Methods for Identifying the Sources of Organic Matter on Lake Bottom

Abstract

The present invention provides a method for identifying the source of lake bottom organic matter, including: obtaining water body data; the water body data includes at least one of topographic data, sediment data, water level data, temperature data and sampled biological distribution data; the temperature data includes vertical temperature data and lateral temperature data; the sampled biological distribution data includes at least the number of aquatic communities obtained at a monitoring sampling point; according to the temperature data and the sampled biological distribution data, the overall biological distribution data is obtained; the overall biological distribution data is the spatial distribution of the aquatic community; using the overall biological distribution data and the water body data, a fused three-dimensional model is generated; according to the fused three-dimensional model, the source of lake bottom organic matter is identified. The present invention establishes a fused three-dimensional model that intuitively displays the spatial distribution and biomass of aquatic communities by analyzing the topographic data, sediment data, water level data, temperature data, and biological distribution data superposition verification; and identifies the source of lake bottom organic matter through the fused three-dimensional model.

Description

Technical Field

[0001] The invention relates to the field of polluted sediment treatment, and more specifically to a method for identifying the source of lake bottom organic matter. Background Art

[0002] Endogenous pollution control and ecological restoration and management are important contents of water environment improvement and strengthening ecological environment protection. In recent years, the Internet of Things technology has developed rapidly, and the real-time monitoring of the water environment has gradually become comprehensive and mature, with the focus on monitoring the water quality of lakes and other water bodies to achieve the goals of deteriorating water quality and preventing black and odor. At the same time, a series of technical routes for water environment improvement and control have also been formed. Based on the Internet of Things technology, the level of informationization of water environment monitoring and management has gradually improved, and the water environment management of some lakes has been greatly improved.

[0003] However, the water ecology of lakes and other water bodies lacks the necessary monitoring, analysis and three-dimensional information technology applications; lake bottom mud is mostly collected through sampling and laboratory testing and analysis, and there is a lack of superposition, fusion, presentation, analysis and three-dimensional information technology applications of three-dimensional scenes of full spatial data such as lake bottom mud, lake water bodies and aquatic communities. There is a lack of three-dimensional scene-based display and analysis of the spatial distribution and migration process (temperature migration) of biological communities, the changes in sediment thickness and organic matter content, etc., and the level of informatization of water ecological management and endogenous management is relatively backward. Summary of the invention

[0004] In view of the above problems, the present invention provides a method for identifying the source of lake bottom organic matter that can be traced and visualized.

[0005] The present invention provides a method for identifying the source of lake bottom organic matter, comprising: acquiring water body data; the water body data at least includes one of topographic data, bottom mud data, water level data, temperature data and sampled biological distribution data; the temperature data includes vertical temperature data and lateral temperature data; the sampled biological distribution data at least includes the number of aquatic communities obtained at a monitoring sampling point; according to the temperature data and the sampled biological distribution data, the overall biological distribution data is obtained; the overall biological distribution data is the spatial distribution of the aquatic community; using the overall biological distribution data and the water body data to generate a fused three-dimensional model; according to the fused three-dimensional model, identifying the source of lake bottom organic matter.

[0006] According to an embodiment of the present invention, overall biological distribution data is obtained based on temperature data and sampled biological distribution data, including: using a Bayesian model to obtain predicted biological distribution data based on vertical temperature data of temperature sampling points; the predicted biological distribution data is a curve of the probability of occurrence of aquatic communities at the temperature sampling points varying with water depth; using the sampled biological distribution data and the predicted biological distribution data, a curve of the number of aquatic communities versus water depth is obtained to determine the overall biological distribution data.

[0007] According to an embodiment of the present invention, sampled biological distribution data and predicted biological distribution data are used to obtain a number-water depth variation curve of an aquatic community for determining overall biological distribution data, including: for each aquatic community, based on the number of aquatic communities in the sampled biological distribution data and the probability of occurrence of the aquatic community at the monitoring sampling point in the predicted biological distribution data, generating a number-water depth variation curve of the aquatic community; if the number of sampling points responding to the vertical temperature is one, determining the overall biological distribution data based on one number-water depth variation curve; if the number of sampling points responding to the vertical temperature is greater than one, determining the overall biological distribution data by interpolation based on multiple number-water depth variation curves.

[0008] According to an embodiment of the present invention, the source of lake bottom organic matter is identified based on the fused three-dimensional model, including: according to the target identification position, obtaining the number of aquatic communities vertically at the target identification position to determine the source of lake bottom organic matter.

[0009] According to an embodiment of the present invention, a fused three-dimensional model is generated using overall biological distribution data and water body data, including: using terrain data, bottom sediment data and water level data to generate a three-dimensional model that is vertically adjusted according to the real-time water level; generating a temperature-water depth variation curve based on vertical temperature data, and fusing the temperature-water depth variation curve with the three-dimensional model to generate a temperature three-dimensional model; fusing the overall biological distribution data with the temperature three-dimensional model to generate a fused three-dimensional model.

[0010] According to an embodiment of the present invention, a three-dimensional model vertically adjusted according to the real-time water level is generated using terrain data, sediment data and water level data, including: receiving thickness data of terrain data and sediment data to generate a static three-dimensional model; using water level data collected in real time to obtain the range of the water body surface contour line for obtaining the three-dimensional model vertically adjusted according to the real-time water level through a surface model construction method.

