A river and lake health monitoring method and system based on data fusion

Abstract

The present invention discloses a river and lake health monitoring method and system based on data fusion, aiming to provide a comprehensive and effective river and lake health assessment and prediction system. The present invention evaluates the health status of each river and lake sub-region, quantifies the health self-repair ability of the river and lake sub-region, and obtains the health self-repair index of the river and lake sub-region. By comparing the health differences of adjacent river and lake sub-regions, the regional health change trend of the target river and lake is revealed. The health status of the river and lake sub-regions in the target river and lake is predicted to form the prediction results of the health status change of each river and lake sub-region. Finally, the present invention corrects the prediction results of the health status change based on the health self-repair index of the river and lake sub-region, and determines the health restoration priority plan for each river and lake sub-region. The data fusion method of the present invention comprehensively considers ecological and environmental factors, and provides strong support for scientific and reasonable river and lake health management.

Description

Technical Field

[0001] The present invention relates to the technical field of river and lake health monitoring, and in particular to a river and lake health monitoring method and system based on data fusion. Background Art

[0002] River and lake ecosystems are one of the important ecosystems in nature, playing a key role in maintaining biodiversity and clean water quality. However, due to the influence of human activities and natural factors, many river and lake ecosystems are facing health problems, such as water pollution and biodiversity reduction. Therefore, developing a river and lake health monitoring method based on data fusion to fully understand the health status of river and lake sub-regions and predict possible health problems in advance is of great significance to maintaining the health of river and lake ecosystems.

[0003] Traditional river and lake monitoring methods usually rely on a single type of data, such as water monitoring data or biodiversity data. This single data source monitoring method is difficult to comprehensively assess the health of river and lake ecosystems and tends to ignore multiple factors. In addition, existing monitoring methods usually lack analysis of the self-repair capacity of river and lake sub-regions and the health differences between adjacent regions, resulting in insufficient comprehensive understanding of the overall status of the ecosystem.

[0004] The present invention makes full use of the advantages of multi-source data and improves the comprehensiveness and accuracy of river and lake health monitoring by comprehensively analyzing various monitoring data. At the same time, by considering the self-repair ability and the differences between adjacent areas, it provides a scientific basis for formulating accurate health restoration plans. Summary of the invention

[0005] In order to solve at least one of the above technical problems, the present invention proposes a river and lake health monitoring method and system based on data fusion.

[0006] A first aspect of the present invention provides a river and lake health monitoring method based on data fusion, comprising:

[0007] Periodically obtain regional health monitoring data of multiple river and lake sub-areas in the target river and lake, wherein the regional health monitoring data includes biodiversity data and water pollutant concentration data;

[0008] Conducting a health assessment on each river and lake sub-region based on the regional health monitoring data to obtain a periodic health assessment report for each river and lake sub-region;

[0009] Analyzing the health self-repair capacity of the river and lake sub-regions in the periodic health assessment report to obtain a health self-repair index of the river and lake sub-regions;

[0010] Analyze the health differences of adjacent river and lake sub-regions based on periodic health assessment reports, and analyze the regional health change trends of target rivers and lakes based on the health differences;

[0011] Randomly obtain the preset single-region health change monitoring data of a river or lake sub-region, and predict the health status of other river or lake sub-regions in the target river or lake based on the regional health change trend and the single-region health monitoring data, and obtain the health status change prediction result of each river or lake sub-region;

[0012] The health status change prediction result is corrected based on the health self-repair index of the river and lake sub-region, and the health restoration priority plan for each river and lake sub-region is determined.

[0013] In this solution, the regional health monitoring data of multiple river and lake sub-areas in the target river and lake are periodically obtained. The regional health monitoring data includes biodiversity data and water pollutant concentration data, specifically:

[0014] Divide the target river or lake into multiple river or lake sub-areas;

[0015] The fish species and quantity, plant species and quantity information of the plurality of river and lake sub-regions are obtained with a monthly data collection cycle, and the biodiversity of each river and lake sub-region is evaluated based on the fish species and quantity, plant species and quantity information to obtain biodiversity data;

[0016] Acquire water pollutant concentration data for each river and lake sub-area according to the data collection cycle;

[0017] The biodiversity data and water pollutant concentration data are integrated into regional health monitoring data.

[0018] In this solution, the health assessment is performed on each river and lake sub-region based on the regional health monitoring data to obtain a periodic health assessment report for each river and lake sub-region, specifically:

[0019] Set the health impact weight of each item in the regional health monitoring data on the river and lake sub-region according to the preset proportion;

[0020] The Simpson diversity index was introduced to calculate each river and lake sub-region to obtain the biodiversity index of each river and lake sub-region;

[0021] Based on the ecological data of target rivers and lakes, determine the biodiversity index thresholds and water pollutant concentration thresholds for sub-regions of rivers and lakes under unhealthy conditions;

[0022] The water pollutant concentration data and biodiversity index of each river and lake sub-region are compared with the biodiversity index threshold and the water pollutant concentration threshold, and a health assessment is performed on each river and lake sub-region based on the health impact weight to obtain a periodic health assessment report for each river and lake sub-region.

[0023] In this solution, the health self-repair capacity of the river and lake sub-regions is analyzed in the periodic health assessment report to obtain the health self-repair index of the river and lake sub-regions, specifically:

[0024] Marking the river and lake sub-areas with health problems according to the periodic health monitoring report to obtain marked sub-areas;

[0025] Sort the periodic health monitoring reports of the marked sub-areas by time series to obtain a time series health monitoring table for each marked sub-area;

[0026] Draw a biodiversity change graph and a water pollutant concentration change graph based on the time series health monitoring table;

[0027] Calculate the average value of periodic changes in biodiversity and the average value of periodic changes in water pollutant concentrations in the biodiversity change graph and water pollutant concentration change graph;

[0028] The health self-repair capacity of the river and lake sub-regions is evaluated based on the periodic variation average values ​​of biodiversity and the periodic variation average values ​​of water pollutant concentrations, and the health self-repair index of the river and lake sub-regions is obtained.

