Analysis of influencing factors and paths of synergistic development of water resources-economic society-ecological environment based on DIM modeling

Abstract

The intersection of climate change and human activities exacerbates the prominent contradiction between environmental resources and economic development. The synergistic development of water resources, economy and society, and ecological environment is particularly urgent. Therefore, accurately identifying its influencing factors and related pathways holds significant practical importance in resolving the contradiction between resources and economic development. This study constructs a system of influencing factors for the synergistic development of “water resources, economic society and ecological environment” from three dimensions, reveals the influencing relationship between indicators through the Decision Making Trial and Evaluation Laboratory (DEMATEL), determines the hierarchical structure of the influencing factors and the related paths through the Interpretive Structural Model (ISM), and classifies the influencing factors through the Matrix Multiplication Method of Cross Influence Matrix Multiplication (MICMAC). The results show that water resource factors are important cause factors and economic, social and ecological factors are essential effect factors. The factors influencing the synergistic development of “water resources, economic society and ecological environment” can be divided into four levels, of which the total water resources, precipitation and NDVI are at the bottom and are the most fundamental factors. The percentage of groundwater supply, total water supply, water resource utilization rate and energy consumption of 10,000 yuan of GDP are the deep core elements. Total grain output, water resources per capita, and water use per capita are the direct influencing factors. Finally, taking the Central Plains Urban Agglomeration as an example, selecting the identified important influencing factors and analyzing the level of synergistic development of its coupled system found that the degree of coupling coordination increased from 0.324 in 2011 to 0.978 in 2020. The water resources system showed a fluctuating change, and it is still the key to synergistic development. Analyzing the relationship between subsystems and clarifying the key factors for synergistic development of coupled systems are important for policy formulation, improving environmental governance and promoting high-quality economic development.

Introduction

Water resources are vital strategic assets essential for human survival, significantly contributing to regional economic development and the protection of ecological environments. At present, with rapid economic development, water resources are becoming increasingly scarce and the ecological environment is being seriously damaged, and socio-economic development and ecological environmental protection under water-scarce conditions are becoming increasingly challenging for the world. According to the environmental report issued by the United Nations, the world is currently confronting three major crises: climate change, biodiversity loss, and pollution¹. At the Climate Change Conference, the United Nations called on countries to work together to address the global economic crisis in climate change and to transform the current economic system sustainably².

Since the 18th National Congress, China’s development has entered a stage of high-quality growth, characterized by accelerated greening and decarbonization efforts. With the continuous advancement of management, all sectors of society have realized the phenomenon of “government failure” in the synergistic development of ecological environment protection and economic and social development³, and that the government cannot effectively manage the ecological environment and promote the high-quality development of the economy by relying on the government’s laws and regulations alone. Therefore, to improve the status of economic development and ecological governance, there is an urgent need to focus on the weak links in the synergistic development of water resources, economy, society and ecology, and to explore the key factors affecting the coupled system, to respond to the actual needs of synergistic sustainable advancement of the integrated system.

Domestic and international research on water resources and ecological impact factors has a long history, and literature has been published on the impact of drivers on ecological resilience⁴, ecosystem services⁵, ecological quality^6,28,36, and ecological risk assessment⁷. The concept of synergy was first introduced by Hermann Haken in 1969; synergy implies coordination and cooperation, and synergy solves the problem of how parts can form a whole by working together⁸. Subsequently, synergy has been studied in different scientific fields. Lu et al.⁹ studied the multidimensional coordinated development of water, society, economy, ecology, and environment in agriculture. Zhao et al.¹⁰ studied the interactions and trade-offs between the economic-social-environmental aspects within the context of water resource limitations by taking the capital region of China as an example. Coupled system as a physical concept refers to the phenomenon where two or more systems influence each other through multiple forms of interaction. Based on this idea, numerous studies on coupled systems have been performed, including the coupling between urbanization and ecological environment quality¹¹, land resources coupling¹², Agroecological coupling¹³, and the coupling between resource capacity and environmental carrying capacity¹⁴.With the increase of urban population and the acceleration of the process of economic development, how to harmonize the interrelationships among resources, economy, society, ecology and environment represent a critical challenge for sustainable development in contemporary times.¹⁵.

