Dynamic river health monitoring method and device, electronic equipment and storage medium

Abstract

The invention discloses a dynamic river health monitoring method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining the multi-source data related to a river basin, constructing a river basin map based on the multi-source data, and positioning the position of a pollution source according to the river basin map, the method comprises the following steps: constructing a three-dimensional map according to geographic information of a river basin and a river basin map, marking a pollution source position to the three-dimensional map, carrying out dynamic health monitoring on the river basin by adopting the marked three-dimensional map, and intelligently monitoring a dynamic river by combining multi-source data fusion, map construction and three-dimensional dynamic visualization. The pollution source tracing efficiency and accuracy can be improved, and the water pollution problem can be quickly positioned and treated.

Description

Technical Field

[0001] This application relates to the technical field of watershed management, and particularly to a method, device, electronic device, and storage medium for dynamic river health monitoring. Background Art

[0002] In current river basin management, the efficiency of water resource monitoring and water pollution prevention and control is generally low, and related technologies are often limited to a single data source or a single monitoring method, resulting in the management of water resources being unable to reflect the basin situation in a timely and comprehensive manner. Most existing technologies rely on static water level data and water quality detection, lacking the ability to trace pollution sources and provide real-time warnings. Although some systems have introduced big data technology, there are still deficiencies in the integration and analysis of basin data.

[0003] In related technologies, most traditional water conservancy management systems rely on manual inspections, unable to monitor the river ecological status in real time and difficult to accurately trace pollution sources. Even with some intelligent monitoring means, the overall level of intelligence and automation has not reached the expected level, affecting the efficient management of water resources and the accuracy of decision-making. Summary of the Invention

[0004] In view of the above problems, this application provides a method for dynamic river health monitoring to at least solve the problems existing in related technologies.

[0005] In a first aspect, an embodiment of this application provides a method for dynamic river health monitoring, the method comprising:

[0006] Obtain multi-source data related to the river basin;

[0007] Based on the multi-source data, construct a river basin map and locate the pollution source position according to the river basin map;

[0008] Construct a 3D map according to the geographical information of the river basin and the river basin map, and mark the pollution source position on the 3D map;

[0009] Use the marked 3D map to perform dynamic health monitoring on the river basin.

[0010] In some embodiments, the constructing a river basin map based on the multi-source data and locating the pollution source according to the river basin map includes:

[0011] Based on the multi-source data, construct a river basin map including geographical entity nodes and pollution propagation relationship edges, wherein the multi-source data includes: water level data, water quality data, meteorological data, terrain data, and sewage discharge data;

[0012] Determine the pollution path based on the river basin atlas, and trace the target pollutants using the pollution path;

[0013] Locate the pollution source position according to the contribution rate of the target pollution source to the pollutants.

[0014] In some embodiments, the constructing a three-dimensional map based on the geographical information of the river basin and the river basin atlas, and marking the pollution source position on the three-dimensional map includes:

[0015] Generate a water level visualization three-dimensional map using GIS technology based on the geographical information of the river basin and the river basin;

[0016] Mark the pollution source position on the water level visualization three-dimensional map, and display the pollution concentration distribution through icons or heat maps.

[0017] In some embodiments, a dynamic river health monitoring method further includes:

[0018] Use the ARIMA-BPNN combined model to perform spatio-temporal prediction on the water level index and water quality index of the river basin.

[0019] In some embodiments, a dynamic river health monitoring method further includes:

[0020] Obtain a user's first operation instruction to zoom and rotate the three-dimensional map based on the first operation instruction;

[0021] Obtain a user's second operation instruction to filter the water level and pollution conditions of the river basin with target conditions, where the target conditions include: time, area, and pollution type;

[0022] Obtain a user's third operation instruction to display the real-time water level and pollution indicators of the target area in the water level visualization three-dimensional map.

[0023] In some embodiments, a dynamic river health monitoring method further includes:

[0024] When it is confirmed that the monitoring is abnormal during the dynamic health monitoring of the river basin using the marked three-dimensional map, generate a color prompt and / or trigger an alarm on the three-dimensional map;

[0025] When the monitoring abnormality meets the preset inspection threshold, use a drone to verify the pollution source corresponding to the monitoring abnormality.

