Obstacle factor measuring method for coordinated development of composite system

Abstract

The invention is suitable for the technical field of drainage basin / region coordinated development, and provides an obstacle factor measurement method for coordinated development of a composite system, which comprises the following steps: step 1, selecting evaluation indexes, and constructing an index framework of water resource, ecological environment and social economy subsystems; 2, calculating the index weight and the development index of each subsystem by adopting a CRITIC method, and evaluating the coordinated development level of the water resource-ecological environment-social economy composite system by utilizing a coupling coordination degree model; and step 3, establishing an improved obstacle degree model, and diagnosing obstacle factors of coordinated development of the WES compound system. The invention provides an improved obstacle degree model suitable for the coordinated development of the compound system, and discusses the coordinated development condition and obstacle factors of the water resource-ecological environment-social economy compound system by taking the Yellow River diversion water receiving area (Henan Province and Shandong Province) at the downstream of the Yellow River as a research object, and verifies the applicability and effectiveness of the model.

Description

Technical Field

[0001] The invention belongs to the technical field of coordinated development of river basins / regions, and in particular relates to a method for measuring obstacle factors of coordinated development of a composite system. Background Art

[0002] As the understanding of the relationship between water resources, ecological environment and social economy continues to deepen, domestic and foreign scholars have found that different functional elements in the process of water resources development and utilization are interconnected and symbiotic, with the form and structure of a complex giant system. The sustainable development of a river basin / region depends on the orderly movement of water resources, ecological environment and social economy subsystems (and their constituent elements) and their coordinated development.

[0003] Accurately identifying the coordinated development status and obstacles of the basin / regional complex system can help decision makers avoid unreasonable development patterns and their negative impacts, and provide scientific guidance for the sustainable development of the basin / region. Most related studies give a qualitative identification result based on the changing characteristics of each subsystem and its components with the coupling coordination degree. In order to obtain more objective and accurate results, some quantitative evaluation methods such as correlation analysis, regression model, logarithmic mean separable index method, random forest algorithm and obstacle degree model have been applied and developed. Among them, the obstacle degree model is simple to calculate and can provide the obstacle degree values ​​of different factors (rather than just the ranking of the obstacle degree of different factors). The results are more intuitive and easy to understand, and have been widely used. However, in terms of calculation principle, the traditional obstacle degree model can only be used for indicators in the form of weighted combination (such as comprehensive development level), but not for indicators in the form of multiplication combination (such as coordinated development level). For this reason, a method for measuring obstacles to the coordinated development of a complex system is proposed. Summary of the invention

[0004] The purpose of the present invention is to provide a method for measuring obstacles to the coordinated development of a composite system, aiming to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A method for measuring obstacles to coordinated development of a complex system includes the following steps:

[0007] Step 1: Select evaluation indicators and construct an indicator framework for water resources, ecological environment and socio-economic subsystems;

[0008] Step 2: Calculate the indicator weight and development index of each subsystem using the CRITIC method, and evaluate the coordinated development level of the water resources-ecological environment-socio-economic complex system using the coupling coordination model;

[0009] Step 3: Establish an improved barrier model and diagnose the barriers to the coordinated development of the WES composite system.

[0010] Furthermore, the specific process of calculating the indicator weights and development index of each subsystem using the CRITIC method is as follows:

[0011] Information entropy and correlation coefficient are used to measure variability and conflict, as follows:

[0012] For a certain subsystem i, the calculation formula for the variability of each indicator is:

[0013] Formula 1:

[0014] In the formula, is the information entropy of the cth indicator in region b, i.e., the variability measure; is the proportion of indicator c in region b in year a, x abc is the index processed by the Min-Max standardization method, with a value range of [0,1]; N is the number of years;

[0015] The calculation formula for the conflict between different indicators is:

[0016] Formula 2:

[0017] In the formula, is the conflict measurement value of the cth indicator in region b; corr(r bc ,r bd ) is the correlation coefficient between the cth index and the dth index in region b; k is the number of indicators in the subsystem;

[0018] The weight coefficient of each indicator is:

[0019] Formula 3:

[0020] In the formula, is the weight coefficient of the cth indicator in region b;

[0021] The evaluation indicators of water resources, ecological environment and socio-economic subsystems are weighted and integrated to calculate the development index of each subsystem:

[0022] Formula 4:

[0023] In the formula, is the development index of subsystem i in region b in year a, and its value range is [0,1].

