Urban agglomeration green development space-time evaluation and attribution identification method based on water-energy-environment association relationship

Abstract

The invention provides an urban agglomeration green development space-time evaluation and attribution identification method based on a water-energy-environment association relationship. The method comprises the following steps: constructing an urban agglomeration green development level evaluation index set based on a water-energy-ring association system; performing standardization processing on the evaluation indexes by adopting a range method to obtain standardized values of different indexes of each subsystem; calculating the index weight of the evaluation index; calculating green development indexes of the urban agglomeration and all cities in the urban agglomeration; grading the green development indexes of the urban agglomeration and the cities in the urban agglomeration according to the classification basis so as to correspondingly obtain the grading result of each region, and evaluating the green development stage of the urban agglomeration and the cities in the urban agglomeration from the perspective of time and space differences; and identifying main influence factors of urban agglomeration green development. The method can more comprehensively reflect complex social development, resource and environment challenges in urban agglomeration green development, and more objectively insight into the stage of urban agglomeration green development and corresponding spatial distribution characteristics.

Description

Technical Field

[0001] The present invention relates to the field of green development evaluation, and specifically to a spatio-temporal evaluation and attribution identification method for the green development of urban agglomerations based on the water-energy-environment correlation relationship. Background Art

[0002] The concept of green development is the evolution and extension of the concept of sustainable development. The understanding of various concepts of green development shows that the concept of green development emphasizes the unified and coordinated development that takes into account multiple dimensions such as economic society, resources, and environment. Many inventions have been committed to constructing comprehensive and complex index systems to measure the level of green development. At present, it is not uncommon to construct an evaluation system for the regional green development level at the macro level, but the evaluation objects mostly focus on the national, provincial or urban scales, and there are few studies at the urban agglomeration scale.

[0003] As an important engine for promoting regional development, urban agglomerations shoulder the heavy responsibilities of supporting the national economic growth, promoting regional coordinated development, and participating in global competition and cooperation. How to coordinate the relationship between urbanization, industrialization and water resources, energy, and environment in the process of urban agglomeration development is a difficult problem that is generally emphasized and urgently needs to be solved by decision-making departments and academic circles at home and abroad. In the existing technology, the evaluation of the green development level of urban agglomerations is still in its infancy, and the existing technology only conducts green development evaluations from one or two aspects of economic society, resources, and environment. However, the elements such as water, energy, and environment in urban agglomerations and the economic society are an organic whole that is mutually based, interdependent, and promotes each other. The green development evaluation system at the urban agglomeration scale based on the water-energy-environment (water-energy-environment) correlation relationship is still blank.

[0004] On the other hand, the diversity of different elements in the dimensions of social economy, water resources, energy, and environment in each city within the urban agglomeration, as well as the interaction between elements, jointly determine the overall green development level of the urban agglomeration. How to evaluate the impact of the spatial heterogeneity of different elements in each city within the urban agglomeration on the overall green development level of the urban agglomeration while comprehensively and systematically quantifying the overall green development characteristics of the urban agglomeration is an urgent problem to be solved in the quantitative evaluation of the green development level of urban agglomerations.

[0005] Therefore, there is currently a lack of a method for evaluating the green development of urban agglomerations based on the water-energy-environment correlation relationship and identifying the dominant influencing factors that restrict the green development level of urban agglomerations from the perspective of spatial differentiation. Summary of the Invention

[0006] In view of the above problems, the present invention proposes a spatio-temporal evaluation and attribution identification method for the green development of urban agglomerations based on the water-energy-environment correlation relationship, and a method for exploring the influence of the spatial heterogeneity of different factors within the urban agglomeration on the overall green development level of the urban agglomeration, in order to provide a decision-making basis for the selection of future green development paths for urban agglomerations.

[0007] The present invention is implemented by the following technical solutions:

[0008] Step 1: Construct an evaluation index set for the green development level of urban agglomerations based on the water-energy-environment correlation system starting from four subsystems of social economy, water resources, energy, and environment. The evaluation index set for the green development level of urban agglomerations includes evaluation indicators corresponding to the social economy subsystem, evaluation indicators corresponding to the water resources subsystem, evaluation indicators corresponding to the energy subsystem, and evaluation indicators corresponding to the environment subsystem; use the range method to standardize the evaluation indicators to obtain the standardized values of different indicators of each subsystem; calculate the index weights of the evaluation indicators. Step 2: Calculate the green development indices of the urban agglomeration and each city within it based on the standardized values and index weights of different indicators of each subsystem; classify the green development indices of the urban agglomeration and each city within it according to the classification basis, so as to obtain the classification results of each region accordingly, and evaluate the stages of green development of the urban agglomeration and each city within it from the perspectives of time and space differences; identify the main influencing factors of the green development of the urban agglomeration according to the standardized values of each indicator in the green development evaluation index set.

[0009] Further, in Step 1, the evaluation indicators corresponding to the social economy subsystem include population density, per capita GDP, urbanization rate, and the proportion of the tertiary industry. The evaluation indicators corresponding to the water resources subsystem include total water resources, water supply modulus, water resources development and utilization rate, water consumption per 10,000 yuan of GDP, and water consumption per 10,000 yuan of industrial added value. The evaluation indicators corresponding to the energy subsystem include total energy consumption, total electricity consumption of the whole society, natural gas supply in the municipal district, energy consumption per 10,000 yuan of GDP, and per capita electricity consumption. The evaluation indicators corresponding to the environment subsystem include the daily urban sewage treatment capacity, wastewater discharge per 10,000 yuan of GDP, ecological environment water use rate, and greening coverage rate of the built-up area.

[0010] Further, in Step 1, the range method is used to standardize the evaluation indicators, and the calculation formula is as follows:

[0011] Positive indicator:

[0012] Negative indicator:

[0013] Where the value after standardization is denoted as y ij , x ij is the j-th index value of the i-th subsystem, and x ijmin and x ijmax correspond to the minimum and maximum values of the j-th evaluation indicator of the i-th subsystem, respectively.

