Water ecological environment pollution risk evaluation method and system based on RRM and GIS spatial analysis

Abstract

The invention relates to the technical field of water ecological environment protection, and particularly provides a water ecological environment pollution risk evaluation method and system based on RRM and GIS spatial analysis, and the method comprises the following steps: collecting water quality data and factor data of a to-be-evaluated region; constructing a preliminary index system for water ecological environment pollution risk evaluation; an SPSS principal component analysis method is adopted, indexes in the preliminary index system are quantitatively screened, a final index system is obtained, and the weight value of each index in the final index system is calculated; constructing an evaluation system GIS database; based on the RRM evaluation model, calculating a membership degree graph layer of each index and a membership degree graph layer of each factor in an evaluation system GIS database; and performing spatial weighted summation on each factor membership map layer to obtain an ecological risk value of the to-be-evaluated region. According to the method, the GIS technology and the RRM model are coupled to evaluate the water ecological environment pollution risk, and technical support can be provided for water ecological environment protection.

Description

Technical Field

[0001] The present invention belongs to the technical field of water ecological environment protection, and specifically relates to a water ecological environment pollution risk assessment method and system based on RRM and GIS spatial analysis. Background Art

[0002] At present, the domestic ecological risk assessment of watershed and regional water ecological environment is mostly qualitative theoretical analysis, and the research objectives are limited to a single indicator of a single system. However, there are many stress factors in the watershed and regional water ecological environment, which will cause different ecological effects. Human activities lead to excessive content of nutrients such as nitrogen and phosphorus in water bodies and sudden changes in the nitrogen-phosphorus ratio, which may cause eutrophication of water bodies; the imbalance between carbon emissions and carbon fixation may cause climate anomalies and affect the size and distribution of rainfall in the basin; human industrial and agricultural activities and native geological background may increase the risk of heavy metal pollution in water bodies. In traditional water ecological environment ecological risk assessment research, the evaluation system is relatively simple, and surface water or groundwater is usually used as a research system alone.

[0003] Solutions of existing technologies: At present, the evaluation system of ecological risk assessment of water ecological environment is relatively simple, and surface water or groundwater is usually used as the research system alone. Comprehensively consider various risk sources (such as human agricultural activities, industrial activities, geological background and natural risk sources) and their mutual coupling mechanism, so as to make the ecological risk assessment index system of watershed and regional water ecological environment more perfect, and combine multi-system research (such as surface water-groundwater ecological environment system), comprehensively combine various ecological effects and various risk factors and their response coupling mechanism, and use multivariate statistical model to couple RRM fuzzy evaluation model and combine spatial calculation model, so as to more truly and comprehensively reflect the ecological risk of regional water ecological environment. Among them, RRM is a relative risk model.

[0004] Existing technical problems: In the process of risk assessment, the selection of evaluation indicators and the determination of weights are crucial. Only using surface water or groundwater as the research object to evaluate the ecological risk of the water ecological environment cannot fully reflect the ecological risk of the water ecological environment within the regional scope, and its evaluation results will also have a certain lag in risk control. In addition, under different hydrogeological conditions, coupling may occur between surface water and groundwater, which will undoubtedly increase the comprehensive ecological risk. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a water ecological environment pollution risk assessment method and system based on RRM and GIS spatial analysis, providing technical support for water ecological environment protection.

[0006] To achieve the above object, the present invention provides the following solutions:

[0007] The water ecological environment pollution risk assessment method based on RRM and GIS spatial analysis includes the following steps:

[0008] Collect water quality data and factor data of the area to be evaluated;

[0009] Based on the correlation analysis method, the water quality data and the factor data are preliminarily screened to construct a preliminary indicator system for water ecological environment pollution risk assessment;

[0010] The SPSS principal component analysis method is used to calculate the characteristic value of each indicator in the preliminary indicator system, and based on the characteristic value, the information sensitivity of each indicator is calculated;

[0011] Based on the information sensitivity of each indicator, quantitatively screen the indicators in the preliminary indicator system to obtain a final indicator system, and calculate the weight value of each indicator in the final indicator system;

[0012] Normalize all data in the final indicator system and build an evaluation system GIS database;

[0013] Based on the RRM evaluation model, the membership layer of each indicator is calculated in the GIS database of the evaluation system, and based on the membership layer of each indicator and the weight value of each indicator, the membership layer of each factor is calculated; the membership layer of each factor is spatially weighted and summed to obtain the ecological risk value of the area to be evaluated, and the water ecological environment pollution risk assessment based on the RRM evaluation model and GIS spatial analysis function is completed.