[0024] Furthermore, the specific process of the step of evaluating the coordinated development level of the water resources-ecological environment-socio-economic complex system by using the coupling coordination degree model is as follows:

[0025] The coupling coordination degree is calculated as:

[0026] Formula 5:

[0027] Where D ab is the coupling coordination degree of the composite system in region b in year a; C ab and T ab are coupling degree and comprehensive development index respectively, expressed as:

[0028] Formula 6:

[0029] Where m is the number of subsystems; is the weight coefficient of subsystem i, set Then Equation 5 can be written as:

[0030] Formula 7:

[0031] Among them, D ab The value range is [0,1], and the coupling coordination degree is divided into five levels: severe mismatch, moderate mismatch, barely coordinated, moderately coordinated and highly coordinated.

[0032] Furthermore, the coupling coordination degrees corresponding to the five levels of severe disorder, moderate disorder, barely coordinated, moderately coordinated and highly coordinated are [0, 0.2], (0.2, 0.4], (0.4, 0.6], (0.6, 0.8] and (0.8, 0.9] respectively.

[0033] Furthermore, in step 3, the obstacle degree model analyzes the influence of factors on the overall development of the system by measuring factor contribution, indicator deviation and obstacle degree, which is expressed as:

[0034] Formula 8:

[0035] In the formula, P is the obstacle degree of the evaluation index x; w is the factor contribution, that is, the weight coefficient of the evaluation index x; (max-x) is the deviation of the index x from the ideal value;

[0036] The step 3 comprises the following steps:

[0037] Step 31: At the indicator level, use Formula 8 to calculate the subsystem development index of each indicator The degree of obstacle;

[0038] Step 32: At the subsystem level, a method for calculating the degree of obstacle based on product combination is proposed to calculate the degree of obstacle of each subsystem to the coordinated development of the entire complex system;

[0039] Step 33: Integrate the obstacle degrees at the indicator level and the subsystem level to obtain the comprehensive obstacle degree of each indicator to the coordinated development of the complex system.

[0040] Furthermore, the specific steps of step 3 are as follows:

[0041] Step 31, indicator level obstacle degree;

[0042] For any subsystem i, the degree of obstacle of each indicator to the subsystem development index is expressed as:

[0043] Formula 9:

[0044] In the formula, is the barrier degree of indicator c in region b to subsystem i in year a; For evaluation indicators The weight coefficient satisfies

[0045] Step 32: Subsystem level obstacle degree;

[0046] Taking the logarithm of both sides of formula 7, we can get the coupling coordination degree calculation formula in the form of weighted combination:

[0047] Formula 10:

[0048] The degree of obstacle of each subsystem to the coordinated development of the entire composite system is expressed as:

[0049] Formula 11:

[0050] In the formula, is the obstacle degree of subsystem i in region b in year a; max' is the ideal value of each subsystem, equal to The maximum value of The value range of is [0,1], so max'=0, then formula 11 is written as:

[0051] Formula 12:

[0052] Step 33, comprehensive obstacle degree calculation;

[0053] Multiply the indicator-level obstacle degree by the corresponding subsystem-level obstacle degree to obtain the comprehensive obstacle degree of each indicator to the coordinated development of the composite system:

[0054] Formula 13:

[0055] Where U abc It is the comprehensive obstacle degree of indicator c in region b in year a.

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

[0057] This paper proposes an improved obstacle degree model suitable for the coordinated development of complex systems. Taking the Yellow River diversion receiving area in the lower reaches of the Yellow River (part of Henan Province and Shandong Province) as the research object, it explores the coordinated development status and obstacle factors of the water resources-ecological environment-socio-economic complex system, and verifies the applicability and effectiveness of the model. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 It is a flow chart of the present invention.