[0014] Further, calculating the index weights of the evaluation indicators in step one specifically includes: introducing a combined weighting calculation method based on the analytic hierarchy process and the entropy weight method, establishing a weighting model for the evaluation index set of the urban agglomeration's green development level, and the weight w of the j-th evaluation indicator in the i-th subsystem ij The calculation formula is as follows:

[0015]

[0016] In the formula, p ij , q ij are respectively the weights of the j-th evaluation indicator in the i-th subsystem calculated by the analytic hierarchy process and the entropy weight method.

[0017] Further, in step two, calculating the green development index of the urban agglomeration and each city within it based on the standardized values of different indicators of each subsystem and the indicator weights specifically includes:

[0018] Constructing the development indices of each subsystem of water resources, energy, environment, and social economy, and the calculation formula is as follows:

[0019]

[0020]

[0021]

[0022]

[0023] In the formula, F 1 (·), F 2 (·), F 3 (·), F 4 (·) are respectively the development index evaluation functions of each subsystem of social economy, water resources, energy, and environment; a j , b j , c j , d j are respectively the weights of different indicators of each subsystem; x′ j , y′ j , u′ j , v′ j are respectively the standardized values of different indicators of each subsystem, and the representative indicators of each subsystem are standardized using the range method; k, l, p, q are the number of indicators of each subsystem;

[0024] Calculating the urban green development index based on the development indices of each subsystem: Based on the calculation results of the development indices of different subsystems, constructing a green development evaluation function, and the calculation result of the green development evaluation function is called the green development index. The larger the green development index, the higher the green development level;

[0025] The calculation formula of the green development index T of each city is as follows:

[0026]

[0027]

[0028] D=αF 1 +βF 2 +γF 3 +δF 4 (10)

[0029] Where C is the coupling degree, which reflects the coupling effect between each subsystem; D is the comprehensive evaluation function of the water-energy-environmental linkage system, and α, β, γ, and δ are the weights of each subsystem respectively;

[0030] After calculating the green development evaluation function results of each city, the average value of the green development evaluation function of each city is calculated, which is the overall green development index of the urban agglomeration.

[0031] Furthermore, in step 2, the green development index of the urban agglomeration and the cities within it is graded according to the classification basis, so as to obtain the classification results of each region accordingly. The classification basis is shown in Table 2:

[0032] Table 2 Classification of green development levels

[0033]

[0034] Furthermore, in step 2, the stage of green development of urban agglomerations and cities within them is assessed from the perspective of temporal and spatial differences, including:

[0035] By classifying the time series data of green development index of urban agglomerations and cities within them, the green development stage of urban agglomerations and cities within them is assessed;

[0036] The global spatial autocorrelation and local spatial autocorrelation analysis methods are used to analyze the spatial agglomeration trend of green development levels within urban agglomerations. The global spatial autocorrelation analysis uses the Moran's I index as a measurement indicator to reflect the aggregation and distribution effect between different cities in the urban agglomeration. The calculation formula of the Moran's I index is as follows:

[0037]

[0038] Where W ij represents the spatial weight matrix; n represents the number of spatial units; x i and x j The green development indexes of regions i and j are respectively, Represents the average value of the green development index; Moran's I ∈ [-1, 1]. At a specific significance level, if Moran's I > 0, it indicates that there is a spatial agglomeration phenomenon in the green development level within the urban agglomeration; the larger the Moran's I index, the more significant the spatial agglomeration characteristics of the green development level. On the contrary, it indicates that there is a spatial difference in the green development level within the urban agglomeration;

[0039] Local spatial autocorrelation analysis uses the local autocorrelation index to obtain the LISA cluster analysis map, and explores the spatial agglomeration degree between the green development index of each city within the urban agglomeration and its adjacent areas. The local autocorrelation index I i The calculation formula is as follows:

[0040]

[0041] In the formula, S 2 Is the variance of the green development index. The local spatial autocorrelation aggregation types are divided into four types: low-low aggregation, low-high aggregation, high-low aggregation, and high-high aggregation.

[0042] Furthermore, in step two, the main influencing factors of the green development of the urban agglomeration are identified according to the standardized values of each index in the green development evaluation index set, specifically including:

[0043] Using the natural breakpoint method to stratify the original values of each index in the green development index of each city and the evaluation index set of the green development level of the urban agglomeration;

[0044] Using the factor detection module in the geographical detector method to explore the influence of different factors in each economic subsystem on the spatial differentiation of the green development of the urban agglomeration;

[0045] Using the interaction detection module in the geographical detector to explore the influence of the two-factor interaction on the green development level of the urban agglomeration.

[0046] Furthermore, the influence of different factors in each subsystem on the spatial differentiation of the green development of the urban agglomeration is measured by the q value, and the calculation formula is as follows:

[0047]

[0048]

[0049] SST = Nσ 2 (15)

[0050] In the formula, Y represents the dependent variable, that is, the green development index, h = 1,..., L, L is the layer of the influencing factor X, and the influencing factor X is each index in the green development level evaluation index set; N h And N are the number of units in layer h and the entire urban agglomeration respectively; Y hiand Y i are the values of the h-th layer and unit i within the entire urban agglomeration respectively; σ h 2 and σ 2 are the variances of the Y values in the h-th layer and the entire urban agglomeration respectively; SSW and SST are the sum of the within-layer variances and the total variance of the whole region respectively; q ∈ [0, 1], the larger the q value, the greater the influence of this factor on the green development level of the urban agglomeration, and vice versa.

[0051] Furthermore, the use of the interaction detection module in the geographical detector to explore the influence of the two-factor interaction on the green development level of the urban agglomeration specifically includes:

[0052] By comparing the q values of the influence of the two factors acting alone on the green development level of the urban agglomeration and the q value when the two interact: q(X1∩X2), and comparing their magnitude relationship according to Table 3, it is judged whether there is an interaction between the two factors and the type of interaction. The detection result of the interaction detection module can show whether the two-factor interaction will enhance or weaken the explanatory power for the green development level of the urban agglomeration compared with the independent action of the single factor.

