Method and device for determining submerged plant distribution scheme, computer equipment and medium

Abstract

The present application relates to the technical field of ecological restoration, and discloses a submerged plant distribution scheme determination method and device, computer equipment and a medium. The method is based on environmental information of a target water area and environmental parameters of different types of submerged plants in the target water area to solve a submerged plant distribution probability model, obtain a first distribution probability of each type of submerged plant, and determine a distribution scheme of different types of submerged plants in the target water area based on the first distribution probability corresponding to each type of submerged plant. The method provided by the present application considers the adaptability of different types of submerged plants to the environment of the target water area when determining the distribution scheme of the submerged plants in the target water area. Based on the obtained distribution scheme, the submerged plants can be planted in the target water area, which can make the distribution of the submerged plants more adaptive to the environment of the target water area, effectively reduce the dramatic succession of the submerged plant community in the ecological restoration project, and make the water ecological restoration more natural and long-acting.

Description

Technical Field

[0001] This invention relates to the field of ecological restoration technology, specifically to a method, apparatus, computer equipment, and medium for determining the distribution scheme of submerged plants. Background Technology

[0002] Aquatic ecology refers to the impact of environmental water factors on organisms and the adaptation of organisms to various water conditions. Water is the origin of all life, and the life activities of any organism cannot be separated from water. Therefore, in order to protect the environment and maintain biodiversity, aquatic ecosystems are usually restored. In existing aquatic ecosystem restoration projects, submerged plants are planted in water bodies to reduce eutrophication and create diverse habitats for other aquatic organisms, thereby improving biodiversity. However, existing schemes generally rely on human experience when planting submerged plants, without considering the compatibility of the plant species with the corresponding aquatic environment. This results in severe succession phenomena in the planted submerged plant communities, leading to poor aquatic ecosystem restoration effects. Summary of the Invention

[0003] In view of this, the present invention provides a method, apparatus, computer equipment and medium for determining the distribution scheme of submerged plants, in order to solve the serious problem of the succession phenomenon of submerged plant communities planted by human experience in related water ecological restoration projects.

[0004] In a first aspect, the present invention provides a method for determining the distribution scheme of submerged plants. The method includes: acquiring information on different types of submerged plants and environmental information of the target water area; extracting environmental parameters corresponding to different types of submerged plants from a pre-constructed submerged plant functional database; solving a pre-constructed submerged plant distribution probability model based on the environmental parameters corresponding to different types of submerged plants and the environmental information of the target water area to obtain the first distribution probability information of each type of submerged plant, wherein the submerged plant distribution probability model is used to characterize the correlation information between the distribution probability of submerged plants and the corresponding environmental parameters and the environmental information of the target water area; and determining the distribution scheme of different types of submerged plants in the target water area based on the first distribution probability information corresponding to different types of submerged plants.

[0005] The method for determining the distribution scheme of submerged plants provided by this invention solves the distribution probability model of submerged plants based on the environmental information of the target water area and the environmental parameters of different types of submerged plants in the target water area, obtaining the first distribution probability of each type of submerged plant. Based on the first distribution probabilities corresponding to different types of submerged plants, the distribution scheme of different types of submerged plants in the target water area is determined. The scheme provided by this invention considers the adaptability of different types of submerged plants to the target water area environment when determining the distribution scheme of submerged plants in the target water area. Based on the environmental parameters of different types of submerged plants and the environmental information of the target water area, the distribution probabilities corresponding to different types of submerged plants are determined, and then the distribution scheme of different types of submerged plants in the target water area is determined. Planting submerged plants in the target water area based on the obtained distribution scheme can make the distribution of submerged plants more adaptable to the environment of the target water area, effectively reduce the drastic succession of submerged plant communities in ecological restoration projects, and make the water ecological restoration more natural and long-term.

[0006] In one optional implementation, the environmental information of the target water area includes water temperature information, water quality information, and water depth information, and the environmental parameters include water temperature parameters, water quality parameters, and water depth parameters.

[0007] The method provided by this optional implementation method can make the distribution pattern of different types of submerged plants in the target water area more accurate.