[0011] According to an embodiment of the present invention, a temperature-water depth variation curve is generated according to vertical temperature data, and the temperature-water depth variation curve is integrated with a three-dimensional model to generate a temperature three-dimensional model, including: in response to the number of sampling points of the vertical temperature being one, a temperature-water depth variation curve is obtained according to the vertical temperature data of the sampling point; vertical layered display is performed according to the temperature-water depth variation curve; in response to the number of sampling points of the vertical temperature being greater than one, multiple temperature-water depth variation curves are obtained according to the vertical temperature data of multiple sampling points; multiple temperature-water depth variation curves are used to form an isothermal surface through uniform interpolation, and vertical layered display is performed; wherein the vertical layered display includes: judging whether the slope of the temperature-water depth variation curve is greater than a threshold value; if If the maximum slope of the temperature-water depth change curve is greater than the threshold, the vertical stratification is represented as surface water layer, oblique surface layer, net water layer, and bottom mud layer in sequence; different layers are rendered in three dimensions with different colors and merged with the three-dimensional model; if the maximum slope of the temperature-water depth change curve is less than the threshold, it is determined whether the maximum temperature difference of the water body is greater than the threshold. If so, the water body is divided into three equal temperature intervals using the horizontal temperature data and the lake bottom temperature data in the vertical temperature data, and then the bottom mud layer is superimposed; the three equal temperature intervals and the bottom mud layer are rendered in three dimensions with different colors and merged with the three-dimensional model; if not, one equal temperature interval is displayed and the bottom mud layer is superimposed; one equal temperature interval and the bottom mud layer are rendered in three dimensions with different colors and merged with the three-dimensional model.

[0012] According to an embodiment of the present invention, obtaining water body data includes: obtaining terrain data using digital elevation model data within a preset range underwater and around; collecting sediment using a borehole sampling method, and detecting the sediment for obtaining continuously changing sediment data of the lake bottom through an interpolation method; the sediment data includes thickness data and organic matter content data; using a water level sensor to collect the water level of a preset water point in real time, and obtaining continuously changing water level data of the water surface through an interpolation method; using a temperature sensor to collect lateral temperature data of a preset monitoring point on the surface of the water body; determining the number of temperature sampling points for vertical temperature based on the lateral temperature data for determining the vertical temperature data; collecting aquatic communities at preset monitoring sampling points to obtain sampled biological distribution data; the aquatic community includes at least one of ephemera, ephemera, aquatic plants, fish animals and benthic animals.

[0013] According to an embodiment of the present invention, determining the number of sampling points of the vertical temperature based on the lateral temperature data for determining the vertical temperature data includes: judging whether the discrete degree of the lateral temperature data is greater than a preset degree; if not, obtaining the vertical temperature data based on a temperature sampling point using temperature sensors at different vertical depths of the sampling point; and if so, collecting the vertical temperature data of the temperature sampling point for each temperature sampling point of the lateral temperature data to obtain the vertical temperature data.

[0014] The second aspect of the present invention provides a device for identifying the source of lake bottom organic matter, which can be used to implement the above method, including: a collection module, used to obtain water body data; the water body data includes at least one of terrain data, bottom mud data, water level data, temperature data and sampled biological distribution data; the temperature data includes vertical temperature data and lateral temperature data; the sampled biological distribution data includes at least the number of aquatic communities obtained by monitoring one sampling point; a model module, used to obtain overall biological distribution data based on temperature data and sampled biological distribution data; the overall biological distribution data is the spatial distribution of aquatic communities; using the overall biological distribution data and water body data to generate a fused three-dimensional model; an identification module, used to identify the source of lake bottom organic matter based on the fused three-dimensional model.

[0015] A third aspect of the present invention provides an electronic device, comprising: one or more processors; a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors execute the above method.

[0016] The fourth aspect of the present invention also provides a computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, causes the processor to execute the above method.

[0017] According to the method for identifying the source of lake bottom organic matter provided by the present invention, the aquatic community distribution of the lake is predicted based on the temperature data of the Internet of Things, and the collected biological distribution data is superimposed and verified, so as to intuitively display the spatial distribution and biomass of the biological community in the three-dimensional model. Since the number of biological communities in the water body is determined, the technical problem that the water ecological environment is difficult to generate and display in real time is at least partially solved, and the technical effect of real-time analysis of the source of organic matter in different locations is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A flow chart of a method for identifying the source of lake bottom organic matter according to an embodiment of the present invention is schematically shown;

[0019] Figure 2 A schematic diagram of a three-dimensional temperature model of thermal stratification superimposed in a three-dimensional space according to an embodiment of the present invention is shown;

[0020] Figure 3 A flowchart of a method for monthly identifying lake bottom organic matter sources according to an embodiment of the present invention is schematically shown;

[0021] Figure 4 A schematic diagram of the monthly average water temperature distribution of a lake according to an embodiment of the present invention is shown schematically;

[0022] Figure 5A structural block diagram of a device for identifying the source of lake bottom organic matter according to an embodiment of the present invention is schematically shown;

[0023] Figure 6 A block diagram of an electronic device suitable for implementing a method for identifying sources of lake bottom organic matter according to an embodiment of the present invention is schematically shown. DETAILED DESCRIPTION

[0024] Below, embodiments of the present invention will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present invention. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of embodiments of the present invention. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of concepts of the present invention.

[0025] The terms used herein are only for describing specific embodiments and are not intended to limit the present invention. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0026] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0027] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0028] It should be noted that the method for identifying the source of lake bottom organic matter of the present invention can be used in the field of identifying the source of lake organic matter, and can also be used in other water bodies besides lakes.

[0029] First, the technical terms involved in the specification are explained as follows:

[0030] DEM data: Digital Elevation Model data is a type of digital geographic data used to describe the topography of the earth's surface. DEM data mainly contains the elevation information of the surface, that is, the height value of each point (or pixel, grid) in the vertical direction. These elevation values ​​are stored in digital form and can be further processed by GIS software or 3D modeling software to generate a 3D terrain model.

[0031] Bottom mud: refers to the general term for various particulate matter deposited at the bottom of water bodies such as rivers, lakes, and reservoirs. It is silt that is gradually deposited in a still water or slow-flowing water environment. The main components of bottom mud include organic matter, inorganic matter, and microorganisms. According to the porosity and water content, it is divided into floating mud, flowing mud, silt, and silty soil. Generally, bottom mud sampling methods (borehole sampling) and remote sensing methods are used to collect and analyze bottom mud data to obtain the thickness of the same type of bottom mud or under the same stress conditions, and to conduct chemical analysis on the composition of the bottom mud, focusing on the content and spatial distribution of organic matter in the bottom mud, and providing data support for the spatial distribution of organic matter.