[0026] In some embodiments, a dynamic river health monitoring method further includes:

[0027] Use color coding or contour coding to distinguish different pollution level areas in the river basin;

[0028] Establish a sliding time axis to view the pollution diffusion process.

[0029] In a second aspect, an embodiment of the present application provides a dynamic river health monitoring device, including:

[0030] An acquisition module, configured to acquire multi-source data related to the river basin;

[0031] A positioning module, configured to construct a river basin map based on the multi-source data and locate pollution sources according to the river basin map;

[0032] A marking module, configured to construct a three-dimensional map based on the geographical information of the river basin and the river basin map, and mark the pollution sources on the three-dimensional map;

[0033] A monitoring module, configured to perform dynamic health monitoring on the river basin by using the marked three-dimensional map.

[0034] In a third aspect, an embodiment of the present application provides an electronic device, including a memory and a processor. A program code that can run on the processor is stored on the memory. When the program code is executed by the processor, the dynamic river health monitoring method introduced in any implementation manner of the first aspect is implemented.

[0035] In a fourth aspect, an embodiment of the present application provides a computer storage medium. The computer storage medium stores one or more programs, and the one or more programs can be executed by the electronic device introduced in the third aspect to implement the dynamic river health monitoring method introduced in any implementation manner of the first aspect.

[0036] A dynamic river health monitoring method, device, electronic device and storage medium provided by an embodiment of the present application. A dynamic river health monitoring method includes: acquiring multi-source data related to the river basin, constructing a river basin map based on the multi-source data, locating the position of the pollution source according to the river basin map, constructing a three-dimensional map based on the geographical information of the river basin and the river basin map, marking the position of the pollution source on the three-dimensional map, and performing dynamic health monitoring on the river basin by using the marked three-dimensional map. By combining multi-source data fusion, map construction, and three-dimensional dynamic visualization to intelligently monitor the dynamic river, the efficiency and accuracy of pollution source tracing can be improved, and water pollution problems can be quickly located and processed.

[0037] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become easily understandable through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In the following, the present application will be described in more detail based on embodiments with reference to the accompanying drawings.

[0039] Figure 1 FIG. shows a schematic flow diagram of a dynamic river health monitoring method proposed in an embodiment of the present application;

[0040] Figure 2 FIG. shows schematic diagrams of each processing link of an exemplary dynamic river health monitoring proposed in an embodiment of the present application;

[0041] Figure 3 FIG. shows a structural block diagram of an exemplary dynamic river health monitoring device proposed in an embodiment of the present application;

[0042] Figure 4 FIG. shows a structural block diagram of an electronic device for executing the dynamic river health monitoring method according to an embodiment of the present application;

[0043] Figure 5 FIG. shows a computer-readable storage medium for storing or carrying an implementation of the dynamic river health monitoring method according to an embodiment of the present application. Detailed Embodiments

[0044] To make the objectives, technical solutions, and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below in combination with embodiments and the accompanying drawings. The illustrative embodiments and descriptions thereof of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0045] In the prior art, most water conservancy management systems rely on manual inspections, unable to monitor the river ecological status in real time, and it is difficult to accurately trace pollution sources. Even with some intelligent monitoring means, the overall level of intelligence and automation still fails to meet expectations, affecting the efficient management of water resources and the accuracy of decision-making.

[0046] To address the above technical problems, the present application proposes a dynamic river health monitoring method, device, electronic device, and storage medium to integrate multi-source data and combine big data analysis, knowledge graphs, and intelligent monitoring, etc., to improve the efficiency of water resource management and water pollution prevention and control. Among them, the dynamic river health monitoring method will be described in detail in subsequent embodiments.