[0014] Preferably, the factor data include natural factors, life factors, agricultural factors, and industrial factors;

[0015] The natural factors include rainfall, NDVI grid data, vegetation NPP grid data and elevation data in the area to be evaluated;

[0016] The living factors include the resident population data, domestic sewage data and domestic garbage discharge of the area to be evaluated;

[0017] The agricultural factors include the cultivated land area, fertilizer application, pesticide application, livestock breeding and agricultural water consumption in the area to be evaluated;

[0018] The industrial factors include the output value of different industries in the area to be evaluated, the discharge of industrial solid waste and the discharge of industrial wastewater.

[0019] Preferably, the method for obtaining the final indicator system is:

[0020] Calculating the characteristic value of each indicator in the preliminary indicator system, and calculating the variance contribution rate of the characteristic value;

[0021] Accumulate the variance contribution rate to obtain the number of retained principal components;

[0022] Based on the eigenvalues, calculating the eigenvectors of the indicators;

[0023] Based on the eigenvector and the eigenvalue, calculating the degree to which each principal component is affected by each indicator;

[0024] Based on the variance contribution rate and the influence degree, the sensitivity of different principal components to the influence of changes in different indicators is obtained;

[0025] Based on the number of retained principal components and the sensitivity, the information sensitivity of each indicator is calculated;

[0026] The information sensitivity rankings of all indicators are added up to obtain the number of retained indicators, thus completing the construction of the final indicator system.

[0027] Preferably, based on the information sensitivity of each indicator in the final indicator system, a weight value of each indicator is obtained.

[0028] Preferably, based on the RRM evaluation model, the method for calculating the membership layer of each indicator and the membership layer of each factor in the evaluation system GIS database is:

[0029] Establishing a fuzzy matrix of each individual indicator in the final indicator system;

[0030] Based on the fuzzy matrix, the RRM fuzzy evaluation model is adopted to calculate the fuzzy evaluation of the index layer on the factor layer;

[0031] Based on the fuzzy evaluation of the indicator layer on the factor layer, the membership layer of each indicator is calculated in the evaluation system GIS database;

[0032] Based on the membership layers of each indicator and the weight values ​​of each indicator, a GIS-based weighted summation model is used to calculate the fuzzy evaluation of the factor layer on the target layer to obtain the membership layers of each factor; wherein the target layer represents the ecological risk value.

[0033] The present invention provides a water ecological environment pollution risk assessment system based on RRM and GIS spatial analysis, which is used to implement the method, including:

[0034] Data collection module, used to collect water quality data and factor data of the area to be evaluated;

[0035] A first indicator screening module is used to perform preliminary screening of the water quality data and the factor data based on a correlation analysis method to construct a preliminary indicator system for water ecological environment pollution risk assessment;

[0036] The second indicator screening module is used to calculate the characteristic value of each indicator in the preliminary indicator system by using the SPSS principal component analysis method, and calculate the information sensitivity of each indicator based on the characteristic value; based on the information sensitivity of each indicator, quantitatively screen the indicators in the preliminary indicator system to obtain the final indicator system, and calculate the weight value of each indicator in the final indicator system;

[0037] A database construction module is used to normalize all data in the final indicator system and construct an evaluation system GIS database;

[0038] The risk assessment module is used to calculate the membership layer of each indicator in the GIS database of the evaluation system based on the RRM evaluation model, and calculate the membership layer of each factor based on the membership layer of each indicator and the weight value of each indicator; perform spatial weighted summation on the membership layer of each factor to obtain the ecological risk value of the area to be evaluated, and complete the water ecological environment pollution risk assessment based on the RRM evaluation model and GIS spatial analysis function.