[0032] Relationship between temperature distribution and biome distribution: Temperature is the main factor affecting the distribution and migration of aquatic biomes, and is directly related to the growth, development, reproduction and migration of aquatic organisms. Each type of organism basically has its own temperature range suitable for survival, especially fish in lakes, which are temperature-sensitive organisms. Due to seasonal temperature changes or special weather, many fish die, which further affects the organic matter content of the bottom mud. Therefore, the present invention also mainly analyzes the thermal distribution of temperature in three dimensions of the water body.

[0033] Bayesian model: A Bayesian model is a model that uses Bayesian inference theory to make predictions. Bayesian statistics is different from general statistical methods. It not only uses model information and data information, but also makes full use of prior information. The Bayesian prediction model can make full use of prior knowledge and observed data to make predictions. At the beginning of the model establishment, a prior probability distribution is defined, which represents the initial belief or hypothesis about the unknown quantity. Subsequently, the prior probability distribution is updated using the collected observation data using Bayes' theorem to obtain the posterior probability distribution. The posterior probability distribution more accurately reflects the new belief about the unknown quantity after considering the observed data.

[0034] Figure 1A flow chart of a method for identifying the source of lake bottom organic matter according to an embodiment of the present invention is schematically shown. The embodiment of the present invention provides a method for identifying the source of lake bottom organic matter, including: S1, obtaining water body data; the water body data includes at least one of terrain data, bottom mud data, water level data, temperature data and sampled biological distribution data; the temperature data includes vertical temperature data and lateral temperature data; the sampled biological distribution data includes at least the number of aquatic communities obtained at a monitoring sampling point; S2, obtaining overall biological distribution data based on the temperature data and the sampled biological distribution data; the overall biological distribution data is the spatial distribution of aquatic communities; S3, using the overall biological distribution data and water body data to generate a fused three-dimensional model; S4, identifying the source of lake bottom organic matter based on the fused three-dimensional model.

[0035] Through the embodiments of the present invention, the present invention mainly studies the dynamic twin three-dimensional model of lakes and other water bodies constructed by integrating three types of data: topographic data representing the underwater topography of the lake, thickness data including the thickness of the lake bottom mud, and water level data of the real-time lake surface water level. Further, based on the three-dimensional model data and the temperature monitoring data of the Internet of Things, the three-dimensional spatial expression and change process simulation of the real-time temperature three-dimensional water body model are studied. By surveying the ecological diversity content of the lake and superimposing and verifying the water ecological monitoring data, the spatial distribution and biomass of the biological community are intuitively displayed in the three-dimensional water body model. Under the condition that the exogenous pollution is effectively controlled, it can provide scientific auxiliary decision-making for the endogenous pollution control of lakes and other water environments, and realize the identification of the source of organic matter in the lake bottom mud.

[0036] On the basis of the above embodiments, the overall biological distribution data is obtained according to the temperature data and the sampled biological distribution data, including: using the Bayesian model to obtain the predicted biological distribution data according to the vertical temperature data of the temperature sampling point; the predicted biological distribution data is a curve of the probability of occurrence of the aquatic community at the temperature sampling point changing with the water depth; using the sampled biological distribution data and the predicted biological distribution data, a curve of the number of aquatic communities-water depth changes is obtained to determine the overall biological distribution data.

[0037] In this embodiment, the Bayesian regularized neural network model is used to analyze the habitat distribution characteristics of the biological community and predict the relative density (occurrence probability) of the biological community.

[0038] Through the embodiments of the present invention, mainly based on the three-dimensional characterization of the thermal stratification of the water body, the spatial distribution of different aquatic communities in the water area is analyzed to a certain extent, including but not limited to the spatial distribution of ephemera, ephemera, large aquatic plants, different fish, benthic animals, etc. For example, the surface water layer of the lake is rich in dissolved oxygen, mainly due to various fish, more algae and large aquatic plants along some shores of the lake, and more benthic animals and plants on the bottom of the lake. At the same time, the Internet of Things monitoring equipment is effectively combined to monitor and evaluate the ecosystem of the lake, including the spatial distribution and biomass monitoring and evaluation of algae, fish, benthic animals, ephemera, etc.

[0039] On the basis of the above embodiments, the sampled biological distribution data and the predicted biological distribution data are used to obtain the number-water depth variation curve of the aquatic community for determining the overall biological distribution data, including: for each aquatic community, according to the number of aquatic communities in the sampled biological distribution data, and the probability of the occurrence of the aquatic community at the monitoring sampling point in the predicted biological distribution data, the number-water depth variation curve of the aquatic community is generated; if the number of sampling points responding to the vertical temperature is one, the overall biological distribution data is determined according to one number-water depth variation curve; if the number of sampling points responding to the vertical temperature is greater than one, the overall biological distribution data is determined by interpolation method according to multiple number-water depth variation curves.

[0040] Through the embodiments of the present invention, for each aquatic community, a quantity-water depth change curve is generated based on the sampling data and the predicted data. When the number of sampling points is different, different methods (direct determination or interpolation method) are used to determine the overall biological distribution data. The Bayesian model is used to predict the biological distribution based on the vertical temperature data, and then combined with the actual sampled biological distribution data to obtain a more comprehensive aquatic community quantity-water depth change curve, thereby determining the overall biological distribution data, and realizing the generation of comprehensive data from one or more sampling points for generating real-time biological community distribution status. At the same time, the migration of organisms can be examined according to the distribution status of biological communities at different times. Through the investigation of the types of lake ecosystems, a single-indicator temperature suitability environmental analysis is performed on the spatial distribution locations of biological communities with a large number of them.

[0041] On the basis of the above-mentioned embodiment, the source of lake bottom organic matter is identified according to the fused three-dimensional model, including: according to the target identification position, obtaining the number of aquatic communities vertically at the target identification position, and determining the source of lake bottom organic matter.

[0042] In this embodiment, the number of aquatic communities is rendered and displayed in the model in the form of markers according to their grid distribution.