[0053] Table 3 Two-factor interaction types

[0054]

[0055]

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] The present invention constructs a spatio-temporal evaluation and attribution analysis method for the green development of urban agglomerations based on the water-energy-environment correlation system theory. The water-energy-environment correlation system theory advocates using a comprehensive and systematic way to balance the relationship among the three, and solving the problems of water resources, energy, and environment from the integrated perspectives of departmental cooperation, element coordination, and system control, promoting the comprehensive and sustainable development in multiple dimensions such as society-resources-environment, which coincides with the concept of green development. Conducting spatio-temporal evaluation of the green development of urban agglomerations from the perspective of the water-energy-environment correlation system can more comprehensively reflect the complex social development, resource, and environmental challenges faced in the green development of urban agglomerations, and more objectively understand the stage and corresponding spatial distribution characteristics of the green development of urban agglomerations.

[0058] Due to the significant differences in water resources, energy, environmental conditions, and social economy among different regions of the urban agglomeration, the various factors within different regions and the interactions among these factors have led to changes in the green development level of the urban agglomeration. In this invention, each city within the urban agglomeration is used as the research unit, and the factor detection module and interaction detection module in the geographical detector are adopted to identify the influencing factors restricting the green development level of the urban agglomeration, so as to better understand the internal mechanism of the green development of the urban agglomeration from the perspective of spatial differentiation and provide a decision-making basis for the urban agglomeration to achieve high-level green development. Brief Description of the Drawings

[0059] Figure 1 It is a flow chart of a method for spatio-temporal evaluation and attribution analysis of the green development of an urban agglomeration based on the water-energy-environment correlation relationship in an embodiment of the present invention;

[0060] Figure 2 It is a box plot of the green development index of the urban agglomeration in the middle reaches of the Yangtze River and the development indices of each subsystem;

[0061] Figure 3 It is a LISA clustering map of the green development level of cities in the middle reaches of the Yangtze River in 2010;

[0062] Figure 4 It is a LISA clustering map of the green development level of cities in the middle reaches of the Yangtze River in 2015;

[0063] Figure 5 It is a LISA clustering map of the green development level of cities in the middle reaches of the Yangtze River in 2020;

[0064] Figure 6 It is the detection result of the interaction of the influencing factors of the green development level of the urban agglomeration in the middle reaches of the Yangtze River in 2020. Detailed Embodiment

[0065] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0066] Please refer to Figure 1 , an embodiment of the present invention provides a method for spatio-temporal evaluation and attribution analysis of the green development of an urban agglomeration based on the water-energy-environment correlation relationship, including the following steps:

[0067] Step 1: Construct an evaluation system for the green development level of the urban agglomeration based on the water-energy-environment correlation system

[0068] Step 1 specifically includes:

[0069] Step 1.1. Determine evaluation indicators

[0070] Green development is a development aggregation behavior that emphasizes integrity, systematicness, coordination, and endogenous gain. It is jointly determined by the mutual connection and interaction among different elements. Its core is to achieve the coordinated progress of population, industry, resources, and environment by reducing pollution emissions and resource consumption. Constructing a suitable evaluation system is the foundation and important basis for the evaluation of urban agglomeration green development. Adhering to the basis for selecting indicators such as systematicness, dynamics, independence, and feasibility, the present invention establishes an evaluation index set for the green development level of urban agglomerations from four subsystems: social economy, water resources, energy, and environment, as shown in Table 1.

[0071] Table 1 Evaluation index set for the green development of urban agglomerations

[0072]

[0073] Step 1.2. Standardize the evaluation indicators

[0074] Since the dimensions and units of different elements in the evaluation system are different, and the numerical differences of different elements are very large, which will affect the evaluation results. Therefore, it is necessary to standardize each index in the evaluation system to avoid the influence of dimension and order of magnitude differences. In the embodiment of the present invention, the range method is used to standardize each index, and the calculation formula is as follows:

[0075] Positive index:

[0076] Negative index:

[0077] In the formula, the value after standardization is represented as y ij , x ij is the j-th index value of the i-th subsystem, and x ijmin and x ijmax correspond to the minimum and maximum values of the j-th evaluation index of the i-th subsystem, respectively.

[0078] Step 1.2. Calculate the index weights of the evaluation indicators in the evaluation index set for the green development level of urban agglomerations

[0079] Introduce a combined weighting calculation method based on the analytic hierarchy process and entropy weight method, and establish a weighting model for the evaluation index set of the green development level of urban agglomerations. The weight w ij of the j-th evaluation index of the i-th subsystem is calculated as follows:

[0080]

[0081] In the formula, p ij , qij They are the weights of the j-th evaluation index of the i-th subsystem calculated by the analytic hierarchy process and the entropy weight method respectively.

[0082] Step 2: Evaluate the spatio-temporal differentiation characteristics of the green development level of the urban agglomeration and conduct attribution analysis

[0083] Step 2 specifically includes:

[0084] Step 2.1: Calculate the green development index of the urban agglomeration and each city within it

[0085] The present invention constructs the green development index of the urban agglomeration based on the coupling coordination degree method, so as to reflect the green development level of the urban agglomeration under the influence of multiple dimensions such as water resources, energy, environment, and social economy.

[0086] As the spatial carrier in the evaluation of the green development of the urban agglomeration, the city is the key node for the interaction between the internal social economy of the urban agglomeration and the natural background conditions such as water resources, energy, and environment. Different cities within the urban agglomeration have different resource endowments, ecological environments, and geographical locations. Therefore, when evaluating the green development level of the urban agglomeration, the present invention takes each city within the urban agglomeration as the calculation unit.

[0087] First, evaluate the green development level of each city. The calculation steps are divided into the following two steps: (1) Construct the development index of each subsystem such as water resources, energy, environment, and social economy; (2) Calculate the urban green development index based on the development index of each subsystem.

