Coupling coordination degree analysis method for water resource-water environment-water ecology-water disaster association system

Abstract

The invention provides a coupling coordination degree analysis method for a water resource-water environment-water ecology-water disaster associated system, and the method comprises the steps: collecting and screening a key factor of the water resource-water environment-water ecology-water disaster associated system, analyzing the temporal and spatial change characteristics of the key factor, and analyzing the coupling coordination degree of the water resource-water environment-water ecology-water disaster associated system. And establishing an index evaluation system of each association system, determining the weight of the index system of each association system, and analyzing the coupling coordination degree of the water resource-water environment-water ecology-water disaster association system. According to the method, the coupling coordination degree among four systems including water resource, water environment, water ecology and water disaster is quantitatively decoupled, and the comprehensiveness of water resource evaluation is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of water resource management, and in particular relates to a coupling coordination degree analysis method for a water resource-water environment-water ecology-water disaster correlation system. Background Art

[0002] Water resource management is an important part of achieving sustainable development of water resources. For the study of coupling effects, the commonly used ones are environmental Kuznets curve, double exponential model, nonlinear dynamics model, coupling degree model, grey correlation analysis, dynamic coupling model, vector autoregression model, spatial regression model, GIS centroid curve optimization analysis, etc. The coupling coordination degree model uses coupling degree to explain the relationship between several subsystems, and further uses coupling development degree to comprehensively evaluate and study the entire system. Because the model is simple and easy to calculate and the results are intuitive, it is widely used in water conservancy, energy, food, economy, population, urbanization and other fields.

[0003] At present, most coupling and coordination models related to water consider water as a whole and couple it with non-water systems, but fail to consider different systems such as water resources, water environment, water ecology, and water disasters separately. Therefore, it is impossible to fully understand the coupling and coordination situation within the water system. In terms of indicator selection, the indicators considered by existing methods are not comprehensive and subjective, resulting in the selected indicators being not representative enough and unable to reflect the characteristics of water. In terms of weight calculation, the subjective and objective combined weighting method is often used. The weight results are neither subjective nor objective, but the weight results of the two methods are prone to contradictions. Increasing the weight calculation method can increase the number of available method results, thereby improving the fault tolerance of the weight results.

[0004] Therefore, how to evaluate the water system more scientifically and comprehensively is a problem that needs to be solved at present. Summary of the invention

[0005] In view of the problems existing in the prior art, the purpose of the present invention is to provide a coupling coordination degree analysis method for a water resources-water environment-water ecology-water disaster related system, adopt a combination of subjective and objective methods to select key factors, adopt multiple weight calculation methods and utilize a combined weighting method based on game theory to select the optimal weights, and propose a coupling coordination degree analysis method for a water resources-water environment-water ecology-water disaster related system, which quantitatively decouples the coupling coordination degrees among the four systems of water resources-water environment-water ecology-water disasters, which is conducive to improving the comprehensiveness of water resources evaluation.

[0006] The objective of the present invention is achieved through the following technical solutions:

[0007] The present invention provides a coupling coordination degree analysis method for a water resources-water environment-water ecology-water disaster correlation system, comprising the following steps:

[0008] Step 1: Collect and screen the key factors of the water resources-water environment-water ecology-water disaster correlation system:

[0009] Determine the scope of the area to be studied, comprehensively sort out the indicators selected from the existing research results on water resources, water environment, water ecology, and water disasters within the area to be studied, and screen out the key factors of the water resources-water environment-water ecology-water disaster correlation system;

[0010] Step 2: Analyze the spatiotemporal variation characteristics of key factors:

[0011] The trend analysis of the time series of each key factor screened in step 1 was performed using methods including the slope method, Cox-Stuart test, and Mann-Kendall test;

[0012] The spatial agglomeration of each key factor was obtained by using Moran's index analysis;

[0013] Step 3: Establish an indicator evaluation system for the water resources-water environment-water ecology-water disaster linkage system:

[0014] By comprehensively using analytical methods including hierarchical analysis method, entropy weight method, CRITIC weight method and projection pursuit evaluation method, the weight distribution results of four sets of water resources, water environment, water ecology and water disaster systems were obtained;

[0015] Step 4: Determine the weight of the water resources-water environment-water ecology-water disaster correlation system indicator system:

[0016] The four sets of weight distribution results obtained in step 3 were subjected to Spearman correlation analysis, and the linear combination coefficients of the significant correlation methods were calculated using the game theory combined weighting method to calculate the most likely weights of the water resources, water environment, water ecology, and water disaster systems.

[0017] Step 5: Analyze the coupling coordination degree of the water resources-water environment-water ecology-water disaster related system:

[0018] According to the calculation formulas of coupling degree, coordination degree and coupling coordination degree, the coupling degree, coordination degree and coupling coordination degree of the water resources-water environment-water ecology-water disaster association system were calculated, and the spatial distribution characteristics were revealed using QGIS software.

[0019] Furthermore, in step 1, the key factors of the water resources-water environment-water ecology-water disaster correlation system include:

[0020] The key factors of the water resources subsystem include per capita water resources, water consumption per 10,000 yuan of GDP, water resources development and utilization rate, per capita water consumption, domestic water consumption, industrial water consumption, agricultural water consumption, and precipitation;

[0021] The key factors of the water environment subsystem include sewage treatment rate, chemical oxygen demand discharge, drinking water quality compliance rate, ammonia nitrogen discharge, proportion of Class I-III water quality sections, total phosphorus discharge, total industrial wastewater discharge, sediment transport and sediment content;

[0022] The key factors of the water ecological subsystem include ecological water consumption, soil and water loss control area, water system connectivity level, water surface ratio and vegetation comprehensive index;

[0023] The key factors of the water disaster subsystem include the population affected by floods, direct economic losses due to floods, the area of ​​crops affected by floods, the number of reservoirs, the length of levees and the total investment in water conservancy construction.

[0024] Furthermore, in step 3, the specific steps of using the projection pursuit evaluation method include:

[0025] S31, normalize the key factors obtained in step 1, and the calculation formula is:

[0026]

[0027] In the formula, x'(i,j) and x(i,j) represent the data of the i-th sample of the j-th key factor before and after normalization, respectively; x max (j) and x min (j) represents the maximum and minimum value of the jth key factor in the sample set.

[0028] S32, synthesize the p-dimensional sample data X(i) into a one-dimensional projection value z(i) with the unit vector A as the projection direction, and the calculation formula is:

[0029]

[0030] In the formula, T represents the transpose of the matrix; a(j) represents the weight corresponding to the key factor;

[0031] Projection pursuit requires that the local projection points are as dense as possible, preferably condensed into several point clusters; and the projection point clusters should be as scattered as possible overall; construct the projection index function Q(A), the calculation formula is:

[0032] Q(A)=S z ·D z

[0033] In the formula, S z Represents the standard deviation of the projection value; D z Represents the local density of projected values.

[0034] S33, transforming the solution of the projection direction A into a solution of a nonlinear optimization problem, the problem is:

[0035] maxQ(A)=S z ·D z

[0036]

[0037] S34, solving the nonlinear optimization problem can obtain the optimal projection direction A * , a in the best projection direction * (j) represents the weight value of the jth key factor.

[0038] Further, the S described in S32 in step 3 z , the calculation formula is:

[0039]

[0040] Where z(j) represents the sample projection value;

[0041] S32 D z , the calculation formula is:

[0042]

[0043] Where R represents the window radius of the local density, R = 0.1S z ; r i,j Represents the distance between samples, r i,j =|z(i)-z(j)|; u(t) represents the unit step function,

[0044] Furthermore, in step 4, the game theory combined weighting method specifically includes the following steps:

[0045] S41, Spearman rank correlation coefficient was used to measure the consistency of the weighting results of the four sets of methods.