[0043] In this embodiment, temperature is one of the key indicators that affect the distribution and changes of aquatic communities in lakes and other water bodies, including the dissolved oxygen content in water, the growth and development of aquatic organisms, and the structure of plankton communities. The position and distribution of aquatic plants are relatively fixed, and the superposition and fusion of three-dimensional space is relatively simple, mainly analyzing the distribution and migration of aquatic animals. The spatial distribution area data of the main biological communities obtained by actual monitoring are used to fit the analysis data of the spatial distribution of aquatic biological communities based on thermal stratification, and are superimposed and displayed in the three-dimensional water body model to intuitively present the three-dimensional distribution of the main biological communities in the lake ecosystem.

[0044] In this embodiment, the organic matter content identification grid unit can be divided into different organic matter content, biological community area, sediment thickness and other factors, or the conventional 1km 1km grid or other unit grids of different sizes. When the thickness of lake bottom mud and the organic matter content change, the characteristics and quantity changes of biological communities in the vertical space of adjacent grids can be analyzed according to the chemical composition of organic matter content and the data changes in the previous and next months. If necessary, isotope labeling can also be used for tracking and verification. Under the condition that exogenous pollution is controlled, it can provide three-dimensional information and scientific auxiliary support for endogenous governance and management, promote the transformation of overall dredging of lakes to local dredging, and obtain scientific analysis and management.

[0045] Through the embodiments of the present disclosure, based on the three-dimensional model of the lake aquatic community water body with superimposed sediment thickness, the organic matter content obtained by sediment testing is fused and superimposed for display (dividing the organic matter content range, and rendering sediments with different organic matter contents in different colors). According to the changes in organic matter content in the regional grids sampled and tested monthly, the spatial distribution and biological migration of fish, large plants, algae, ephemera, etc. are effectively combined to provide identification and analysis of the source of organic matter content.

[0046] On the basis of the above embodiment, the overall biological distribution data and water body data are used to generate a fused three-dimensional model, including: using terrain data, sediment data and water level data to generate a three-dimensional model that is vertically adjusted according to the real-time water level; generating a temperature-water depth change curve based on the vertical temperature data, and fusing the temperature-water depth change curve with the three-dimensional model to generate a temperature three-dimensional model; fusing the overall biological distribution data with the temperature three-dimensional model to generate a fused three-dimensional model.

[0047] In this embodiment, considering that the distribution, development, growth and other processes of aquatic plants and animals are affected by factors such as light, temperature and dissolved oxygen content, light mainly affects the distribution of aquatic plants. Since the spatial distribution of aquatic plants is relatively fixed and data collection is easy, there is no need for separate analysis and research. Dissolved oxygen mainly comes from the surface water layer of thermal stratification, aquatic plants and the decomposition and release of organic matter on the lake bottom. The relevant release sources have been analyzed and applied, so this indicator is not studied separately.

[0048] Through the embodiments of the present invention, it is proposed for the first time to integrate lake bottom mud, underwater topography, real-time liquid level and other data to build a three-dimensional twin simulation model of lake water. The present invention mainly studies the distribution and changes of temperature in the three-dimensional space of the water body, as well as the distribution changes and biomass of aquatic biological communities in the three-dimensional space of the water body, and performs correlation fitting analysis, studies the three-dimensional spatial distribution of aquatic biological communities and the superposition and fusion display based on the three-dimensional model of the water body, as well as the spatial distribution change process and the change process of organic matter content in lake bottom mud. It can intuitively display the organic matter content of lake bottom mud, and can also identify and analyze sources according to the spatial distribution and migration process of biological communities, providing scientific assistance for the monitoring and management of water ecology, endogenous governance and management, and providing an intuitive three-dimensional view for subsequent analysis and identification.

[0049] On the basis of the above-mentioned embodiment, a three-dimensional model vertically adjusted according to the real-time water level is generated using terrain data, sediment data and water level data, including: receiving thickness data of terrain data and sediment data to generate a static three-dimensional model; using the water level data collected in real time to obtain the range of the water surface contour line of the water body for obtaining the three-dimensional model vertically adjusted according to the real-time water level through the surface model construction method.

[0050] Through the embodiments of the present invention, a static three-dimensional model is generated using terrain and sediment data, and then adjusted according to real-time water level data, thereby ensuring the real-time and accuracy of the model.

[0051] On the basis of the above-mentioned embodiment, a temperature-water depth change curve is generated according to the vertical temperature data, and the temperature-water depth change curve is integrated with the three-dimensional model to generate a temperature three-dimensional model, including: in response to the number of sampling points of the vertical temperature being one, a temperature-water depth change curve is obtained according to the vertical temperature data of the sampling point; vertical layered display is performed according to the temperature-water depth change curve; in response to the number of sampling points of the vertical temperature being greater than one, multiple temperature-water depth change curves are obtained according to the vertical temperature data of multiple sampling points; multiple temperature-water depth change curves are used to form an isothermal surface through uniform interpolation, and vertical layered display is performed; wherein, the vertical layered display includes: judging whether the slope of the temperature-water depth change curve is greater than a threshold value; If the maximum slope of the temperature-water depth change curve is greater than the threshold, the vertical stratification is represented as surface water layer, oblique surface layer, net water layer, and bottom mud layer in turn; different layers are rendered in three dimensions with different colors and merged with the three-dimensional model; if the maximum slope of the temperature-water depth change curve is less than the threshold, it is determined whether the maximum temperature difference of the water body is greater than the threshold. If so, the water body is divided into three equal temperature intervals using the lateral temperature data and the lake bottom temperature data in the vertical temperature data, and then the bottom mud layer is superimposed; the three equal temperature intervals and the bottom mud layer are rendered in three dimensions with different colors and merged with the three-dimensional model; if not, one equal temperature interval is displayed and the bottom mud layer is superimposed; one equal temperature interval and the bottom mud layer are rendered in three dimensions with different colors and merged with the three-dimensional model.