[0088] The calculation formulas for the development indexes of each subsystem such as water resources, energy, environment, and social economy are as follows:

[0089]

[0090]

[0091]

[0092]

[0093] In the formula, F 1 (·), F 2 (·), F 3 (·), F 4 (·) are the evaluation functions of the development indexes of the social economy, water resources, energy, and environment subsystems respectively; a j , b j , c j , d j are the weights of different indexes of each subsystem respectively; x′ j , y′ j , u′ j , v′j They are the standardized values of different indicators of each subsystem, and the range method is used to standardize the representative indicators of each subsystem; k, l, p, and q are the number of indicators of each subsystem.

[0094] Based on the calculation results of the development indices of different subsystems, a green development evaluation function is constructed. The green development evaluation function takes into account the coupling degree between each system and the overall coordination of the system, and can indicate whether the subsystems promote each other at a high level or restrict each other at a low level. The calculation result of the green development evaluation function is called the green development index in the present invention. The larger the green development index, the higher the level of green development. The calculation formula (i.e., the green development evaluation function) of the green development index (T) of each city is as follows:

[0095]

[0096]

[0097] D = αF 1 + βF 2 + γF 3 + δF 4 (10)

[0098] In the formula, C is the coupling degree, which reflects the coupling effect between each subsystem; D is the comprehensive evaluation function of the water-energy-environment correlation system, and α, β, γ, and δ are the weights of each subsystem respectively.

[0099] After calculating the results of the green development evaluation function of each city, calculate the average value of the green development evaluation function of each city, which is the green development index of the overall urban agglomeration.

[0100] Step 2.2. Evaluate the spatio-temporal differentiation characteristics of the green development level of the urban agglomeration

[0101] In order to better analyze the stage at which the green development level of the urban agglomeration is located, the present invention classifies the calculation results of the green development indices of the urban agglomeration and each city within it, and the classification basis is shown in Table 2. By classifying the time series data of the green development indices of the urban agglomeration and each city within it, the stages at which the urban agglomeration and each city within it are in green development are evaluated.

[0102] Table 2 Classification of green development levels

[0103]

[0104] The present invention uses the global spatial autocorrelation and local spatial autocorrelation analysis methods to analyze the spatial agglomeration trend of the green development level within the urban agglomeration.

[0105] Global spatial autocorrelation analysis often uses Moran's I index as a measure to reflect the agglomeration and dispersion effects among different cities in an urban agglomeration. The calculation formula of this index is as follows:

[0106]

[0107] In the formula, W ij represents the spatial weight matrix; n represents the number of spatial units; x i and x j correspond to the green development indices of region i and region j respectively, and represents the average value of the green development index. Moran's I ∈ [-1, 1]. At a specific significance level, if Moran's I > 0, it indicates that the green development levels in the urban agglomeration show a spatial agglomeration phenomenon. The larger the Moran's I index, the more significant the spatial agglomeration characteristics of the green development level. On the contrary, it indicates that the green development levels in the urban agglomeration show spatial differences.

[0108] The local autocorrelation index is used to obtain the LISA cluster analysis map to explore the spatial agglomeration degree between the green development index of each city in the urban agglomeration and its adjacent regions. The calculation formula of the local autocorrelation index I i is as follows:

[0109]

[0110] In the formula, S 2 is the variance of the green development index. The local spatial autocorrelation aggregation types can be divided into four types: low-low aggregation, low-high aggregation, high-low aggregation, and high-high aggregation.

[0111] Step 2.3. Identify the main influencing factors of the green development of the urban agglomeration

[0112] Use the natural breakpoint method to stratify the original values of the green development indices of each city and each index in the green development level evaluation index set;

[0113] Use the factor detection module in the geographical detector method to explore the influence of different evaluation indices in various subsystems such as economy and society, water resources, energy, and environment on the spatial differentiation of the green development of the urban agglomeration.

[0114] The influence of different evaluation indices on the spatial differentiation of the green development of the urban agglomeration can be measured by the q value, and the calculation formula is as follows:

[0115]

[0116] SST = Nσ 2 (15)

[0117] In the formula, Y represents the dependent variable (the green development index in the present invention), h = 1,..., L. L is the layer of the influencing factor X (each index in the green development level evaluation index set in the present invention). N h and N are the number of units in layer h and the entire urban agglomeration respectively. Y hi and Y i are the values of unit i in layer h and the entire urban agglomeration respectively. σ h 2 and σ 2 are the variances of the Y values in layer h and the entire urban agglomeration respectively. SSW and SST are the sum of the within-layer variances and the total variance of the whole region respectively. q ∈ [0, 1], the larger the q value, the greater the influence of the factor on the green development level of the urban agglomeration, and vice versa.

[0118] The interaction detection module in the geographical detector is used to explore the influence of the two-factor interaction on the green development level of the urban agglomeration.

[0119] By comparing the q values of the influence of the two factors acting alone on the green development level of the urban agglomeration and the q value when the two interact: q(X1∩X2), and comparing their magnitude relationship according to Table 3, it is judged whether there is an interaction between the two factors and the type of interaction. The detection result of the interaction detection module can show whether the two-factor interaction will enhance or weaken the explanatory power for the green development level of the urban agglomeration compared with the single-factor independent action.

[0120] Table 3 Two-factor interaction types

[0121]

[0122] In the embodiment of the present invention, the middle reaches of the Yangtze River urban agglomeration and its internal prefecture-level cities are taken as example objects, and data on various dimensions such as economy and society, water resources, energy, and environment of 28 prefecture-level cities in the middle reaches of the Yangtze River urban agglomeration from 2010 to 2020 are collected, and a spatio-temporal evaluation and attribution analysis of the green development of the urban agglomeration based on the water-energy-environment correlation system are carried out. The specific steps are as follows:

[0123] I. Spatio-temporal evaluation of the green development of the urban agglomeration

[0124] 1. Data collection and preprocessing of each city

[0125] In this embodiment, data on water resources, energy, environment, social economy, etc. of each city are obtained from the "Statistical Yearbooks", "Water Resources Bulletins", "Ecological Environment Bulletins", "China Urban Construction Yearbooks" and "China Urban Statistical Yearbooks" of Hubei, Hunan, Jiangxi provinces and each city. The time span of data collection is from 2010 to 2020. And the extreme difference method is used to standardize the indicators of each city. Since the data series of the energy subsystem of three county-level cities directly under the jurisdiction of the province, namely Xiantao, Tianmen and Qianjiang, are missing, these three cities are not considered in the calculation process.

