engineering application needs. This not only causes the ecological restoration efficiency to fail to meet the preset standards and the engineering operation and maintenance costs to remain high, but also fails to meet the core technical requirement of "synergistic promotion of ecological restoration and landscape beautification" in complex aquatic environments. Specifically, this is reflected in:

[0003] (i) The technical means are limited and rely on manual experience, lacking parameterized standards. Traditional aquatic plant design methods rely heavily on the subjective experience of designers, lacking scientific and systematic parametric design standards. Key technical aspects such as plant variety selection, density determination, and community combination structure design are highly dependent on the individual experience of designers. Limited by the depth and accuracy of designers' understanding of the ecological characteristics of aquatic plants and water environment parameters, it is impossible to establish a quantitative correspondence between the characteristics of aquatic plants and water purification needs. It is difficult to achieve a precise match between aquatic plant configuration and water purification goals. In engineering practice, artificial configuration is carried out only based on vague empirical rules such as "wet plants are suitable for shallow water areas," resulting in problems such as low plant survival rates and water purification effects failing to meet preset targets after the design scheme is implemented. (ii) The ecological benefits are separated from the landscape design, and the ability to coordinate and optimize multiple objectives is insufficient. In existing technologies, even if some solutions attempt to introduce intelligent assisted design methods, their technical focus is still limited to the optimization of the appearance of aquatic plant landscapes, such as the surface design of flower color matching and plant height layering. They do not incorporate core ecological benefit indicators into the design system, resulting in a serious disconnect between the "landscape beautification" function and the "ecological purification" function of aquatic plants. At the same time, they do not take into account economic cost parameters, and cannot achieve the technical effect of multi-objective synergistic optimization. It is difficult to achieve a synergistic balance of "landscape aesthetics-ecological function-economic cost", and cannot meet the practical requirements of engineering design. (iii) Lack of dynamic feedback mechanism during maintenance period, resulting in low efficiency in adjusting the plan. Aquatic environments are highly dynamic, with phenomena such as a sudden surge in ammonia nitrogen concentration during the rainy season and fluctuations in plant metabolic efficiency caused by water temperature changes. However, existing design schemes enter a static execution phase after delivery, lacking the ability to track water quality parameters in real time and the technology to adjust plant configuration schemes in conjunction with these parameters. This makes it impossible to adapt to the dynamic changes in the aquatic environment, resulting in the inability to quickly locate the root cause of the problem and optimize the design scheme when anomalies occur. This leads to delays in ecological restoration, a significant increase in engineering operation and maintenance costs, and an inability to guarantee the long-term stability of the aquatic ecological restoration effect. For example, when core water quality indicators such as ammonia nitrogen content are abnormally elevated, existing technologies require a cumbersome process of manual on-site inspection, sample laboratory testing, and designer experience judgment to locate problematic plants (such as plant species that inefficiently absorb ammonia nitrogen), and then readjust the planting scheme. The entire process takes several weeks or even months, which not only delays the best time for ecological restoration but also significantly increases the operation and maintenance costs of manpower and seedlings due to repeated construction. This disconnected "design-construction-maintenance" technical model cannot meet the long-term needs of complex aquatic ecological restoration. (iv) Weak data integration capabilities, and inability to effectively link multi-dimensional information. Existing design tools lack the ability to perform multi-dimensional data correlation analysis, making it difficult to achieve in-depth integration and linkage analysis of multi-dimensional data such as ecology, landscape, and economy. This results in a lack of scientific data support for the optimization and adjustment of design schemes, which can only rely on the experience of designers for trial and error. Consequently, the optimization of schemes lacks a scientific basis, significantly reducing design efficiency and scheme accuracy. This fails to meet the technical requirements of large-scale and refined aquatic plant design and restricts the large-scale application of aquatic plant design technology.

[0004] In summary, existing aquatic plant design technologies rely on human experience throughout the entire process from decision-making and optimization to maintenance implementation. This results in blind spots and delays, making it difficult to adapt to the dynamic changes in complex aquatic environments and meet the dual core requirements of ecological restoration and landscape beautification. Consequently, the ecological benefits of existing aquatic plant configuration schemes are disconnected from engineering practice. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of existing technologies, such as the reliance on human experience in the entire process of aquatic plant design from decision-making and optimization to maintenance, which makes it difficult to adapt to the dynamic changes in complex aquatic environments and meet the dual core requirements of ecological restoration and landscape beautification. This results in a disconnect between the ecological benefits of existing aquatic plant configuration schemes and engineering practice. The invention provides a parametric configuration design method and system for aquatic plants.

[0006] In a first aspect, the present invention provides a method for parametric configuration design of aquatic plants, comprising the following steps: Step 1: Construct a parameterized standard module. The parameterized standard module is established based on the dual objectives of ecological function and landscape benefits of aquatic plants. The parameterized standard module includes several ecological indicator standards and landscape indicator standards. Step 2: Construct a data fusion resource module and establish a multi-database linkage data fusion mechanism. The data fusion resource database includes a multi-dimensional database covering the ecological habits, purification efficiency, plant morphological characteristics, and economic costs of aquatic plants. Step 3: Build a scheme design module. The scheme design module is constructed according to the design process of "demand input - intelligent recommendation - scheme optimization - scheme output". It selects aquatic plants that meet the requirements from the parameterized standard module and the data fusion resource module to generate an aquatic plant configuration scheme.