[0046] S42, assume that the basic weight vector set W = {W1, W2, W3, W4} obtained by using the hierarchical analysis method, entropy weight method, CRITIC weight method, and projection pursuit evaluation method in step 3, where Let α = {α1, α2, α3, α4} be the linear combination coefficients, then W * These vectors can be combined linearly to form:

[0047]

[0048] Where W1, W2, W3, and W4 represent the basic weight results calculated by the analytic hierarchy process, entropy weight method, CRITIC weight method, and projection pursuit evaluation method, respectively.

[0049] S43, with W * The goal is to minimize the deviation of any weight vector in W, optimize the linear combination coefficients, and determine the weight coefficients. The calculation formula is:

[0050]

[0051] In the formula, α k represents the linear combination coefficient; represents the transpose of any weight vector; Represents the transpose of the base set of weight vectors.

[0052] S44, according to the differential properties of the matrix, the deviation is minimized and converted into the optimal first-order derivative matrix, the combined optimization coefficient α is obtained and normalized, and the calculation formula is:

[0053]

[0054] In the formula, Represents the portfolio optimization weight.

[0055] S45, calculate the combination weight, the calculation formula is:

[0056]

[0057] Furthermore, step 5 specifically includes the following steps:

[0058] S51, the calculation formula for the coupling degree C among water resources, water environment, water ecology and water disaster subsystems is:

[0059]

[0060] In the formula, U1, U2, U3, and U4 represent the development levels of water resources, water environment, water ecology, and water disaster subsystems respectively; a i 、b j 、c m d n Represents the indicator weights of water resources, water environment, water ecology, and water disaster subsystems; w i 、x j ,y m 、z n They represent the standardized data of water resources, water environment, water ecology and water disaster subsystems respectively; l, q, s and t represent the number of indicators of water resources, water environment, water ecology and water disaster subsystems respectively.

[0061] S52, the calculation formula for the coordination degree T among water resources, water environment, water ecology and water disaster subsystems is:

[0062] T=α1×U1+α2×U2+α3×U3+α4×U4

[0063] In the formula, α1, α2, α3, and α4 represent the weights of water resources, water environment, water ecology, and water disaster subsystems, respectively.

[0064] S53, the calculation formula for the coupling coordination degree D among water resources, water environment, water ecology and water disaster subsystems is:

[0065]

[0066] Compared with the prior art, the present invention has the following beneficial effects:

[0067] Compared with the existing water resources-water environment-water ecosystem coupling coordination model, the present invention introduces a water disaster system, making the water resources evaluation more comprehensive and fully considering the role of the water disaster system in water resources evaluation. It has important reference significance for the scheduling of multiple reservoirs in the basin and the investment in water conservancy facilities. At the same time, it optimizes the indicator system selection and weight distribution calculation, making the coupling coordination model evaluation more scientific. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] The present invention will be further described below in conjunction with the accompanying drawings and embodiments:

[0069] Figure 1 It is a schematic diagram of the calculation flow of the coupling coordination degree analysis method of the water resources-water environment-water ecology-water disaster correlation system of the present invention;

[0070] Figure 2 This is a schematic diagram of the study area and location distribution of the embodiment of the present invention;

[0071] Figure 3 A schematic diagram of spatial distribution of total water consumption provided by an embodiment of the present invention;

[0072] Figure 4 A schematic diagram of the time series changes of the total water consumption provided by an embodiment of the present invention;

[0073] Figure 5 A schematic diagram of the trend change of the Mann-Kendall test of total water consumption provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0074] Example

[0075] like Figure 1 As shown, this embodiment provides a coupling coordination degree analysis method for a water resources-water environment-water ecology-water disaster correlation system, including the following steps:

[0076] Step 1: Collect and screen the key factors of the water resources-water environment-water ecology-water disaster correlation system:

[0077] Determine the scope of the area to be studied, comprehensively sort out the existing research results on water resources, water environment, water ecology, and water disasters within the area to be studied, and select indicators to screen out the key factors of the water resources-water environment-water ecology-water disaster correlation system.

