River ecological environment data monitoring method and system based on big data

Abstract

The invention relates to the technical field of river ecological environment data monitoring, in particular to a river ecological environment data monitoring method and system based on big data. Comprising the following steps: S1, collecting historical information data of a river, then performing unit region division on the river, and classifying the historical information data according to the divided unit regions; s2, performing quantitative index analysis on the historical information data according to the structural data and functional representation of the river; potential laws and trends in river ecological environment data can be mined through a big data analysis technology, prospective guidance is provided for ecological restoration and management, the quality of a river ecological system can be comprehensively and accurately evaluated by comprehensively considering multiple aspects such as river health degree, pressure bearing and restoration capability, ecological service value and the like, and the quality of the river ecological system is improved. And the quantitative index selection and characterization method enables the evaluation to be more scientific and objective, and provides a clear target and direction for ecological restoration.

Description

Technical Field

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

[0002] In the field of river ecological environment monitoring, we are mainly committed to collecting river ecological environment data through various means to assess the health of river ecosystems and provide a basis for ecological restoration and management. Its purpose is to protect the integrity and stability of river ecosystems and improve the quality and sustainable utilization of water resources.

[0003] At present, the existing technology has many defects in practical application, which has a serious impact on the purpose of protecting the river ecological environment. Fixed monitoring stations can only obtain data from local areas and cannot reflect the differences in different locations of the river, resulting in inaccurate assessment of the river ecosystem. Secondly, there is a lack of a comprehensive indicator system for the quality evaluation of river ecosystems, which makes it difficult to comprehensively measure the health, pressure bearing and recovery capacity, and ecological service value of rivers. In terms of ecological restoration, it lacks specificity and it is difficult to formulate personalized restoration measures according to the specific conditions of different unit areas. Therefore, a river ecological environment data monitoring method and system based on big data is proposed. Summary of the invention

[0004] The purpose of the present invention is to provide a river ecological environment data monitoring method and system based on big data to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, one of the purposes of the present invention is to provide a river ecological environment data monitoring method based on big data, comprising the following steps:

[0006] S1. Collect historical information data of the river, then divide the river into unit areas, and classify the historical information data according to the divided unit areas;

[0007] S2. Analyze historical information data based on the structural data and functional characterization of the river to obtain the pressure-bearing resilience and ecological service value, and make development predictions based on the historical pressure-bearing resilience and historical ecological service value;

[0008] S3. Set the river health standard. Set the dynamic river health standard according to the structural position of the unit area. Then compare the predicted river health standard with the pressure resilience and ecological service value of the unit area.

[0009] S4. Collect historical river management plans and analyze the effectiveness of management plans by combining the historical pressure-bearing resilience and historical ecological service value of unhealthy unit areas;

[0010] S5. Establish an ecological assessment model, input the unhealthy unit area, output the governance demand index of each unhealthy unit area according to the ecological assessment model, and then generate ecological restoration measures according to the governance demand index;

[0011] S6. Analyze the impact of ecological restoration measures in unhealthy unit areas in combination with the river direction, obtain auxiliary impact data of ecological restoration measures in upstream unhealthy unit areas on downstream unhealthy unit areas, and then dynamically adjust the downstream unhealthy unit areas based on the auxiliary impact data.

[0012] As a further improvement of the technical solution, S1 establishes a data transmission channel with the River Management Office, and uploads historical information data of the river through staff, while obtaining geographic data of the river that needs to be monitored.

[0013] As a further improvement of the present technical solution, S1 divides the river into unit areas with the river channel, river bank and river bank belt at intervals of one hundred meters along the flow direction, and divides the entire river into multiple unit areas. At the same time, the geographical data of the unit area is combined with the historical information data to perform the same geographical location division, and obtain the historical information data corresponding to each unit area.

[0014] As a further improvement of the technical solution, the steps of S2 are as follows:

[0015] S2.1. Use heterogeneity test, redundancy test and responsiveness test statistical methods to examine and select quantitative indicators suitable for the structural and functional characterization of river ecosystems from historical information data;

[0016] Using water use efficiency and benthic macroinvertebrates to characterize the stress resilience of river ecosystems;

[0017] Taking water conservation, carbon fixation and oxygen release, air purification, biological habitat, and leisure and entertainment ecological services as the objects, the ecological service value of river ecosystems is quantitatively evaluated by means of functional value and selected capacity value evaluation methods;

[0018] S2.2. Make development forecasts based on historical pressure-bearing resilience and historical ecological service value to obtain predicted pressure-bearing resilience and predicted ecological service value.