[0047] Next, the application scenarios of the dynamic river health monitoring method provided in the embodiments of the present application will be introduced:

[0048] Please refer to Figure 1 , Figure 1This is a schematic flowchart of a dynamic river health monitoring method provided in an embodiment of the present application. In this embodiment, the dynamic river health monitoring method can be applied to a dynamic river health monitoring device 300 as shown in Figure 3 and an electronic device 200 as shown in Figure 4 . Among them, the electronic device can include one or more. Information can be transmitted between multiple electronic devices in a wireless and / or wired manner. Multiple electronic devices can cooperate to complete the dynamic river health monitoring method. Exemplarily, the electronic device can include a computer, a mobile terminal, a tablet, etc., and the present application does not limit it. A dynamic river health monitoring method of the present application can include S110 to S140.

[0049] S110: Obtain multi-source data related to the river basin.

[0050] In an embodiment of the present application, the multi-source data includes: water level data, water quality data, meteorological data, terrain data, and sewage discharge data.

[0051] Among them, during the data acquisition process, water quality monitoring data of downstream pollution areas, general surveys of pollution sources, geographical information (such as river flow direction, basin distribution, etc.), and historical pollution event data can also be collected.

[0052] S120: Construct a river basin map based on the multi-source data, and locate the pollution source location according to the river basin map.

[0053] In some embodiments, S120 includes S121 to S123.

[0054] S121: Construct a river basin map that includes geographical entity nodes and pollution propagation relationship edges based on the multi-source data.

[0055] In an embodiment of the present application, based on the collected data, the ontology structure of the knowledge graph is constructed. Pollution sources (such as industrial pollution, agricultural pollution, domestic pollution, etc.), pollutants (such as chemical oxygen demand, ammonia nitrogen, etc.), and geographical locations (such as rivers, basins, etc.) are used as nodes, and the relationships between them (such as "pollution source → pollutant", "pollutant → pollution area") are used as edges.

[0056] S122: Determine the pollution path based on the river basin map, and trace the target pollutant using the pollution path.

[0057] In an embodiment of the present application, starting from the abnormal water quality indicators in the downstream pollution area, the source path of the pollutant is traced through relationship reasoning in the knowledge graph. For example, according to the link of "abnormal water quality indicators → pollutant → pollution source", the possible pollution source is determined.

[0058] In some embodiments, a three-dimensional map service can be utilized to further narrow down the scope of the pollution source by combining geographical information such as river flow directions and basin distributions. For example, through map analysis, it is determined that the pollution source may be located in a certain area upstream of the river.

[0059] S123: Locate the pollution source position according to the contribution rate of the target pollution source to the pollutant.

[0060] In the embodiments of the present application, the specific pollution source position is located according to the contribution rate of the pollution source to the pollutant in the knowledge graph. For example, if a certain pollutant mainly comes from agricultural non-point source pollution, the agricultural activities in this area can be further queried.

[0061] S130: Construct a three-dimensional map based on the geographical information of the river basin and the river basin atlas, and mark the pollution source position on the three-dimensional map.

[0062] In some embodiments, S130 includes S131 to S132.

[0063] S131: Generate a three-dimensional map of water level visualization using GIS technology based on the geographical information of the river basin and the river basin.

[0064] In this embodiment, a three-dimensional map is constructed using Geographic Information System (GIS) technology, combining geographical spatial information with real-time data. The map can display the three-dimensional terrain of water bodies such as rivers, lakes, and reservoirs, intuitively presenting the distribution and terrain characteristics of the water bodies.

[0065] S132: Mark the pollution source position on the three-dimensional map of water level visualization, and display the pollution concentration distribution through icons or heat maps.

[0066] In the embodiments of the present application, the water level height is displayed in real time on the three-dimensional map in the form of color coding or contour lines. For example, different colors are used to represent different water level intervals, with high water level areas represented by red and normal water levels represented by green; the positions of pollution sources are marked on the map, and the pollution concentration distribution is displayed in the form of icons or heat maps, and the heat map can more intuitively display the diffusion range and intensity of the pollution.

[0067] S140: Dynamically monitor the health of the river basin using the marked three-dimensional map.

[0068] In the embodiments of the present application, through the integration of multi-source data, a comprehensive river basin atlas can be constructed, which can be extended to the management of other basins, with strong generality and scalability. Combining multi-source data fusion, atlas construction, three-dimensional dynamic visualization intelligent monitoring of dynamic rivers can achieve comprehensive control and accurate prediction of water resources, improve the utilization efficiency of water resources, and can be applicable to scenarios with different basins and different management requirements.