[0078] Specifically, the research results are mainly the results in the relevant publicly published literature. The data of relevant national departments include China Urban Construction Statistical Yearbook, China City Statistical Yearbook, China River Sediment Bulletin, China Water Resources Statistical Yearbook, China Flood and Drought Prevention Bulletin, etc.; the data of relevant provincial departments include provincial water resources bulletin, provincial statistical yearbook, provincial water resources department, provincial ecological environment department; the data of relevant municipal departments include municipal water resources bulletin, municipal ecological environment bureau, municipal ecological environment status bulletin, etc.; network and institutional data include EPS data platform, surface water cover remote sensing dataset, multi-source FVC remote sensing dataset, GIMMS NDVI, PKU GIMMS NDVI, etc.

[0079] The key factors of the water resources subsystem include per capita water resources, water consumption per 10,000 yuan of GDP, water resources development and utilization rate, per capita water consumption, domestic water consumption, industrial water consumption, agricultural water consumption, and precipitation;

[0080] The key factors of the water environment subsystem include sewage treatment rate, chemical oxygen demand discharge, drinking water quality compliance rate, ammonia nitrogen discharge, proportion of Class I-III water quality sections, total phosphorus discharge, total industrial wastewater discharge, sediment transport and sediment content;

[0081] The key factors of the water ecological subsystem include ecological water consumption, soil and water loss control area, water system connectivity level, water surface ratio and vegetation comprehensive index;

[0082] The key factors of the water disaster subsystem include the population affected by floods, direct economic losses due to floods, the area of ​​crops affected by floods, the number of reservoirs, the length of levees and the total investment in water conservancy construction.

[0083] Step 2: Analyze the spatiotemporal variation characteristics of key factors:

[0084] The trend analysis of the time series of each key factor screened in step 1 was performed using methods including the slope method, Cox-Stuart test, and Mann-Kendall test;

[0085] The Moran index analysis was used to obtain the spatial agglomeration of each key factor.

[0086] Step 3: Establish an indicator evaluation system for the water resources-water environment-water ecology-water disaster linkage system:

[0087] By comprehensively using analytical methods including hierarchical analysis method, entropy weight method, CRITIC weight method and projection pursuit evaluation method, we obtained the weight distribution results of four sets of water resources, water environment, water ecology and water disaster systems.

[0088] Specifically, the specific steps of the projection pursuit evaluation method used in this embodiment include:

[0089] S31, normalize the key factors obtained in step 1, and the calculation formula is:

[0090]

[0091] In the formula, x'(i,j) and x(i,j) represent the data of the i-th sample of the j-th key factor before and after normalization, respectively; x max (j) and x min (j) represents the maximum and minimum value of the jth key factor in the sample set.

[0092] S32, synthesize the p-dimensional sample data X(i) into a one-dimensional projection value z(i) with the unit vector A as the projection direction, and the calculation formula is:

[0093]

[0094] In the formula, T represents the transpose of the matrix; a(j) represents the weight corresponding to the key factor.

[0095] Projection pursuit requires that the local projection points are as dense as possible, preferably condensed into several point clusters; and the projection point clusters should be as scattered as possible overall; construct the projection index function Q(A), the calculation formula is:

[0096] Q(A)=S z ·D z

[0097] In the formula, S z Represents the standard deviation of the projection value; D z Represents the local density of projected values.

[0098] The S z , the calculation formula is:

[0099]

[0100] Where z(j) represents the sample projection value.

[0101] S32 D z , the calculation formula is:

[0102]

[0103] Where R represents the window radius of the local density, R = 0.1S z ; r i,j Represents the distance between samples, r i,j =|z(i)-z(j)|; u(t) represents the unit step function,

[0104] S33, transforming the solution of the projection direction A into a solution of a nonlinear optimization problem, the problem is:

[0105] maxQ(A)=S z ·D z

[0106]

[0107] S34, solving the nonlinear optimization problem can obtain the optimal projection direction A * , a in the best projection direction * (j) represents the weight value of the jth key factor.