[0059] Figure 2 It is the water receiving area of ​​the lower reaches of the Yellow River (part of Henan Province and Shandong Province).

[0060] Figure 3 It is the interannual changes of water resources, ecological environment and socio-economic subsystem development index from 2001 to 2020.

[0061] Figure 4 It is the coupling coordination degree of the water resources-ecological environment-socio-economic complex system from 2001 to 2020; the upper edge, lower edge and horizontal line of the box plot are the maximum, minimum and quartile values ​​of the coupling coordination degree of cities in Henan Province and Shandong Province, respectively; the dotted line is the mean of the coupling coordination degree of the two provinces; EHB, HB, MB, RB, and MU on the right are extremely high coordination, high coordination, moderate coordination, barely coordinated, and moderately uncoordinated, respectively.

[0062] Figure 5 is the obstacle degree of the coordinated development of the water resources-ecological environment-socio-economic complex system from 2001 to 2020; (a) to (d) are the obstacle degrees of each indicator to the coordinated development of the water resources-ecological environment-socio-economic complex system in the four periods of 2001-2005, 2006-2010, 2011-2015 and 2016-2020, respectively.

[0063] Figure 6 Comparison of coupling coordination barriers of WES systems from 2001 to 2005. DETAILED DESCRIPTION

[0064] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0065] The specific implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0066] An embodiment of the present invention provides a study of the Yellow River lower reaches (part of Henan Province and Shandong Province) to explore the coordinated development of the water resources-ecological environment-socio-economic complex system and its obstacles, and verifies the applicability and effectiveness of the model. The details are as follows:

[0067] 1. Study area;

[0068] The Yellow River lower reaches water receiving area is the area below Taohuayu in Zhengzhou, Henan, which uses the Yellow River water. It involves four provincial administrative regions, namely Henan, Shandong, Hebei and Tianjin. This paper mainly considers 23 prefecture-level cities in Henan and Shandong provinces, with a total area of ​​199,500 km 2 ,like Figure 2 As shown. Among them, Henan Province includes five cities along the Yellow River, namely Zhengzhou, Kaifeng, Jiaozuo, Xinxiang and Puyang, as well as five cities that draw water from the Yellow River, namely Hebi, Anyang, Xuchang, Zhoukou and Shangqiu; Shandong Province includes nine cities along the Yellow River, namely Heze, Jining, Tai'an, Jinan, Zibo, Dongying, Binzhou, Dezhou and Liaocheng, as well as four cities that draw water from the Yellow River, namely Weifang, Qingdao, Yantai and Weihai. Most of the study area belongs to the Yellow River alluvial plain, with flat terrain, concentrated precipitation, rainy and hot seasons in the same season, and an average annual precipitation of about 630 mm. The Yellow River is an important surface water source in the region, providing water source guarantee for local agricultural irrigation, industrial production, ecological construction and residents' lives.

[0069] The interaction among water resources, ecological environment and social economy in the study area is strong: the water resources endowment is poor, and the total water resources in 2020 are 34.861 billion m 3 The per capita water resources are only 243.68m 3 , which is about 1 / 10 of the national average. The rate of water resource development and utilization far exceeds the ecological warning line. The shortage of water resources has become a constraint on industrial and agricultural development and ecological environmental protection. The ecological environment is relatively fragile. Since the implementation of the unified dispatching of the Yellow River water volume and ecological water replenishment in 1999, problems such as wetland shrinkage and biodiversity reduction have been effectively curbed. However, the pollutants entering the river in some cities exceed the carrying capacity of the water environment, further exacerbating the water shortage situation. Social and economic development continues to improve, but the population base is large (the population density in 2020 is 623.95 people / km 3 , much higher than the national average of 148.77 people / km 3 ), the industrial structure is unreasonable, and the pressure on resource consumption and environmental capacity is becoming increasingly prominent.