[0069] In some embodiments, a dynamic river health monitoring method further includes:

[0070] Using the ARIMA - BPNN combined model to perform spatio - temporal prediction on the water level index and water quality index of the river basin.

[0071] In the embodiments of the present application, it is implemented through the combined model of the water level prediction algorithm ARIMA and the water quality prediction algorithm backpropagation neural network (BPNN).

[0072] Among them, the water level prediction can be achieved through various models, and the specific selection depends on the characteristics of the data (such as linearity, non - linearity, seasonality, etc.).

[0073] The following is the optimized model:

[0074] Autoregressive Integrated Moving Average Model (ARIMA)

[0075] It is applicable to water level data with linear trends and seasonal characteristics. The ARIMA model transforms the non - stationary time series into a stationary series through differencing (I), and then combines the autoregressive (AR) and moving average (MA) parts for modeling.

[0076] Model formula: ARIMA(p, d, q): where p is the order of the autoregressive term, d is the differencing order, and q is the order of the moving average term.

[0077] The model expression is:

[0079] (1 - \sum_{i = 1}^{p}\phi_i L^i)(1 - L)^d X_t=(1+\sum_{j = 1}^{q}\theta_jL^j)\epsilon_t

[0081] Among them, (L) is the lag operator, (\phi_i) is the autoregressive parameter, (\theta_j) is the moving average parameter, and (\epsilon_t) is white noise.

[0082] Water quality prediction algorithm

[0083] Water quality prediction involves modeling the dynamic changes of water quality indicators (such as dissolved oxygen, total phosphorus, ammonia nitrogen, etc.).

[0084] The following is the optimized model:

[0085] The model expression is:

[0086] The ARIMA part is the same as above.

[0087] ​​BPNN: Model the non - linear relationship through a multi - layer perceptron network. The expression for its forward propagation is:

[0089] y = f(\sum_{i = 1}^{n}w_i x_i + b)

[0091] where (f) is the activation function (such as sigmoid or ReLU), (w_i) are the weights, and (b) is the bias.

[0092] The pollution source tracing model is as follows:

[0093] The pollution source tracing model is used to identify the sources and propagation paths of pollutants. The following is the optimized model:

[0094] Receptor model based on factor analysis

[0095] By analyzing the composition and concentration of pollutants in water samples, they are reduced to a few factors, and each factor represents a pollution source, thereby determining the contribution of the pollution source.

[0096] Model expression:

[0097] Factor analysis model:

[0099] X = F\cdot A+E

[0101] where (X) is the observed data matrix, (F) is the factor score matrix, (A) is the factor loading matrix, and (E) is the error matrix.

[0102] Traceability model based on machine learning

[0103] Use algorithms such as neural networks and support vector machines (SVM), and through training on known pollution source data, establish a mapping relationship between pollution sources and pollutant concentrations.

[0104] Model expression:

[0105] SVM: Classify or regress based on the principle of maximum margin. Its optimization problem is:

[0107] \min_{w,b}\frac{1}{2}|w|^2 + C\sum_{i = 1}^{n}\xi_i

[0109] where (w) is the weight vector, (b) is the bias, (C) is the regularization parameter, and (\xi_i) are the slack variables.

[0110] ​​​​​​Neural network: It models complex non-linear relationships through a multi-layer perceptron, and its forward propagation formula is the same as that of BPNN.

[0111] In this embodiment, the above combined model can be used to analyze the pollutant component spectrum, train a multi-classification model based on historical pollution event data, and generate a tracing path by combining river flow direction data and a pollution diffusion model.

[0112] In some embodiments, a dynamic river health monitoring method further includes S210 to S230, where:

[0113] S210: Obtain a user's first operation instruction to scale and rotate a 3D map based on the first operation instruction.

[0114] In the embodiments of the present application, the user can view the detailed information on the map from macroscopic to microscopic through the scaling and rotation operations of the first operation instruction.