[0007] This invention provides a parametric configuration design method for aquatic plants. By constructing a parametric standard module including ecological and landscape indicator standards, it can provide quantitative basis for the design and optimization of aquatic plant configuration schemes based on the dual objectives of ecological function and landscape benefits of aquatic plants. This enables precise design of aquatic plant configuration schemes, reducing reliance on human experience. Furthermore, by constructing a multi-dimensional database and employing a multi-database linkage data fusion mechanism, it can provide data support for design recommendation and optimization, achieving quantitative linkage between plant varieties, planting quantity, purification effect, landscape score, and cost. Simultaneously, through the algorithm design process of the scheme design module, it automatically matches plant varieties to obtain optimized combination structures, enabling the rapid acquisition of aquatic plant configuration schemes that balance ecological effectiveness and landscape value. This achieves a shift from "experience-driven" to "data-driven" precise design of aquatic plant configuration.

[0008] Preferably, in step 1, the ecological index standard includes several ecological parameter thresholds set for the water quality improvement target of the designed water body. The ecological parameter thresholds include basic water quality indicators and ecological efficiency indicators. The basic water quality indicators include pH value, dissolved oxygen content and ammonia nitrogen content. The ecological efficiency indicators include ammonia nitrogen removal rate of aquatic plants and dissolved oxygen increase.

[0009] Preferably, in step 1, the landscape index standards include quantitative evaluation standards for the spatial hierarchy, seasonal characteristics, and visual comfort of the landscape combination structure; the spatial hierarchy includes the vertical layer ratio of emergent plants, floating plants, and submerged plants; the seasonal characteristics include the duration of flowering period, the diversity of flower colors, and the rate of change of leaf color; and the visual comfort is evaluated based on the ratio of viewing distance to plant height.

[0010] Preferably, in step 2, the data fusion resource module includes a basic database, a purification efficiency database, a landscape evaluation database, and an economic cost database; The basic database includes morphological characteristics and ecological adaptability parameters of no less than 100 aquatic plants; The purification efficiency database includes a dynamic correlation model of "plant variety-planting quantity-purification effect". The dynamic correlation model includes single-variety purification parameters and combined purification coefficients. The single-variety purification parameters include the ammonia nitrogen removal rate and dissolved oxygen increase of each plant variety. The combined purification coefficient includes the purification parameter increase rate of multi-variety mixed planting relative to single-variety planting. The landscape evaluation database includes a quantitative correspondence between plant landscape characteristics and aesthetic scores, and includes plant combination rules and morphological characteristic parameters. The economic cost database includes real-time updated models of seedling prices, construction costs, and maintenance costs. Seedling prices include a market price list categorized by seedling height and crown width. Construction costs include transportation costs. The maintenance cost model includes formulas relating annual pruning, pest and disease control costs, and planting area. This enables a dynamic correlation between purification efficiency, landscape features, and economic costs, providing data support for an efficient design process.

[0011] Preferably, in step 3, the design process includes: Step 3.1, Requirements Input: Receive user input of design boundary conditions and break down design objectives. The design boundary conditions include water area, initial water quality parameters, landscape theme, and budget range. The design objectives include ecological objectives, landscape objectives, or economic objectives. Step 3.2, Intelligent Recommendation: Based on the initial water quality parameters and design objectives, calculate the minimum planting quantity and screen plants that meet the purification efficiency standards; and select aquatic plant varieties that meet the landscape index standards from the plants that meet the ecological efficiency standards. Step 3.3: Solution optimization: Determine the dominant combination from the aquatic plant species identified in Step 3.2. The dominant combination has ecological synergy advantages, landscape layering advantages, or economic advantages based on purification efficiency. Step 3.4: Solution Output: Output the quantitative report of the advantageous combination obtained in Step 3.3. The quantitative report includes a list of varieties, planting quantity, expected purification effect, landscape score and total cost.

[0012] Through an efficient design process, the corresponding selection, configuration, and cost calculation of plant varieties can be achieved, and aquatic plant configuration schemes that take into account both ecological effectiveness and landscape value can be generated quickly, thereby improving design efficiency.

[0013] Preferably, in step 3.2, the minimum planting quantity satisfies: .

[0014] Preferably, the method further includes step 4: constructing a dynamic feedback module. This module is designed to monitor water and plant growth data in real time during the maintenance period based on a dynamic feedback mechanism of "real-time monitoring - anomaly diagnosis - strategy optimization." When abnormal data is detected, it traces the source and recommends suitable plant varieties, calculates the amount of additional planting and / or replaces plant varieties, and dynamically adjusts the aquatic plant configuration scheme during the maintenance period. This dynamic feedback module enables the dynamic adjustment of the aquatic plant configuration scheme, achieving continuous optimization of ecological benefits.