[0126] 2. Calculation of the weights of each index in the urban agglomeration green development system

[0127] The calculation results of the weights of each index in the urban agglomeration green development system are shown in Table 4.

[0128] Table 4 Calculation results of the combined weights of each index in the evaluation index set of the green development level of the middle reaches of the Yangtze River urban agglomeration

[0129]

[0130] II. Calculation of the urban agglomeration green development index and evaluation of spatio-temporal differentiation characteristics

[0131] 1. Calculation results of the green development index of the urban agglomeration and each city

[0132] The green development index of the middle reaches of the Yangtze River urban agglomeration and the development indices of each subsystem within the urban agglomeration are shown in Table 5. In 2020, the green development index of the middle reaches of the Yangtze River urban agglomeration is 0.711, reaching the development level of intermediate coordination. Among them, the green development indices of Changsha, Changde and Yueyang rank the top three, being 0.773, 0.763 and 0.744 respectively.

[0133] Table 5 Calculation results of the green development index of the middle reaches of the Yangtze River urban agglomeration and each city within it

[0134]

[0135]

[0136] 2. Evaluation of the spatio-temporal differentiation characteristics of the urban agglomeration green development level

[0137] (1) Evaluation of the temporal characteristics of the green development level of the middle reaches of the Yangtze River urban agglomeration

[0138] The temporal characteristics of the green development level of each city within the middle reaches of the Yangtze River urban agglomeration and the development levels of each subsystem within the time period from 2010 to 2020 are as Figure 2As shown in the figure, the green development index of each prefecture-level city in the Middle Reaches of the Yangtze River Urban Agglomeration shows a fluctuating growth trend, with a relatively large increase at the beginning and gradually stabilizing later. The average value of the green development index varies between [0.6, 0.7], which is the primary coordination state. As time goes by, the minimum value and the average value of the green development index of each city are continuously increasing, the median gradually approaches the upper quartile, and the distribution changes from being scattered to being concentrated and gradually converges towards higher values. Although there is still a certain gap between the upper and lower quartiles, indicating that the green development levels of each city are still unevenly distributed, the gap between the maximum value and the minimum value becomes smaller, and the overall gap between cities gradually narrows. From the perspective of the development index of each subsystem, the social and economic development index shows an upward trend during the evaluation period, and the box interval between the upper and lower quartiles gradually shrinks, indicating that the social and economic development levels of each city are gradually converging. The water resource development index shows a fluctuating upward trend during the evaluation period; affected by the inter-annual change of the total water resource volume, the distribution of the water resource development index does not show an obvious trend of dispersion or convergence. The change trend of the energy development index during the evaluation period can be divided into two stages. There is no obvious change from 2010 to 2015, and it shows a fluctuating downward trend from 2016 to 2020, which is also the reason for the slowdown in the growth rate of the green development index during this period. The environmental development index shows a slow growth trend during the evaluation period, the minimum value gradually approaches the average value, but the change range of the maximum value is relatively not obvious, and the overall gap in the environmental protection development levels between cities gradually shrinks.

[0139] (2) Evaluation of the Spatial Characteristics of the Green Development Level in the Middle Reaches of the Yangtze River Urban Agglomeration

[0140] To more intuitively analyze the characteristics of the green development differences in the urban agglomeration from the perspective of the city domain, in this embodiment, the global spatial autocorrelation Moran's I of the green development index of the Middle Reaches of the Yangtze River Urban Agglomeration from 2010 to 2020 is calculated using formula (11). As shown in Table 6. During the evaluation period, Moran's I is between [-0.105, 0.062], the P value is greater than 0.1, and the absolute value of the Z score does not exceed 1.65, indicating that the green development index of the Middle Reaches of the Yangtze River Urban Agglomeration presents a spatial heterogeneous pattern, and there is no obvious agglomeration trend among the 28 cities as a whole.

[0141] Table 6 Global Autocorrelation Moran's I Index of Green Development in the Middle Reaches of the Yangtze River Urban Agglomeration from 2010 to 2020

[0142]

[0143]

[0144] Select three typical years of 2010, 2015, and 2020 to analyze the spatial agglomeration degree of the green development index of each city in the Middle Reaches of the Yangtze River Urban Agglomeration and its adjacent areas, as Figure 3 、 Figure 4 、 Figure 5As shown in the figure. Wuhan is of the high-low type in all three typical years and belongs to the high-value heterogeneous center, indicating that Wuhan is still in the development stage of gathering various elements such as water resources and energy from surrounding cities, relatively squeezing the ecological environment space of surrounding cities, resulting in a significant difference in the green development index between Wuhan and surrounding cities. In 2010, Yingtan City in the southwestern part of the Middle Reaches of the Yangtze River Urban Agglomeration was of the low-high type, and the coupling coordination degree of the water-energy-environment correlation system was relatively low compared with surrounding cities, belonging to the low-value heterogeneous center. However, there was no obvious heterogeneous aggregation state in 2015 and 2020, indicating that there was no obvious gap in the green development level between Yingtan City and surrounding cities.

[0145] By analyzing the spatial aggregation of the green development index of each city in three typical years, it can be found that at present, there is no high-high aggregation area in the Middle Reaches of the Yangtze River Urban Agglomeration, and there is a lack of a central city that can lead the overall coordinated development of the urban agglomeration. Therefore, it is difficult to effectively promote the improvement of the green development level of surrounding cities through the radiation trickle-down effect within the urban agglomeration. In the future, each city should deeply analyze the resource and environmental constraints it faces, base on the actual situation, adopt city-specific policies, and formulate effective measures targeted to make up for the shortcomings and promote the green development of the city. Further strengthen and improve the construction of the sharing and allocation platform for water resources, energy and other fields within the urban agglomeration, promote the two-way circulation of water resources and energy among regions, and continuously promote the construction of the integrated ecological environment governance system of the urban agglomeration; focus on the cross-border areas with strong endogenous cooperation motivation, actively play the radiation and driving role of the areas with high-level coordinated development of water-energy-environment multi-dimensional cooperation on the surrounding areas, and promote the spillover diffusion effect and spatial aggregation effect of high-level coordinated development of regional water resources, energy and environment in a way of driving the whole by parts, so as to promote the high-level green development of the Middle Reaches of the Yangtze River Urban Agglomeration as a whole.