[0019] As a further improvement of the technical solution, the steps of S3 are as follows:

[0020] S3.1. Obtain the requirements for setting river health standards and the required time for this environmental protection management;

[0021] S3.2. Dynamically analyze the river health standard in combination with the structural position of each unit area to obtain the river health standard corresponding to each unit area;

[0022] S3.3. According to the required time of governance, the predicted resilience to pressure and predicted ecological service value corresponding to the unit area are intercepted, and then the predicted resilience to pressure and predicted ecological service value are compared with the river health standard. When the predicted resilience to pressure and predicted ecological service value of the unit area do not meet the river health standard, the unit area is regarded as an unhealthy unit area. Conversely, when the predicted resilience to pressure and predicted ecological service value of the unit area meet the river health standard, the unit area will continue to be monitored.

[0023] As a further improvement of the technical solution, the step of S4 is as follows:

[0024] S4.1. Collect historical river management plans, and extract the corresponding historical pressure-bearing resilience and historical ecological service value of unhealthy unit areas according to the time period corresponding to the historical management plans;

[0025] S4.2. Combine the historical pressure-bearing resilience and historical ecological service value extracted in S4.1 with the historical governance plan to analyze the effectiveness of the governance plan and obtain the governance effect of each unhealthy unit area.

[0026] As a further improvement of the technical solution, the step of S5 is as follows:

[0027] S5.1. Use the InVEST model and the MIKE model to establish an ecological assessment model for the river;

[0028] S5.2. Input the unhealthy unit area, output the governance demand index of each unhealthy unit area according to the ecological assessment model, then analyze the ecological restoration measures according to the governance demand index, and generate ecological restoration measures according to the analysis results.

[0029] As a further improvement of the technical solution, the step of S6 is as follows:

[0030] S6.1. Establish an ecological restoration simulation model, and input the unhealthy unit areas in sequence according to the river location, with the upstream having a higher priority than the downstream. Then, according to the ecological restoration simulation model, analyze the impact of the ecological restoration measures on the unhealthy unit areas in combination with the river direction, and obtain the auxiliary impact data of the ecological restoration measures on the downstream unhealthy unit areas;

[0031] S6.2. Combine the auxiliary impact data with ecological restoration measures to dynamically adjust the measures for each unhealthy unit area, thereby updating the ecological restoration measures for each unhealthy unit area.

[0032] The second object of the present invention is to provide a river ecological environment data monitoring system based on big data, including any one of the above-mentioned river ecological environment data monitoring methods based on big data, including a quantitative index analysis unit, a governance scheme effect analysis unit and a measure dynamic adjustment unit;

[0033] The quantitative index analysis unit is used to divide the river into unit areas, and to perform quantitative index analysis on the historical information data according to the structural data and functional representation of the river;

[0034] The treatment scheme effect analysis unit is used to compare the predicted river health standard of the unit area with the pressure-bearing resilience and ecological service value, collect historical treatment plans of the river, and analyze the effect of the treatment scheme by combining the historical treatment plans with the historical pressure-bearing resilience and historical ecological service value of the unhealthy unit area;

[0035] The dynamic adjustment unit of measures is used to output the governance demand index of each unhealthy unit area according to the ecological assessment model, and then generate ecological restoration measures according to the governance demand index, and then analyze the impact of the ecological restoration measures on the unhealthy unit area in combination with the river direction, and dynamically adjust the downstream unhealthy unit area according to the auxiliary impact data.

[0036] Compared with the prior art, the present invention has the following beneficial effects:

[0037] 1. A river ecological environment data monitoring method and system based on big data. Through big data analysis technology, it can explore the potential laws and trends in river ecological environment data, provide forward-looking guidance for ecological restoration and management, and comprehensively consider multiple aspects such as river health, pressure bearing and recovery capacity, and ecological service value. It can comprehensively and accurately evaluate the quality of river ecosystems. The selection and characterization methods of quantitative indicators make the evaluation more scientific and objective, providing clear goals and directions for ecological restoration.

[0038] 2. A river ecological environment data monitoring method and system based on big data, which dynamically analyzes each unit area according to the required time and river health standards, determines the corresponding river health standards, and can achieve refined management of the river ecosystem, identify and manage unhealthy unit areas, solve problems in the river ecological environment in a targeted manner, and improve the efficiency and effectiveness of ecological restoration.