[0029] In this scheme, the health differences of adjacent river and lake sub-regions are analyzed based on periodic health assessment reports, and the regional health change trends of target rivers and lakes are analyzed based on the health differences, specifically:

[0030] Extract information on fish species and abundance and plant species and abundance for each river and lake sub-area based on periodic health assessment reports;

[0031] Import the fish species and quantity information of two adjacent river and lake sub-areas into sets A and B respectively;

[0032] Calculate the intersection and union of sets A and B, introduce the Jaccard similarity coefficient, divide the size of the intersection by the size of the union, and get the similarity coefficient of fish species and quantity in adjacent river and lake sub-areas;

[0033] Calculate the similarity coefficients of plant species and quantities in adjacent river and lake sub-regions, and analyze the health differences of adjacent river and lake sub-regions based on the similarity coefficients of fish species and quantities and plant species and quantities, wherein the health differences include differences in biodiversity and differences in water pollutant concentrations;

[0034] The health differences of adjacent river and lake sub-regions in regional continuity are plotted into health difference curve change diagrams;

[0035] The regional health change trend within the preset range of the target rivers and lakes is analyzed based on the health difference curve change diagram.

[0036] In this scheme, the preset single-region health change monitoring data of a river or lake sub-region is randomly obtained, and the health status of other river or lake sub-regions in the target river or lake is predicted based on the regional health change trend and the single-region health monitoring data, and the health status change prediction result of each river or lake sub-region is obtained, specifically:

[0037] Randomly obtain the health monitoring data of a river or lake sub-area within a preset time period in the target river or lake to obtain the preset single-area health change monitoring data;

[0038] Introducing a Kriging model, fitting the Kriging model according to the regional health change trend, and introducing a spatial interpolation method to perform numerical prediction through the fitted Kriging model;

[0039] The preset single-region health change monitoring data is spatially interpolated according to the Kriging model and spatial interpolation method, and the health change status of other river and lake sub-regions in the target river and lake is predicted to obtain the predicted results of the health status change of each river and lake sub-region.

[0040] In this solution, the health self-repair index based on the river and lake sub-region corrects the health status change prediction result, and determines the health restoration priority plan for each river and lake sub-region, specifically:

[0041] Obtain the length of the preset time period, and calculate the self-repair degree of the river and lake sub-area according to the health self-repair index of the river and lake sub-area and the length of time;

[0042] Correcting the predicted health status change result based on the self-repair degree of the river and lake sub-region;

[0043] According to the health self-repair index of the river and lake sub-region, the health self-repair time length of each river and lake sub-region in the health status change results is evaluated to obtain the health self-repair time period of each river and lake sub-region;

[0044] If the healthy self-repair time period is greater than the preset time period, a health restoration priority plan for each river and lake sub-area is determined.

[0045] The second aspect of the present invention also provides a river and lake health monitoring system based on data fusion, the system comprising: a memory, a processor, the memory comprising a river and lake health monitoring method program based on data fusion, and when the river and lake health monitoring method program based on data fusion is executed by the processor, the following steps are implemented:

[0046] Periodically obtain regional health monitoring data of multiple river and lake sub-areas in the target river and lake, wherein the regional health monitoring data includes biodiversity data and water pollutant concentration data;

[0047] Conducting a health assessment on each river and lake sub-region based on the regional health monitoring data to obtain a periodic health assessment report for each river and lake sub-region;

[0048] Analyzing the health self-repair capacity of the river and lake sub-regions in the periodic health assessment report to obtain a health self-repair index of the river and lake sub-regions;

[0049] Analyze the health differences of adjacent river and lake sub-regions based on periodic health assessment reports, and analyze the regional health change trends of target rivers and lakes based on the health differences;

[0050] Randomly obtain the preset single-region health change monitoring data of a river or lake sub-region, and predict the health status of other river or lake sub-regions in the target river or lake based on the regional health change trend and the single-region health monitoring data, and obtain the health status change prediction result of each river or lake sub-region;

[0051] The health status change prediction result is corrected based on the health self-repair index of the river and lake sub-region, and the health restoration priority plan for each river and lake sub-region is determined.

[0052] In this solution, the health self-repair capacity of the river and lake sub-regions is analyzed in the periodic health assessment report to obtain the health self-repair index of the river and lake sub-regions, specifically:

[0053] Marking the river and lake sub-areas with health problems according to the periodic health monitoring report to obtain marked sub-areas;

[0054] Sort the periodic health monitoring reports of the marked sub-areas by time series to obtain a time series health monitoring table for each marked sub-area;

[0055] Draw a biodiversity change graph and a water pollutant concentration change graph based on the time series health monitoring table;

[0056] Calculate the average value of periodic changes in biodiversity and the average value of periodic changes in water pollutant concentrations in the biodiversity change graph and water pollutant concentration change graph;

[0057] The health self-repair capacity of the river and lake sub-regions is evaluated based on the periodic variation average values ​​of biodiversity and the periodic variation average values ​​of water pollutant concentrations, and the health self-repair index of the river and lake sub-regions is obtained.

[0058] In this scheme, the health differences of adjacent river and lake sub-regions are analyzed based on periodic health assessment reports, and the regional health change trends of target rivers and lakes are analyzed based on the health differences, specifically:

[0059] Extract information on fish species and abundance and plant species and abundance for each river and lake sub-area based on periodic health assessment reports;

[0060] Import the fish species and quantity information of two adjacent river and lake sub-areas into sets A and B respectively;

[0061] Calculate the intersection and union of sets A and B, introduce the Jaccard similarity coefficient, divide the size of the intersection by the size of the union, and get the similarity coefficient of fish species and quantity in adjacent river and lake sub-areas;

[0062] Calculate the similarity coefficients of plant species and quantities in adjacent river and lake sub-regions, and analyze the health differences of adjacent river and lake sub-regions based on the similarity coefficients of fish species and quantities and plant species and quantities, wherein the health differences include differences in biodiversity and differences in water pollutant concentrations;

[0063] The health differences of adjacent river and lake sub-regions in regional continuity are plotted into health difference curve change diagrams;

[0064] The regional health change trend within the preset range of the target rivers and lakes is analyzed based on the health difference curve change diagram.