[0015] Preferably, the real-time monitoring includes deploying a sensor system and a plant growth monitoring system to sample at a set sampling frequency; the anomaly diagnosis includes comparing real-time monitoring data with ecological parameter thresholds, and tracing the cause of abnormal data exceeding the thresholds; the strategy optimization includes calculating the amount of additional planting based on the purification efficiency target and adjusting the replacement varieties, wherein the amount of additional planting meets the following requirements: It can achieve rapid response to abnormalities during the maintenance period, solving the pain point of delayed repair in existing aquatic plant planting projects.

[0016] In a second aspect, the present invention provides a parametric configuration design system for aquatic plants, used in a parametric design method for ecological configuration of aquatic plants as described above. The system includes a parametric standard module, a data fusion resource module, and a scheme design module. The data fusion resource library includes a basic database, a purification efficiency database, a landscape evaluation database, and an economic cost database. The scheme design module is configured to select aquatic plants that meet the requirements from the parametric standard module and the data fusion resource module according to a design process of "demand input - intelligent recommendation - scheme optimization - scheme output," thereby generating an aquatic plant configuration scheme. This parametric configuration design system for aquatic plants, through the parametric standard module and the data fusion resource module, rapidly generates aquatic plant configuration schemes that balance ecological efficiency and landscape value according to a specific design process, achieving precise design and improving design efficiency.

[0017] Preferably, the system also includes a dynamic feedback module, which is configured to dynamically adjust the aquatic plant configuration scheme and continuously optimize ecological benefits based on a dynamic feedback mechanism of "real-time monitoring - anomaly diagnosis - strategy optimization." This achieves continuous optimization of ecological efficiency during the maintenance period and improves restoration efficiency.

[0018] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. This invention provides a parametric configuration design method for aquatic plants. By constructing a parametric standard module that includes ecological index standards and landscape index standards, it can provide quantitative basis for the design and optimization of the scheme based on the dual objectives of ecological function and landscape benefits of aquatic plants, realize the precise design of aquatic plant configuration schemes, and reduce the reliance on human experience. 2. This invention provides a parametric configuration design method for aquatic plants. By constructing a multi-dimensional database and adopting a multi-database linkage data fusion mechanism, it can provide data support for design recommendation and optimization, and realize the quantitative linkage of plant varieties, planting quantity, purification effect, landscape score and cost. 3. This invention provides a parametric configuration design method for aquatic plants. Through an algorithmic design process, it automatically matches plant varieties to obtain an optimized combination structure, which can quickly obtain aquatic plant configuration schemes that take into account both ecological effectiveness and landscape value, and realize the precise design of aquatic plant configuration from "experience-driven" to "data-driven". 4. This invention provides a parametric configuration design system for aquatic plants. Through a parametric standard module and a data fusion resource module, it can quickly generate aquatic plant configuration schemes that take into account both ecological effectiveness and landscape value according to a specific design process, thereby achieving precise design and improving design efficiency. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating a parametric configuration design method for aquatic plants, as shown in Example 1.

[0020] Figure 2 This is a schematic diagram of the data fusion resource module described in Example 1.

[0021] Figure 3 This is a schematic diagram of the dynamic feedback mechanism of the dynamic feedback module described in Example 1. Detailed Implementation

[0022] The present invention will now be described in further detail with reference to specific embodiments. However, this should not be construed as limiting the scope of the present invention to the following embodiments; all technologies implemented based on the content of the present invention fall within the scope of the present invention.

[0023] Unless otherwise specified, the terms "upper," "lower," "left," "right," "center," "inner," and "outer," etc., used in the description of specific embodiments of the present invention to indicate orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings, or the orientation or positional relationship in which the product / equipment / device is usually placed during use. These terms are merely for the purpose of facilitating the description of the present invention or simplifying the description in specific embodiments, and for enabling those skilled in the art to quickly understand the solution, and do not indicate or imply that a particular device / component / element must have a specific orientation, or be constructed and operated in a specific positional relationship. Therefore, they should not be construed as limitations on the present invention.

[0024] Furthermore, the use of terms such as "horizontal," "vertical," "suspended," "parallel," and "coaxial" does not imply that the corresponding device / component / element must be absolutely horizontal, vertical, suspended, parallel, or coaxial. Slight tilt or deviation is permissible, as long as it does not affect the normal function of the relevant component. For example, "horizontal" simply means that its direction is more horizontal relative to "vertical," not that the structure must be perfectly horizontal; a slight tilt is acceptable. "Coaxial" means that two components are arranged as coaxially as possible, allowing them to move coaxially or approximately coaxially when their relative positions change. Alternatively, it can be simplified to mean that the corresponding device / component / element, when arranged in "horizontal," "vertical," "suspended," "parallel," or "coaxial" directions, can have an error / deviation of ±10% relative to the corresponding direction, more preferably within ±8%, more preferably within ±6%, more preferably within ±5%, and more preferably within ±4%. For example, the deviation in the "coaxial" direction is controlled within 0.2-1mm, preferably within 0.2-0.5mm. As long as the corresponding device / component / element is within the error / deviation range, it can still achieve its function in the solution of the present invention.

[0025] Furthermore, the use of terms such as "first," "second," and "third" in terminology is merely for distinguishing descriptions of identical or similar components and should not be interpreted as emphasizing or implying the relative importance of a particular component.