[0039] Preferably, the second indicator screening module includes:

[0040] An eigenvalue calculation unit, used to calculate the eigenvalue of each indicator in the preliminary indicator system, and calculate the variance contribution rate of the eigenvalue;

[0041] A principal component retention number determination unit is used to accumulate the variance contribution rate to obtain the number of retained principal components;

[0042] A feature vector calculation unit, used for calculating the feature vector of each indicator based on the feature value;

[0043] An influence degree calculation unit, used for calculating the influence degree of each principal component on each indicator based on the eigenvector and the eigenvalue;

[0044] A sensitivity calculation unit, used for obtaining the sensitivity of different principal components to the influence of changes in different indicators based on the variance contribution rate and the influence degree;

[0045] An information sensitivity calculation unit, used to calculate the information sensitivity of each indicator based on the number of retained principal components and the sensitivity;

[0046] The indicator screening unit is used to sort and sum the information sensitivity of all indicators, obtain the number of retained indicators, and complete the construction of the final indicator system.

[0047] Preferably, the risk assessment module includes:

[0048] A fuzzy matrix construction unit, used to establish the fuzzy matrix of each single indicator in the final indicator system;

[0049] The first module evaluation unit is used to calculate the fuzzy evaluation of the index layer on the factor layer based on the fuzzy matrix and using the RRM fuzzy evaluation model;

[0050] An indicator membership layer calculation unit is used to calculate the membership layer of each indicator in the evaluation system GIS database based on the fuzzy evaluation of the indicator layer on the factor layer;

[0051] The factor membership layer calculation unit is used to calculate the fuzzy evaluation of the factor layer on the target layer based on the membership layer of each indicator and the weight value of each indicator, and obtain the membership layer of each factor by adopting a weighted summation model based on GIS; wherein the target layer represents the ecological risk value.

[0052] Compared with the prior art, the present invention has the following beneficial effects:

[0053] 1. Using the principal component analysis of SPSS, quantitative screening of indicators in the preliminary indicator system is carried out according to the sensitivity of indicator information, so as to build a more perfect preliminary indicator system for risk assessment;

[0054] 2. Based on the RRM model, GIS technology and fuzzy comprehensive risk assessment method are coupled to calculate the regional water ecological environment pollution risk more objectively and realistically;

[0055] 3. Spatial weighted summation of each factor's membership layer can realize spatial analysis of water ecological environment pollution risk assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0057] Figure 1 The present invention is a flowchart of a method for water ecological environment pollution risk assessment based on RRM and GIS spatial analysis proposed in an embodiment of the present invention.

[0058] Figure 2 This is the regional water ecological environment eutrophication risk assessment result calculated by the embodiment of the present invention.

[0059] Figure 3 This is the regional water ecological environment carbon emission risk assessment result calculated by the embodiment of the present invention.

[0060] Figure 4 This is the risk assessment result of heavy metal pollution in the regional water ecological environment calculated by the embodiment of the present invention. DETAILED DESCRIPTION

[0061] 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.

[0062] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0063] Embodiment 1

[0064] like Figure 1 As shown in the figure, the water ecological environment pollution risk assessment method based on RRM and GIS spatial analysis includes the following steps:

[0065] S1: Collect water quality data and factor data of the area to be evaluated.

[0066] A further embodiment is that the factor data includes natural factors, life factors, agricultural factors, and industrial factors;

[0067] Natural factors include rainfall, NDVI raster data, vegetation NPP raster data, and elevation data in the area to be evaluated;

[0068] Living factors include the resident population data, domestic sewage data, and domestic waste discharge of the area to be evaluated;

[0069] Agricultural factors include the cultivated land area, fertilizer application, pesticide application, livestock breeding and agricultural water use in the area to be evaluated;

[0070] Industrial factors include the output value of different industries in the evaluated area, industrial solid waste emissions and industrial wastewater emissions.