[0065] The present invention discloses a river and lake health monitoring method and system based on data fusion, aiming to provide a comprehensive and effective river and lake health assessment and prediction system. The present invention evaluates the health status of each river and lake sub-region, quantifies the health self-repair ability of the river and lake sub-region, and obtains the health self-repair index of the river and lake sub-region. By comparing the health differences of adjacent river and lake sub-regions, the regional health change trend of the target river and lake is revealed. The health status of the river and lake sub-regions in the target river and lake is predicted to form the prediction results of the health status change of each river and lake sub-region. Finally, the present invention corrects the prediction results of the health status change based on the health self-repair index of the river and lake sub-region, and determines the health restoration priority plan for each river and lake sub-region. The data fusion method of the present invention comprehensively considers ecological and environmental factors, and provides strong support for scientific and reasonable river and lake health management. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1A flow chart of a river and lake health monitoring method based on data fusion according to the present invention is shown;

[0067] Figure 2 A flow chart showing the method of obtaining the health self-repair index of a river or lake sub-region according to the present invention is shown;

[0068] Figure 3 A flow chart showing the regional health change trend obtained by the present invention is shown;

[0069] Figure 4 A block diagram of a river and lake health monitoring system based on data fusion according to the present invention is shown. DETAILED DESCRIPTION

[0070] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0071] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0072] Figure 1 A flow chart of a river and lake health monitoring method based on data fusion of the present invention is shown.

[0073] like Figure 1 As shown, the first aspect of the present invention provides a river and lake health monitoring method based on data fusion, comprising:

[0074] S102, periodically obtaining regional health monitoring data of multiple river and lake sub-regions in the target river and lake, wherein the regional health monitoring data includes biodiversity data and water pollutant concentration data;

[0075] S104, performing a health assessment on each river and lake sub-region according to the regional health monitoring data to obtain a periodic health assessment report for each river and lake sub-region;

[0076] S106, analyzing the health self-repair capability of the river and lake sub-regions in the periodic health assessment report to obtain a health self-repair index of the river and lake sub-regions;

[0077] S108, analyzing the health differences of adjacent river and lake sub-regions based on the periodic health assessment report, and analyzing the regional health change trend of the target river and lake based on the health differences;

[0078] S110, randomly obtaining preset single-region health change monitoring data of a river or lake sub-region, and predicting the health status of other river or lake sub-regions in the target river or lake based on the regional health change trend and the single-region health monitoring data, to obtain a health status change prediction result for each river or lake sub-region;

[0079] S112, based on the health self-repair index of the river and lake sub-region, the predicted result of the health status change is corrected, and a health restoration priority plan for each river and lake sub-region is determined.

[0080] It should be noted that, if the target rivers and lakes are large enough, the health status of each river and lake sub-area will be different. By evaluating the health status of each river and lake sub-area in the target rivers and lakes, we can have a more detailed understanding of the health status of each river and lake sub-area in the target rivers and lakes, which will help to timely discover the health problems of each river and lake sub-area, and deal with the river and lake sub-areas with health problems in a targeted manner to prevent the health problems from spreading further and affecting other river and lake sub-areas. Since rivers and lakes have the ability to self-repair in an unhealthy state until they reach a healthy state, by analyzing the periodic health assessment reports, we can judge the health self-repair ability of the river and lake sub-areas and predict the changes in the health status of each river and lake sub-area within the preset time period. , and obtain the prediction result. Since the prediction result does not take into account the health self-repair ability of the river and lake sub-regions, the prediction result of the health status change is corrected according to the health self-repair index to make the prediction result more in line with the actual situation and reduce the prediction error. By predicting the health status of the river and lake sub-regions, the resource consumption of data monitoring can be reduced, and the problem of not being able to directly monitor data due to environmental reasons in the river and lake sub-regions can be avoided. Finally, the priority plan for health restoration is determined according to the health status of each river and lake sub-region, the health problems of the target rivers and lakes are accurately governed, and the governance priority of the river and lake sub-regions is determined, so as to avoid the further spread of health problems and improve governance efficiency. The target rivers and lakes include rivers and large lakes.

[0081] According to an embodiment of the present invention, the regional health monitoring data of multiple river and lake sub-areas in the target river and lake are periodically obtained, and the regional health monitoring data includes biodiversity data and water pollutant concentration data, specifically:

[0082] Divide the target river or lake into multiple river or lake sub-areas;

[0083] The fish species and quantity, plant species and quantity information of the plurality of river and lake sub-regions are obtained with a monthly data collection cycle, and the biodiversity of each river and lake sub-region is evaluated based on the fish species and quantity, plant species and quantity information to obtain biodiversity data;

[0084] Acquire water pollutant concentration data for each river and lake sub-area according to the data collection cycle;

[0085] The biodiversity data and water pollutant concentration data are integrated into regional health monitoring data.

[0086] According to an embodiment of the present invention, the health assessment of each river and lake sub-region is performed according to the regional health monitoring data to obtain a periodic health assessment report for each river and lake sub-region, specifically:

[0087] Set the health impact weight of each item in the regional health monitoring data on the river and lake sub-region according to the preset proportion;

[0088] The Simpson diversity index was introduced to calculate each river and lake sub-region to obtain the biodiversity index of each river and lake sub-region;

[0089] Based on the ecological data of target rivers and lakes, determine the biodiversity index thresholds and water pollutant concentration thresholds for sub-regions of rivers and lakes under unhealthy conditions;

[0090] The water pollutant concentration data and biodiversity index of each river and lake sub-region are compared with the biodiversity index threshold and the water pollutant concentration threshold, and a health assessment is performed on each river and lake sub-region based on the health impact weight to obtain a periodic health assessment report for each river and lake sub-region.

[0091] It should be noted that the Simpson diversity index is the Simpson diversity index. The value range of the Simpson index is 0 to 1. The closer the value is to 1, the lower the species diversity is, and the closer the value is to 0, the higher the species diversity is. The calculation formula of the Simpson index is as follows: d = 1-Σ(ni / N)^2, where d represents the Simpson index, ni represents the number of individuals of the i-th species, and N represents the total number of individuals in the entire ecosystem; the periodic health monitoring report is obtained under the condition that the health status of the river and lake sub-areas is not deteriorating.

[0092] Figure 2 A flow chart of obtaining the health self-repair index of a river or lake sub-region according to the present invention is shown.