[0070] 2. Research methods;

[0071] In order to explore the coordinated development level and obstacles of water resources, ecological environment and socio-economy, this study established a systematic research framework, which includes three progressive processes: (1) Through literature review, evaluation indicators are selected to construct the indicator framework of water resources, ecological environment and socio-economy subsystems. (2) The CRITIC method is used to calculate the indicator weights and development index of each subsystem, and the coupled coordination degree model is used to evaluate the coordinated development level of the water resources-ecological environment-socio-economy complex system. (3) An improved obstacle degree model is established, and the obstacles to the coordinated development of the WES complex system are diagnosed.

[0072] 2.1. Evaluation index system;

[0073] Drawing on existing research results and combining the actual situation of the study area, this paper constructs a water resources-ecological environment-socio-economic composite system evaluation index system for the Yellow River lower reaches receiving area, which contains 21 indicators, in accordance with the principles of comprehensiveness, effectiveness, representativeness, independence and accessibility, as shown in Table 1. In order to eliminate the influence of factors such as area, population, and GDP on the evaluation results as much as possible and to better carry out comparative analysis between different regions, all indicators use per capita and per-area ratio values. In addition, all indicators are regarded as positive (+) or negative (-) unidirectional indicators and are standardized to eliminate the influence of indicator dimensions and magnitudes.

[0074] Table 1 Evaluation index system of water resources-ecological environment-socio-economic complex system in the Yellow River diversion receiving area in the lower reaches

[0075]

[0076] 2.2. Analysis of coordinated development level;

[0077] 2.2.1. Subsystem development index;

[0078] The subsystem development index is used to measure the development level of the three subsystems of water resources, ecological environment and social economy, and can be obtained by weighted integration of evaluation indicators. The CRITIC method uses standard deviation and correlation coefficient to measure variability and conflict respectively, but the standard deviation is very likely to have a large measurement value for data sequences that do not obey the normal distribution or have many outliers. Therefore, the present invention considers using information entropy instead of standard deviation to measure variability. For a certain subsystem i, the calculation formula for the variability of each indicator is:

[0079] Formula 1:

[0080] In the formula, is the information entropy of the cth indicator in region b, i.e., the variability measure; is the proportion of indicator c in region b in year a, x abcIt is an indicator processed by the Min-Max standardization method, with a value range of [0,1]; N is the number of years.

[0081] The calculation formula for the conflict between different indicators is:

[0082] Formula 2:

[0083] In the formula, is the conflict measurement value of the cth indicator in region b; corr(r bc ,r bd ) is the correlation coefficient between the c-th index and the d-th index in area b; k is the number of indicators of the subsystem, which is 7 in the present invention.

[0084] The weight coefficient of each indicator is:

[0085] Formula 3:

[0086] In the formula, is the weight coefficient of the cth indicator in area b. On this basis, the evaluation indicators of water resources, ecological environment and socio-economic subsystems are weighted and integrated to calculate the development index of each subsystem:

[0087] Formula 4:

[0088] In the formula, is the development index of subsystem i in region b in year a, and its value range is [0,1]. The larger the value, the higher the level of development of the subsystem.

[0089] 2.2.2 Level of coordinated development of complex systems;

[0090] The coupling coordination model can measure the coordinated development level of multiple subsystems. For a composite system, its coupling coordination can be calculated as:

[0091] Formula 5:

[0092] Where D ab is the coupling coordination degree of the composite system in region b in year a; C ab and T ab are coupling degree and comprehensive development index respectively, which can be expressed as:

[0093] Formula 6:

[0094] Where m is the number of subsystems, which is taken as 3 in this paper; is the weight coefficient of subsystem i. Considering that different subsystems often play an equally important role, Then Equation 5 can be written as:

[0095] Formula 7:

[0096] From the above formula, we can see that D ab It is a generalized multiplication combination indicator. When the development index of one (or two) subsystems is lower than that of other subsystems, D ab The value will also decrease, so it can be considered that the development of this subsystem is relatively lagging, which affects the coupling coordination level of the composite system.