[0026] Furthermore, in the description of the embodiments of the present invention, "several", "more than", and "a number of" represent at least two. The number can be any number, such as two, three, four, five, six, seven, eight, or nine, and can even exceed nine.

[0027] Furthermore, in the description of the technical solution of this invention, unless otherwise explicitly specified / limited / restricted, the terms "set up," "install," "connect," "link," "provided with," "laid out," and "arranged" should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to connection methods commonly used in the art, such as welding, riveting, bolting, and threaded connections. Such connections can be mechanical, electrical, or communication connections; they can be direct connections or indirect connections through an intermediate medium; and they can refer to the internal communication between two components.

[0028] Example 1 like Figures 1-3 As shown, a parametric configuration design method for aquatic plants includes the following steps: Step 1: Establish a parameterized standard module based on the dual objectives of ecological function and landscape benefits of aquatic plants. The parameterized standard module includes several ecological indicator standards and landscape indicator standards.

[0029] Step 1 is used to construct a parameterized standard module that includes ecological and landscape indicator standards. This module can provide quantitative basis for the design and optimization of the scheme based on the dual objectives of ecological function and landscape benefits of aquatic plants, realize the precise design of aquatic plant configuration schemes, reduce reliance on human experience, form reusable and verifiable design specifications, improve the matching degree between the scheme and actual ecological needs, and overcome the problems of existing design methods relying on human experience and lacking parameterized standards.

[0030] In an optional implementation, the ecological indicator standard includes several ecological parameter thresholds set for the water quality improvement target of the designed water body. The ecological parameter thresholds include basic water quality indicators and ecological efficiency indicators. The basic water quality indicators include pH value, dissolved oxygen content and ammonia nitrogen content, and the ecological efficiency indicators include ammonia nitrogen removal rate of aquatic plants and dissolved oxygen increase.

[0031] Specifically, ecological indicator standards can be based on the "Surface Water Environmental Quality Standard" (GB 3838-2002), and key ecological parameter thresholds can be set for the water quality improvement targets of the designed water bodies.

[0032] In optional implementations, landscape index standards include quantitative evaluation standards for the spatial hierarchy, seasonal characteristics, and visual comfort of the landscape composition structure. Spatial hierarchy includes the vertical layering ratio of emergent, floating, and submerged plants; seasonal characteristics include the duration of flowering, flower color diversity, and leaf color change rate; and visual comfort can be evaluated based on the ratio of viewing distance to plant height. These landscape index standards, by combining aesthetic principles, behavioral psychology, and landscape design specifications, establish quantitative evaluation standards for the landscape composition structure corresponding to aquatic plant configuration schemes.

[0033] Specifically, landscape design standards can be based on the "Standard for Basic Terminology of Landscape Architecture" (CJJ / T91-2017).

[0034] Step 2: Construct a data fusion resource module and establish a multi-database linkage data fusion mechanism. The data fusion resource database includes a multi-dimensional database covering the ecological habits, purification efficiency, plant morphological characteristics, and economic costs of aquatic plants.

[0035] Step 2 is used to build a multi-dimensional database. By adopting a multi-database linkage data fusion mechanism, it can provide data support for the design and optimization of aquatic plant configuration schemes, and realize the quantitative linkage of plant varieties, planting quantity, purification effect, landscape score, cost, etc.

[0036] In one or more implementations, the data fusion resource module includes a basic database, a purification efficiency database, a landscape evaluation database, and an economic cost database. Each database header is linked through software algorithms to achieve data association and fusion. For example, when "ammonia nitrogen target value" is input, the software algorithm can automatically call the purification efficiency database and the basic database to filter a list of plants that meet the corresponding ammonia nitrogen target value and are suitable for the design water landscape characteristics.

[0037] In an optional implementation, the basic database includes morphological characteristics and ecological adaptability parameters of no less than 100 common aquatic plants.

[0038] In an optional implementation, the purification efficiency database includes a dynamic correlation model of "plant variety-planting quantity-purification effect". The purification effect of the dynamic correlation model is quantified by single-variety purification parameters and combined purification coefficients. Single-variety purification parameters may include the ammonia nitrogen removal rate and dissolved oxygen increase of each plant variety, and combined purification coefficients may include the purification parameter increase rate of multi-variety mixed planting relative to single-variety planting.

[0039] In an optional implementation, the landscape evaluation database includes a quantified correspondence between plant landscape characteristics and aesthetic scores, and includes plant combination rules and morphological characteristic parameters. The correspondence between plant landscape characteristics and aesthetic scores can be quantified through a correlation table between flower color, leaf color and visual comfort scores, and between plant combination structure and spatial experience.

[0040] In an optional implementation, the economic cost database includes real-time updated models of seedling prices, construction costs, and maintenance costs. Seedling prices include a market price list categorized by seedling height and crown width. Construction costs include transportation costs. The maintenance cost model includes formulas relating annual pruning and pest control costs to planting area. This enables a dynamic correlation between purification efficiency, landscape features, and economic costs, providing data support for an efficient design process.