[0008] In one optional implementation, the submerged plant distribution probability model includes a first relation, a second relation, and a third relation. The step of solving the pre-constructed submerged plant distribution probability model based on environmental parameters corresponding to different types of submerged plants and environmental information of the target water area to obtain the first distribution probability information for each type of submerged plant includes: solving the pre-constructed first relation based on water temperature parameters and water temperature information for each type of submerged plant to obtain the second distribution probability information for each type of submerged plant. The first relation is used to characterize the correlation between the distribution probability of submerged plants and the water temperature of the water area and the water temperature parameters of the submerged plants; and solving the second relation based on water quality parameters and water quality information for each type of submerged plant... Solving the pre-constructed second relation yields the third distribution probability information corresponding to different types of submerged plants. The second relation characterizes the correlation between the distribution probability of submerged plants and the water quality and water quality parameters of the submerged plants. Solving the pre-constructed third relation based on the water depth parameters and water depth information of each type of submerged plant yields the fourth distribution probability information corresponding to different types of submerged plants. The second relation characterizes the correlation between the distribution probability of submerged plants and the water quality and water depth parameters of the submerged plants. Based on the second, third, and fourth distribution probability information of each type of submerged plant, the first distribution probability information corresponding to each type of submerged plant is determined.

[0009] In one alternative implementation, the first relation is:

[0010]

[0011] Among them, P i,T μ represents the first probability distribution information of submerged plant i. i,T σ represents the optimal temperature for submerged plant i. i，T x represents the variance of the temperature distribution of submerged plants. T This indicates the temperature of the target water body.

[0012] In one alternative implementation, the second relation is:

[0013]

[0014] Among them, P i，Nut σ represents the second probability distribution information of submerged plant i. i，N σ represents the variance of the total nitrogen concentration distribution of submerged plant i. i，P x represents the variance of the total phosphorus concentration distribution of submerged plant i. N x represents the total nitrogen concentration in the target water area. P The total phosphorus concentration in the target water body is expressed in μ. i，N This represents the optimal total nitrogen concentration (μ) for submerged plant i. i，P This indicates the optimal total phosphorus concentration for submerged plants.

[0015] In one alternative implementation, the third relation is:

[0016]

[0017] Among them, P i，Z σ represents the third probability distribution information of submerged plant i. i，Z μ represents the variance of the distribution of submerged plant i with respect to water depth. i，Z Indicates the optimal water depth for submerged plant i, x Z Indicates the water depth of the target area.

[0018] In one optional implementation, the step of determining the distribution scheme of different types of submerged plants in the target water area based on the first distribution probability information corresponding to different submerged plants includes: obtaining a preset submerged plant probability distribution threshold; and determining the distribution scheme of different types of submerged plants in the target water area based on the preset submerged plant probability distribution threshold and the first distribution probability information of various types of submerged plants.

[0019] The method provided in this optional embodiment determines the distribution pattern of different types of submerged plants in the target water area based on the distribution threshold and the first distribution probability information of various types of submerged plants, which can make the determination of the distribution pattern more accurate.

[0020] Secondly, the present invention provides a device for determining the distribution scheme of submerged plants. The device includes: an acquisition module for acquiring information on different types of submerged plants in a target water area and environmental information of the target water area; an extraction module for extracting environmental parameters corresponding to different types of submerged plants from a pre-constructed submerged plant functional database; a solution module for solving a pre-constructed submerged plant distribution probability model based on the environmental parameters corresponding to different types of submerged plants and the environmental information of the target water area to obtain first distribution probability information for each type of submerged plant, wherein the submerged plant distribution probability model is used to characterize the correlation information between the distribution probability of submerged plants and the corresponding environmental parameters and the environmental information of the target water area; and a determination module for determining the distribution scheme of different types of submerged plants in the target water area based on the first distribution probability information corresponding to different types of submerged plants.

[0021] In one optional implementation, the environmental information of the target water area includes water temperature information, water quality information, and water depth information, and the environmental parameters include water temperature parameters, water quality parameters, and water depth parameters.

[0022] In one optional implementation, the solution model includes: a first solution unit, used to solve a pre-constructed first relational expression based on water temperature parameters and water temperature information of various types of submerged plants, to obtain second distribution probability information corresponding to different types of submerged plants, wherein the first relational expression is used to characterize the correlation between the distribution probability of submerged plants and the water temperature of the water body and the water temperature parameters of the submerged plants; and a second solution unit, used to solve the pre-constructed second relational expression based on water quality parameters and water quality information of various types of submerged plants, to obtain third distribution probability information corresponding to different types of submerged plants, wherein the second relational expression is used to characterize the distribution probability of submerged plants and the water temperature parameters of the water body. The first unit is used to determine the first distribution probability information corresponding to different types of submerged plants based on the second, third, and fourth distribution probability information of various types of submerged plants. The second unit is used to characterize the relationship between the distribution probability of submerged plants and the water quality and water depth parameters of submerged plants. The third unit is used to determine the first distribution probability information corresponding to different types of submerged plants based on the second, third, and fourth distribution probability information of various types of submerged plants.

[0023] In one alternative implementation, the first relation is:

[0024]

[0025] Among them, P i，T μ represents the first probability distribution information of submerged plant i. i，T σ represents the optimal temperature for submerged plant i. i，T x represents the variance of the temperature distribution of submerged plants. T This indicates the temperature of the target water body.