[0097] D ab The value range is [0,1]. The larger the value, the higher the level of coordinated development of the composite system. According to previous related research, the coupling coordination degree can be divided into five levels: severe disorder, moderate disorder, barely coordinated, moderately coordinated and highly coordinated. Table 2 shows the specific classification of coupling coordination levels.

[0098] Table 2 Classification of coupling coordination degree

[0099] Coupling Coordination Subcategories [0,0.2] Serious disorder (0.2,0.4] Moderate Disorder (0.4,0.6] Barely coordinated (0.6,0.8] Moderate coordination (0.8,0.9] Highly coordinated

[0100] 2.3、Measurement of obstacles;

[0101] The obstacle degree model analyzes the influence of factors on the overall development of the system by measuring factor contribution, indicator deviation and obstacle degree, which can be expressed as:

[0102] Formula 8:

[0103] In the formula, P is the obstacle degree of evaluation index x; w is the factor contribution, that is, the weight coefficient of evaluation index x; (max-x) is the deviation of index x from the ideal value, and for the standardized evaluation index max = 1. It can be seen that the denominator in the above formula is the weighted combination of all factor deviations, so the traditional obstacle model is used to measure the evaluation index in the form of weighted combination (such as a subsystem development index The overall system development index T ab ) of the obstacle degree, and for the product combination form evaluation index (coupling coordination degree D ab ) is obviously not applicable.

[0104] In view of this, the present invention proposes an improved obstacle degree model to quantitatively measure the obstacle degree of each indicator to the coordinated development of the composite system. Specifically, the entire calculation process is divided into two levels: indicator and subsystem. At the indicator level, the development index of each indicator on the subsystem is calculated using formula 8. At the subsystem level, a barrier degree measurement method based on product combination is proposed to calculate the barrier degree of each subsystem to the coordinated development of the entire complex system. On this basis, the barrier degrees at the two levels are integrated to obtain the comprehensive barrier degree of each indicator to the coordinated development of the complex system.

[0105] (1) Barriers at the indicator level;

[0106] For any subsystem i, the degree of obstacle of each indicator to the subsystem development index can be expressed as:

[0107] Formula 9:

[0108] In the formula, is the barrier degree of indicator c in region b to subsystem i in year a; For evaluation indicators The weight coefficient satisfies

[0109] (2) Subsystem level obstacle degree;

[0110] Consider transforming the coupling coordination degree formula into a weighted combination form, and then evaluate the obstacle degree of each subsystem to the coordinated development of the water resources-ecological environment-social economy complex system according to the calculation principle of the obstacle degree model. Take the logarithm of both sides of formula 7 to obtain the coupling coordination degree calculation formula in the weighted combination form:

[0111] Formula 10:

[0112] The degree of obstacle of each subsystem to the coordinated development of the entire composite system can be expressed as:

[0113] Formula 11:

[0114] In the formula, is the obstacle degree of subsystem i in region b in year a; max' is the ideal value of each subsystem, equal to The maximum value of . The value range of is [0,1], so max'=0, then formula 11 can be written as:

[0115] Formula 12:

[0116] (3) Calculation of comprehensive obstacle degree;

[0117] By multiplying the indicator-level obstacle degree with the corresponding subsystem-level obstacle degree, we can get the comprehensive obstacle degree of each indicator to the coordinated development of the composite system:

[0118] Formula 13:

[0119] Where U abc It is the comprehensive obstacle degree of indicator c in region b in year a.

[0120] 3. Result analysis;

[0121] 3.1. The level of coordinated development of the WES system;

[0122] The development index and coupling coordination degree of water resources, ecological environment and socio-economic subsystems of each city from 2001 to 2020 were calculated respectively, and the coordinated development level of the water resources-ecological environment-socio-economic complex system in the receiving area of ​​the lower reaches of the Yellow River was analyzed.