[0052] In this embodiment, based on the temperature-depth curve data obtained from actual monitoring statistics, regardless of whether a lake or other water body has obvious thermal stratification, the temperature-depth curve data can be superimposed and fused with the three-dimensional dynamic twin model of the water body to form a three-dimensional water body model of the monthly mean temperature thermal distribution. The model is described as follows: For lakes with thermal stratification, according to the temperature range of the thermal stratification, within the corresponding temperature range, the vertical stratification is represented in sequence as: surface water layer, oblique surface layer, clean water layer, bottom mud layer, and rendered in three dimensions with different colors, and superimposed and fused with the three-dimensional model of the water body for display, such as Figure 2 As shown; for lakes without thermal stratification, it is only necessary to automatically divide the lake into three equal temperature intervals according to the upper temperature of the lake surface and the lake bottom temperature, and superimpose the bottom mud layer for display; isothermal lakes only need to display one temperature interval and superimpose the bottom mud layer.

[0053] Through the embodiments of the present invention, a temperature-water depth variation curve is generated according to vertical temperature data, and how to display temperature stratification is determined according to the number of sampling points and the slope of the temperature curve, so as to intuitively display the differences in temperature indicators of different layers.

[0054] On the basis of the above embodiments, water body data is obtained, including: using digital elevation model data within a preset range underwater and around to obtain terrain data; using a borehole sampling method to collect sediment, and detecting the sediment for obtaining continuously changing sediment data of the lake bottom through interpolation; the sediment data includes thickness data and organic matter content data; using a water level sensor to collect the water level of a preset water point in real time, and obtaining continuously changing water level data of the water surface through interpolation; using a temperature sensor to collect lateral temperature data of a preset monitoring point on the water body surface; determining the number of temperature sampling points for vertical temperature based on the lateral temperature data to determine the vertical temperature data; collecting aquatic communities at preset monitoring sampling points to obtain sampled biological distribution data; the aquatic community includes at least one of ephemera, ephemera, aquatic plants, fish animals and benthic animals.

[0055] In this embodiment, topographic measurements are performed according to the maximum underwater terrain boundary range that may appear during the flood season of lakes, reservoirs, rivers, etc., to obtain high-precision (1:500 scale) underwater and surrounding terrain DEM data within a certain range, and vectorization and standardization are performed, so that it can be directly imported into the supporting equipment and information system of the present invention. Since the terrain changes slowly and the influencing factors are complex, the terrain data can be regarded as stable and unchanging data within a certain period of time and only needs to be collected once. The terrain data can be reused later as one of the fixed basic data for building a three-dimensional model of water bodies and conducting thermal distribution and aquatic community ecological distribution research.

[0056] In this embodiment, the lake surface is used as a reference to divide the data collection grid into evenly spaced grids, such as Grids are used to sample, analyze and process the sediment data within each grid, and the thickness and organic matter content data of the entire lake bottom sediment are analyzed using an interpolation algorithm. Other notes are as follows: The recommended frequency for collecting sediment data is monthly, which corresponds to the time dimension of the subsequent study of the distribution of the monthly mean temperature of lake water bodies in the three-dimensional space of the water body, as well as the spatial distribution and migration changes of the corresponding aquatic communities, so as to facilitate source identification and analysis; The content of sediment data collection in this invention mainly focuses on the thickness of the sediment and the content of organic matter, and evaluation and analysis are performed according to the divided grid areas. The grid here and the grid for sediment data collection can be different, and can be divided based on comprehensive consideration of factors such as sediment thickness, organic matter content range, and biological community aggregation area.

[0057] In this embodiment, since the water surface of water bodies such as lakes is relatively still (without considering the influence of wind and waves), the construction of three-dimensional models of water bodies such as lakes only needs to consider the changes in vertical water level elevation; for water bodies with different water levels such as rivers, the water levels of multiple sections can be monitored, and the interpolation method can be used to obtain continuous surface water level change data.

[0058] Through the embodiments of the present invention, based on the real-time water level monitoring data of lakes and other water bodies, the water surface contour line range of lakes and other water bodies under the corresponding water level conditions is obtained, the lake bottom mud topography and thickness data are integrated, and the three-dimensional modeling of the lake water body is performed using the surface model construction method, forming a dynamic water body three-dimensional model construction mode and method for superimposing lake bottom mud topography constraints and vertically adjusting the real-time water level of the lake surface. Among them, the thickness distribution of the lake bottom mud can be interpolated according to the number of sampling points using the inverse distance weighted method or the kriging method, diffused to the unsampled lake bottom area, and automatically calculated The thickness of the corresponding sediment category.

[0059] On the basis of the above embodiment, the number of sampling points of the vertical temperature is determined according to the lateral temperature data for determining the vertical temperature data, including: judging whether the discrete degree of the lateral temperature data is greater than a preset degree; if not, according to a temperature sampling point, using temperature sensors at different vertical depths of the sampling point to obtain the vertical temperature data; if so, for each temperature sampling point of the lateral temperature data, collecting the vertical temperature data of the temperature sampling point to obtain the vertical temperature data.

[0060] In this embodiment, the lateral water temperature distribution of the lake varies due to factors such as lake shape, distance from the shore, aquatic vegetation, runoff into the lake, wind direction, and sun exposure. However, due to direct contact between the surface water and the atmosphere, it is greatly disturbed by wind. Under the influence of solar radiation and wind and waves, the temperature distribution of the upper water body of the lake is relatively uniform. When the influencing factors are complex and the temperature variation range is small, the same temperature is generally used to express the lake surface temperature.

[0061] Furthermore, the processing method when the surface temperature changes greatly is as follows: When the lake surface is large and the temperature difference is large, the expression of the horizontal water temperature distribution of the lake is obtained by observing and recording the water temperature at different locations. Through investigation and analysis, representative temperature monitoring stations are selected, including deep water areas, shallow water areas, lake entrances, lake exits and other different lake areas to ensure that the lateral distribution of lake water temperature can be fully reflected. When measuring water temperature, in order to realize the real-time collection and remote transmission of water temperature data, the shore monitoring station is selected for permanent installation; and the upper water temperature in the center of the lake or in areas where it is inconvenient to install thermometers is seasonally collected, and the relationship between the temperature in this area and the temperature of the existing monitoring points is analyzed, so as to realize the correction of the lateral temperature distribution of the lake. For the lateral temperature of different monitoring points, the interpolation method is used for distribution.