[0071] Specifically, in this embodiment, existing surface water quality data is collected in the region, and the existing water quality data comes from the Provincial Department of Ecology and Environment and the National Surface Water Quality Automatic Monitoring System. The surface water and groundwater resources in each region come from the provincial water resources bulletin, the website of the Provincial Hydrology and Water Resources Bureau, or the provincial water conservancy and water affairs website. In addition, surface water sampling points are evenly distributed in the region to collect and test water samples.

[0072] Collect factor data within the regional scope. Data such as rainfall are from the China Meteorological Data Platform website. NDVI and vegetation NPP data are downloaded from the website of the Resource and Environmental Science Data Center of the Chinese Academy of Sciences (http: / / www.resdc.cn / Default.aspx). Elevation and other related data are downloaded from the Geospatial Data Cloud website, the download path is: \DEM digital elevation data\SRTMDEM 90M resolution original elevation data. Data such as permanent population, domestic sewage, domestic garbage discharge, cultivated land area, fertilizer application, pesticide application, animal husbandry, and output value of different industries, industrial solid waste discharge, industrial wastewater discharge, and agricultural water use are all from the yearbook of the National Bureau of Statistics website.

[0073] S2: Based on the correlation analysis method, water quality data and factor data are preliminarily screened to construct a preliminary indicator system for water ecological environment pollution risk assessment (including water quality indicator data and factor data that may affect water quality indicators). The correlation analysis calculation formula is as follows:

[0074] ,

[0075] Where r represents the correlation coefficient; cov(X,Y) represents the covariance of variables X and Y; D(X) and D(Y) represent the standard deviations of variables X and Y, respectively.

[0076] S3: SPSS principal component analysis method is used to calculate the characteristic value of each indicator in the preliminary indicator system, and based on the characteristic value, the information sensitivity of each indicator is calculated; based on the information sensitivity of each indicator, the indicators in the preliminary indicator system are quantitatively screened to obtain the final indicator system, and the weight value of each indicator in the final indicator system is calculated.

[0077] A further implementation method is that the method for obtaining the final indicator system is:

[0078] Calculating the characteristic value of each indicator in the preliminary indicator system, and calculating the variance contribution rate of the characteristic value;

[0079] Accumulate the variance contribution rate to obtain the number of retained principal components;

[0080] Based on the eigenvalues, calculating the eigenvectors of the indicators;

[0081] Based on the eigenvector and the eigenvalue, calculating the degree to which each principal component is affected by each indicator;

[0082] Based on the variance contribution rate and the influence degree, the sensitivity of different principal components to the influence of changes in different indicators is obtained;

[0083] Based on the number of retained principal components and the sensitivity, the information sensitivity of each indicator is calculated;

[0084] The information sensitivity rankings of all indicators are added up to obtain the number of retained indicators, thus completing the construction of the final indicator system.

[0085] S4: Standardize all data in the final indicator system and construct the evaluation system GIS database. In this embodiment, in order to eliminate the impact of the difference in the dimensions of different data, standardize all data.

[0086] Forward data normalization: ;

[0087] Negative data normalization: .

[0088] Where D i represents the normalized value; X i represents the measured value of variable i; X max With X min They represent the maximum and minimum values ​​of all test values ​​of variable i respectively.

[0089] All data are imported into ArcGIS to form vector data, and finally converted into raster data using different functions in the ArcGIS toolbox.

[0090] S5: Based on the RRM evaluation model, calculate the membership layer of each indicator in the GIS database of the evaluation system, and calculate the membership layer of each factor based on the membership layer of each indicator and the weight value of each indicator; perform spatial weighted summation on the membership layer of each factor to obtain the ecological risk value of the area to be evaluated, and complete the water ecological environment pollution risk assessment based on the RRM evaluation model and GIS spatial analysis function. The evaluation results include the eutrophication risk of the water ecological environment, the carbon emission risk of the water ecological environment, and the heavy metal pollution risk of the water ecological environment. Figure 2 , Figure 3 , Figure 4 shown.

[0091] The risk of eutrophication of the water ecological environment is usually described by its probability and intensity. The calculation formula is as follows:

[0092] ,

[0093] Where: R T represents the water ecological environment eutrophication risk index; T Di represents the normalized value of the i-th indicator among the factors affecting the risk of eutrophication of the water ecological environment; W Ti represents the weight of the i-th risk source; n represents the number of evaluation indicators.