[0039] 3. A river ecological environment data monitoring method and system based on big data, which analyzes the effectiveness of governance plans for unhealthy unit areas in combination with historical governance plans, obtains the governance effect of each unit area, and provides lessons for subsequent ecological restoration. At the same time, it analyzes ecological restoration measures based on governance demand indicators, and can formulate more scientific and reasonable ecological restoration measures to improve the pertinence and effectiveness of ecological restoration. In addition, by establishing an ecological restoration simulation model and considering the auxiliary impact of ecological restoration measures in upstream unhealthy unit areas on downstream unhealthy unit areas, the overall optimization of the river ecosystem can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is the overall flow chart of the present invention;

[0041] Figure 2 A flowchart for obtaining the predicted pressure resilience and predicted ecological service value for the present invention;

[0042] Figure 3 A flowchart for obtaining the river health standard corresponding to each unit area in the present invention;

[0043] Figure 4 A flowchart for obtaining the treatment effect of each unhealthy unit area in the present invention;

[0044] Figure 5 A flowchart of the present invention for generating ecological restoration measures according to the analysis results;

[0045] Figure 6 A flowchart for updating ecological restoration measures for each unhealthy unit area of ​​the present invention;

[0046] Figure 7 It is a structural principle diagram of the quantitative index analysis unit of the present invention.

[0047] The meaning of each number in the figure is:

[0048] 10. Quantitative indicator analysis unit; 20. Governance plan effectiveness analysis unit; 30. Dynamic adjustment of measures unit. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] like Figure 1 - Figure 7As shown, one of the purposes of the present invention is to provide a river ecological environment data monitoring method based on big data, comprising the following steps:

[0051] S1. Collect historical information data of the river, then divide the river into unit areas, and classify the historical information data according to the divided unit areas;

[0052] S1 establishes a data transmission channel with the River Management Office, and uploads historical information data of the river through staff, and obtains the geographic data of the river that needs to be monitored. The specific steps are as follows:

[0053] Determine the data transmission method: develop a special data sharing platform, set user permissions, and the staff of the River Management Office log in to the platform to upload data. The recipient also obtains and manages data on the platform;

[0054] Data collation and upload: The staff of the River Management Office will collate the historical information data of the river, including but not limited to water quality monitoring records, ecological restoration project documents, river flow change data, etc. At the same time, for geographic data, such as the geographical location coordinates of the river, the scope of the basin, the direction of the river, etc., the geographic information system (GIS) software can be used to organize it, and then the staff will upload the organized data to the corresponding channel according to the determined data transmission method.

[0055] S1 divides the river into unit areas with the river channel, river bank and river bank belt at intervals of 100 meters along the flow direction, and divides the entire river into multiple unit areas. At the same time, the geographical data of the unit area is combined with the historical information data to divide the same geographical location, and obtain the historical information data corresponding to each unit area. The specific steps are as follows:

[0056] Data collection and collation: Obtain the geographical data of the river, including the direction of the river, the shape of the river bank, the scope of the riparian zone, etc.;

[0057] Determine the method of unit area division: divide the river channel, river bank and riparian zone into units with an interval of 100 meters along the flow direction, and number each unit area for subsequent management and analysis;

[0058] Division by geographic location: Determine the geographic location coordinates of each unit area based on geographic data, match the historical information data according to the geographic location, and associate the geographic data of each unit area with the corresponding historical information data. Database management systems or spreadsheet software can be used for storage and management.

[0059] S2. Analyze historical information data based on the structural data and functional characterization of the river to obtain the pressure-bearing resilience and ecological service value, and make development predictions based on the historical pressure-bearing resilience and historical ecological service value;

[0060] The steps of S2 are as follows:

[0061] S2.1. Use heterogeneity test, redundancy test and responsiveness test statistical methods to examine and select quantitative indicators suitable for the structural and functional characterization of river ecosystems from historical information data;

[0062] Using water use efficiency and benthic macroinvertebrates to characterize the stress resilience of river ecosystems;

[0063] Taking water conservation, carbon fixation and oxygen release, air purification, biological habitat, and leisure and entertainment ecological services as the objects, the ecological service value of the river ecosystem is quantitatively evaluated by means of functional value and selected capacity value evaluation methods. The specific steps are as follows:

[0064] Heterogeneity test: Calculate the degree of difference of each data index between different unit areas. Methods such as variance analysis and coefficient of variation can be used to measure the heterogeneity of data, and then select indicators with higher heterogeneity. These indicators can better reflect the differences between different regions and have an important impact on the structure and functionality of river ecosystems.