[0041] Step 3: Build the scheme design module. The scheme design module is constructed according to the design process of "demand input - intelligent recommendation - scheme optimization - scheme output". It selects aquatic plants that meet the requirements from the parameterized standard module and the data fusion resource module to generate an aquatic plant configuration scheme.

[0042] Step 3 is used to automatically match plant varieties and obtain the optimized combination structure of aquatic plant configuration schemes based on the parameterized standard module and data fusion resource module through the design process of software algorithm. It can quickly obtain aquatic plant configuration schemes that take into account both ecological efficiency and landscape value, realize the corresponding selection, configuration and cost calculation of plant varieties, and quickly generate the landscape combination structure of aquatic plant configuration schemes that take into account both ecological efficiency and landscape value, improve design efficiency, and realize the precise design of aquatic plant configuration from "experience-driven" to "data-driven".

[0043] In one or more implementations, the design process includes: Step 3.1, Requirements Input: Receive the design boundary conditions input by the user and break down the design objectives.

[0044] Specifically, step 3.1 may include step 3.1.1, accepting user input of design boundary conditions and design objectives. Design boundary conditions may include water area, initial water quality parameters, landscape theme, and budget range, etc.; step 3.1.2, decomposing design objectives. Design objectives may include ecological objectives, landscape objectives, or economic objectives. For example, ecological objectives may include water quality improvement objectives, which can be transformed into purification requirements for aquatic plants. Landscape themes can be mapped to corresponding landscape indicators.

[0045] Step 3.2, Intelligent Recommendation: Based on the initial water quality parameters and design objectives, calculate the minimum planting quantity, screen out plants that meet the purification efficiency standards, and select aquatic plant varieties that meet the landscape index standards from the plants that meet the ecological efficiency standards.

[0046] Specifically, step 3.2 may include step 3.2.1: Based on the initial water quality parameters and water quality improvement targets, calculate the minimum planting quantity, which satisfies the following: To obtain aquatic plant varieties that can meet ecological benefits with minimal planting quantity; Step 3.2.2: In conjunction with landscape index standards, select aquatic plant varieties that meet the requirements of flower color, flowering period and layering from the plants that meet the ecological efficiency standards, so as to obtain aquatic plant varieties that meet ecological efficiency and landscape theme, and initially determine the set of aquatic plant varieties that meet the current design goals.

[0047] Step 3.3: Solution optimization: Determine the dominant combination from the aquatic plant species identified in Step 3.2. The dominant combination has ecological synergy advantages, landscape layering advantages, or economic advantages based on purification efficiency.

[0048] Specifically, the aquatic plant varieties determined in step 3.2 can be ecologically optimized based on purification efficiency to obtain a combination of aquatic plant varieties with ecological synergy advantages. The landscape hierarchy of the aquatic plant varieties determined in step 3.2 can be optimized based on the plant combination ratio of the vertical structure of the combination to obtain a combination of aquatic plant varieties with landscape hierarchy advantages. The economic optimization of the combination can be achieved by calculating the total cost of different schemes of the aquatic plant variety combination determined in step 3.2 to obtain a combination of aquatic plant varieties with economic advantages.

[0049] Step 3.4: Solution Output: Output the quantitative report of the advantageous combination obtained in Step 3.3. The quantitative report may include a list of varieties, planting quantity, expected purification effect, landscape score and total cost.

[0050] In one or more embodiments, step 4 is further included: constructing a dynamic feedback module. This module is designed to monitor water and plant growth data in real time during the maintenance period based on a dynamic feedback mechanism of "real-time monitoring - anomaly diagnosis - strategy optimization." When abnormal data is detected, the module traces the source and recommends suitable plant varieties, calculates the amount of additional planting and / or replacement plant varieties, and dynamically adjusts the aquatic plant configuration scheme during the maintenance period. The dynamic feedback module enables dynamic adjustment of the aquatic plant configuration scheme, achieving continuous optimization of ecological benefits.

[0051] In optional implementations, real-time monitoring includes deploying sensor systems and plant growth monitoring systems to sample at a set sampling frequency; anomaly diagnosis includes comparing real-time monitoring data with ecological parameter thresholds and tracing the causes of abnormal data exceeding the thresholds; strategy optimization includes calculating the amount of additional planting based on the purification efficiency target and adjusting the replacement varieties, with the additional planting amount meeting the following requirements: It can achieve rapid response to anomalies during the maintenance period, quickly correlate and locate the causes of abnormal data, solve the pain point of delayed repair in existing aquatic plant planting projects, and ensure that landscape indicators continue to meet standards.

[0052] In an optional implementation, the sensor system may include several deployed pH sensors, dissolved oxygen sensors, and online ammonia nitrogen monitors. The sampling frequency may be set to once per day. The plant growth monitoring system may include on-site sampling records of vegetation coverage, growth images, or survival rates. The sampling record interval may be set according to actual conditions.