[0146] 3. Attribution Analysis of Influencing Factors of the Green Development Level of the Urban Agglomeration

[0147] In this embodiment, three typical years of 2010, 2015, and 2020 are selected, and the factor detection module in the geographical detector is used to identify the influencing factors of the green development level of the Middle Reaches of the Yangtze River Urban Agglomeration, and the results are shown in Table 7.

[0148] Table 7 Detection Results of Influencing Factors of the Green Development Level of the Middle Reaches of the Yangtze River Urban Agglomeration in 2010, 2015, and 2020

[0149]

[0150]

[0151] The main factors of the spatial differentiation of green development in the Middle Reaches of the Yangtze River Urban Agglomeration vary in different typical years. In 2010, the factors that had a greater impact on the green development of the urban agglomeration were water consumption per 10,000 yuan of industrial added value, daily urban sewage treatment capacity, population density, and water consumption per 10,000 yuan of GDP, with their explanatory powers being 0.728, 0.688, 0.581, and 0.562 respectively. This indicates that the green development level of the Middle Reaches of the Yangtze River Urban Agglomeration during this period was mainly affected by factors such as industrial water use efficiency, regional sewage treatment level, population density, and water resource utilization efficiency. Around 2010 was a period of rapid urbanization and industrialization. The influx of a large number of people into cities would lead to spatial changes in subsystems such as water, energy, and the environment. On the other hand, the extensive development model came at the cost of water use efficiency, and long-term high-intensity pollution emissions had severely degraded the ecological environment. Improving water use efficiency and enhancing the pollution treatment level were the keys to improving the overall green development level of the urban agglomeration during this period.

[0152] In 2015, the main influencing factors were water consumption per 10,000 yuan of industrial added value, per capita electricity consumption, per capita GDP, and greening rate of built-up areas, with their explanatory powers being 0.636, 0.539, 0.504, and 0.475 respectively; the explanatory power of industrial water use efficiency ranked first in both of these two periods, indicating that improving industrial water use efficiency was the key to optimizing water resource utilization, improving the ecological environment, and thus enhancing the green development level of the urban agglomeration. Compared with 2010, the level of residential electricity consumption, regional economic development level, and urban greening level during this period were also important foundations for achieving high-level green development.

[0153] The factors with greater influence in 2020 were the energy consumption per 10,000 yuan of GDP, the water use rate for ecological environment, the per capita GDP, and the population density, with their explanatory powers being 0.707, 0.578, 0.447, and 0.445 respectively. This indicates that during this period, the high-level development of the urban agglomeration was mainly affected by the energy utilization efficiency, the attention paid to the ecological environment, the economic development level, and the population density within the region. Compared with the previous two typical years, the energy utilization efficiency is the key factor for the spatial variation of the high-level development of the urban agglomeration at the present stage. The reason is that although the energy consumption per 10,000 yuan of GDP of the urban agglomeration as a whole gradually decreased during the evaluation period, the decline rate of the energy consumption per 10,000 yuan of GDP showed a gradually narrowing trend, which to a certain extent means that the pressure of energy conservation and consumption reduction will increase in the future, and the cost of consumption reduction will continue to rise. How to further improve the energy utilization efficiency in the future is the breakthrough point for the urban agglomeration to move from the basic coordinated development level to the highly coordinated development level. From the analysis of the environmental subsystem, the factors with greater influence in the three typical years of 2010, 2015, and 2020 were the daily urban sewage treatment capacity, the greening rate of the built-up area, and the water use rate for ecological environment in turn. With the continuous promotion of the plan, the pollution treatment capacity of each city has been continuously improved, and meeting the people's needs for a high-quality urban and rural living environment has gradually become the focus of the environmental protection of the urban agglomeration at the present stage. Compared with 2015, the population density in the region has once again become an influencing factor with a greater explanatory power at the present stage. The main reason is that the current aging problem has gradually become prominent, and the change in the population size will inevitably be reflected in the demand for water resources and energy, as well as the accompanying environmental problems.

[0154] The geographical detector interactive detection module was used to identify the explanatory degree of the interactive effects of different factors on the green development level of the Middle Reaches Urban Agglomeration at the present stage (2020), as Figure 6 shown. The results show that the explanatory power of the pairwise interaction of 18 influencing factors on the change of the green development index is greater than that of the independent action of each factor, and there are double-factor enhancement effects (Bi-Enhance, BE) and non-linear enhancement effects (Nonlinear-Enhance, NE) among the factors, indicating that the interactive synergy of each factor in the water resources, energy, environment and social economy subsystems has a more obvious impact on the green development level of the urban agglomeration. The differences in the green development level within the Middle Reaches Urban Agglomeration are the result of the combined action of various factors within different subsystems.