[0026] In one alternative implementation, the second relation is:

[0027]

[0028] Among them, P i，Nut σ represents the second probability distribution information of submerged plant i. i，N σ represents the variance of the total nitrogen concentration distribution of submerged plant i. i，P x represents the variance of the total phosphorus concentration distribution of submerged plant i. N x represents the total nitrogen concentration in the target water area. P The total phosphorus concentration in the target water body is expressed in μ. i，N This represents the optimal total nitrogen concentration (μ) for submerged plant i. i，P This indicates the optimal total phosphorus concentration for submerged plants.

[0029] In one alternative implementation, the third relation is:

[0030]

[0031] Among them, P i，Z σ represents the third probability distribution information of submerged plant f. i，Z μ represents the variance of the distribution of submerged plant i with respect to water depth. i，Z Indicates the optimal water depth for submerged plant i, x Z Indicates the water depth of the target area.

[0032] Thirdly, the present invention provides a computer device, comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the computer instructions to perform the method for determining the distribution scheme of submerged plants described in the first aspect or any corresponding embodiment.

[0033] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the method for determining the distribution scheme of submerged plants according to the first aspect or any corresponding embodiment described above. Attached Figure Description

[0034] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0035] Figure 1 This is a flowchart illustrating a method for determining the distribution scheme of submerged plants according to an embodiment of the present invention.

[0036] Figure 2 This is a flowchart illustrating another method for determining the distribution scheme of submerged plants according to an embodiment of the present invention;

[0037] Figure 3 This is a schematic diagram illustrating the distribution probability of various submerged plants according to an embodiment of the present invention;

[0038] Figure 4 This is a structural block diagram of a device for determining the distribution scheme of submerged plants according to an embodiment of the present invention;

[0039] Figure 5 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0041] In aquatic ecological restoration projects, planting submerged plants in water bodies reduces eutrophication and creates diverse habitats for other aquatic organisms, thereby increasing biodiversity. However, in related technologies, the planting of submerged plants is generally based on human experience without considering the compatibility of the plant species with the corresponding aquatic environment. This leads to severe succession phenomena in the planted submerged plant communities, resulting in poor aquatic ecological restoration effects.

[0042] In view of this, the method for determining the distribution scheme of submerged plants provided by the embodiments of the present invention can be applied to a processor for execution to determine the distribution scheme of aquatic plants. The method provided by the embodiments of the invention considers the adaptability of different types of submerged plants to the target water environment when determining the distribution scheme of submerged plants in the target water area. Based on the environmental parameters of different types of submerged plants and the environmental information of the target water area, the distribution probability corresponding to different types of submerged plants is determined, thereby determining the distribution scheme of different types of submerged plants in the target water area. Planting submerged plants in the target water area based on the obtained distribution scheme can make the distribution of submerged plants more adaptable to the environment of the target water area, effectively reduce the community succession phenomenon of submerged plants, and improve the aquatic ecological restoration effect.

[0043] According to an embodiment of the present invention, a method for determining the distribution scheme of submerged plants is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0044] This embodiment provides a method for determining the distribution pattern of submerged plants, which can be used in the aforementioned processor. Figure 1 This is a flowchart of a method for determining the distribution scheme of submerged plants according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps:

[0045] Step S101: Obtain information on different types of submerged plants in the target water area and environmental information of the target water area.

[0046] For example, the target water area can be any water area where the distribution scheme of submerged plants is to be determined. In this embodiment of the application, the target water area can be a 10m×10m water area along the shore of an urban lake in a certain area. The environmental information of the target water area may include, but is not limited to, the water depth distribution, water temperature distribution, and water quality information within the target water area. During the construction period, the water temperature of the target water area is 25℃, the total nitrogen (TN) concentration is 4mg / L, the total phosphorus (TP) concentration is 1.2mg / L, and the water depth is 0-3m. The native species of the target water area include *Vallisneria natans*, *Potamogeton malaianus*, *Potamogeton microdentatum*, *Gnaphalium affine*, *Ceratophyllum demersum*, and *Myriophyllum spicatum*.

[0047] Step S102: Extract the environmental parameters corresponding to different types of submerged plants from the pre-constructed submerged plant functional database.

[0048] For example, the submerged plant functional database includes the names of submerged plants, descriptions of their functional characteristics, suitable water quality ranges, suitable water depth ranges, and suitable growth temperatures. Based on information about different types of submerged plants in the target water area, environmental parameters corresponding to different types of submerged plants can be extracted from the submerged plant functional database. In this embodiment, the environmental parameters of submerged plants may include, but are not limited to, information about the optimal living environment of the submerged plant and information about the distribution patterns of the plant under different environments. Based on information about different types of submerged plants, functional characteristic information of *Vallisneria natans*, *Potamogeton malaianus*, *Potamogeton microdentatum*, *Gnaphalium affine*, *Ceratophyllum demersum*, and *Myriophyllum spicatum* is extracted from the submerged plant functional database.