[0053] This embodiment presents a parametric configuration design method for aquatic plants. By constructing a parametric standard module, it establishes a quantitative coupling standard between ecology and landscape, which can solve the problem of the separation between ecology and landscape in traditional design. By constructing a dynamic, multi-dimensional database that includes the physiological characteristics of aquatic plants, water purification efficiency, landscape features, and economic costs, it achieves a dynamic correlation between "plant varieties - planting quantity - purification efficiency - landscape features - economic costs," upgrading data from "storage" to "decision support." Through a scheme design module, based on the parametric standard module and the multi-dimensional database, it automates the design process. Software algorithms automatically complete variety selection, ratio optimization, and cost calculation, quickly generating aquatic plant configuration schemes that meet both ecological function and landscape benefits. This can improve design efficiency by more than 60%. Furthermore, during the maintenance period, it combines sensor systems and plant growth monitoring systems to monitor water and plant growth data in real time, enabling rapid response to anomalies during the maintenance period (response time ≤ 24 hours). This allows for dynamic adjustment of the design scheme and continuous optimization of ecological benefits, effectively solving the pain point of "repair lag" in existing aquatic plant planting projects.

[0054] This embodiment illustrates a parametric configuration design method for aquatic plants, taking a core artificial water feature in a community park as an example. The designed water area is approximately 5000 m², with an average water depth of 1.2 m, and the landscape is positioned as an "urban ecological waterfront space".

[0055] Corresponding to step 1, with the dual objectives of ecological function and landscape benefits, and based on the "Surface Water Environmental Quality Standard" (GB3838-2002) and the "Basic Terminology Standard for Landscape Architecture" (CJJ / T 91-2017), a dedicated parameterized standard module for this artificial water feature was established, as shown in Table 1: Table 1. Data related to the parameterization standard module

[0056] Corresponding to step 2, a data fusion resource module is constructed, and a multi-database linkage data fusion mechanism is established. The data fusion resource module includes a basic database, a purification efficiency database, a landscape evaluation database, and an economic cost database.

[0057] The basic data and corresponding landscape evaluation data are shown in Table 2 below: Table 2. Relevant data from the basic database and the corresponding landscape evaluation database.

[0058] The purification efficiency data are shown in Table 3 below: Table 3. Relevant data from the purification efficiency database

[0059] The economic cost data for the corresponding local market price of artificial water features in a certain year are shown in Table 4 below: Table 4. Relevant data from the economic cost database

[0060] Corresponding to step 3, the scheme design module is built. The scheme design module follows the design process of "requirement input - intelligent recommendation - scheme optimization - scheme output". It selects aquatic plants that meet the requirements from the parameterized standard module and the data fusion resource module to generate an aquatic plant configuration scheme.

[0061] Corresponding to the requirements input in step 3.1, input the design boundary conditions, including a water feature area of ​​5000m², a water depth of 1.2m (volume of 6000m³), a landscape theme of "ecological waterfront + four-season landscape", and a total budget of 200,000 yuan; break down the design objectives, which include ecological objectives, landscape objectives, and economic objectives. Among them, the ecological objective is to reduce ammonia nitrogen from 0.8mg / L to 0.56mg / L within 90 days (total removal = 6000m³ × (0.8-0.56)mg / L = 1440g); the landscape objective is to ensure flowering coverage from May to December, with clear layers of emergent, floating, and submerged plants; the economic objective is that the total cost (seedlings + 1 year of maintenance) ≤ 150,000 yuan (with 50,000 yuan reserved for monitoring and emergency response).

[0062] In step 3.2, intelligent recommendation, the minimum planting quantity is calculated based on the initial water quality parameters and design objectives.

[0063] Specifically, in this embodiment, the purification task is allocated according to "40% emergent plants + 20% floating plants + 40% submerged plants". The minimum planting quantity for each type is calculated as follows: Minimum planting quantity = total purification requirement / (plant monthly purification rate × restoration cycle). Among them, emergent plants need to handle 1440g × 40% = 576g of purification, and the average monthly purification rate is taken as 0.09g / (m²). d)×30d=2.7g / (m² The repair cycle is 3 months, and the minimum planting volume is 576 / (2.7×3)=71.1m² (take 72m²); floating plants: need to bear 288g, and the monthly purification rate is 0.045g / (m²). d)×30=1.35g / (m² Minimum planting area (monthly): 288 / (1.35×3) = 71.1 m² (take 72 m²); Submerged plants: require a capacity of 576 g, monthly purification rate 0.07 g / (m²) d)×30=2.1g / (m² (Month), minimum planting area = 576 / (2.1×3) = 91.4m² (take 92m²).

[0064] Then, from the plant varieties that meet the purification efficiency standards, and in combination with the landscape index standards, a combination of aquatic plant varieties with flowering periods covering May to December was selected, excluding some varieties that wither in winter, resulting in a combination of cattail, sweet flag, canna lily, lotus, water lily, valerian, and whorled hydrilla verticillata.

[0065] Corresponding to step 3.3, determine the dominant combination from the aquatic plant varieties identified in step 3.2.

[0066] Specifically, in response to ecological synergistic optimization, the emergent layer can adopt the advantageous combination of "24m² of cattail, 24m² of calamus, and 24m² of canna lily, which increases the purification coefficient by 15% and the actual purification amount reaches 662g, exceeding the target by 15%"; the submerged layer can adopt the advantageous combination of "46m² of Vallisneria natans and 46m² of Hydrilla verticillata, which increases the purification coefficient by 20% and the actual purification amount reaches 691g".