[0062] In this embodiment, a temperature sensor and an online monitoring system are used to monitor the water temperature at different water depths in real time. The water depth monitoring interval of the temperature monitoring sensor probe is planned according to the water depth at the monitoring station, including at least the temperature 0.5m below the surface of the lake, the lake bottom and the center of the vertical depth of the lake. When the temperature distribution gradient (≥0.2℃ / m) of adjacent monitoring points is large, the vertical density of the monitoring points should be appropriately increased to capture the thickness of the thermocline when some lakes have it. Based on the temperature acquisition sensors at different water depths mentioned above, the same data acquisition frequency is set, such as 5min / time, 15min / time, etc., and the hourly temperature curves at each temperature monitoring depth are generated according to the collected data. The temperature data of different depths collected at the same time are fused with the three-dimensional model of the water body, and the new temperature monitoring data are fused hourly to generate a three-dimensional water body model that can not only view the real-time thermal distribution, but also preview the change process of the three-dimensional water body model of the historical thermal distribution for 24 hours a day.

[0063] Among them, when the lateral temperature difference is small, the lake surface is used as the reference, and the temperature at the same underwater depth is regarded as the same value to display the vertical one-dimensional thermal distribution three-dimensional model; if the lateral temperature difference is large and multiple temperature monitoring stations are set up, a vertical continuous temperature change curve can be formed, and an isothermal surface can be formed by uniform interpolation based on the same temperature monitoring values ​​of multiple monitoring stations, thereby constructing a three-dimensional model of thermal distribution water body with different lateral temperature distributions.

[0064] Through the embodiments of the present invention, whether to add vertical temperature sampling points is determined according to the discrete degree of the lateral temperature data, thereby reducing the sampling cost while ensuring data accuracy.

[0065] Based on the above embodiments, Figure 3 A flowchart of a method for monthly identifying lake bottom organic matter sources according to an embodiment of the present invention is schematically shown. Figure 3 As shown, the method also includes: measurement of underwater topography of the lake and topographic data within a certain range around it; collection, processing and analysis of lake bottom sediment data; real-time water level data collection and access, construction of a three-dimensional dynamic twin model of lake sediment and water body, and integration of integrated modeling, display equipment and systems; lateral temperature analysis of the lake surface; a three-dimensional spatiotemporal expression method of a three-dimensional water body model of real-time thermal distribution of lakes based on temperature monitoring; a three-dimensional spatiotemporal expression method of a three-dimensional water body model of monthly mean temperature thermal distribution; single indicator analysis, three-dimensional fusion display and migration change analysis of the ecological spatial distribution of aquatic communities in lakes; spatial analysis based on the distribution display of organic matter content in lake bottom sediment and identification of endogenous organic matter sources; access to a three-dimensional water body model that integrates monthly end-of-month sediment data in the lake, and development of an information system that can express the three-dimensional spatiotemporal temperature changes, biological community changes, sediment pollution changes and source identification analysis of lakes.

[0066] In this embodiment, based on the above-mentioned index measurement and temperature analysis, the real-time water temperature monitoring data is further used. When the sensor probes at different water depths are fixed at the same temperature monitoring station, the temperature at different depths is monitored in real time and the monthly average is calculated. Figure 4 The schematic diagram of the monthly average water temperature distribution of the lake according to the embodiment of the present invention is shown schematically. Figure 4 As shown, the vertical distribution of monthly mean temperature in three-dimensional water bodies is studied. Based on the monthly change data of lake thermal stratification or temperature in each temperature zone, combined with the monthly aquatic biological area and biomass monitoring mean evolution data, model data of aquatic biological distribution area, biomass and temperature relationship are generated as the basis for aquatic animal migration changes and prediction analysis, and fused and superimposed in the three-dimensional water body model. The spatial location distribution of different aquatic organisms and the monthly data of organic matter content in lake bottom mud are integrated to analyze the sources of organic matter in different locations, providing auxiliary support for the ecological management and endogenous control of lakes and other water environments.

[0067] It should be noted that large plants, algae and other aquatic terrestrial plants only need to be evaluated on a monthly basis for their biomass; aquatic animals need to be statistically analyzed based on monthly data for the spatial distribution and biomass changes of the same biological species, and the aggregation areas of the organisms should be gradually analyzed, and the changes in biomass should be statistically analyzed. Due to the high mobility of aquatic animals, statistics can be made based on daily monitoring data to obtain the regional locations and biomass of the main divisions of the biological communities each month, and areas with smaller numbers can be ignored. The locations of aquatic plants are relatively fixed, and only regular monitoring and evaluation of biomass is required.

[0068] Through the embodiments of the present disclosure, the temperature change process in the three-dimensional space of the water body is analyzed on a monthly basis, the spatial distribution and migration of the aquatic community are analyzed, the vertical thermal distribution data, the biological community monitoring and analysis prediction data, the monthly thickness of the lake bottom mud and the organic matter content data are superimposed and fused, and the algorithm services and software programs are integrated to form an information system that can express the three-dimensional space of the lake water body.

[0069] Based on the above method for identifying the source of lake bottom organic matter, the present invention also provides a device for identifying the source of lake bottom organic matter, which can be used to implement any of the above methods.

[0070] Figure 5 The structure block diagram of the device for identifying the source of lake bottom organic matter according to an embodiment of the present invention is schematically shown. Figure 5 As shown, the device for identifying the source of lake bottom organic matter in this embodiment includes a collection module, a model module and an identification module.

[0071] The acquisition module is used to obtain water body data; the water body data includes at least one of topographic data, sediment data, water level data, temperature data and sampled biological distribution data; the temperature data includes vertical temperature data and lateral temperature data; the sampled biological distribution data includes at least the number of aquatic communities obtained by monitoring a sampling point. In one embodiment, the acquisition module can be used to perform the operation S1 described above, which will not be repeated here.