[0094] The carbon emission risk of the water ecological environment refers to the risk level of the water ecological environment ecosystem after being disturbed by external carbon emissions and carbon fixation. The calculation formula is as follows:

[0095] ,

[0096] In the formula, R C represents the carbon emission risk index of water ecological environment; C Di represents the normalized value of the ith indicator among the factors affecting the carbon emission risk of water ecological environment; W Ci represents the weight of the i-th risk source; n represents the number of evaluation indicators.

[0097] The risk of heavy metal pollution in the water ecological environment usually affects the water quality and the health of the water ecological environment. The calculation formula for the risk index of heavy metal pollution in the water ecological environment is as follows:

[0098] ,

[0099] In the formula, R M represents the risk index of heavy metal pollution in water ecological environment; M Di represents the normalized value of the i-th indicator among the factors affecting the risk of heavy metal pollution; W Mi represents the weight of the i-th risk source; n represents the number of evaluation indicators.

[0100] A further implementation method is that, based on the RRM evaluation model, the method for calculating the membership layer of each indicator and the membership layer of each factor in the evaluation system GIS database is:

[0101] Establish the fuzzy matrix of each single indicator in the final indicator system: ,

[0102] Based on the fuzzy matrix, the RRM fuzzy evaluation model is used to calculate the fuzzy evaluation of the indicator layer on the factor layer: , .

[0103] In the formula, B i represents the factor level risk; R i Represents single indicator risk; A i It represents the membership of the evaluation index to the i-th level; o is the fuzzy matrix composite operation.

[0104] Based on the fuzzy evaluation of the indicator layer on the factor layer, the membership layer of each indicator is calculated in the evaluation system GIS database;

[0105] Based on the membership layers of each indicator and the weight values ​​of each indicator, a GIS-based weighted summation model is used to calculate the fuzzy evaluation of the factor layer on the target layer to obtain the membership layers of each factor; among which, the target layer represents the ecological risk value.

[0106] ,

[0107] In the formula, Q represents the target layer risk; B represents the single factor layer risk; W m represents the membership of the evaluation index to the mth factor layer; o is the fuzzy matrix composite operation.

[0108] In this embodiment, the membership layers of each indicator are first calculated in GIS, and the membership layers of the natural factor, life factor, agricultural factor, industrial factor and other factor levels are calculated based on the weighted summation function of GIS and the weight value of each indicator. Then, the membership layers are spatially weighted summed to finally realize the spatial analysis of water ecological environment pollution risk assessment, and the data of each grid is the risk value of the location.

[0109] Embodiment 2

[0110] The present invention also provides a water ecological environment pollution risk assessment system based on RRM and GIS spatial analysis, which is used to implement the method, including:

[0111] Data collection module, used to collect water quality data and factor data of the area to be evaluated;

[0112] The first indicator screening module is used to preliminarily screen water quality data and factor data based on correlation analysis to build a preliminary indicator system for water ecological environment pollution risk assessment;

[0113] The second indicator screening module is used to calculate the characteristic value of each indicator in the preliminary indicator system by using the SPSS principal component analysis method, and calculate the information sensitivity of each indicator based on the characteristic value; based on the information sensitivity of each indicator, quantitatively screen the indicators in the preliminary indicator system to obtain the final indicator system, and calculate the weight value of each indicator in the final indicator system;

[0114] The database construction module is used to normalize all data in the final indicator system and build the evaluation system GIS database;

[0115] The risk assessment module is used to calculate the membership layers of various indicators and factors in the evaluation system GIS database based on the RRM evaluation model, obtain the ecological risk value of the area to be evaluated, and complete the water ecological environment pollution risk assessment based on the RRM evaluation model and GIS spatial analysis function.