[0115] S220: Obtain a user's second operation instruction to filter the water level and pollution situation of the river basin under target conditions based on the second operation instruction, where the target conditions include: time, region, and pollution type.

[0116] In the embodiments of the present application, the user can set and filter data according to the second operation instruction with conditions such as time, region, and pollution type, focusing on the water level and pollution situation in a specific region or time period.

[0117] S230: Obtain a user's third operation instruction to display the real-time water level and pollution indicators of the target area in the water level visualization 3D map based on the third operation instruction.

[0118] In the embodiments of the present application, by clicking on a certain point or area on the map, a detailed information box can pop up to display data such as the real-time water level and pollution indicators of the area.

[0119] In some embodiments, a dynamic river health monitoring method further includes S240 to S250, where:

[0120] S240: When it is confirmed that the monitoring is abnormal during the dynamic health monitoring of the river basin using the marked 3D map, generate a color prompt and / or trigger an alarm in the 3D map.

[0121] In the embodiments of the present application, through methods such as color coding and threshold alarms, areas with abnormal water levels or excessive pollution are quickly identified. Once the data exceeds the normal range, the system automatically triggers an alarm to remind decision-makers to take measures.

[0122] S250: When the monitoring abnormality meets the preset inspection threshold, use a drone to verify the pollution source corresponding to the monitoring abnormality.

[0123] In the embodiments of the present application, for the identified abnormal situations, the system will issue early warning information in real time, support the rapid response and decision-making of unmanned aerial vehicles, identify potential faults or abnormal situations, such as dike cracks, seepage, equipment aging, etc., and can also achieve multi-source data verification: combining multi-source data such as remote sensing monitoring and on-site monitoring to verify the inference results of the river basin atlas.

[0124] In some embodiments, a dynamic river health monitoring method further includes S260 to S270, where:

[0125] S260: Use color coding or contour coding to distinguish different pollution level areas in the river basin;

[0126] S270: Establish a sliding time axis to view the pollution diffusion process.

[0127] In this embodiment, by using different display methods in combination with the basin conditions, the pollution levels and the diffusion of pollution in different time periods are better displayed, so as to provide a basis for finding and rectifying the upstream pollution sources according to the prediction results. For example, it is recommended to strengthen the treatment of industrial wastewater or the control of agricultural non-point source pollution in a certain area, and better display the water quality changes after the rectification of the pollution sources.

[0128] Applied to the above content, refer to Figure 2 For each processing link of the dynamic river health monitoring shown in each processing link of the dynamic river health monitoring, the present application can achieve real-time monitoring of water level changes, meteorological conditions and water quality changes by using the big data of a certain river basin in combination with three-dimensional map services. Through big data analysis, the water level changes in the next few days are predicted, and early warnings are given for possible water pollution situations.

[0129] In a certain area, based on the dynamic river health monitoring method of the present invention, the sewage discharge behavior of a certain factory upstream was successfully traced, and the specific pollution source was located in combination with a three-dimensional map. The water quality model was used to predict the pollution diffusion, and corresponding measures were taken in time to avoid the spread of pollution.

[0130] Based on the dynamic river health monitoring method of the present invention, a certain area has realized the intelligent scheduling of multiple reservoirs, allocated water resources through an optimization algorithm, guaranteed the agricultural irrigation and urban water use demands, and improved the water use efficiency.

[0131] In summary, through the integration of multi-source data, this application constructs a comprehensive river basin atlas. This technology can be extended and applied to the management of other basins, with strong versatility, scalability, and displayability. By combining three-dimensional map services and knowledge graph technology, the present invention provides a new solution in the field of water resource management, enabling comprehensive control and accurate prediction of water resources, optimizing water resource scheduling through algorithms, improving the utilization efficiency of water resources, and being applicable to scenarios of different basins and different management requirements. The intelligent inspection combined with unmanned aerial vehicles and remote sensing technology can provide automated support for the management of river basins and reduce the workload of manual inspections.