[0065] Redundancy test: Analyze the correlation between various indicators. You can use correlation coefficient matrix, principal component analysis and other methods to remove redundant indicators with high correlation and retain independent and representative indicators.

[0066] Responsiveness test: observe the response of each indicator to environmental changes at different time points, compare the changes of indicators in different seasons and under different hydrological conditions, and select indicators that respond significantly to environmental changes. These indicators can better reflect the dynamic changes of river ecosystems;

[0067] Determine quantitative indicators: Consider the results of heterogeneity, redundancy and responsiveness tests, and select quantitative indicators suitable for the structural and functional characterization of river ecosystems;

[0068] Water use efficiency characterization: Collect water use data of rivers, calculate water use efficiency indicators, and analyze the relationship between water use efficiency and the pressure-bearing and resilience capacity of river ecosystems. Improving water use efficiency means less pressure on river ecosystems, which is conducive to the recovery of ecosystems.

[0069] Characterization of large benthic invertebrates: Conduct river benthic surveys, collect samples of large benthic invertebrates, analyze the species, quantity, distribution and other characteristics of large benthic invertebrates, and establish the relationship between large benthic invertebrates and the stress-bearing and resilience of river ecosystems. The presence or abundance of certain sensitive species can reflect the health status and resilience of the ecosystem;

[0070] Determine the ecological service objects: define water conservation, carbon fixation and oxygen release, air purification, biological habitat, leisure and entertainment and other ecological services as the evaluation objects;

[0071] Functional value assessment: For water conservation, its functional value can be assessed by calculating indicators such as the water storage capacity of the river basin and the soil permeability coefficient;

[0072] For carbon fixation and oxygen release, the principles of photosynthesis and respiration can be used to calculate the amount of carbon dioxide fixed and the amount of oxygen released by the river ecosystem, and then evaluate its value;

[0073] For air purification, we can consider the absorption and purification of air pollutants by vegetation around rivers and evaluate its value in improving air quality;

[0074] For biological habitats, we can analyze the living space and food resources that river ecosystems provide for different organisms and assess their value to biodiversity conservation;

[0075] For recreation, the economic value of river ecosystems as recreational sites can be assessed by investigating indicators such as the number of tourists and tourism revenue;

[0076] Selection capacity value assessment: Considering people's preference and willingness to pay for different ecological services, the conditional valuation method, travel cost method and other methods are used to assess the selection capacity value of river ecosystems;

[0077] Comprehensive assessment of ecological service value: Integrate the functional value and selection capacity value to obtain the total ecological service value of the river ecosystem.

[0078] S2.2. Carry out development forecast based on historical pressure-bearing resilience and historical ecological service value, and obtain predicted pressure-bearing resilience and predicted ecological service value. The specific steps are as follows:

[0079] Collect historical data on resilience and ecosystem service value: ensure that the data is complete and accurate, covering a sufficiently long time series to reflect the dynamic changes of river ecosystems. These data include water efficiency indicators, macrobenthic invertebrate diversity data, and ecosystem service value-related data such as water conservation, carbon fixation and oxygen release over the past years;

[0080] Model selection: Select a suitable prediction model based on data characteristics and prediction objectives. For the selected model, perform parameter estimation and model fitting. Divide historical data into training sets and validation sets. The training set is used to train the model, and the validation set is used to evaluate the prediction performance of the model. Use appropriate evaluation indicators to measure the accuracy of the model. The formula is as follows:

[0081]

[0082] Among them, y i For the actual pressure-bearing resilience and ecological service value, is the predicted pressure resilience and ecological service value, n is the number of data points in the validation set, MSE is the accuracy value, and the smaller the MES, the higher the accuracy of the model prediction;

[0083] Projections: Use the evaluated and adjusted model to make projections of future stress resilience and ecosystem service values ​​based on the latest known data points.

[0084] S3. Set the river health standard. Set the dynamic river health standard according to the structural position of the unit area. Then compare the predicted river health standard with the pressure resilience and ecological service value of the unit area.