[0116] A further implementation method is that the second indicator screening module includes:

[0117] The eigenvalue calculation unit is used to calculate the eigenvalue of each indicator in the preliminary indicator system and calculate the variance contribution rate of the eigenvalue;

[0118] A principal component retention number determination unit is used to obtain the number of retained principal components based on the cumulative variance contribution rate;

[0119] A characteristic vector calculation unit, used for calculating the characteristic vector of each indicator based on the characteristic value;

[0120] An influence degree calculation unit, used to calculate the influence degree of each principal component on each indicator based on the eigenvector and eigenvalue;

[0121] The sensitivity calculation unit is used to obtain the sensitivity of different principal components to the changes of different indicators based on the variance contribution rate and the degree of influence;

[0122] An information sensitivity calculation unit, used to calculate the information sensitivity of each indicator based on the number of retained principal components and the sensitivity;

[0123] The indicator screening unit is used to sort and sum the information sensitivity of all indicators, obtain the number of retained indicators, and complete the construction of the final indicator system.

[0124] A further implementation is that the risk assessment module includes:

[0125] The fuzzy matrix construction unit is used to establish the fuzzy matrix of each single indicator in the final indicator system;

[0126] The first module evaluation unit is used to calculate the fuzzy evaluation of the index layer on the factor layer based on the fuzzy matrix and the RRM fuzzy evaluation model;

[0127] The indicator membership layer calculation unit is used to calculate the membership layer of each indicator in the evaluation system GIS database based on the fuzzy evaluation of the indicator layer on the factor layer;

[0128] The factor membership layer calculation unit is used to calculate the fuzzy evaluation of the factor layer on the target layer based on the membership layer of each indicator and the weight value of each indicator, and obtain the membership layer of each factor by adopting a GIS-based weighted summation model; among which, the target layer represents the ecological risk value.

[0129] The embodiments described above are only descriptions of the preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A water ecological environment pollution risk assessment method based on RRM and GIS spatial analysis is characterized by: The following steps are involved: Collect water quality data and factor data of the area to be evaluated; Based on the correlation analysis method, the water quality data and the factor data are preliminarily screened to construct a preliminary indicator system for water ecological environment pollution risk assessment; The SPSS principal component analysis method is used to calculate the characteristic value of each indicator in the preliminary indicator system, and based on the characteristic value, the information sensitivity of each indicator is calculated; Based on the information sensitivity of each indicator, quantitatively screen the indicators in the preliminary indicator system to obtain a final indicator system, and calculate the weight value of each indicator in the final indicator system; Normalize all data in the final indicator system and build an evaluation system GIS database; Based on the RRM evaluation model, the membership layer of each indicator is calculated in the evaluation system GIS database, and based on the membership layer of each indicator and the weight value of each indicator, the membership layer of each factor is calculated; The specific calculation method is: Establishing a fuzzy matrix of each individual indicator in the final indicator system; Based on the fuzzy matrix, the RRM fuzzy evaluation model is adopted to calculate the fuzzy evaluation of the index layer on the factor layer; Based on the fuzzy evaluation of the indicator layer on the factor layer, the membership layer of each indicator is calculated in the evaluation system GIS database; Based on the membership layer of each indicator and the weight value of each indicator, a GIS-based weighted summation model is used to calculate the fuzzy evaluation of the factor layer on the target layer to obtain the membership layer of each factor; wherein the target layer represents the ecological risk value; The spatial weighted summation of the membership layers of each factor is performed to obtain the ecological risk value of the area to be evaluated, and the water ecological environment pollution risk assessment based on the RRM evaluation model and GIS spatial analysis function is completed.

2. The water ecological environment pollution risk assessment method based on RRM and GIS spatial analysis according to claim 1 is characterized in that: The factor data include natural factors, life factors, agricultural factors and industrial factors; The natural factors include rainfall, NDVI grid data, vegetation NPP grid data and elevation data in the area to be evaluated; The living factors include the resident population data, domestic sewage data and domestic garbage discharge of the area to be evaluated; The agricultural factors include the cultivated land area, fertilizer application, pesticide application, livestock breeding and agricultural water consumption in the area to be evaluated; The industrial factors include the output value of different industries in the area to be evaluated, the discharge of industrial solid waste and the discharge of industrial wastewater.