[0155] The explanatory power of the pairwise interaction of different factors on the green development level of the urban agglomeration is divided into two categories. One category is that the single-factor explanatory power is relatively strong, and after interacting with other factors, the explanatory power of the two-factor interaction on the green development level of the urban agglomeration is further improved. Taking the energy consumption per 10,000 yuan of GDP (X 13 ) as an example, the energy consumption per 10,000 yuan of GDP (X 13)In 2020, the single-factor explanatory power for the green development level of the urban agglomeration was 0.707. After the interaction of other factors with the energy consumption per 10,000 yuan of GDP (X 13 ), the average explanatory power for the green development level can reach 0.822. This is attributed to the relatively strong single-factor explanatory power of the energy consumption per 10,000 yuan of GDP (X 13 ). After the interaction of other factors with the energy consumption per 10,000 yuan of GDP (X 13 ), the explanatory power for the green development level of the urban agglomeration can be further improved on the basis of the single-factor explanatory power (0.707) of the energy consumption per 10,000 yuan of GDP (X 13 ). Another category is that after the interaction with other factors, the improvement of the explanatory power of the two factors for the green development of the urban agglomeration is more obvious compared with the single-factor explanatory power. Taking the total water resources as an example, the single-factor explanatory power of the total water resources (X 5 ) is 0.363, but the average explanatory power after the pairwise interaction with other factors is 0.767. There are 11 groups showing a non-linear enhancement effect in the interaction with other factors, indicating that the explanatory power of most factors for the green development level of the urban agglomeration is more obvious after the interaction with the total water resources (X 5 ). Although the total water resources in the Middle Reaches of the Yangtze River Urban Agglomeration are relatively abundant, compared with the action of other single factors, the total water resources are not the dominant driving factor for the green development of the urban agglomeration. However, as an irreplaceable basis for industrial and agricultural production, residents' lives, and environmental improvement, water resources have a significant impact on the green development level of the urban agglomeration after the interaction with other influencing factors.

[0156] Generally speaking, since factors such as the energy utilization efficiency, ecological environment guarantee degree, and economic development level in the current stage are the dominant driving factors leading to the spatial differences in the green development level of the urban agglomeration, in the future development process of urban agglomeration integration, the resource and environmental constraints existing in each city should be considered, and the cooperation and complementarity of water resources, energy and other elements among different cities should be reasonably guided and regulated. Targeted efforts should be made to strengthen the weak links in the fields of energy utilization efficiency and urban and rural beautiful environment guarantee in different regions, and gradually narrow the differences in the green development levels of different cities within the urban agglomeration; make full use of the regional policy orientation of urban agglomeration development, give priority to the development and promotion of energy-efficient and green production methods, adhere to the adjustment of industrial structure and the exploration of potential for efficiency improvement, promote the continuous transformation of residents' lifestyles towards green and low-carbon directions, and promote the joint protection and co-governance of the ecological environment, and make efforts from all dimensions to improve the green development level of the urban agglomeration.

[0157] Considering that the impact of the interaction of different driving factors on the green development level of urban agglomerations is higher than the impact of each factor independently on multi-dimensional coordinated development, in the future, whether it is to improve the utilization efficiency of water resources and energy, or to improve the environmental conditions of urban agglomerations, the multi-dimensional coordinated development relationship of water-energy-environment needs to be incorporated into the formulation of the diversified development strategies of urban agglomerations. On the premise of following the laws of social and economic development, it is necessary to further consider the individual impacts and interactions of various factors on the trend of multi-dimensional coordinated development of water-energy-environment in urban agglomerations, and explore the evolution mechanism and improvement path of regional green development from the perspective of cross-system coordination and multi-factor interaction.

[0158] As described above, it is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed by the present invention should be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A spatiotemporal evaluation and attribution identification method for green development of urban agglomerations based on the water-energy-environment relationship, characterized by: include Step 1: Starting from the four subsystems of social economy, water resources, energy, and environment, a set of green development level evaluation indicators for urban agglomerations based on the water-energy-environment linkage system is constructed, wherein the set of green development level evaluation indicators for urban agglomerations includes evaluation indicators corresponding to the social economy subsystem, evaluation indicators corresponding to the water resources subsystem, evaluation indicators corresponding to the energy subsystem, and evaluation indicators corresponding to the environment subsystem; the evaluation indicators are standardized by the range method to obtain standardized values ​​of different indicators of each subsystem; and the indicator weights of the evaluation indicators are calculated; Step 2: Calculate the green development index of the urban agglomeration and the cities within it based on the standardized values ​​of different indicators of each subsystem and the indicator weights; grade the green development index of the urban agglomeration and the cities within it according to the classification criteria, so as to obtain the classification results of each region accordingly, and evaluate the stage of green development of the urban agglomeration and the cities within it from the perspective of time and space differences; identify the main influencing factors of green development of the urban agglomeration based on the standardized values ​​of each indicator in the green development evaluation index set.

2. The spatiotemporal evaluation and attribution identification method for green development of urban agglomerations based on the water-energy-environment relationship as claimed in claim 1, characterized in that: In step one, the evaluation indicators corresponding to the social and economic subsystem include population density, per capita GDP, urbanization rate, and proportion of the tertiary industry; the evaluation indicators corresponding to the water resources subsystem include total water resources, water supply modulus, water resources development and utilization rate, water consumption per 10,000 yuan of GDP, and water consumption per 10,000 yuan of industrial added value; the evaluation indicators corresponding to the energy subsystem include total energy consumption, total social electricity consumption, natural gas supply in urban areas, energy consumption per 10,000 yuan of GDP, and per capita electricity consumption; the evaluation indicators corresponding to the environment subsystem include daily urban sewage treatment capacity, wastewater discharge per 10,000 yuan of GDP, ecological environment water use rate, and green coverage rate of built-up areas.

3. The spatiotemporal evaluation and attribution identification method for green development of urban agglomerations based on the water-energy-environment relationship as claimed in claim 2 is characterized by: In step 1, the range method is used to standardize the evaluation index, and the calculation formula is as follows: Positive indicators: Negative indicators: In the formula, the standardized value is expressed as y ij , x ij is the jth index value of the ith subsystem, x ijmin and x ijmax They correspond to the minimum and maximum values ​​of the j-th evaluation index of the ith subsystem respectively.

4. The spatiotemporal evaluation and attribution identification method for green development of urban agglomerations based on the water-energy-environment relationship as claimed in claim 2, characterized in that: The indicator weights of the evaluation indicators in step 1 are calculated, specifically including: introducing a combined weighting calculation method based on the combination of hierarchical analysis method and entropy weight method, establishing a weighting model for the evaluation indicator set of the green development level of urban agglomerations, and the weight w of the jth evaluation indicator of the i-th subsystem ij The calculation formula is as follows: In the formula, p ij ,q ij are the weights of the j-th evaluation index of the ith subsystem calculated by the analytic hierarchy process and the entropy weight method, respectively.