[0085] The steps for S3 are as follows:

[0086] S3.1. Obtain the requirements for setting river health standards and the required time for this environmental protection management;

[0087] Obtain the specific requirements of this environmental governance, including the definition of river health standards, the scope and target values ​​of various indicators, determine the time nodes of governance requirements, and understand the urgency and phased goals of the governance tasks;

[0088] A detailed analysis of river health standards may include water quality indicators (such as dissolved oxygen, chemical oxygen demand, ammonia nitrogen, etc.), ecological indicators (such as biodiversity index, richness of large benthic invertebrates, etc.), and hydrological indicators (such as flow variation range, water level stability, etc.).

[0089] S3.2. Dynamically analyze the river health standard in combination with the structural position of each unit area to obtain the river health standard corresponding to each unit area. The specific steps are as follows:

[0090] Geographic information association: associate the geographic information of each unit area (such as river channel location, riparian characteristics, relationship with the surrounding environment, etc.) with the overall structural position of the river;

[0091] Consider influencing factors: Analyze specific influencing factors that different unit areas may be affected by, such as surrounding land use types (agriculture, industry, residential areas, etc.), pollution source distribution (factory sewage outlets, urban sewage treatment plant discharge, etc.), ecological functional areas (wetlands, nature reserves, etc.), and consider changes in hydrological conditions, such as the impact of water flow velocity, water depth, riverbed topography, etc. on different unit areas;

[0092] Dynamically adjust health standards: Dynamically adjust river health standards based on the structural location and influencing factors of the unit area. For unit areas with higher pollution risks, appropriately increase the requirements for certain water quality indicators; for areas with important ecological functions, strengthen attention to ecological indicators such as biodiversity;

[0093] Determine the health standards for unit areas: Consider the overall health standards of the river and the specific conditions of the unit areas, and determine the river health standards corresponding to each unit area.

[0094] S3.3. According to the required time of governance, the predicted pressure-bearing recovery capacity and predicted ecological service value corresponding to the unit area are intercepted, and then the predicted pressure-bearing recovery capacity and predicted ecological service value are compared with the river health standard. When the predicted pressure-bearing recovery capacity and predicted ecological service value of the unit area do not meet the river health standard, the unit area is regarded as an unhealthy unit area. On the contrary, when the predicted pressure-bearing recovery capacity and predicted ecological service value of the unit area meet the river health standard, the unit area is continuously monitored. The specific calculation formula is as follows:

[0095] EVIu=w1×PCRu+w2×ESVu

[0096] Among them, PCR u is the predicted pressure resilience of the unit area, ESV u EVI is the predicted ecological service value of the unit area. u is a comprehensive evaluation index of pressure-bearing resilience and ecological service value. w1 and w2 are weight coefficients set according to actual conditions, indicating the relative importance of pressure-bearing resilience and ecological service value. HBS u is the river health standard corresponding to the unit area;

[0097] When EVI u <HBS u , then the unit area is an unhealthy unit area;

[0098] When EVI u ≥HBS u , then continue to monitor the unit area.

[0099] S4. Collect historical river management plans and analyze the effectiveness of management plans by combining the historical pressure-bearing resilience and historical ecological service value of unhealthy unit areas;

[0100] The steps of S4 are as follows:

[0101] S4.1. Collect historical river management plans, and extract the corresponding historical pressure-bearing resilience and historical ecological service value of unhealthy unit areas according to the time period corresponding to the historical management plans;

[0102] S4.2. Combine the historical pressure-bearing resilience and historical ecological service value extracted in S4.1 with the historical governance plan to analyze the governance effect of the governance plan and obtain the governance effect of each unhealthy unit area. The specific steps are as follows:

[0103] Extract corresponding data: determine the scope and number of unhealthy unit areas, and search for historical pressure resilience and historical ecological service value data corresponding to these unhealthy unit areas in the existing data set according to the time period of the historical governance plan;

[0104] Analysis of the effectiveness of the governance plan: Select appropriate indicators to measure the effectiveness of the governance plan, such as the degree of improvement in pressure-bearing resilience, the increase in ecological service value, etc., and compare the historical pressure-bearing resilience and historical ecological service value before and after the governance. You can calculate the difference, rate of change, etc., and then analyze other factors that may affect the governance effect, such as changes in climate conditions, surrounding human activities, etc. Finally, combine multiple indicators and factors to conduct a comprehensive evaluation of the governance plan effect for each unhealthy unit area;

[0105] Obtain the effect of the program governance: Based on the comprehensive assessment results, determine the effect of the program governance for each unhealthy unit area, summarize and analyze the governance effects, and provide experience and reference for future river governance.