[0132] Please refer to Figure 3 , Figure 3 which is a structural block diagram of a dynamic river health monitoring device provided by this application and is applied to a hot standby multicast system. The hot standby multicast system includes a service processing unit, a switch, and a client. The switch is respectively connected to each end device and the client in the service processing unit. A dynamic river health monitoring device 300 includes: an acquisition module 310, a positioning module 320, a marking module 330, and a monitoring module 340, where:

[0133] The acquisition module 310 is used to acquire multi-source data related to the river basin.

[0134] The positioning module 320 is used to construct a river basin atlas based on the multi-source data and locate the pollution sources according to the river basin atlas.

[0135] The marking module 330 is used to construct a three-dimensional map according to the geographical information of the river basin and the river basin atlas, and mark the pollution sources on the three-dimensional map.

[0136] The monitoring module 340 is used to perform dynamic health monitoring on the river basin using the marked three-dimensional map.

[0137] The device embodiments in this application may further include other modules, which specifically correspond to the content in the above method part.

[0138] It should be noted that the device embodiments in this application correspond to the foregoing method embodiments. The specific principles in the device embodiments can be referred to the content in the foregoing method embodiments and will not be elaborated here.

[0139] In several embodiments provided in this embodiment, the coupling between modules can be electrical, mechanical, or other forms of coupling.

[0140] In addition, in each embodiment of the present invention, each functional module can be integrated into a processing module, or each module can exist physically alone, or two or more modules can be integrated into one module. The above integrated module can be implemented in the form of hardware or in the form of a software functional module.

[0141] Please refer to Figure 4 , Figure 4 which is a structural block diagram of an electronic device 200 that can execute the above-mentioned dynamic river health monitoring method provided by an embodiment of the present application. The electronic device 200 can be a device such as a smart phone, a tablet computer, a computer, or a portable computer.

[0142] The electronic device 200 further includes a processor 202 and a memory 204. Among them, a program that can execute the content in the foregoing embodiments is stored in the memory 204, and the processor 202 can execute the program stored in the memory 204.

[0143] Among them, the processor 202 can include one or more cores for processing data and a message matrix unit. The processor 202 connects various parts within the entire electronic device 200 through various interfaces and lines, and by running or executing instructions, programs, code sets, or instruction sets stored in the memory 204, and by calling data stored in the memory 204, it executes various functions of the electronic device 200 and processes data. Optionally, the processor 202 can be implemented in at least one hardware form of digital signal processing (DSP), field-programmable gate array (FPGA), or programmable logic array (PLA). The processor 202 can integrate one or a combination of several of a central processing unit (CPU), a graphics processing unit (GPU), and a modem decoder, etc. Among them, the CPU mainly processes the operating system, user interface, and application programs, etc.; the GPU is responsible for rendering and drawing the display content; the modem is used to process wireless communication. It can be understood that the above-mentioned modem decoder can also be not integrated into the processor and be implemented separately through a communication chip.

[0144] The memory 204 may include a Random Access Memory (RAM), or may also include a Read-Only Memory. The memory 204 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 204 may include a program storage area and a data storage area. The program storage area may store instructions for implementing an operating system, instructions for implementing at least one function (such as instructions for a user to obtain a random number), instructions for implementing the following various method embodiments, etc. The data storage area may also store data created during the use of the terminal (such as random numbers), etc.

[0145] The electronic device 200 may further include a network module and a screen. The network module is used to receive and send electromagnetic waves, and implement the mutual conversion between electromagnetic waves and electrical signals, so as to communicate with a communication network or other devices, for example, communicate with an audio playback device. The network module may include various existing circuit elements for performing these functions, such as antennas, radio frequency transceivers, digital signal processors, encryption / decryption chips, subscriber identity module (SIM) cards, memories, and so on. The network module can communicate with various networks such as the Internet, enterprise intranets, wireless networks, or communicate with other devices through a wireless network. The above-mentioned wireless network may include a cellular phone network, a wireless local area network, or a metropolitan area network. The screen can display interface content and perform data interaction.

[0146] Please refer to Figure 5 , Figure 5 which shows a structural block diagram of a computer-readable storage medium provided by an embodiment of the present application. Program code 410 is stored in the computer-readable storage medium 400, and the program code 410 can be called by a processor to execute the methods described in the above method embodiments.