[0108] Step 4: Determine the weight of the water resources-water environment-water ecology-water disaster correlation system indicator system:

[0109] The four sets of weight distribution results obtained in step 3 were subjected to Spearman correlation analysis, and the linear combination coefficients of the significant correlation methods were calculated using the game theory combined weighting method to obtain the most likely weights of the water resources, water environment, water ecology, and water disaster systems.

[0110] The game theory combined weighting method specifically includes the following steps:

[0111] S41, Spearman rank correlation coefficient was used to measure the consistency of the weighting results of the four sets of methods.

[0112] S42, assume that the basic weight vector set W = {W1, W2, W3, W4} obtained by using the hierarchical analysis method, entropy weight method, CRITIC weight method, and projection pursuit evaluation method in step 3, where Let α = {α1, α2, α3, α4} be the linear combination coefficients, then W * These vectors can be combined linearly to form:

[0113]

[0114] Where W1, W2, W3, and W4 represent the basic weight results calculated by the analytic hierarchy process, entropy weight method, CRITIC weight method, and projection pursuit evaluation method, respectively.

[0115] S43, with W *The goal is to minimize the deviation of any weight vector in W, optimize the linear combination coefficients, and determine the weight coefficients. The calculation formula is:

[0116]

[0117] In the formula, α k represents the linear combination coefficient; represents the transpose of any weight vector; Represents the transpose of the base set of weight vectors.

[0118] S44, according to the differential properties of the matrix, the deviation is minimized and converted into the optimal first-order derivative matrix, the combined optimization coefficient α is obtained and normalized, and the calculation formula is:

[0119]

[0120] In the formula, Represents the portfolio optimization weight.

[0121] S45, calculate the combination weight, the calculation formula is:

[0122]

[0123] Step 5: Analyze the coupling coordination degree of the water resources-water environment-water ecology-water disaster related system:

[0124] According to the calculation formulas of coupling degree, coordination degree and coupling coordination degree, the coupling degree, coordination degree and coupling coordination degree of the water resources-water environment-water ecology-water disaster correlation system are calculated, and the spatial distribution characteristics are revealed by using QGIS software. The specific steps include:

[0125] S51, the calculation formula for the coupling degree C among water resources, water environment, water ecology and water disaster subsystems is:

[0126]

[0127] In the formula, U1, U2, U3, and U4 represent the development levels of water resources, water environment, water ecology, and water disaster subsystems respectively; a i 、b j 、c m d n Represents the indicator weights of water resources, water environment, water ecology, and water disaster subsystems; w i 、x j ,y m 、z n They represent the standardized data of water resources, water environment, water ecology and water disaster subsystems respectively; l, q, s and t represent the number of indicators of water resources, water environment, water ecology and water disaster subsystems respectively.

[0128] S52, the calculation formula for the coordination degree T among water resources, water environment, water ecology and water disaster subsystems is:

[0129] T=α1×U1+α2×U2+α3×U3+α4×U4

[0130] In the formula, α1, α2, α3, and α4 represent the weights of water resources, water environment, water ecology, and water disaster subsystems, respectively.

[0131] S53, the calculation formula for the coupling coordination degree D among water resources, water environment, water ecology and water disaster subsystems is:

[0132]

[0133] Application examples:

[0134] The study area is the prefecture-level cities in the Yellow River Basin in Shaanxi Province, including Xi'an, Tongchuan, Baoji, Xianyang, Weinan in Guanzhong, Yan'an and Yulin in northern Shaanxi, and Shangluo in southern Shaanxi. Figure 2 ), the permanent population and GDP of the study area account for 85% and 90% of the total in Shaanxi Province respectively.