5. The spatiotemporal evaluation and attribution identification method for green development of urban agglomerations based on the water-energy-environment relationship as claimed in claim 4, characterized in that: In step 2, the green development index of the urban agglomeration and each city within it is calculated based on the standardized values ​​of different indicators of each subsystem and the indicator weights, including: Construct the development index of each subsystem of water resources, energy, environment, and social economy. The calculation formula is as follows: Where F1(·), F2(·), F3(·), and F4(·) are the development index evaluation functions of the social economy, water resources, energy, and environment subsystems, respectively; a j , b j 、c j ,d j are the weights of different indicators of each subsystem; x' j ,y' j 、u' j 、v' j are the standardized values ​​of different indicators of each subsystem, and the range method is used to standardize the representative indicators of each subsystem; k, l, p, q are the number of indicators of each subsystem; Calculate the city's green development index based on the development index of each subsystem: Based on the calculation results of the development index of different subsystems, construct a green development evaluation function. The calculation result of the green development evaluation function is called the green development index. The larger the green development index, the higher the level of green development. The calculation formula of the green development index T of each city is as follows: D=αF1+βF2+γF3+δF4 (10) Where C is the coupling degree, which reflects the coupling effect between each subsystem; D is the comprehensive evaluation function of the water-energy-environmental linkage system, and α, β, γ, and δ are the weights of each subsystem respectively; After calculating the green development evaluation function results of each city, the average value of the green development evaluation function of each city is calculated, which is the overall green development index of the urban agglomeration.

6. The spatiotemporal evaluation and attribution identification method for green development of urban agglomerations based on the water-energy-environment relationship as claimed in claim 5, characterized in that: In step 2, the green development index of the urban agglomeration and the cities within it is graded according to the classification basis, so as to obtain the classification results of each region accordingly. The classification basis is shown in Table 2: Table 2 Classification of green development levels 7. The spatiotemporal evaluation and attribution identification method for green development of urban agglomerations based on the water-energy-environment relationship as claimed in claim 1, characterized in that: Step 2 evaluates the stage of green development of urban agglomerations and cities within them from the perspective of temporal and spatial differences, including: By classifying the time series data of green development index of urban agglomerations and cities within them, the green development stage of urban agglomerations and cities within them is assessed; The global spatial autocorrelation and local spatial autocorrelation analysis methods are used to analyze the spatial agglomeration trend of green development levels within urban agglomerations. The global spatial autocorrelation analysis uses the Moran's I index as a measurement indicator to reflect the agglomeration and distribution effects between different cities in an urban agglomeration. The calculation formula of the Moran's I index is as follows: Where W ij represents the spatial weight matrix; n represents the number of spatial units; x i and x j The green development indexes of regions i and j are respectively, It represents the average value of the green development index; Moran's I∈[-1,1], at a specific significance level, if Moran's I>0, it indicates that the green development level in the urban agglomeration is spatially clustered; the larger the Moran's I index is, the more significant the spatial agglomeration characteristics of the green development level are; otherwise, it indicates that the green development level in the urban agglomeration is spatially different; The local spatial autocorrelation analysis uses the local autocorrelation index to obtain the LISA cluster analysis map to explore the spatial agglomeration degree of the green development index of each city in the urban agglomeration and its adjacent areas. The local autocorrelation index I i The calculation formula is as follows: In the formula, S 2 is the variance of the green development index. The local spatial autocorrelation aggregation types are divided into four types: low-low aggregation, low-high aggregation, high-low aggregation and high-low aggregation.

8. The spatiotemporal evaluation and attribution identification method for green development of urban agglomerations based on the water-energy-environment relationship as claimed in claim 1, characterized in that: In step 2, the main influencing factors of green development of urban agglomerations are identified based on the standardized values ​​of each indicator in the green development evaluation index set, including: The natural breakpoint method is used to stratify the data of the original values ​​of each indicator in the green development index of each city and the green development level evaluation index of the urban agglomeration; The factor detection module in the geographic detector method is used to explore the influence of different factors in various economic subsystems on the spatial differentiation of green development in urban agglomerations; The interaction detection module in the geographic detector is used to explore the influence of two-factor interaction on the green development level of urban agglomerations.

9. The spatiotemporal evaluation and attribution identification method for green development of urban agglomerations based on the water-energy-environment relationship according to claim 8, characterized in that: The influence of different factors in each subsystem on the spatial differentiation of green development in urban agglomerations is measured by the q value, and the calculation formula is as follows: SST=Nσ 2 (15) In the formula, Y represents the dependent variable, i.e., the green development index, h = 1,…,L, L is the layer of influencing factor X, and influencing factor X is each indicator in the green development level evaluation index set; N h and N are the number of units in layer h and the entire urban agglomeration respectively; Y hi and Y i are the values ​​of unit i in layer h and the entire urban agglomeration respectively; σ h 2 and σ 2 are the variances of the Y values ​​in the h layer and the entire urban agglomeration, respectively; SSW and SST are the sum of the variances within the layer and the total variance of the entire region, respectively; q∈[0,1], the larger the q value, the greater the influence of this factor on the green development level of the urban agglomeration, and vice versa.

10. The spatiotemporal evaluation and attribution identification method for green development of urban agglomerations based on the water-energy-environment relationship according to claim 9, characterized in that: The use of the interaction detection module in the geographic detector to explore the influence of the two-factor interaction on the green development level of the urban agglomeration specifically includes: By comparing the influence q value of the two factors acting alone on the green development level of urban agglomerations and the q value of their interaction: q(X1∩X2), and comparing their size relationship according to Table 3, it is determined whether there is an interaction between the two factors and the type of interaction. The detection results of the interaction detection module can indicate whether the interaction of the two factors will enhance or weaken the explanatory power of the green development level of urban agglomerations compared with the independent effect of the single factor. Table 3 Two-factor interaction types

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