[0123] 3.1.1. Development index of each subsystem;

[0124] from Figure 3 It can be seen that the change trends of the water resources (WR), ecological environment (EE), and social economy (SE) subsystem development indexes in Henan and Shandong provinces from 2001 to 2020 are basically the same, and the correlation coefficients between the two are 0.85, 0.96, and 0.92, respectively. Overall, the development indexes of the water resources, ecological environment, and social economy subsystems in the two provinces are all on the rise, indicating that the development levels of the three subsystems in the Yellow River diversion area in the lower reaches of the Yellow River are generally improving, and Shandong is slightly higher than Henan Province. The difference is that the development index of the social economy subsystem continued to increase rapidly throughout the study period, reaching a level similar to that of the water resources subsystem in 2012, and continued to rise to the highest level in 2020, 0.92 and 0.81, respectively; the growth rates of the water resources and ecological environment subsystems slowed down after 2003 and 2008, respectively, which resulted in the highest development level of the water resources subsystem before 2005 and the lowest level after 2018.

[0125] 3.1.2. The level of coordinated development of complex systems;

[0126] from Figure 4 It can be seen that the coupling coordination degree of the water resources-ecological environment-socio-economic complex system in Henan Province and Shandong Province showed a continuous upward trend from 0.46 and 0.44 in 2001 to 0.86 and 0.87 in 2020, respectively. Specifically, it was barely coordinated or below in 2001-2002, began to shift to moderate coordination in 2003, and further improved and maintained at a high level of coordination in 2015. It should be noted that the growth rate of the coupling coordination degree gradually decreased during the entire study period, which was mainly affected by the slowdown in the development of the water resources and ecological environment subsystems.

[0127] Further analysis of the discreteness of the coupling coordination degree of each city found that the distance between the upper and lower edge lines of the box plot gradually decreased from 2001 to 2020, and the height of the box also showed a decreasing trend, which shows that the differences in the coupling coordination levels of various cities in the Yellow River diversion area in the lower reaches of the Yellow River are gradually decreasing, and they are constantly gathering towards a higher level. It should be noted that most of the time, the distance from the lower edge line to the box is greater than the distance from the upper edge line to the box, which indicates that the coupling coordination level of some cities is significantly lower than that of other cities, thereby lowering the minimum value. The statistics of the coupling coordination degree of each city in each year are shown in Table 3:

[0128] Table 3 Coupling coordination degree of each city in each year

[0129]

[0130]

[0131]

[0132] From Table 3, we can find that the situations in Henan Province and Shandong Province are completely different. The cities with the minimum values ​​in Shandong Province in each year are relatively fixed, mainly Weifang, Jining and Heze; while in Henan Province, the situation is more scattered, and all 10 cities have experienced minimum values ​​in a certain period, indicating that the stability of the coupled and coordinated development of cities in Henan Province is poor.

[0133] 3.2. Diagnosis of obstacle factors;

[0134] The obstacle degree of each indicator to the coordinated development of the water resources-ecological environment-socio-economic complex system was calculated for the four periods of 2001-2005, 2006-2010, 2011-2015 and 2016-2020. The results are as follows: Figure 5 As time goes by, the polygons formed by the blue and red lines become more and more irregular, and the number of "spikes" continues to increase, indicating that the obstacles affecting the coordinated development of the complex system are becoming more and more prominent and their role is becoming more and more important. Overall, the obstacle degree of social and economic indicators was relatively large before 2010, and the obstacle degree of water resources and ecological environment indicators was relatively large after 2010.