[0049] Step S103: Solve the pre-constructed submerged plant distribution probability model based on the environmental parameters corresponding to different types of submerged plants and the environmental information of the target water area to obtain the first distribution probability information of each type of submerged plant. The submerged plant distribution probability model is used to characterize the correlation between the distribution probability of submerged plants and the corresponding environmental parameters and the environmental information of the target water area.

[0050] For example, in this embodiment of the application, the environmental parameters of different submerged plants and the environmental information of the target water area are substituted into the submerged plant distribution model to solve the problem, so as to obtain the first distribution probability information corresponding to different types of submerged plants. The first distribution probability information is used to characterize the distribution probability information of the corresponding type of submerged plant in the target water area.

[0051] Step S104: Determine the distribution scheme of different types of submerged plants in the target water area based on the first distribution probability information corresponding to different submerged plants.

[0052] For example, based on the first distribution probability corresponding to different types of submerged plants, the distribution of different types of submerged plants in the target water area can be determined. For example, the planting amount of different types of submerged plants can be determined by the magnitude of the first distribution probability, and then the distribution plan can be determined.

[0053] The method for determining the distribution scheme of submerged plants provided in this embodiment solves the distribution probability model of submerged plants based on the environmental information of the target water area and the environmental parameters of different types of submerged plants in the target water area. This yields the first distribution probability for each type of submerged plant, and based on the first distribution probabilities corresponding to different types of submerged plants, the distribution scheme of different types of submerged plants in the target water area is determined. The solution provided by this invention considers the adaptability of different types of submerged plants to the target water area environment when determining the distribution scheme. Based on the environmental parameters of different types of submerged plants and the environmental information of the target water area, the distribution probabilities corresponding to different types of submerged plants are determined, thereby determining the distribution scheme of different types of submerged plants in the target water area. Planting submerged plants in the target water area based on the obtained distribution scheme can make the distribution of submerged plants more adaptable to the environment of the target water area, effectively reducing the drastic succession phenomenon of submerged plant communities in ecological restoration projects, making the water ecological restoration more natural and long-term.

[0054] This embodiment provides a method for determining the distribution pattern of submerged plants, which can be used in the aforementioned processor. Figure 2 This is a flowchart of a method for determining the distribution scheme of submerged plants according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps:

[0055] Step S201: Obtain information on different types of submerged plants and environmental information of the target water area. For details, please refer to [link to relevant documentation]. Figure 1 Step S101 of the illustrated embodiment will not be described again here.

[0056] Step S202: Extract environmental parameters corresponding to different species of submerged plants from the pre-constructed submerged plant functional database. For details, please refer to [link to relevant documentation]. Figure 1 Step S102 of the illustrated embodiment will not be described again here.

[0057] Step S203: Based on the environmental parameters corresponding to different types of submerged plants and the environmental information of the target water area, the pre-constructed submerged plant distribution probability model is solved to obtain the first distribution probability information for each type of submerged plant. The submerged plant distribution probability model is used to characterize the correlation between the distribution probability of submerged plants and the corresponding environmental parameters and the environmental information of the target water area. For details, please refer to... Figure 1 Step S103 of the illustrated embodiment will not be described again here.

[0058] In some alternative implementations, the environmental information of the target water area includes water temperature information, water quality information, and water depth information, and the environmental parameters include water temperature parameters, water quality parameters, and water depth parameters.

[0059] Specifically, the probability model for the distribution of submerged plants includes a first relation, a second relation, and a third relation, and step S203 above includes:

[0060] Step S2031: Solve the pre-constructed first relational expression based on the water temperature parameters and water temperature information of various types of submerged plants to obtain the second distribution probability information corresponding to different types of submerged plants. The first relational expression is used to characterize the correlation between the distribution probability of submerged plants and the water temperature of the water body and the water temperature parameters of submerged plants.

[0061] For example, in the embodiments of this application, the water temperature parameters may include, but are not limited to, the optimal growth temperature of submerged plants and the distribution variance of submerged plants at different temperatures; the water temperature parameters of various types of submerged plants and the water temperature information of the target water area are substituted into the first relational formula to solve for the second distribution probability information of different types of submerged plants in the target water area when considering the influence of water temperature.