[0072] The model module is used to obtain the overall biological distribution data according to the temperature data and the sampled biological distribution data; the overall biological distribution data is the spatial distribution of the aquatic community; and the fused three-dimensional model is generated by using the overall biological distribution data and the water body data. In one embodiment, the model module can be used to perform the operations S2-S3 described above, which will not be described in detail here.

[0073] The identification module is used to identify the source of lake bottom organic matter according to the fused three-dimensional model. In one embodiment, the identification module can be used to perform the operation S4 described above, which will not be described in detail here.

[0074] On the basis of the above embodiment, the model module also includes: developing a front-end hardware device, which has a built-in interface for importing or automatically accessing terrain data, sediment data, water level data and temperature data, and a built-in three-dimensional water body modeling program under different conditions, which can generate and view the three-dimensional spatial distribution model of the water body at any time, as follows: the device is managed based on the project dimension, and can create and save three-dimensional water body models of multiple lakes and update them dynamically in real time; the device can import terrain data in the form of vector files and present it in two dimensions, and the recommended data format is ".shp and .dwg"; the device uniformly adopts the CGCS2000 National Geodetic Plane Coordinate System and the 1985 National Elevation Coordinate System as the benchmark, and can import the lake bottom sediment thickness data of the same lake in the same project, and seamlessly integrate and overlay the lake bottom terrain data for display, and display the latest in chronological order. The device has built-in multiple water level data configuration functions, and can select single water point location and multiple water point locations. Single water point location is a relatively static lake surface with consistent water surface elevation, and multiple water point locations are rivers with large water surface elevation difference and obvious fluid flow: including the following contents: a. Manual input of lake water surface elevation data of control points; b. Manual import of continuous water level monitoring data of control points, and the data format is Excel; c. Built-in communication protocol, automatic access to real-time water level data of lake control points; The device has built-in program for three-dimensional modeling of lake bottom sediment and water body, and automatically constructs and displays three-dimensional twin models according to the parameters imported, accessed and configured in the above steps; The device provides a data interface for sharing the results of three-dimensional modeling of lake bottom sediment and water body and exporting data, and can share lake twin data to other platforms for application.

[0075] Through the embodiments of the present disclosure, after the first modeling is completed, it is only necessary to update the water level data to view the three-dimensional spatial distribution of the bottom sediment and the water body. The dynamic three-dimensional water body changes can be viewed at any time by connecting to the real-time water level, and the evolution process can be viewed based on the time series water level data.

[0076] Figure 6 A block diagram of an electronic device suitable for implementing a method for identifying sources of lake bottom organic matter according to an embodiment of the present invention is schematically shown.

[0077] like Figure 6 As shown, the electronic device 600 according to an embodiment of the present invention includes a processor 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage part 608 to a random access memory (RAM) 603. The processor 601 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 601 may also include an onboard memory for caching purposes. The processor 601 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present invention.

[0078] In RAM 603, various programs and data required for the operation of electronic device 600 are stored. Processor 601, ROM 602 and RAM 603 are connected to each other via bus 604. Processor 601 performs various operations of the method flow according to the embodiment of the present invention by executing the program in ROM 602 and / or RAM 603. It should be noted that the program can also be stored in one or more memories other than ROM 602 and RAM 603. Processor 601 can also perform various operations of the method flow according to the embodiment of the present invention by executing the program stored in the one or more memories.

[0079] According to an embodiment of the present invention, the electronic device 600 may further include an input / output (I / O) interface 605, which is also connected to the bus 604. The electronic device 600 may further include one or more of the following components connected to the I / O interface 605: an input portion 606 including a keyboard, a mouse, etc.; an output portion 607 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 608 including a hard disk, etc.; and a communication portion 609 including a network interface card such as a LAN card, a modem, etc. The communication portion 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as needed, so that a computer program read therefrom is installed into the storage portion 608 as needed.

[0080] The present invention also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiment; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present invention is implemented.

[0081] The embodiment of the present invention also includes a computer program product, which includes a computer program, and the computer program contains program code for executing the method shown in the flowchart. When the computer program product is run in a computer system, the program code is used to enable the computer system to implement the method provided by the embodiment of the present invention.

[0082] According to an embodiment of the present invention, the program code for executing the computer program provided by the embodiment of the present invention can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (e.g., using an Internet service provider to connect through the Internet).

[0083] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0084] It will be appreciated by those skilled in the art that the features described in the various embodiments and / or claims of the present invention may be combined and / or combined in various ways, even if such combinations and / or combinations are not explicitly described in the present invention. In particular, the features described in the various embodiments and / or claims of the present invention may be combined and / or combined in various ways without departing from the spirit and teachings of the present invention. All of these combinations and / or combinations fall within the scope of the present invention.

[0085] The embodiments of the present invention are described above. However, these embodiments are only for the purpose of illustration, and are not intended to limit the scope of the present invention. Although each embodiment is described above, it does not mean that the measures in each embodiment cannot be used in combination. The scope of the present invention is defined by the attached claims and their equivalents. Without departing from the scope of the present invention, those skilled in the art may make various substitutions and modifications, which should all fall within the scope of the present invention.

Claims

1. A method for identifying the source of lake bottom organic matter, characterized in that: include: Acquire water body data; the water body data includes at least one of topographic data, sediment data, water level data, temperature data and sampled biological distribution data; the temperature data includes vertical temperature data and lateral temperature data; the sampled biological distribution data includes at least the number of aquatic communities obtained at a monitoring sampling point; According to the temperature data and the sampled biological distribution data, the overall biological distribution data is obtained; the overall biological distribution data is the spatial distribution of the aquatic community; Generate a fused three-dimensional model using the overall biological distribution data and the water body data; Based on the fused three-dimensional model, the source of lake bottom organic matter is identified.