[0067] Specifically, in order to optimize the landscape layers, emergent plants can be arranged along the shore at a water depth of 1-2m to form a staggered zone of 1-2.5m in height; floating plants can be arranged in a dotted pattern at a water depth of 2-3m with a coverage of 15% to avoid blocking the light of submerged plants; and submerged plants can be evenly arranged at a water depth of 3-5m with a coverage of 30%.

[0068] Specifically, based on economic optimization, the total cost calculation is: seedling cost (72×(30+50+25) / 3+72×(80+60) / 2 +92×(40+35) / 2)+1 year of maintenance (5000×5)=11010 yuan+25000 yuan=36010 yuan, which is far lower than the budget of 150,000 yuan.

[0069] Corresponding to step 3.4, the solution output is shown in Table 5 below: Table 5. Quantitative Report of Advantage Combinations

[0070] Corresponding to step 4, construct a dynamic feedback module to monitor water and plant growth data in real time during the maintenance period based on a dynamic feedback mechanism of "real-time monitoring - anomaly diagnosis - strategy optimization".

[0071] Specifically, a sensor system consisting of five pH / dissolved oxygen sensors (1 set / 1000m²) and two ammonia nitrogen online monitoring instruments is deployed to collect data in real time. The data is sampled once a day and transmitted to the management platform in real time. Images of vegetation growth are taken monthly, and on-site sampling is conducted quarterly (to measure survival rate and coverage). The duration of lotus flowering and the height of Vallisneria natans are recorded to monitor plant growth.

[0072] Specifically, on the 60th day of maintenance, the ammonia nitrogen concentration was monitored at 0.65 mg / L (below 0.56 mg / L), and the survival rate of Vallisneria natans was only 70% (lower than the expected 80%). Upon investigation, related data revealed that the coverage of floating plants reached 18% (15% over the design), resulting in insufficient light in the submerged layer (the measured light intensity was only 60% of the design value). This weakened the photosynthesis of Vallisneria natans and reduced the purification efficiency, necessitating the addition or replacement of planted varieties.

[0073] Specifically, the supplementary amount = current excess amount / (recommended plant purification rate × adjustment cycle). The calculated excess amount is 6000m³ × (0.65-0.56) mg / L = 540g. The adjustment plan is as follows: ① Reduce water lilies by 8m², reducing the floating water coverage to 15%; ② Supplement with 15m² of *Hydrilla verticillata* (purification rate 0.08g / (m²)). d) Adjustment cycle: 1 month), Supplementation amount = 540 / (0.08×30×1) = 225m². Correction: Based on the existing submerged layer, supplementing 15m² is sufficient (Hydrilla verticillata has better low light tolerance than Vallisneria natans); ③ Landscape compensation: The reduced water lilies are replaced with 5m² of duckweed (year-round coverage, low light requirement) to ensure seasonal continuity. Based on continuous real-time monitoring, after one month, the ammonia nitrogen content was monitored to drop to 0.51mg / L, the survival rate of Vallisneria natans rebounded to 78%, and the landscape coverage did not decrease, meeting the design requirements.

[0074] Example 2 like Figures 1-3 As shown, a parametric configuration design system for aquatic plants is used in the parametric design method for ecological configuration of aquatic plants in Example 1. The system includes a parametric standard module, a data fusion resource module, and a scheme design module. The data fusion resource library includes a basic database, a purification efficiency database, a landscape evaluation database, and an economic cost database. The scheme design module is constructed to select aquatic plants that meet the requirements from the parametric standard module and the data fusion resource module according to the design process of "demand input - intelligent recommendation - scheme optimization - scheme output", and generate an aquatic plant configuration scheme.

[0075] This embodiment of a parametric configuration design system for aquatic plants, through a parametric standard module and a data fusion resource module, can quickly generate aquatic plant configuration schemes that take into account both ecological effectiveness and landscape value according to a specific design process, thereby achieving design precision and improving design efficiency.

[0076] In one or more embodiments, a dynamic feedback module is also included. This module is configured to dynamically adjust the aquatic plant configuration scheme and continuously optimize ecological benefits based on a dynamic feedback mechanism of "real-time monitoring - anomaly diagnosis - strategy optimization." This achieves continuous optimization of ecological efficiency during the maintenance period and improves restoration efficiency.

[0077] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An aquatic plant parameterization configuration design method, characterized by, Includes the following steps: Step 1: Construct a parameterized standard module. The parameterized standard module is established based on the dual objectives of ecological function and landscape benefits of aquatic plants. The parameterized standard module includes several ecological indicator standards and landscape indicator standards. Step 2: Construct a data fusion resource module and establish a multi-database linkage data fusion mechanism. The data fusion resource database includes a multi-dimensional database covering the ecological habits, purification efficiency, plant morphological characteristics, and economic costs of aquatic plants. Step 3: Build a scheme design module. The scheme design module is constructed according to the design process of "demand input - intelligent recommendation - scheme optimization - scheme output". It selects aquatic plants that meet the requirements from the parameterized standard module and the data fusion resource module to generate an aquatic plant configuration scheme.