[0135] The key factors of the water resources-water environment-water ecology-water disaster system were screened by the method described in the embodiment. The specific indicators selected for the water resources-water environment-water ecology-water disaster system and the weight calculation results are shown in Table 1.

[0136] Table 1 Results of weights of indicators using different weight calculation methods

[0137]

[0138] The slope method, Cox-Stuart test, and Mann-Kendall test were used to analyze the trend of the time series of key factors, and the following results were obtained: Figure 5 The Mann-Kendall test trend diagram of total water consumption is shown in the figure. The spatial distribution of key factors is obtained using QGIS software. Figure 3 The schematic diagram of the spatial distribution of total water consumption is shown in Figure 4 Schematic diagram of the time series changes in total water consumption.

[0139] Finally, it should be noted that the above is only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred arrangement scheme, a person skilled in the art should understand that the technical solution of the present invention (such as the use of various formulas, the sequence of steps, etc.) can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A coupling coordination degree analysis method for a water resources-water environment-water ecology-water disaster correlation system, characterized in that: The method comprises the following steps: Step 1: Collect and screen the key factors of the water resources-water environment-water ecology-water disaster correlation system: Determine the scope of the area to be studied, comprehensively sort out the indicators selected from the existing research results on water resources, water environment, water ecology, and water disasters within the area to be studied, and screen out the key factors of the water resources-water environment-water ecology-water disaster correlation system; Step 2: Analyze the spatiotemporal variation characteristics of key factors: The trend analysis of the time series of each key factor screened in step 1 was performed using methods including the slope method, Cox-Stuart test, and Mann-Kendall test; The Moran index analysis was used to obtain the spatial agglomeration of each key factor; Step 3: Establish an indicator evaluation system for the water resources-water environment-water ecology-water disaster linkage system: By comprehensively using analytical methods including hierarchical analysis method, entropy weight method, CRITIC weight method and projection pursuit evaluation method, the weight distribution results of four sets of water resources, water environment, water ecology and water disaster systems were obtained; Step 4: Determine the weight of the water resources-water environment-water ecology-water disaster correlation system indicator system: The four sets of weight distribution results obtained in step 3 were subjected to Spearman correlation analysis, and the linear combination coefficients of the significant correlation methods were calculated using the game theory combined weighting method to calculate the most likely weights of the water resources, water environment, water ecology, and water disaster systems; Step 5: Analyze the coupling coordination degree of the water resources-water environment-water ecology-water disaster related system: According to the calculation formulas of coupling degree, coordination degree and coupling coordination degree, the coupling degree, coordination degree and coupling coordination degree of the water resources-water environment-water ecology-water disaster association system were calculated, and the spatial distribution characteristics were revealed using QGIS software.

2. According to claim 1, the coupling coordination degree analysis method of the water resources-water environment-water ecology-water disaster correlation system is characterized by: In step 1, the key factors of the water resources-water environment-water ecology-water disaster correlation system include: The key factors of the water resources subsystem include per capita water resources, water consumption per 10,000 yuan of GDP, water resources development and utilization rate, per capita water consumption, domestic water consumption, industrial water consumption, agricultural water consumption, and precipitation; The key factors of the water environment subsystem include sewage treatment rate, chemical oxygen demand discharge, drinking water quality compliance rate, ammonia nitrogen discharge, proportion of Class I-III water quality sections, total phosphorus discharge, total industrial wastewater discharge, sediment transport and sediment content; The key factors of the water ecological subsystem include ecological water consumption, soil and water loss control area, water system connectivity level, water surface ratio and vegetation comprehensive index; The key factors of the water disaster subsystem include the population affected by floods, direct economic losses due to floods, the area of ​​crops affected by floods, the number of reservoirs, the length of levees and the total investment in water conservancy construction.