[0062] Step S2032: Solve the pre-constructed second relation based on the water quality parameters and water quality information of various types of submerged plants to obtain the third distribution probability information corresponding to different types of submerged plants. The second relation is used to characterize the correlation between the distribution probability of submerged plants and the water quality of the water area and the water quality parameters of submerged plants.

[0063] For example, in the embodiments of this application, the water quality parameters may include, but are not limited to, the optimal water quality for the growth of submerged plants and the distribution variance of submerged plants under different water qualities; the water quality parameters of various types of submerged plants and the water quality information of the target water area are substituted into the second relational expression to obtain the third distribution probability information of different types of submerged plants in the target water area when considering the influencing factors of water quality.

[0064] Step S2033: Solve the pre-constructed third relation based on the water depth parameters and water depth information of various types of submerged plants to obtain the fourth distribution probability information corresponding to different types of submerged plants. The second relation is used to characterize the correlation between the distribution probability of submerged plants and the water quality and water depth parameters of submerged plants.

[0065] For example, in the embodiments of this application, the water depth parameters may include, but are not limited to, the optimal growth water depth of submerged plants and the distribution variance of submerged plants at different water depths; the water depth parameters of various types of submerged plants and the water depth information of the target water area are substituted into the second relational expression to obtain the third distribution probability information of different types of submerged plants in the target water area when considering the influence of water depth.

[0066] Step S2034: Based on the second, third, and fourth distribution probability information of various types of submerged plants, determine the first distribution probability information corresponding to each type of submerged plant.

[0067] For example, in the embodiments of this application, the first distribution probability information corresponding to different types of submerged plants can be determined by the following formula:

[0068] P i =P i，T P i，Nut P i，Z

[0069] Where i represents the type of submerged plant, P i P represents the first probability distribution information of plant i. i，T P represents the second probability distribution information of submerged plant i. i，Nut P represents the third probability distribution information of submerged plant i. i，Z This represents the fourth probability distribution information for submerged plant i.

[0070] In some alternative implementations, the first relation is:

[0071]

[0072] Among them, P i，T μ represents the first probability distribution information of submerged plant i. i，T σ represents the optimal temperature for submerged plant i. i，T x represents the variance of the temperature distribution of submerged plants. T This indicates the temperature of the target water body.

[0073] In some alternative implementations, the second relation is:

[0074]

[0075] Among them, P i，Nut σ represents the second probability distribution information of submerged plant i. i，N σ represents the variance of the total nitrogen concentration distribution of submerged plant i. i，P x represents the variance of the total phosphorus concentration distribution of submerged plant i. N x represents the total nitrogen concentration in the target water area. P The total phosphorus concentration in the target water body is expressed in μ. i，N This represents the optimal total nitrogen concentration (μ) for submerged plant i. i，P This indicates the optimal total phosphorus concentration for submerged plants.

[0076] In some alternative implementations, the third relation is:

[0077]

[0078] Among them, P i，Z σ represents the third probability distribution information of submerged plant i. i，Z μ represents the variance of the distribution of submerged plant i with respect to water depth. i，Z Indicates the optimal water depth for submerged plant i, x Z Indicates the water depth of the target area.

[0079] Step S204: Determine the distribution scheme of different types of submerged plants in the target water area based on the first distribution probability information corresponding to different submerged plants. For details, please refer to [link to details]. Figure 1 Step S104 of the illustrated embodiment will not be described again here.

[0080] Specifically, step S204 includes:

[0081] Step S2041: Obtain the preset probability distribution threshold for submerged plants.

[0082] For example, in the embodiments of this application, the preset submerged plant distribution threshold may include, but is not limited to, 0.5.

[0083] Step S2042: Determine the distribution scheme of different types of submerged plants in the target water area based on the preset probability distribution threshold of submerged plants and the first distribution probability information of various types of submerged plants.

[0084] For example, in this embodiment of the application, the distribution scheme of different types of submerged plants is determined based on the first distribution probability information of different types of submerged plants and the preset submerged plant probability distribution threshold. For example, when the first distribution probability of a certain type of submerged plant is less than the preset threshold, the submerged plant of that type will not be planted in the corresponding location of the target water area.

[0085] The following specific embodiment illustrates the method for determining the distribution scheme of submerged plants provided by the present invention.

[0086] Example:

[0087] The distribution plan for submerged plants is determined through the following steps:

[0088] 1. Construction of a functional database for submerged plants: The functional database for submerged plants should include the names of submerged plants, descriptions of their functional characteristics, suitable water quality ranges for growth, suitable water depth ranges for growth, and suitable growth temperatures;

[0089] 2. Collection and organization of on-site data for project implementation: The selected area is a 10m×10m water area along the shore of an urban lake in a certain city, where submerged plant diversity will be constructed. During the construction period, the water temperature at this location is 25℃, the TN concentration is 4mg / L, the TP concentration is 1.2mg / L, and the water depth is 0-3m. The native species in this area include Vallisneria natans, Potamogeton malaianus, Potamogeton microdentatum, Gorgonium truncatum, Ceratophyllum demersum, and Myriophyllum spicatum.