[0093] According to an embodiment of the present invention, the periodic health assessment report is analyzed to determine the health self-repair capability of the river and lake sub-regions to obtain the health self-repair index of the river and lake sub-regions, specifically:

[0094] S202, marking the river and lake sub-areas with health problems according to the periodic health monitoring report to obtain marked sub-areas;

[0095] S204, sorting the periodic health monitoring reports of the marked sub-regions in time series to obtain a time series health monitoring table for each marked sub-region;

[0096] S206, drawing a biodiversity change graph and a water pollutant concentration change graph according to the time series health monitoring table;

[0097] S208, calculating the periodic variation average value of the biodiversity and the periodic variation average value of the water pollutant concentration in the biodiversity variation graph and the water pollutant concentration variation graph;

[0098] S210, evaluating the health self-repair capacity of the river and lake sub-regions according to the periodic variation average value of biodiversity and the periodic variation average value of water pollutant concentrations, and obtaining a health self-repair index of the river and lake sub-regions.

[0099] It should be noted that since rivers and lakes have the ability to resist unhealthy problems and can self-repair unhealthy conditions, the degree of health restoration in each health cycle is analyzed through periodic health monitoring reports to obtain the health self-repair index of the river and lake sub-area; the health self-repair index is calculated through the average value of the periodic changes in biodiversity and the average value of the periodic changes in water pollutant concentrations. The average daily changes in biodiversity and water pollutant concentrations in the river and lake sub-areas can be used to derive the average daily self-repair capacity of the river and lake sub-areas. The health restoration index of the river and lake sub-area is obtained by multiplying the daily increase in the biodiversity index and the decrease in the water pollutant concentration by the corresponding health impact weight.

[0100] Figure 3 A flow chart of obtaining regional health change trends according to the present invention is shown.

[0101] According to an embodiment of the present invention, the health differences of adjacent river and lake sub-regions are analyzed based on periodic health assessment reports, and the regional health change trend of target rivers and lakes is analyzed based on the health differences, specifically:

[0102] S302, extracting fish species and quantity information and plant species and quantity information of each river and lake sub-area based on the periodic health assessment report;

[0103] S304, importing the fish species and quantity information of two adjacent river and lake sub-areas into sets A and B respectively;

[0104] S306, calculating the intersection and union of sets A and B, introducing the Jaccard similarity coefficient, dividing the size of the intersection by the size of the union, and obtaining the similarity coefficients of fish species and numbers in adjacent river and lake sub-areas;

[0105] S308, calculating the similarity coefficients of plant species and quantities in adjacent river and lake sub-regions, and analyzing the health differences of adjacent river and lake sub-regions based on the similarity coefficients of fish species and quantities and plant species and quantities, wherein the health differences include differences in biodiversity and differences in water pollutant concentrations;

[0106] S310, plotting the health differences of adjacent river and lake sub-regions of regional continuity into a health difference curve change diagram;

[0107] S312, analyzing the regional health change trend within a preset interval of the target river or lake according to the health difference curve change diagram.

[0108] It should be noted that by introducing the Jaccard similarity coefficient to evaluate the health differences of two adjacent river and lake sub-regions, the regional health change trend of the target river and lake within the preset interval can be analyzed according to the progression of the region. The Jaccard similarity coefficient can quickly calculate the health differences of two adjacent river and lake sub-regions, reducing manual data calculations and avoiding the misjudgment of differences due to subjective factors; the A and B sets are a set that stores information on fish species and quantities in the same river and lake sub-region; the Jaccard similarity coefficient is a statistical indicator for measuring the similarity between two sets; the preset interval is composed of a preset number of continuous river and lake sub-regions.

[0109] According to an embodiment of the present invention, the preset single-region health change monitoring data of a river or lake sub-region is randomly obtained, and the health status of other river or lake sub-regions in the target river or lake is predicted based on the regional health change trend and the single-region health monitoring data, so as to obtain the prediction result of the health status change of each river or lake sub-region, specifically:

[0110] Randomly obtain the health monitoring data of a river or lake sub-area within a preset time period in the target river or lake to obtain the preset single-area health change monitoring data;

[0111] Introducing a Kriging model, fitting the Kriging model according to the regional health change trend, and introducing a spatial interpolation method to perform numerical prediction through the fitted Kriging model;

[0112] The preset single-region health change monitoring data is spatially interpolated according to the Kriging model and spatial interpolation method, and the health change status of other river and lake sub-regions in the target river and lake is predicted to obtain the predicted results of the health status change of each river and lake sub-region.

[0113] It should be noted that by obtaining the health change monitoring data of a river or lake sub-region to predict the health change status of other river or lake sub-regions within a preset time period, the consumption of data monitoring resources can be effectively reduced, and data gaps caused by the difficulty in obtaining health data of some river or lake sub-regions can be avoided; the introduction of spatial interpolation method can greatly improve the accuracy of prediction; the Kriging model is a geostatistical method for interpolation and spatial statistics.

[0114] According to an embodiment of the present invention, the health self-repair index based on the river and lake sub-region is used to correct the health status change prediction result, and the health restoration priority scheme of each river and lake sub-region is determined, specifically:

[0115] Obtain the length of the preset time period, and calculate the self-repair degree of the river and lake sub-area according to the health self-repair index of the river and lake sub-area and the length of time;

[0116] Correcting the predicted health status change result based on the self-repair degree of the river and lake sub-region;

[0117] According to the health self-repair index of the river and lake sub-region, the health self-repair time length of each river and lake sub-region in the health status change results is evaluated to obtain the health self-repair time period of each river and lake sub-region;

[0118] If the healthy self-repair time period is greater than the preset time period, a health restoration priority plan for each river and lake sub-area is determined.

[0119] It should be noted that since the health self-repair ability of river and lake sub-regions is not taken into account in the prediction process of changes in the health status of river and lake sub-regions, the health self-repair index is used to correct the prediction results of changes in health status. The corrected prediction results take into account the degree of self-repair of different sub-regions, thereby improving the personalization and accuracy of the prediction; the health restoration priority scheme is to analyze the health restoration ability and degree of river and lake sub-regions within a preset time period, determine which river and lake sub-regions cannot complete self-repair within the preset time period, and determine the urgency of health restoration for each river and lake sub-region, give priority to repairing areas with high health urgency, avoid the spread of health problems to other river and lake sub-regions, help optimize the allocation of governance resources, ensure that resources are more effectively used in areas that need the most attention, and improve overall governance efficiency.