[0106] S5. Establish an ecological assessment model, input the unhealthy unit area, output the governance demand index of each unhealthy unit area according to the ecological assessment model, and then generate ecological restoration measures according to the governance demand index;

[0107] The steps of S5 are as follows:

[0108] S5.1. Use the InVEST model and the MIKE model to establish an ecological assessment model for the river;

[0109] S5.2. Input the unhealthy unit area, output the governance demand index of each unhealthy unit area according to the ecological assessment model, and then analyze the ecological restoration measures according to the governance demand index. Generate ecological restoration measures based on the analysis results. The specific calculation formula is as follows:

[0110] E=n1Iinv+n2Imike

[0111] Among them, I inv is the ecological index output by the InVEST model, I mike is the hydrological index output by the MIKE model, E is the comprehensive evaluation index, n1 and n2 are weight coefficients, which are determined according to the specific evaluation focus;

[0112] D=Etarget+Ecurrent

[0113] Among them, D is the governance demand indicator, E targer is the target value of comprehensive evaluation index under healthy state, E current is the current comprehensive assessment index value of the unhealthy unit area;

[0114] Water quality improvement demand formula:

[0115] Dwater=Ccurrent-Ctarget

[0116] Among them, C target is the target pollutant concentration, C current is the current pollutant concentration, D water Demand indicators for water quality improvement;

[0117] Dwater=r×A

[0118] Among them, r is the removal efficiency of pollutants by aquatic plants, and A is the increase in the planting area of ​​aquatic plants;

[0119] Water regulation requirements:

[0120] Dflow=Qtarget-Qcurrent

[0121] Among them, Q target is the target flow, Q current is the current flow rate, D flow Demand indicators for water regulation;

[0122] Dflow=k×x

[0123] Among them, k is the influence coefficient of the regulation measure on the flow, and x is the parameter of the regulation measure (dam height, gate opening change, etc.);

[0124] Biodiversity enhancement needs:

[0125] Dbio=Htarget-Hcurrent

[0126] Among them, H target is the target pollutant concentration, H current is the current pollutant concentration, D bio Demand indicators for water quality improvement;

[0127] Dbio=s×W

[0128] Among them, s is the improvement coefficient of wetland to habitat suitability, and W is the increase in wetland area;

[0129] S6. Analyze the impact of ecological restoration measures in unhealthy unit areas in combination with the river direction, obtain auxiliary impact data of ecological restoration measures in upstream unhealthy unit areas on downstream unhealthy unit areas, and then dynamically adjust the downstream unhealthy unit areas based on the auxiliary impact data.

[0130] The steps of S6 are as follows:

[0131] S6.1. Establish an ecological restoration simulation model, and input the unhealthy unit areas in sequence according to the river location, with the upstream having a higher priority than the downstream. Then, according to the ecological restoration simulation model, analyze the impact of the ecological restoration measures on the unhealthy unit areas in combination with the river direction, and obtain the auxiliary impact data of the ecological restoration measures on the downstream unhealthy unit areas;

[0132] S6.2. Combine the auxiliary impact data with the ecological restoration measures to dynamically adjust the measures for each unhealthy unit area, thereby updating the ecological restoration measures for each unhealthy unit area. The specific steps are as follows:

[0133] Establish an ecological restoration simulation model: determine the model's input parameters, including the river's geographic information, hydrological data, ecological indicators, etc., select system dynamics models, agent-based models, etc., which can simulate the effects and mutual influences of ecological restoration measures, and then calibrate and verify the model's parameters to ensure the model's accuracy and reliability;

[0134] Input unhealthy unit areas: According to the river location, the unhealthy unit areas are input into the model in the order from upstream to downstream, and the location information and health status of each unit area are marked;

[0135] Restoration measures impact analysis: For each unhealthy unit area, determine its ecological restoration measures, such as planting aquatic plants, building wetlands, improving river morphology, etc., simulate the impact of these restoration measures on the river direction, consider factors such as water flow, material transfer, and biological migration, and then analyze the auxiliary impact of the restoration measures of the upstream unhealthy unit area on the downstream unhealthy unit area. For example, the improvement of water quality in the upstream may reduce the pollution pressure in the downstream, and the restoration of the habitat in the upstream may promote the biodiversity in the downstream;