[0135] From 2001 to 2005, the main obstacle factor in Henan and Shandong provinces was the average grain output per mu of S5, with obstacle degrees of 9.45% and 11.56% respectively. During this period, the two provinces were in a development stage dominated by traditional agriculture, with a low level of economic development, relatively backward agricultural production technology, and low grain output, which restricted the coupling and coordination level of the WES system; from 2006 to 2010, with the continuous popularization of technologies such as irrigation, fertilization, mechanical input, and improved variety promotion, agricultural production efficiency was significantly improved, and the average grain output per mu increased significantly, and its obstacle degree also decreased accordingly. On the contrary, the proportion of the output value of the tertiary industry in S7 became the main obstacle factor during this period, with obstacle degrees of 15.85% and 10.43% respectively, indicating that the two provinces are facing a severe situation of industrial transformation; from 2011 to 2015, Shandong Province promoted the implementation of industrial transformation and upgrading measures such as "transforming the mode" and "adjusting the structure", and various types of resource services for the tertiary industry developed rapidly, and its obstacle degree was also reduced to below 10%. However, Henan Province was limited by its large population base and weak economic foundation, and its development was relatively slow. Therefore, the proportion of the output value of the tertiary industry was still the main obstacle factor for the coupling and coordination of the WES system, with an obstacle degree of 14.50%. At the same time, the social and economic development of the two provinces has made great progress during this period, and the pressure on water resources and ecological environment has increased significantly. The obstacle degrees of indicators such as W1 water production modulus, W2 per capita water resources, E1 per capita wetland area, and E2 vegetation coverage have gradually increased, among which the vegetation coverage has reached 10.80% and 9.86%; from 2016 to 2020, the social economy continued to develop at a high speed, while the development of water resources and ecological environment was relatively slow (see Figure 3 ), resulting in more prominent problems of insufficient support of water resources and ecological environment for social and economic development. The obstacle degree of the four indicators has further increased to more than 10%, becoming the main factor restricting the coupling coordination of the two provinces. It should be noted that the obstacle degree of per mu grain output in Shandong Province from 2016 to 2020 was also relatively large, at 11.19%. This is because during this period, due to the influence of meteorological disasters, pests and diseases, the per mu grain output in many places such as Jinan and Qingdao showed a short-term decrease or no growth. However, in the long run, with the continuous improvement of agricultural production levels, the per mu grain output will continue to grow, so there is no need to focus on this factor in the future.

[0136] In summary, the present invention proposes an improved barrier degree model based on the calculation principle of barrier degree and coupling coordination degree, which solves the problem that the traditional barrier degree model cannot be applied to the coupling coordination degree in the form of multiplication combination, and is more reasonable in theory. The model was applied to the Yellow River diversion receiving area in the lower reaches of the Yellow River, and the results were consistent with relevant studies. To some extent, it proves that the improved barrier degree model can identify the main obstacles that restrict the coordinated development of the complex system, and has high effectiveness and accuracy. Taking 2001-2005 as an example, the results of the traditional barrier degree model and the measurement results of the improved barrier degree model are further compared, as shown in Figure 2. Figure 6As shown in the figure, it can be seen that the results of the traditional obstacle model are highly similar to the improved obstacle model, but the obstacle values ​​of each indicator have certain deviations. Among them, the obstacle degree of S5 per mu grain output in Henan Province and Shandong Province decreased from 9.45% and 11.56% to 8.02% and 9.54%, respectively, which may lead to misjudgment of key obstacle factors.

[0137] The above are only preferred embodiments of the present invention. It should be pointed out that, for those skilled in the art, several modifications and improvements can be made without departing from the concept of the present invention. These should also be regarded as the protection scope of the present invention. These will not affect the effect of the implementation of the present invention and the practicality of the patent.

Claims

1. A method for measuring obstacles to the coordinated development of a complex system, characterized in that: The following steps are involved: Step 1: Select evaluation indicators and construct an indicator framework for water resources, ecological environment and socio-economic subsystems; Step 2: Calculate the indicator weight and development index of each subsystem using the CRITIC method, and evaluate the coordinated development level of the water resources-ecological environment-socio-economic complex system using the coupling coordination model; Step 3: Establish an improved barrier model and diagnose the barriers to the coordinated development of the WES composite system.