2. The method of claim 1, wherein, In step 1, the ecological indicator standard includes several ecological parameter thresholds set for the water quality improvement target of the designed water body. The ecological parameter thresholds include basic water quality indicators and ecological efficiency indicators. The basic water quality indicators include pH value, dissolved oxygen content and ammonia nitrogen content. The ecological efficiency indicators include ammonia nitrogen removal rate of aquatic plants and dissolved oxygen increase.

3. The parametric configuration design method for aquatic plants according to claim 1, characterized in that, In step 1, the landscape index standards include the spatial hierarchy of the landscape combination structure, seasonal characteristics, and quantitative evaluation standards for visual comfort; the spatial hierarchy includes the vertical layer ratio of emergent plants, floating plants, and submerged plants; the seasonal characteristics include the duration of flowering period, flower color diversity, and leaf color change rate; and the visual comfort is evaluated based on the ratio of viewing distance to plant height.

4. The parametric configuration design method for aquatic plants according to claim 1, characterized in that, In step 2, the data fusion resource module includes a basic database, a purification efficiency database, a landscape evaluation database, and an economic cost database; The basic database includes morphological characteristics and ecological adaptability parameters of no less than 100 aquatic plants; The purification efficiency database includes a dynamic correlation model of "plant variety-planting quantity-purification effect". The dynamic correlation model includes single-variety purification parameters and combined purification coefficients. The single-variety purification parameters include the ammonia nitrogen removal rate and dissolved oxygen increase of each plant variety. The combined purification coefficient includes the purification parameter increase rate of multi-variety mixed planting relative to single-variety planting. The landscape evaluation database includes a quantitative correspondence between plant landscape characteristics and aesthetic scores, and includes plant combination rules and morphological characteristic parameters. The economic cost database includes real-time updated seedling prices, construction costs, and maintenance cost models. The seedling prices include a market price list for seedlings categorized by height and crown width. The construction costs include transportation costs. The maintenance cost model includes a formula relating annual pruning and pest control costs to the planting area.

5. The parametric configuration design method for aquatic plants according to claim 1, characterized in that, Step 3, the design process specifically includes: Step 3.1, Requirements Input: Receive user input of design boundary conditions and break down design objectives. The design boundary conditions include water area, initial water quality parameters, landscape theme, and budget range. The design objectives include ecological objectives, landscape objectives, or economic objectives. Step 3.2, Intelligent Recommendation: Based on the initial water quality parameters and design objectives, calculate the minimum planting quantity and screen plants that meet the purification efficiency standards; and select aquatic plant varieties that meet the landscape index standards from the plants that meet the ecological efficiency standards. Step 3.3: Solution optimization: Determine the dominant combination from the aquatic plant species identified in Step 3.

2. The dominant combination has ecological synergy advantages, landscape layering advantages, or economic advantages based on purification efficiency. Step 3.4: Solution Output: Output the quantitative report of the advantageous combination obtained in Step 3.

3. The quantitative report includes a list of varieties, planting quantity, expected purification effect, landscape score and total cost.

6. The parametric configuration design method for aquatic plants according to claim 5, characterized in that, In step 3.2, the minimum planting quantity must meet the following requirements: .

7. A parametric configuration design method for aquatic plants according to any one of claims 1-6, characterized in that, It also includes step 4, constructing a dynamic feedback module. The dynamic feedback module is constructed to monitor the water and plant growth data in real time during the maintenance period based on a dynamic feedback mechanism of "real-time monitoring-anomaly diagnosis-strategy optimization". When abnormal data is detected, it traces the source and recommends suitable plant varieties, calculates the amount of additional planting and / or the replacement of plant varieties, and dynamically adjusts the aquatic plant configuration scheme during the maintenance period.

8. The parametric configuration design method for aquatic plants according to claim 7, characterized in that, The real-time monitoring includes deploying a sensor system and a plant growth monitoring system to sample at a set sampling frequency; the anomaly diagnosis includes comparing real-time monitoring data with ecological parameter thresholds and tracing the cause of abnormal data exceeding the thresholds; the strategy optimization includes calculating the amount of additional planting based on the purification efficiency target and adjusting the replacement varieties, with the additional planting amount meeting the following requirements: .

9. A parametric configuration design system for aquatic plants, characterized in that, A parametric design method for ecological configuration of aquatic plants according to any one of claims 1-8 includes a parametric standard module, a data fusion resource module, and a scheme design module. The data fusion resource module includes a basic database, a purification efficiency database, a landscape evaluation database, and an economic cost database. The scheme design module is configured to select aquatic plants that meet the requirements from the parametric standard module and the data fusion resource module according to the design process of "demand input - intelligent recommendation - scheme optimization - scheme output" to generate an aquatic plant configuration scheme.

10. A parametric configuration design system for aquatic plants according to claim 9, characterized in that, It also includes a dynamic feedback module, which is configured to dynamically adjust the aquatic plant configuration scheme and continuously optimize the ecological benefits based on a dynamic feedback mechanism of "real-time monitoring-anomaly diagnosis-strategy optimization".

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