[0136] Obtain auxiliary impact data: Extract auxiliary impact data of upstream unhealthy unit areas on downstream unhealthy unit areas from simulation results, such as changes in water quality, biological populations, and water flow conditions. At the same time, these impacts can be represented by quantitative data, such as how much the concentration of a certain pollutant in the downstream is reduced due to upstream remediation measures, or how much the number of a certain organism in the downstream is increased;

[0137] Dynamic adjustment of measures: Combine auxiliary impact data with ecological restoration measures for each unhealthy unit area to dynamically adjust measures;

[0138] If the remediation measures in the upstream have a positive impact on the downstream, the remediation measures in the downstream unit area can be appropriately adjusted to make full use of this auxiliary effect. If the improvement of water quality in the upstream reduces the pollution pressure in the downstream, the scale of construction of sewage treatment facilities in the downstream can be reduced.

[0139] On the contrary, if the restoration measures in the upstream have a negative impact on the downstream, the restoration measures in the downstream need to be adjusted to cope with it. If the construction of dams in the upstream leads to a decrease in water flow in the downstream, it may be necessary to increase water replenishment measures in the downstream.

[0140] Update ecological restoration measures: Based on the results of dynamic adjustments, update the ecological restoration measures for each unhealthy unit area, record the updated measures, and rerun the simulation model to verify the adjusted effects.

[0141] The second object of the present invention is to provide a river ecological environment data monitoring system based on big data, including any one of the above-mentioned river ecological environment data monitoring methods based on big data, including a quantitative index analysis unit 10, a treatment plan effect analysis unit 20 and a measure dynamic adjustment unit 30;

[0142] The quantitative index analysis unit 10 is used to divide the river into unit areas, and to perform quantitative index analysis on the historical information data according to the structural data and functional representation of the river;

[0143] The treatment scheme effect analysis unit 20 is used to compare the predicted river health standard of the unit area with the pressure-bearing resilience and the ecological service value, and collect historical treatment plans of the river, and analyze the effect of the treatment scheme by combining the historical treatment plans with the historical pressure-bearing resilience and the historical ecological service value of the unhealthy unit area;

[0144] The dynamic adjustment unit 30 of measures is used to output the governance demand index of each unhealthy unit area according to the ecological assessment model, and then generate ecological restoration measures according to the governance demand index, and then analyze the impact of the ecological restoration measures on the unhealthy unit area in combination with the river direction, and dynamically adjust the downstream unhealthy unit area according to the auxiliary impact data.

[0145] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A river ecological environment data monitoring method based on big data, characterized by: The steps include: S1. Collect historical information data of the river, then divide the river into unit areas, and classify the historical information data according to the divided unit areas; S2. Analyze historical information data based on the structural data and functional characterization of the river to obtain the pressure-bearing resilience and ecological service value, and make development predictions based on the historical pressure-bearing resilience and historical ecological service value; S3. Set the river health standard. Set the dynamic river health standard according to the structural position of the unit area. Then compare the predicted river health standard with the pressure resilience and ecological service value of the unit area. S4. Collect historical river management plans and analyze the effectiveness of management plans by combining the historical pressure-bearing resilience and historical ecological service value of unhealthy unit areas; S5. Establish an ecological assessment model, input the unhealthy unit area, output the governance demand index of each unhealthy unit area according to the ecological assessment model, and then generate ecological restoration measures according to the governance demand index; S6. Analyze the impact of ecological restoration measures in unhealthy unit areas in combination with the river direction, obtain auxiliary impact data of ecological restoration measures in upstream unhealthy unit areas on downstream unhealthy unit areas, and then dynamically adjust the downstream unhealthy unit areas based on the auxiliary impact data.

2. The method for monitoring river ecological environment data based on big data according to claim 1 is characterized by: The S1 establishes a data transmission channel with the River Management Office, and uploads historical information data of the river through staff, while obtaining geographic data of the river that needs to be monitored.

3. The method for monitoring river ecological environment data based on big data according to claim 1 is characterized by: The S1 divides the river into unit areas with the river channel, river bank and river bank belt at intervals of one hundred meters along the flow direction, and divides the entire river into multiple unit areas. At the same time, the geographical data of the unit area is combined with the historical information data to perform the same geographical location division, and obtain the historical information data corresponding to each unit area.