[0120] According to an embodiment of the present invention, it also includes:

[0121] Obtain the pollution status of the river and lake sub-areas under the preset conditions, and obtain the pollution status data of the polluted river and lake sub-areas;

[0122] Real-time monitoring of pollution changes in polluted river and lake sub-areas and adjacent river and lake sub-areas;

[0123] Calculate the pollution diffusion rate of the polluted river and lake sub-areas and the increased concentration of pollutants in adjacent river and lake sub-areas based on the pollution changes;

[0124] Analyze the impact of the polluted river and lake sub-region on the upstream river and lake sub-region and the downstream river and lake sub-region based on the increased concentration of the pollutants to obtain impact data;

[0125] A secondary revision is made based on the impact data and the predicted results of the health status change, and a secondary revision is made to the health restoration priority plan.

[0126] It should be noted that due to the existence of human activities in a certain river or lake sub-region in the target river or lake, the pollutant concentration in the river or lake sub-region increases. Due to the spread of pollutants, the health monitoring change prediction results will become accurate. The degree of influence of the polluted river or lake sub-region on the upstream and downstream river or lake sub-regions is analyzed, and the health status change prediction results and the health restoration priority plan are revised for a second time according to the degree of influence. According to the embodiment of the present invention, the prediction of the health status changes of other river or lake sub-regions due to the growth of pollutants in a certain river or lake sub-region can be timely corrected, so that the invention can improve the response to changes in various pollution situations, be more in line with actual conditions, continuously update the pollution status, more accurately analyze the trend of pollution spread, and timely capture the development and spread process of pollution events. The preset condition is that only one river or lake sub-region is polluted. The adjacent river or lake sub-regions include upstream adjacent river or lake sub-regions and downstream adjacent river or lake sub-regions.

[0127] Figure 4 A block diagram of a river and lake health monitoring system based on data fusion according to the present invention is shown.

[0128] The second aspect of the present invention further provides a river and lake health monitoring system 4 based on data fusion, the system comprising: a memory 41, a processor 42, the memory comprising a river and lake health monitoring method program based on data fusion, the river and lake health monitoring method program based on data fusion when executed by the processor, implements the following steps:

[0129] Periodically obtain regional health monitoring data of multiple river and lake sub-areas in the target river and lake, wherein the regional health monitoring data includes biodiversity data and water pollutant concentration data;

[0130] Conducting a health assessment on each river and lake sub-region based on the regional health monitoring data to obtain a periodic health assessment report for each river and lake sub-region;

[0131] Analyzing the health self-repair capacity of the river and lake sub-regions in the periodic health assessment report to obtain a health self-repair index of the river and lake sub-regions;

[0132] Analyze the health differences of adjacent river and lake sub-regions based on periodic health assessment reports, and analyze the regional health change trends of target rivers and lakes based on the health differences;

[0133] Randomly obtain the preset single-region health change monitoring data of a river or lake sub-region, and predict the health status of other river or lake sub-regions in the target river or lake based on the regional health change trend and the single-region health monitoring data, and obtain the health status change prediction result of each river or lake sub-region;

[0134] The health status change prediction result is corrected based on the health self-repair index of the river and lake sub-region, and the health restoration priority plan for each river and lake sub-region is determined.

[0135] It should be noted that, if the target rivers and lakes are large enough, the health status of each river and lake sub-area will be different. By evaluating the health status of each river and lake sub-area in the target rivers and lakes, we can have a more detailed understanding of the health status of each river and lake sub-area in the target rivers and lakes, which will help to timely discover the health problems of each river and lake sub-area, and deal with the river and lake sub-areas with health problems in a targeted manner to prevent the health problems from spreading further and affecting other river and lake sub-areas. Since rivers and lakes have the ability to self-repair in an unhealthy state until they reach a healthy state, by analyzing the periodic health assessment reports, we can judge the health self-repair ability of the river and lake sub-areas and predict the changes in the health status of each river and lake sub-area within the preset time period. , and obtain the prediction result. Since the prediction result does not take into account the health self-repair ability of the river and lake sub-regions, the prediction result of the health status change is corrected according to the health self-repair index to make the prediction result more in line with the actual situation and reduce the prediction error. By predicting the health status of the river and lake sub-regions, the resource consumption of data monitoring can be reduced, and the problem of not being able to directly monitor data due to environmental reasons in the river and lake sub-regions can be avoided. Finally, the priority plan for health restoration is determined according to the health status of each river and lake sub-region, the health problems of the target rivers and lakes are accurately governed, and the governance priority of the river and lake sub-regions is determined, so as to avoid the further spread of health problems and improve governance efficiency. The target rivers and lakes include rivers and large lakes.

[0136] According to an embodiment of the present invention, the regional health monitoring data of multiple river and lake sub-areas in the target river and lake are periodically obtained, and the regional health monitoring data includes biodiversity data and water pollutant concentration data, specifically:

[0137] Divide the target river or lake into multiple river or lake sub-areas;

[0138] The fish species and quantity, plant species and quantity information of the plurality of river and lake sub-regions are obtained with a monthly data collection cycle, and the biodiversity of each river and lake sub-region is evaluated based on the fish species and quantity, plant species and quantity information to obtain biodiversity data;

[0139] Acquire water pollutant concentration data for each river and lake sub-area according to the data collection cycle;

[0140] The biodiversity data and water pollutant concentration data are integrated into regional health monitoring data.

[0141] According to an embodiment of the present invention, the health assessment of each river and lake sub-region is performed according to the regional health monitoring data to obtain a periodic health assessment report for each river and lake sub-region, specifically:

[0142] Set the health impact weight of each item in the regional health monitoring data on the river and lake sub-region according to the preset proportion;

[0143] The Simpson diversity index was introduced to calculate each river and lake sub-region to obtain the biodiversity index of each river and lake sub-region;

[0144] Based on the ecological data of target rivers and lakes, determine the biodiversity index thresholds and water pollutant concentration thresholds for sub-regions of rivers and lakes under unhealthy conditions;

[0145] The water pollutant concentration data and biodiversity index of each river and lake sub-region are compared with the biodiversity index threshold and the water pollutant concentration threshold, and a health assessment is performed on each river and lake sub-region based on the health impact weight to obtain a periodic health assessment report for each river and lake sub-region.