[0090] 3. Screening of submerged plants: Functional characteristics of submerged plants such as Vallisneria natans, Potamogeton malaianus, Potamogeton microdentatum, Euphorbia tirucalli, Ceratophyllum demersum, and Myriophyllum spicatum were obtained from the submerged plant database. Based on the judgment, all of them can meet the planting requirements of this area.

[0091] 4. Construct a submerged plant ecological niche model and calculate the distribution probability of submerged plants based on site conditions:

[0092] Based on the selected plants *Vallisneria natans*, *Potamogeton malaianus*, *Potamogeton microdentatum*, *Gnaphalium affine*, *Ceratophyllum demersum*, and *Myriophyllum spicatum* in this embodiment, distribution models for temperature, total nitrogen concentration, total phosphorus concentration, and water depth under the implementation scenario were constructed based on normal distribution. The distribution probabilities of each type of submerged plant were calculated. The parameter values ​​used in this embodiment are shown in Table 1.

[0093] Table 1

[0094]

[0095] Based on the calculated distribution probability of submerged plants along the spatial distribution, an appropriate distribution probability threshold is selected. In this scheme, a distribution probability threshold P>0.5 is chosen, allowing the application of this type of submerged plant in the design. Finally, a distribution probability map of submerged plants is obtained, and the submerged plant design is carried out accordingly. Note that if more than two types of submerged plants meet the distribution probability requirements in the same area, they should be mixed and planted in the corresponding area. This is to simulate the coexistence and growth of plant diversity in nature. The distribution probabilities of each submerged plant obtained based on the calculation results are as follows: Figure 3 As shown.

[0096] Based on the above calculations, this plan designs *Snapdragon* and *Vallisneria natans* in areas less than 3.2m from the shore; *Ceratophyllum demersum*, *Vallisneria natans*, *Gnaphalium affine*, *Myriophyllum spicatum*, and *Potamogeton pectinatus* in the range of 3.2–7.1m from the shore; and *Myriophyllum spicatum* and *Potamogeton pectinatus* in the range of 7.1–10m from the shore. According to the calculations, *Potamogeton pectinatus* is not suitable for planting in this area. Since the calculations show that at least two submerged plant species meet the distribution probability requirements in each area, this plan, in addition to planting different species of submerged plants according to the calculations, should mix and plant different submerged plant species in the corresponding areas. This is to simulate the coexistence and growth of plant diversity in nature. Based on the submerged plant planting density requirements, a planting density of 20 clumps / m² is selected, and the selected species are evenly distributed and mixed.

[0097] This embodiment also provides a device for determining the distribution scheme of submerged plants. This device is used to implement the above embodiments and preferred embodiments, and details already described will not be repeated. As used below, the term "module" can be a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0098] This embodiment provides a device for determining the distribution pattern of submerged plants, such as... Figure 4 As shown, it includes:

[0099] The acquisition module 401 is used to acquire information on different types of submerged plants in the target water area and environmental information of the target water area;

[0100] Extraction module 402 is used to extract environmental parameters corresponding to different types of submerged plants from a pre-constructed submerged plant functional database;

[0101] The solver module 403 is used to solve the pre-constructed submerged plant distribution probability model based on the environmental parameters corresponding to different types of submerged plants and the environmental information of the target water area, to obtain the first distribution probability information of each type of submerged plant. The submerged plant distribution probability model is used to characterize the correlation information between the distribution probability of submerged plants and the corresponding environmental parameters and the environmental information of the target water area.

[0102] The determination module 404 is used to determine the distribution scheme of different types of submerged plants in the target water area based on the first distribution probability information corresponding to different submerged plants.

[0103] In some alternative implementations, the environmental information of the target water area includes water temperature information, water quality information, and water depth information, and the environmental parameters include water temperature parameters, water quality parameters, and water depth parameters.

[0104] In some alternative implementations, the solution model 403 includes:

[0105] The first solving unit is used to solve the pre-constructed first relational formula based on the water temperature parameters and water temperature information of various types of submerged plants, and obtain the second distribution probability information corresponding to different types of submerged plants. The first relational formula is used to characterize the relationship between the distribution probability of submerged plants and the water temperature of the water body and the water temperature parameters of submerged plants.

[0106] The second solution unit is used to solve the pre-constructed second relation based on the water quality parameters and water quality information of various types of submerged plants, and obtain the third distribution probability information corresponding to different types of submerged plants. The second relation is used to characterize the correlation between the distribution probability of submerged plants and the water quality of the water area and the water quality parameters of submerged plants.