4. The method for monitoring river ecological environment data based on big data according to claim 1 is characterized in that: The steps of S2 are as follows: S2.

1. Use heterogeneity test, redundancy test and responsiveness test statistical methods to examine and select quantitative indicators suitable for the structural and functional characterization of river ecosystems from historical information data; Using water use efficiency and benthic macroinvertebrates to characterize the stress-bearing resilience of river ecosystems; Taking water conservation, carbon fixation and oxygen release, air purification, biological habitat, and leisure and entertainment ecological services as the objects, the ecological service value of river ecosystems is quantitatively evaluated by means of functional value and selected capacity value evaluation methods; S2.

2. Make development forecasts based on historical pressure-bearing resilience and historical ecological service value to obtain predicted pressure-bearing resilience and predicted ecological service value.

5. The method for monitoring river ecological environment data based on big data according to claim 1 is characterized by: The steps of S3 are as follows: S3.

1. Obtain the requirements for setting river health standards and the required time for this environmental protection management; S3.

2. Dynamically analyze the river health standard in combination with the structural position of each unit area to obtain the river health standard corresponding to each unit area; S3.

3. According to the required time of governance, the predicted resilience to pressure and predicted ecological service value corresponding to the unit area are intercepted, and then the predicted resilience to pressure and predicted ecological service value are compared with the river health standard. When the predicted resilience to pressure and predicted ecological service value of the unit area do not meet the river health standard, the unit area is regarded as an unhealthy unit area. Conversely, when the predicted resilience to pressure and predicted ecological service value of the unit area meet the river health standard, the unit area will continue to be monitored.

6. The method for monitoring river ecological environment data based on big data according to claim 1 is characterized by: The steps of S4 are as follows: S4.

1. Collect historical river management plans, and extract the corresponding historical pressure-bearing resilience and historical ecological service value of unhealthy unit areas according to the time period corresponding to the historical management plans; S4.

2. Combine the historical pressure-bearing resilience and historical ecological service value extracted in S4.1 with the historical governance plan to analyze the effectiveness of the governance plan and obtain the governance effect of each unhealthy unit area.

7. The method for monitoring river ecological environment data based on big data according to claim 1 is characterized by: The steps of S5 are as follows: S5.

1. Use the InVEST model and the MIKE model to establish an ecological assessment model for the river; S5.

2. Input the unhealthy unit area, output the governance demand index of each unhealthy unit area according to the ecological assessment model, then analyze the ecological restoration measures according to the governance demand index, and generate ecological restoration measures according to the analysis results.

8. The method for monitoring river ecological environment data based on big data according to claim 1 is characterized by: The steps of S6 are as follows: S6.

1. Establish an ecological restoration simulation model, and input the unhealthy unit areas in sequence according to the river location, with the upstream having a higher priority than the downstream. Then, according to the ecological restoration simulation model, analyze the impact of the ecological restoration measures on the unhealthy unit areas in combination with the river direction, and obtain the auxiliary impact data of the ecological restoration measures on the downstream unhealthy unit areas; S6.

2. Combine the auxiliary impact data with ecological restoration measures to dynamically adjust the measures for each unhealthy unit area, thereby updating the ecological restoration measures for each unhealthy unit area.

9. A method for realizing a river ecological environment data monitoring system based on big data, comprising a river ecological environment data monitoring method based on big data as claimed in any one of claims 1 to 8, characterized in that: It includes a quantitative index analysis unit (10), a governance scheme effect analysis unit (20) and a measure dynamic adjustment unit (30); The quantitative index analysis unit (10) is used to divide the river into unit areas, and to perform quantitative index analysis on the historical information data according to the structural data and functional representation of the river; The treatment scheme effect analysis unit (20) is used to compare the predicted river health standard with the pressure-bearing resilience and ecological service value of the unit area, collect historical treatment plans of the river, and analyze the effect of the treatment scheme by combining the historical treatment plans with the historical pressure-bearing resilience and historical ecological service value of the unhealthy unit area; The dynamic adjustment unit (30) of the measures is used to output the governance demand index of each unhealthy unit area according to the ecological assessment model, and then generate ecological restoration measures according to the governance demand index, and then analyze the impact of the restoration measures on the unhealthy unit area in combination with the river direction, and dynamically adjust the downstream unhealthy unit area according to the auxiliary impact data.

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