3. According to claim 1, the coupling coordination degree analysis method of the water resources-water environment-water ecology-water disaster correlation system is characterized by: In step 3, the specific steps of using the projection pursuit evaluation method include: S31, normalize the key factors obtained in step 1, and the calculation formula is: In the formula, x'(i,j) and x(i,j) represent the data of the i-th sample of the j-th key factor before and after normalization, respectively; x max (j) and x min (j) represents the maximum and minimum values ​​of the jth key factor in the sample set; S32, synthesize the p-dimensional sample data X(i) into a one-dimensional projection value z(i) with the unit vector A as the projection direction, and the calculation formula is: In the formula, T represents the transpose of the matrix; a(j) represents the weight corresponding to the key factor; Projection pursuit requires that the local projection points are as dense as possible, preferably condensed into several point clusters; and the projection point clusters should be as scattered as possible overall; construct the projection index function Q(A), the calculation formula is: Q(A)=S z ·D z In the formula, S z Represents the standard deviation of the projection value; D z represents the local density of the projected values; S33, transforming the solution of the projection direction A into a solution of a nonlinear optimization problem, the problem is: maxQ(A)=S z ·D z S34, solving the nonlinear optimization problem can obtain the optimal projection direction A * , a in the best projection direction * (j) represents the weight value of the jth key factor.

4. According to claim 3, the coupling coordination degree analysis method of the water resources-water environment-water ecology-water disaster correlation system is characterized by: S described in S32 in step 3 z , the calculation formula is: Where z(j) represents the sample projection value; S32 D z , the calculation formula is: Where R represents the window radius of the local density, R = 0.1S z ; r i,j Represents the distance between samples, r i,j =|z(i)-z(j)|; u(t) represents the unit step function, 5. According to claim 1, the coupling coordination degree analysis method of the water resources-water environment-water ecology-water disaster correlation system is characterized by: In step 4, the game theory combined weighting method specifically includes the following steps: S41, Spearman rank correlation coefficient was used to measure the consistency of the weighting results of the four sets of methods; S42, assume that the basic weight vector set W = {W1, W2, W3, W4} obtained by using the hierarchical analysis method, entropy weight method, CRITIC weight method, and projection pursuit evaluation method in step 3, where Let α = {α1, α2, α3, α4} be the linear combination coefficients, then W * These vectors can be combined linearly to form: In the formula, W1, W2, W3, and W4 represent the basic weight results calculated by the analytic hierarchy process, entropy weight method, CRITIC weight method, and projection pursuit evaluation method, respectively; S43, with W * The goal is to minimize the deviation of any weight vector in W, optimize the linear combination coefficients, and determine the weight coefficients. The calculation formula is: In the formula, α k represents the linear combination coefficient; represents the transpose of any weight vector; represents the transpose of the basic weight vector set; S44, according to the differential properties of the matrix, the deviation is minimized and converted into the optimal first-order derivative matrix, the combined optimization coefficient α is obtained and normalized, and the calculation formula is: In the formula, represents the combination optimization weight; S45, calculate the combination weight, the calculation formula is:

6. The coupling coordination degree analysis method of the water resources-water environment-water ecology-water disaster correlation system according to claim 1 is characterized in that: Step 5 specifically includes the following steps: S51, the calculation formula for the coupling degree C among water resources, water environment, water ecology and water disaster subsystems is: In the formula, U1, U2, U3, and U4 represent the development levels of water resources, water environment, water ecology, and water disaster subsystems respectively; a i , b j 、c m d n Represents the indicator weights of water resources, water environment, water ecology, and water disaster subsystems; w i 、x j ,y m 、z n Respectively represent the standardized data of water resources, water environment, water ecology, and water disaster subsystems; l, q, s, and t represent the number of indicators of water resources, water environment, water ecology, and water disaster subsystems; S52, the calculation formula for the coordination degree T among water resources, water environment, water ecology and water disaster subsystems is: T=α1×U1+α2×U2+α3×U3+α4×U4 In the formula, α1, α2, α3, and α4 represent the weights of water resources, water environment, water ecology, and water disaster subsystems respectively; S53, the calculation formula for the coupling coordination degree D among water resources, water environment, water ecology and water disaster subsystems is:

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