[0107] The third solution unit is used to solve the pre-constructed third relation based on the water depth parameters and water depth information of various types of submerged plants, and obtain the fourth distribution probability information corresponding to different types of submerged plants. The second relation is used to characterize the relationship between the distribution probability of submerged plants and the water quality and water depth parameters of submerged plants.

[0108] The first determining unit is used to determine the first distribution probability information corresponding to different types of submerged plants based on the second, third, and fourth distribution probability information of various types of submerged plants.

[0109] In some alternative implementations, the first relation is:

[0110]

[0111] Among them, P i，T μ represents the first probability distribution information of submerged plant i. i，T σ represents the optimal temperature for submerged plant i. i，T x represents the variance of the temperature distribution of submerged plants. T This indicates the temperature of the target water body.

[0112] In some alternative implementations, the second relation is:

[0113]

[0114] Among them, P i，Nut σ represents the second probability distribution information of submerged plant i. i，N σ represents the variance of the total nitrogen concentration distribution of submerged plant i. i，P x represents the variance of the total phosphorus concentration distribution of submerged plant i. N x represents the total nitrogen concentration in the target water area. PThe total phosphorus concentration in the target water body is expressed in μ. i，N This represents the optimal total nitrogen concentration (μ) for submerged plant i. i，P This indicates the optimal total phosphorus concentration for submerged plants.

[0115] In some alternative implementations, the third relation is:

[0116]

[0117] Among them, P i，Z σ represents the third probability distribution information of submerged plant i. i，Z μ represents the variance of the distribution of submerged plant f with respect to water depth. i，Z Indicates the optimal water depth for submerged plant i, x Z Indicates the water depth of the target area.

[0118] In some alternative implementations, the determining module 404 includes:

[0119] The acquisition unit is used to acquire a preset threshold for the probability distribution of submerged plants;

[0120] The second determining unit is used to determine the distribution scheme of different types of submerged plants in the target water area based on the preset submerged plant probability distribution threshold and the first distribution probability information of various types of submerged plants.

[0121] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0122] In this embodiment, the device for determining the distribution scheme of submerged plants is presented in the form of a functional unit. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0123] This invention also provides a computer device having the above-described features. Figure 4 The apparatus shown is for determining the distribution scheme of submerged plants.

[0124] Please see Figure 5 , Figure 5 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 5As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 5 Take a processor 10 as an example.

[0125] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0126] The memory 20 stores instructions executable by at least one processor 10 to cause the at least one processor 10 to perform the method shown in the above embodiments.

[0127] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0128] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0129] The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0130] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0131] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for determining the distribution scheme of submerged plants, characterized in that, The method includes: Obtain information on different types of submerged plants in the target water area and environmental information of the target water area; The environmental parameters corresponding to the different types of submerged plants were extracted from the pre-constructed submerged plant functional database. Based on the environmental parameters corresponding to the different types of submerged plants and the environmental information of the target water area, the pre-constructed submerged plant distribution probability model is solved to obtain the first distribution probability information of each type of submerged plant. The submerged plant distribution probability model is used to characterize the correlation information between the distribution probability of submerged plants and the corresponding environmental parameters and the environmental information of the target water area. The distribution scheme of different types of submerged plants in the target water area is determined based on the first distribution probability information corresponding to different submerged plants. The environmental information of the target water area includes water temperature information, water quality information, and water depth information, and the environmental parameters include water temperature parameters, water quality parameters, and water depth parameters. The submerged plant distribution probability model includes a first relation, a second relation, and a third relation. The step of solving the pre-constructed submerged plant distribution probability model based on the environmental parameters corresponding to different types of submerged plants and the environmental information of the target water area to obtain the first distribution probability information for each type of submerged plant includes: The first relational formula is solved based on the water temperature parameters of various types of submerged plants and the water temperature information to obtain the second distribution probability information corresponding to different types of submerged plants. The first relational formula is used to characterize the correlation between the distribution probability of submerged plants and the water temperature of the water body and the water temperature parameters of submerged plants. The pre-constructed second relation is solved based on the water quality parameters of various types of submerged plants and the water quality information to obtain the third distribution probability information corresponding to different types of submerged plants. The second relation is used to characterize the correlation between the distribution probability of submerged plants and the water quality of the water area and the water quality parameters of submerged plants. Based on the water depth parameters of various types of submerged plants and the water depth information, the pre-constructed third relation is solved to obtain the fourth distribution probability information corresponding to different types of submerged plants. The third relation is used to characterize the correlation between the distribution probability of submerged plants and the water quality and water depth parameters of submerged plants. Based on the second, third, and fourth distribution probability information of various types of submerged plants, the first distribution probability information corresponding to different types of submerged plants is determined.