[0146] It should be noted that the Simpson diversity index is the Simpson diversity index. The value range of the Simpson index is 0 to 1. The closer the value is to 1, the lower the species diversity is, and the closer the value is to 0, the higher the species diversity is. The calculation formula of the Simpson index is as follows: d = 1-Σ(ni / N)^2, where d represents the Simpson index, ni represents the number of individuals of the i-th species, and N represents the total number of individuals in the entire ecosystem; the periodic health monitoring report is obtained under the condition that the health status of the river and lake sub-areas is not deteriorating.

[0147] According to an embodiment of the present invention, the periodic health assessment report is analyzed to determine the health self-repair capability of the river and lake sub-regions to obtain the health self-repair index of the river and lake sub-regions, specifically:

[0148] Marking the river and lake sub-areas with health problems according to the periodic health monitoring report to obtain marked sub-areas;

[0149] Sort the periodic health monitoring reports of the marked sub-areas by time series to obtain a time series health monitoring table for each marked sub-area;

[0150] Draw a biodiversity change graph and a water pollutant concentration change graph based on the time series health monitoring table;

[0151] Calculate the average value of periodic changes in biodiversity and the average value of periodic changes in water pollutant concentrations in the biodiversity change graph and water pollutant concentration change graph;

[0152] The health self-repair capacity of the river and lake sub-regions is evaluated based on the periodic variation average values ​​of biodiversity and the periodic variation average values ​​of water pollutant concentrations, and the health self-repair index of the river and lake sub-regions is obtained.

[0153] It should be noted that since rivers and lakes have the ability to resist unhealthy problems and can self-repair unhealthy conditions, the degree of health restoration in each health cycle is analyzed through periodic health monitoring reports to obtain the health self-repair index of the river and lake sub-area; the health self-repair index is calculated through the average value of the periodic changes in biodiversity and the average value of the periodic changes in water pollutant concentrations. The average daily changes in biodiversity and water pollutant concentrations in the river and lake sub-area can be used to derive the average daily self-repair capacity of the river and lake sub-area. The health restoration index of the river and lake sub-area is obtained by multiplying the daily increase in the biodiversity index and the decrease in the water pollutant concentration by the corresponding health impact weight.

[0154] According to an embodiment of the present invention, the health differences of adjacent river and lake sub-regions are analyzed based on periodic health assessment reports, and the regional health change trend of target rivers and lakes is analyzed based on the health differences, specifically:

[0155] Extract information on fish species and abundance and plant species and abundance for each river and lake sub-area based on periodic health assessment reports;

[0156] Import the fish species and quantity information of two adjacent river and lake sub-areas into sets A and B respectively;

[0157] Calculate the intersection and union of sets A and B, introduce the Jaccard similarity coefficient, divide the size of the intersection by the size of the union, and get the similarity coefficient of fish species and quantity in adjacent river and lake sub-areas;

[0158] Calculate the similarity coefficients of plant species and quantities in adjacent river and lake sub-regions, and analyze the health differences of adjacent river and lake sub-regions based on the similarity coefficients of fish species and quantities and plant species and quantities, wherein the health differences include differences in biodiversity and differences in water pollutant concentrations;

[0159] The health differences of adjacent river and lake sub-regions in regional continuity are plotted into health difference curve change diagrams;

[0160] The regional health change trend within the preset range of the target rivers and lakes is analyzed based on the health difference curve change diagram.

[0161] It should be noted that by introducing the Jaccard similarity coefficient to evaluate the health differences of two adjacent river and lake sub-regions, the regional health change trend of the target river and lake within the preset interval can be analyzed according to the progression of the region. The Jaccard similarity coefficient can quickly calculate the health differences of two adjacent river and lake sub-regions, reducing manual data calculations and avoiding the misjudgment of differences due to subjective factors; the A and B sets are a set that stores information on fish species and quantities in the same river and lake sub-region; the Jaccard similarity coefficient is a statistical indicator for measuring the similarity between two sets; the preset interval is composed of a preset number of continuous river and lake sub-regions.

[0162] According to an embodiment of the present invention, the preset single-region health change monitoring data of a river or lake sub-region is randomly obtained, and the health status of other river or lake sub-regions in the target river or lake is predicted based on the regional health change trend and the single-region health monitoring data, so as to obtain the prediction result of the health status change of each river or lake sub-region, specifically:

[0163] Randomly obtain the health monitoring data of a river or lake sub-area within a preset time period in the target river or lake to obtain the preset single-area health change monitoring data;

[0164] Introducing a Kriging model, fitting the Kriging model according to the regional health change trend, and introducing a spatial interpolation method to perform numerical prediction through the fitted Kriging model;

[0165] The preset single-region health change monitoring data is spatially interpolated according to the Kriging model and spatial interpolation method, and the health change status of other river and lake sub-regions in the target river and lake is predicted to obtain the predicted results of the health status change of each river and lake sub-region.

[0166] It should be noted that by obtaining the health change monitoring data of a river or lake sub-region to predict the health change status of other river or lake sub-regions within a preset time period, the consumption of data monitoring resources can be effectively reduced, and data gaps caused by the difficulty in obtaining health data of some river or lake sub-regions can be avoided; the introduction of spatial interpolation method can greatly improve the accuracy of prediction; the Kriging model is a geostatistical method for interpolation and spatial statistics.

[0167] According to an embodiment of the present invention, the health self-repair index based on the river and lake sub-region is used to correct the health status change prediction result, and the health restoration priority scheme of each river and lake sub-region is determined, specifically:

[0168] Obtain the length of the preset time period, and calculate the self-repair degree of the river and lake sub-area according to the health self-repair index of the river and lake sub-area and the length of time;

[0169] Correcting the predicted health status change result based on the self-repair degree of the river and lake sub-region;

[0170] According to the health self-repair index of the river and lake sub-region, the health self-repair time length of each river and lake sub-region in the health status change results is evaluated to obtain the health self-repair time period of each river and lake sub-region;

[0171] If the healthy self-repair time period is greater than the preset time period, a health restoration priority plan for each river and lake sub-area is determined.

[0172] It should be noted that since the health self-repair ability of river and lake sub-regions is not taken into account in the prediction process of changes in the health status of river and lake sub-regions, the health self-repair index is used to correct the prediction results of changes in health status. The corrected prediction results take into account the degree of self-repair of different sub-regions, thereby improving the personalization and accuracy of the prediction; the health restoration priority scheme is to analyze the health restoration ability and degree of river and lake sub-regions within a preset time period, determine which river and lake sub-regions cannot complete self-repair within the preset time period, and determine the urgency of health restoration for each river and lake sub-region, give priority to repairing areas with high health urgency, avoid the spread of health problems to other river and lake sub-regions, help optimize the allocation of governance resources, ensure that resources are more effectively used in areas that need the most attention, and improve overall governance efficiency.