2. The method for measuring obstacles to the coordinated development of a complex system according to claim 1 is characterized in that: The specific process of using the CRITIC method to calculate the indicator weights and development index steps of each subsystem is as follows: Information entropy and correlation coefficient are used to measure variability and conflict, as follows: For a certain subsystem i, the calculation formula for the variability of each indicator is: Formula 1: In the formula, is the information entropy of the cth indicator in region b, i.e., the variability measure; is the proportion of indicator c in region b in year a, x abc is the index processed by the Min-Max standardization method, with a value range of [0,1]; N is the number of years; The calculation formula for the conflict between different indicators is: Formula 2: In the formula, is the conflict measurement value of the cth indicator in region b; corr(r bc ,r bd ) is the correlation coefficient between the cth index and the dth index in region b; k is the number of indicators in the subsystem; The weight coefficient of each indicator is: Formula 3: In the formula, is the weight coefficient of the cth indicator in region b; The evaluation indicators of water resources, ecological environment and socio-economic subsystems are weighted and integrated to calculate the development index of each subsystem: Formula 4: In the formula, is the development index of subsystem i in region b in year a, and its value range is [0,1].

3. The method for measuring obstacles to the coordinated development of a complex system according to claim 1 is characterized in that: The specific process of using the coupling coordination degree model to evaluate the coordinated development level of the water resources-ecological environment-socio-economic complex system is as follows: The coupling coordination degree is calculated as: Formula 5: Where D ab is the coupling coordination degree of the composite system in region b in year a; C ab and T ab are coupling degree and comprehensive development index respectively, expressed as: Formula 6: Where m is the number of subsystems; is the weight coefficient of subsystem i, set Then Equation 5 can be written as: Among them, D ab The value range is [0,1], and the coupling coordination degree is divided into five levels: severe mismatch, moderate mismatch, barely coordinated, moderately coordinated and highly coordinated.

4. The method for measuring obstacles to coordinated development of a complex system according to claim 3 is characterized in that: The coupling coordination degrees corresponding to the five levels of severe disorder, moderate disorder, barely coordinated, moderately coordinated and highly coordinated are [0, 0.2], (0.2, 0.4], (0.4, 0.6], (0.6, 0.8] and (0.8, 0.9] respectively.

5. The method for measuring obstacles to coordinated development of complex systems according to claim 1 is characterized in that: In step 3, the obstacle degree model analyzes the influence of factors on the overall development of the system by measuring factor contribution, indicator deviation and obstacle degree, which is expressed as: Formula 8: In the formula, P is the obstacle degree of the evaluation index x; w is the factor contribution, that is, the weight coefficient of the evaluation index x; (max-x) is the deviation of the index x from the ideal value; The step 3 comprises the following steps: Step 31: At the indicator level, use Formula 8 to calculate the subsystem development index of each indicator The degree of obstacle; Step 32: At the subsystem level, a method for calculating the degree of obstacle based on product combination is proposed to calculate the degree of obstacle of each subsystem to the coordinated development of the entire complex system; Step 33: Integrate the obstacle degrees at the indicator level and the subsystem level to obtain the comprehensive obstacle degree of each indicator to the coordinated development of the complex system.

6. The method for measuring obstacles to coordinated development of a complex system according to claim 5 is characterized in that: The specific steps of step 3 are as follows: Step 31, indicator level obstacle degree; For any subsystem i, the degree of obstacle of each indicator to the subsystem development index is expressed as: Formula 9: In the formula, is the barrier degree of indicator c in region b to subsystem i in year a; For evaluation indicators The weight coefficient satisfies Step 32: Subsystem level obstacle degree; Taking the logarithm of both sides of formula 7, we can get the coupling coordination degree calculation formula in the form of weighted combination: Formula 10: The degree of obstacle of each subsystem to the coordinated development of the entire composite system is expressed as: Formula 11: In the formula, is the obstacle degree of subsystem i in region b in year a; max' is the ideal value of each subsystem, which is equal to ln The maximum value of The value range of is [0,1], so max'=0, then formula 11 is written as: Formula 12: Step 33, comprehensive obstacle degree calculation; Multiply the indicator-level obstacle degree by the corresponding subsystem-level obstacle degree to obtain the comprehensive obstacle degree of each indicator to the coordinated development of the composite system: Formula 13: Where U abc It is the comprehensive obstacle degree of indicator c in region b in year a.

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