2. The method according to claim 1, characterized in that, The first relation is: in, Submerged plants The first distribution probability information, Submerged plants The optimal temperature This represents the variance of the temperature distribution of submerged plants. This indicates the temperature of the target water body.

3. The method according to claim 1, characterized in that, The second relation is: in, Submerged plants The second distribution probability information, Submerged plants The variance of the total nitrogen concentration distribution, Submerged plants The variance of the total phosphorus concentration distribution. This indicates the total nitrogen concentration in the target water area. This indicates the total phosphorus concentration in the target water area. Submerged plants The optimal total nitrogen concentration, Submerged plants The optimal total phosphorus concentration.

4. The method according to claim 1, characterized in that, The third relation is: in, Submerged plants The third distribution probability information, Submerged plants The variance of the water depth distribution. Submerged plants The most suitable water depth Indicates the water depth of the target area.

5. The method according to claim 1, characterized in that, The steps of determining the distribution scheme of different types of submerged plants in the target water area based on the first distribution probability information corresponding to different submerged plants include: Obtain the preset threshold for the probability distribution of submerged plants; Based on the preset probability distribution threshold of submerged plants and the first distribution probability information of various types of submerged plants, the distribution scheme of different types of submerged plants in the target water area is determined.

6. A device for determining the distribution pattern of submerged plants, characterized in that, The device includes: The acquisition module is used to acquire information on different types of submerged plants in the target water area and environmental information of the target water area; The extraction module is used to extract the environmental parameters corresponding to the different types of submerged plants from a pre-constructed submerged plant functional database. The solution module is used to solve the pre-constructed submerged plant distribution probability model based on the environmental parameters corresponding to the different types of submerged plants and the environmental information of the target water area, so as to obtain the first distribution probability information of each type of submerged plant. The submerged plant distribution probability model is used to characterize the correlation information between the distribution probability of submerged plants and the corresponding environmental parameters and the environmental information of the target water area. The determination module is used to determine the distribution scheme of different types of submerged plants in the target water area based on the first distribution probability information corresponding to different submerged plants; The environmental information of the target water area includes water temperature information, water quality information, and water depth information, and the environmental parameters include water temperature parameters, water quality parameters, and water depth parameters. The solution module includes: The first solving unit is used to solve the pre-constructed first relational expression based on the water temperature parameters of various types of submerged plants and the water temperature information, respectively, to obtain the second distribution probability information corresponding to different types of submerged plants. The first relational expression is used to characterize the correlation between the distribution probability of submerged plants and the water temperature of the water body and the water temperature parameters of submerged plants. The second solving unit is used to solve the pre-constructed second relation based on the water quality parameters of various types of submerged plants and the water quality information, respectively, to obtain the third distribution probability information corresponding to different types of submerged plants. The second relation is used to characterize the correlation between the distribution probability of submerged plants and the water quality of the water area and the water quality parameters of submerged plants. The third solution unit is used to solve the pre-constructed third relation based on the water depth parameters of various types of submerged plants and the water depth information, respectively, to obtain the fourth distribution probability information corresponding to different types of submerged plants. The third relation is used to characterize the correlation between the distribution probability of submerged plants and the water quality and water depth parameters of submerged plants. The first determining unit is used to determine the first distribution probability information corresponding to different types of submerged plants based on the second, third, and fourth distribution probability information of various types of submerged plants.

7. The apparatus according to claim 6, characterized in that, The first relation is: in, Submerged plants The first distribution probability information, Submerged plants The optimal temperature This represents the variance of the temperature distribution of submerged plants. This indicates the temperature of the target water body.

8. The apparatus according to claim 6, characterized in that, The second relation is: in, Submerged plants The second distribution probability information, Submerged plants The variance of the total nitrogen concentration distribution, Submerged plants The variance of the total phosphorus concentration distribution. This indicates the total nitrogen concentration in the target water area. This indicates the total phosphorus concentration in the target water area. Submerged plants The optimal total nitrogen concentration, Submerged plants The optimal total phosphorus concentration.

9. The apparatus according to claim 6, characterized in that, The third relation is: in, Submerged plants The third distribution probability information, Submerged plants The variance of the water depth distribution. Submerged plants The most suitable water depth Indicates the water depth of the target area.

10. A computer device, characterized in that, include: The system includes a memory and a processor, which are interconnected and the memory stores computer instructions. The processor executes the computer instructions to perform the method for determining the distribution scheme of submerged plants as described in any one of claims 1 to 5.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the method for determining the distribution scheme of submerged plants as described in any one of claims 1 to 5.

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