[0147] The computer-readable storage medium 400 may be an electronic memory such as a flash memory, an Electrically Erasable Programmable Read-Only Memory (EEPROM), an EPROM, a hard disk, or a ROM. Optionally, the computer-readable storage medium includes a non-transitory computer-readable storage medium. The computer-readable storage medium 400 has a storage space for the program code 410 for executing any method steps in the above methods. These program code 410 can be read out from or written into one or more computer program products. The program code 410 can be compressed in an appropriate form, for example.

[0148] The embodiments of the present application also provide a computer program product or a computer program. The computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the dynamic river health monitoring method described in the above various optional implementation manners.

[0149] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for dynamically monitoring river health, characterized in that, The method includes: Obtaining multi-source data related to the river basin; Constructing a river basin atlas based on the multi-source data, and locating the pollution source location according to the river basin atlas; Constructing a 3D map according to the geographical information of the river basin and the river basin atlas, and marking the pollution source location on the 3D map; Performing dynamic health monitoring on the river basin using the marked 3D map.

2. The dynamic river health monitoring method according to claim 1, characterized in that The constructing a river basin atlas based on the multi-source data and locating the pollution source according to the river basin atlas includes: Constructing a river basin atlas including geographical entity nodes and pollution propagation relationship edges based on the multi-source data, where the multi-source data includes: water level data, water quality data, meteorological data, terrain data, and sewage discharge data; Determining the pollution path based on the river basin atlas, and tracing the target pollutant using the pollution path; Locating the pollution source location according to the contribution rate of the target pollution source to the pollutant.

3. The dynamic river health monitoring method according to claim 1, characterized in that The constructing a 3D map according to the geographical information of the river basin and the river basin atlas and marking the pollution source location on the 3D map includes: Generating a water level visualization 3D map according to the geographical information of the river basin and the river basin using GIS technology; Marking the pollution source location on the water level visualization 3D map, and displaying the pollution concentration distribution through icons or heat maps.

4. A dynamic river health monitoring method according to claim 1, characterized in that The method further includes: Performing spatio-temporal prediction on the water level index and water quality index of the river basin using an ARIMA-BPNN combined model.

5. The dynamic river health monitoring method according to claim 3, characterized in that The method further includes: Obtaining a user's first operation instruction to zoom and rotate the 3D map based on the first operation instruction; Obtaining a user's second operation instruction to screen the water level and pollution conditions of the river basin under target conditions, where the target conditions include: time, region, and pollution type; Obtaining a user's third operation instruction to display the real-time water level and pollution indicators of the target area in the water level visualization 3D map based on the third operation instruction.

6. The dynamic river health monitoring method according to claim 1, characterized in that The method further includes: When it is confirmed that the monitoring is abnormal during the dynamic health monitoring of the river basin using the marked 3D map, generating a color prompt and / or triggering an alarm on the 3D map; When the monitoring abnormality meets the preset inspection threshold, using a drone to verify the pollution source corresponding to the monitoring abnormality.

7. A dynamic river health monitoring method according to claim 1, characterized in that, The method further includes: Using a color coding method or a contour coding method to distinguish different pollution level areas of the river basin; Establishing a sliding time axis to view the pollution diffusion process.

8. A dynamic river health monitoring device, characterized in that, The device includes: An acquisition module for obtaining multi-source data related to the river basin; A positioning module for constructing a river basin atlas based on the multi-source data and locating the pollution source according to the river basin atlas; A marking module for constructing a 3D map according to the geographical information of the river basin and the river basin atlas, and marking the pollution source on the 3D map; A monitoring module for performing dynamic health monitoring on the river basin using the marked 3D map.

9. An electronic device, characterized in that, The electronic device includes a memory and a processor, and program code that can run on the processor is stored on the memory. When the program code is executed by the processor, a dynamic river health monitoring method as described in any one of claims 1-7 is implemented.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores program code, and the program code can be called and executed by one or more processors to implement a dynamic river health monitoring method as described in any one of claims 1-7.

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