[0173] According to an embodiment of the present invention, it also includes:

[0174] Obtain the pollution status of the river and lake sub-areas under the preset conditions, and obtain the pollution status data of the polluted river and lake sub-areas;

[0175] Real-time monitoring of pollution changes in polluted river and lake sub-areas and adjacent river and lake sub-areas;

[0176] Calculate the pollution diffusion rate of the polluted river and lake sub-areas and the increased concentration of pollutants in adjacent river and lake sub-areas based on the pollution changes;

[0177] Analyze the impact of the polluted river and lake sub-region on the upstream river and lake sub-region and the downstream river and lake sub-region based on the increased concentration of the pollutants to obtain impact data;

[0178] A secondary revision is made based on the impact data and the predicted results of the health status change, and a secondary revision is made to the health restoration priority plan.

[0179] It should be noted that due to the existence of human activities in a certain river or lake sub-region in the target river or lake, the pollutant concentration in the river or lake sub-region increases. Due to the spread of pollutants, the health monitoring change prediction results will become accurate. The degree of influence of the polluted river or lake sub-region on the upstream and downstream river or lake sub-regions is analyzed, and the health status change prediction results and the health restoration priority plan are revised for a second time according to the degree of influence. According to the embodiment of the present invention, the prediction of the health status changes of other river or lake sub-regions due to the growth of pollutants in a certain river or lake sub-region can be timely corrected, so that the invention can improve the response to changes in various pollution situations, be more in line with actual conditions, continuously update the pollution status, more accurately analyze the trend of pollution spread, and timely capture the development and spread process of pollution events. The preset condition is that only one river or lake sub-region is polluted. The adjacent river or lake sub-regions include upstream adjacent river or lake sub-regions and downstream adjacent river or lake sub-regions.

[0180] The present invention discloses a river and lake health monitoring method and system based on data fusion, aiming to provide a comprehensive and effective river and lake health assessment and prediction system. The present invention evaluates the health status of each river and lake sub-region, quantifies the health self-repair ability of the river and lake sub-region, and obtains the health self-repair index of the river and lake sub-region. By comparing the health differences of adjacent river and lake sub-regions, the regional health change trend of the target river and lake is revealed. The health status of the river and lake sub-regions in the target river and lake is predicted to form the prediction results of the health status change of each river and lake sub-region. Finally, the present invention corrects the prediction results of the health status change based on the health self-repair index of the river and lake sub-region, and determines the health restoration priority plan for each river and lake sub-region. The data fusion method of the present invention comprehensively considers ecological and environmental factors, and provides strong support for scientific and reasonable river and lake health management.

[0181] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0182] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0183] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0184] Those skilled in the art can understand that: all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiments; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), disks or optical disks, and other media that can store program codes.

[0185] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

[0186] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A river and lake health monitoring method based on data fusion, characterized in that: The following steps are involved: Periodically obtain regional health monitoring data of multiple river and lake sub-areas in the target river and lake, wherein the regional health monitoring data includes biodiversity data and water pollutant concentration data; Conducting a health assessment on each river and lake sub-region based on the regional health monitoring data to obtain a periodic health assessment report for each river and lake sub-region; Analyzing the health self-repair capacity of the river and lake sub-regions in the periodic health assessment report to obtain a health self-repair index of the river and lake sub-regions; Analyze the health differences of adjacent river and lake sub-regions based on periodic health assessment reports, and analyze the regional health change trends of target rivers and lakes based on the health differences; Randomly obtain the preset single-region health change monitoring data of a river or lake sub-region, and predict the health status of other river or lake sub-regions in the target river or lake based on the regional health change trend and the single-region health monitoring data, and obtain the prediction result of the health status change of each river or lake sub-region; Based on the health self-repair index of the river and lake sub-regions, the predicted results of health status changes are corrected, and a health restoration priority plan for each river and lake sub-region is determined; The periodic health assessment report is analyzed to determine the health self-repair capacity of the river and lake sub-regions to obtain the health self-repair index of the river and lake sub-regions, specifically: Marking river and lake sub-areas with health problems according to the periodic health assessment report to obtain marked sub-areas; Sort the periodic health assessment reports of the marked sub-areas by time series to obtain a time series health monitoring table for each marked sub-area; Draw a biodiversity change graph and a water pollutant concentration change graph based on the time series health monitoring table; Calculate the average value of periodic changes in biodiversity and the average value of periodic changes in water pollutant concentrations in the biodiversity change graph and water pollutant concentration change graph; The health self-repair capacity of the river and lake sub-regions is evaluated based on the periodic variation average values ​​of biodiversity and the periodic variation average values ​​of water pollutant concentrations, and the health self-repair index of the river and lake sub-regions is obtained.

2. A method for monitoring river and lake health based on data fusion according to claim 1, characterized in that: The regional health monitoring data of multiple river and lake sub-regions in the target river and lake are periodically obtained, and the regional health monitoring data includes biodiversity data and water pollutant concentration data, specifically: Divide the target river or lake into multiple river or lake sub-areas; The fish species and quantity, plant species and quantity information of the plurality of river and lake sub-regions are obtained with a monthly data collection cycle, and the biodiversity of each river and lake sub-region is evaluated based on the fish species and quantity, plant species and quantity information to obtain biodiversity data; Acquire water pollutant concentration data for each river and lake sub-area according to the data collection cycle; The biodiversity data and water pollutant concentration data are integrated into regional health monitoring data.

3. A method for monitoring river and lake health based on data fusion according to claim 2, characterized in that: The health assessment of each river and lake sub-region is performed according to the regional health monitoring data to obtain a periodic health assessment report for each river and lake sub-region, specifically: Set the health impact weight of each item in the regional health monitoring data on the river and lake sub-region according to the preset proportion; The Simpson diversity index was introduced to calculate the biodiversity of each river and lake sub-region, and the biodiversity index of each river and lake sub-region was obtained; Based on the ecological data of target rivers and lakes, determine the biodiversity index thresholds and water pollutant concentration thresholds for sub-regions of rivers and lakes under unhealthy conditions; The water pollutant concentration data and biodiversity index of each river and lake sub-area are compared with the biodiversity index threshold and the water pollutant concentration threshold, and a health assessment is performed on each river and lake sub-area based on the health impact weight to obtain a periodic health assessment report for each river and lake sub-area.