3. The water ecological environment pollution risk assessment method based on RRM and GIS spatial analysis according to claim 1 is characterized in that: The method for obtaining the final indicator system is: Calculating the characteristic value of each indicator in the preliminary indicator system, and calculating the variance contribution rate of the characteristic value; Accumulate the variance contribution rate to obtain the number of retained principal components; Based on the eigenvalues, calculating the eigenvectors of the indicators; Based on the eigenvector and the eigenvalue, calculating the degree to which each principal component is affected by each indicator; Based on the variance contribution rate and the influence degree, the sensitivity of different principal components to the influence of changes in different indicators is obtained; Based on the number of retained principal components and the sensitivity, the information sensitivity of each indicator is calculated; The information sensitivity rankings of all indicators are added up to obtain the number of retained indicators, thus completing the construction of the final indicator system.

4. The water ecological environment pollution risk assessment method based on RRM and GIS spatial analysis according to claim 1 is characterized in that: Based on the information sensitivity of each indicator in the final indicator system, a weight value of each indicator is obtained.

5. A water ecological environment pollution risk assessment system based on RRM and GIS spatial analysis, used to implement the method described in any one of claims 1 to 4, characterized in that: include: Data collection module, used to collect water quality data and factor data of the area to be evaluated; A first indicator screening module is used to perform preliminary screening of the water quality data and the factor data based on a correlation analysis method to construct a preliminary indicator system for water ecological environment pollution risk assessment; The second indicator screening module is used to calculate the characteristic value of each indicator in the preliminary indicator system by using the SPSS principal component analysis method, and calculate the information sensitivity of each indicator based on the characteristic value; Based on the information sensitivity of each indicator, quantitatively screen the indicators in the preliminary indicator system to obtain a final indicator system, and calculate the weight value of each indicator in the final indicator system; A database construction module is used to normalize all data in the final indicator system and construct an evaluation system GIS database; The risk assessment module is used to calculate the membership layer of each indicator in the evaluation system GIS database based on the RRM evaluation model, and calculate the membership layer of each factor based on the membership layer of each indicator and the weight value of each indicator; The spatial weighted summation of the membership layers of each factor is performed to obtain the ecological risk value of the area to be evaluated, and the water ecological environment pollution risk assessment based on the RRM evaluation model and GIS spatial analysis function is completed.

6. The water ecological environment pollution risk assessment system based on RRM and GIS spatial analysis according to claim 5 is characterized in that: The second indicator screening module includes: An eigenvalue calculation unit, used to calculate the eigenvalue of each indicator in the preliminary indicator system, and calculate the variance contribution rate of the eigenvalue; A principal component retention number determination unit is used to accumulate the variance contribution rate to obtain the number of retained principal components; A feature vector calculation unit, used for calculating the feature vector of each indicator based on the feature value; An influence degree calculation unit, used for calculating the influence degree of each principal component on each indicator based on the eigenvector and the eigenvalue; A sensitivity calculation unit, used for obtaining the sensitivity of different principal components to the influence of changes in different indicators based on the variance contribution rate and the influence degree; An information sensitivity calculation unit, used to calculate the information sensitivity of each indicator based on the number of retained principal components and the sensitivity; The indicator screening unit is used to sort and sum the information sensitivity of all indicators, obtain the number of retained indicators, and complete the construction of the final indicator system.

7. The water ecological environment pollution risk assessment system based on RRM and GIS spatial analysis according to claim 5 is characterized in that: The risk assessment module includes: A fuzzy matrix construction unit, used to establish the fuzzy matrix of each single indicator in the final indicator system; The first module evaluation unit is used to calculate the fuzzy evaluation of the index layer on the factor layer based on the fuzzy matrix and using the RRM fuzzy evaluation model; An indicator membership layer calculation unit is used to calculate the membership layer of each indicator in the evaluation system GIS database based on the fuzzy evaluation of the indicator layer on the factor layer; The factor membership layer calculation unit is used to calculate the fuzzy evaluation of the factor layer on the target layer based on the membership layer of each indicator and the weight value of each indicator, and obtain the membership layer of each factor by adopting a weighted summation model based on GIS; wherein the target layer represents the ecological risk value.

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