2. The method according to claim 1, wherein: The step of obtaining overall biological distribution data according to the temperature data and the sampled biological distribution data comprises: Using the Bayesian model, based on the vertical temperature data of the temperature sampling point, the predicted biological distribution data is obtained; the predicted biological distribution data is a curve of the probability of occurrence of aquatic communities at the temperature sampling point changing with water depth; The sampled biological distribution data and the predicted biological distribution data are used to obtain a curve of the number-water depth variation of the aquatic community to determine the overall biological distribution data.

3. The method according to claim 2, wherein: The method of using the sampled biological distribution data and the predicted biological distribution data to obtain a curve of the number of aquatic communities and water depth for determining the overall biological distribution data includes: For each aquatic community, a quantity-water depth change curve of the aquatic community is generated according to the quantity of the aquatic community in the sampled biological distribution data and the probability of the aquatic community appearing at the monitoring sampling point in the predicted biological distribution data; In response to the number of sampling points of the vertical temperature being one, the overall biological distribution data is determined according to a quantity-water depth variation curve; In response to the number of sampling points of the vertical temperature being greater than one, the overall biological distribution data is determined by interpolation based on a plurality of quantity-water depth variation curves.

4. The method according to claim 2, wherein: The identifying the source of lake bottom organic matter according to the fused three-dimensional model includes: According to the target identification position, the number of aquatic communities in the vertical direction of the target identification position is obtained to determine the source of organic matter on the lake bottom.

5. The method according to claim 1, wherein: Using the overall biological distribution data and the water body data, a fused three-dimensional model is generated, including: Using the terrain data, sediment data and water level data, a three-dimensional model adjusted vertically according to the real-time water level is generated; generating a temperature-water depth variation curve according to the vertical temperature data, and fusing the temperature-water depth variation curve with the three-dimensional model to generate a temperature three-dimensional model; The overall biological distribution data is fused with the temperature three-dimensional model to generate a fused three-dimensional model.

6. The method according to claim 5, wherein: The method of using the terrain data, the bottom mud data and the water level data to generate a three-dimensional model vertically adjusted according to the real-time water level includes: Receiving the terrain data and the thickness data of the bottom mud data, and generating a static three-dimensional model; By using the water level data collected in real time, the contour line range of the water surface is obtained so as to obtain a three-dimensional model adjusted vertically according to the real-time water level through the surface model construction method.

7. The method according to claim 5, wherein: The step of generating a temperature-water depth variation curve according to the vertical temperature data, and fusing the temperature-water depth variation curve with the three-dimensional model to generate a temperature three-dimensional model includes: In response to the number of the vertical temperature sampling points being one, a temperature-water depth variation curve is obtained according to the vertical temperature data of the sampling point; and a vertical layered display is performed according to the temperature-water depth variation curve; In response to the number of vertical temperature sampling points being greater than one, a plurality of temperature-water depth variation curves are obtained according to the vertical temperature data of the plurality of sampling points; an isothermal surface is formed by uniform interpolation using the plurality of temperature-water depth variation curves for vertical layered display; The vertical layered display includes: Determining whether the slope of the temperature-water depth variation curve is greater than a threshold; If the maximum slope of the temperature-water depth variation curve is greater than a threshold, the vertical layers are sequentially represented as a surface water layer, an inclined surface layer, a clean water layer, and a bottom mud layer; different layers are three-dimensionally rendered with different colors and merged with the three-dimensional model; If the maximum slope of the temperature-water depth change curve is less than the threshold, it is determined whether the maximum temperature difference of the water body is greater than the threshold. If so, the water body is divided into three equal temperature intervals using the lateral temperature data and the lake bottom temperature data in the vertical temperature data, and then a bottom mud layer is superimposed; the three equal temperature intervals and the bottom mud layer are three-dimensionally rendered with different colors and merged with the three-dimensional model; if not, one equal temperature interval is displayed and a bottom mud layer is superimposed; one equal temperature interval and the bottom mud layer are three-dimensionally rendered with different colors and merged with the three-dimensional model.

8. The method according to claim 1, wherein: The obtaining of water body data comprises: The terrain data is obtained by using digital elevation model data in a preset range underwater and around; Bottom mud is collected by using a borehole sampling method, and the bottom mud is detected to obtain the bottom mud data of continuous changes of the lake bottom by an interpolation method; the bottom mud data includes thickness data and organic matter content data; Using a water level sensor to collect the water level of a preset water point in real time, and obtaining the water level data of the continuously changing water surface by interpolation method; Use temperature sensors to collect lateral temperature data of preset monitoring points on the surface of the water body; Determine the number of temperature sampling points of the vertical temperature according to the lateral temperature data for determining the vertical temperature data; Aquatic communities at preset monitoring sampling points are collected to obtain sampled biological distribution data; the aquatic communities include at least one of ephemera, ephemera plants, aquatic plants, fish animals and benthic animals.

9. The method according to claim 8, wherein: The step of determining the number of sampling points of the vertical temperature according to the lateral temperature data for determining the vertical temperature data comprises: Determining whether the discrete degree of the lateral temperature data is greater than a preset degree; If not, then based on a temperature sampling point, vertical temperature data is obtained using temperature sensors at different depths vertical to the sampling point; If so, for each temperature sampling point of the lateral temperature data, the vertical temperature data of the temperature sampling point is collected to obtain the vertical temperature data.

10. A device for identifying the source of organic matter on the lake bottom, characterized in that: The device can be used to implement the method according to any one of claims 1 to 9, and the device comprises: A collection module, used to obtain water body data; the water body data includes at least one of topographic data, sediment data, water level data, temperature data and sampled biological distribution data; the temperature data includes vertical temperature data and lateral temperature data; the sampled biological distribution data includes at least the number of aquatic communities obtained by monitoring a sampling point; A model module, for obtaining overall biological distribution data according to the temperature data and the sampled biological distribution data; the overall biological distribution data is the spatial distribution of aquatic communities; and generating a fused three-dimensional model using the overall biological distribution data and the water body data; The identification module is used to identify the source of lake bottom organic matter based on the fused three-dimensional model.

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