4. A method for monitoring river and lake health based on data fusion according to claim 1, characterized in that: The analysis of the health differences of adjacent river and lake sub-regions based on the periodic health assessment report and the analysis of the regional health change trend of the target river and lake based on the health differences are specifically as follows: Extract information on fish species and abundance and plant species and abundance for each river and lake sub-area based on periodic health assessment reports; Import the fish species and quantity information of two adjacent river and lake sub-areas into sets A and B respectively; Calculate the intersection and union of sets A and B, introduce the Jaccard similarity coefficient, divide the size of the intersection by the size of the union, and get the similarity coefficient of fish species and quantity in adjacent river and lake sub-areas; Calculate the similarity coefficients of plant species and quantities in adjacent river and lake sub-regions, and analyze the health differences of adjacent river and lake sub-regions based on the similarity coefficients of fish species and quantities and plant species and quantities, wherein the health differences include differences in biodiversity and differences in water pollutant concentrations; The health differences of adjacent river and lake sub-regions in regional continuity are plotted into health difference curve change diagrams; The regional health change trend within the preset range of the target rivers and lakes is analyzed based on the health difference curve change diagram.

5. The method for monitoring river and lake health based on data fusion according to claim 1 is characterized in that: The preset single-region health change monitoring data of a river or lake sub-region is randomly obtained, and the health status of other river or lake sub-regions in the target river or lake is predicted based on the regional health change trend and the single-region health monitoring data, so as to obtain the prediction result of the health status change of each river or lake sub-region, specifically: Randomly obtain the health monitoring data of a river or lake sub-area within a preset time period in the target river or lake to obtain the preset single-area health change monitoring data; Introducing a Kriging model, fitting the Kriging model according to the regional health change trend, and introducing a spatial interpolation method to perform numerical prediction through the fitted Kriging model; The preset single-region health change monitoring data is spatially interpolated according to the Kriging model and spatial interpolation method to predict the health change status of other river and lake sub-regions in the target river and lake, and obtain the prediction results of the health status change of each river and lake sub-region.

6. A method for monitoring river and lake health based on data fusion according to claim 5, characterized in that: The health self-repair index based on the river and lake sub-region is used to correct the health status change prediction result, and determine the health restoration priority plan for each river and lake sub-region, specifically: Obtain the length of the preset time period, and calculate the self-repair degree of the river and lake sub-area according to the health self-repair index of the river and lake sub-area and the length of time; Correcting the predicted health status change result based on the self-repair degree of the river and lake sub-region; According to the health self-repair index of the river and lake sub-region, the health self-repair time length of each river and lake sub-region in the health status change results is evaluated to obtain the health self-repair time period of each river and lake sub-region; If the healthy self-repair time period is greater than the preset time period, a health restoration priority plan for each river and lake sub-area is determined.

7. A river and lake health monitoring system based on data fusion, characterized in that: The river and lake health monitoring system based on data fusion includes a storage device and a processor. The storage device includes a river and lake health monitoring method program based on data fusion. When the river and lake health monitoring method program based on data fusion is executed by the processor, the following steps are implemented: Periodically obtain regional health monitoring data of multiple river and lake sub-areas in the target river and lake, wherein the regional health monitoring data includes biodiversity data and water pollutant concentration data; Conducting a health assessment on each river and lake sub-region based on the regional health monitoring data to obtain a periodic health assessment report for each river and lake sub-region; Analyzing the health self-repair capacity of the river and lake sub-regions in the periodic health assessment report to obtain a health self-repair index of the river and lake sub-regions; Analyze the health differences of adjacent river and lake sub-regions based on periodic health assessment reports, and analyze the regional health change trends of target rivers and lakes based on the health differences; Randomly obtain the preset single-region health change monitoring data of a river or lake sub-region, and predict the health status of other river or lake sub-regions in the target river or lake based on the regional health change trend and the single-region health monitoring data, and obtain the prediction result of the health status change of each river or lake sub-region; Based on the health self-repair index of the river and lake sub-regions, the predicted results of health status changes are corrected, and a health restoration priority plan for each river and lake sub-region is determined; The periodic health assessment report is analyzed to determine the health self-repair capacity of the river and lake sub-regions to obtain the health self-repair index of the river and lake sub-regions, specifically: Marking river and lake sub-areas with health problems according to the periodic health assessment report to obtain marked sub-areas; Sort the periodic health assessment reports of the marked sub-areas by time series to obtain a time series health monitoring table for each marked sub-area; Draw a biodiversity change graph and a water pollutant concentration change graph based on the time series health monitoring table; Calculate the average value of periodic changes in biodiversity and the average value of periodic changes in water pollutant concentrations in the biodiversity change graph and water pollutant concentration change graph; The health self-repair capacity of the river and lake sub-regions is evaluated based on the periodic variation average values ​​of biodiversity and the periodic variation average values ​​of water pollutant concentrations, and the health self-repair index of the river and lake sub-regions is obtained.

8. A river and lake health monitoring system based on data fusion according to claim 7, characterized in that: The analysis of the health differences of adjacent river and lake sub-regions based on the periodic health assessment report and the analysis of the regional health change trend of the target river and lake based on the health differences are specifically as follows: Extract information on fish species and abundance and plant species and abundance for each river and lake sub-area based on periodic health assessment reports; Import the fish species and quantity information of two adjacent river and lake sub-areas into sets A and B respectively; Calculate the intersection and union of sets A and B, introduce the Jaccard similarity coefficient, divide the size of the intersection by the size of the union, and get the similarity coefficient of fish species and quantity in adjacent river and lake sub-areas; Calculate the similarity coefficients of plant species and quantities in adjacent river and lake sub-regions, and analyze the health differences of adjacent river and lake sub-regions based on the similarity coefficients of fish species and quantities and plant species and quantities, wherein the health differences include differences in biodiversity and differences in water pollutant concentrations; The health differences of adjacent river and lake sub-regions in regional continuity are plotted into health difference curve change diagrams; The regional health change trend within the preset range of the target rivers and lakes is analyzed based on the health difference curve change diagram.

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