There has been an increase in the number of existing studies on coupled water resources, economic and social, and ecological systems. The studies that have been conducted have mainly quantitatively evaluated the resource carrying capacity of the coupled system by geo-detectors, regression analyses, or improved PSR models, and summarized the most significant influencing factors^16–18. However, it fails in depth the relationship between the factors in the indicator system and to distinguish the importance of the influencing factors. Second, an analysis of socio-economic factors affecting the development of priority areas for ecosystem services found that high urbanization in the middle and lower reaches of the Xiangjiang River Basin has resulted in a high proportion of impervious areas, and that aquifers have been damaged by over-exploitation in the economic development¹⁹. Xu et al.²⁰ studied Jiangsu Province found that environmental factors were the main factors affecting the coordinated development of the coupled system. Li et al.^21,35 studied the Yellow River Basin and found an inhibitory effect of precipitation on coordinated development over a long time series. The above studies have only listed the important factors that constrain the coordinated development of the coupled system from one side, such as the meteorological environment or the economy and society. There is a lack of identification of the interactions among water resources, economic and social, and ecological factors. On this basis, this study introduces the DEMATEL-ISM-MICMAC model into the coupled system of “water resources-economy and society-ecology and environment”, in order to explore a suitable method to reveal the hierarchical structure and inner connection between the influencing factors within the coupled system. From the perspective of empirical analysis, identify the interaction relationship between factors, determine the key factors affecting “water resources, economic society and ecological environment”, and provide a theoretical basis for future scientific and efficient research on the synergistic development of water resources, economic society and ecological environment system.

Therefore, this study will sort out the system of factors influencing the synergistic development of water resources, economy-society and ecological environment(WEE) through expert interviews and literature research, study the structure and internal connection between the influencing factors by using the Delphi method and the DEMATEL-ISM-MICMAC method, and analyze the interactions and relationships between the factors, and identify the key factors influencing the synergistic development of WEE. Provide a theoretical basis for future scientific and efficient research on the WEE couple systems.

Materials and methods

Study area

Central Plains Urban Agglomeration(CPUA) (33°08′-36° 02 ′N, 111°08′-115° 15 ′E) is situated in the central and eastern regions of China, encompassing the middle and lower reaches of the Yellow River, including 18 prefectures and cities in Henan Province, Changzhi, Jincheng and Yuncheng in Shanxi Province, Xingtai and Handan in Hebei Province, Liaocheng and Heze in Shandong Province, Huaibei, Bengbu, Suzhou, Fuyang and Bozhou in Anhui Province, totaling 30 cities (Fig. 1). The CPUA is not only related to the high-quality economic growth of the central region, but also plays a linking role in the industrial upgrading of the eastern region and the economic development of the western region. However, the CPUA within the development of regional differentiation is obvious, the conditions of water resources endowment is poor, the amount of water resources is in serious shortage, the time distribution is extremely uneven, the contradiction between supply and demand is prominent. A series of environmental pollution problems triggered by urbanization and industrialization have made the region face the great test of balancing economic development and ecological environment protection.

Fig. 1.

Central plains urban agglomeration study area.

In the questionnaire stage, 15 experts and scholars in different fields were selected as respondents and the results were analyzed for reliability. The data on water resources and the ecological environment are get from regional water resources bulletins (http://www.mwr.gov.cn/sj/tjgb/szygb/)and surveys; the economic and social data are obtained from regional statistical bulletins on national economic and social development (https://www.henan.gov.cn/zwgk/zfxxgk/fdzdgknr/tjxx/tjgb/).

Index system construction

This study combines expert interviews and literature research to select 35 influencing factors (as shown in Table 1) from three dimensions to analyze the key influencing factors of coordinated development of WEE.

Table 1.

System of indicators of impact factors.

Water resources		Economy and society		Ecological environment
a1	Total water resources6,28,36	b1	GDP per capita33	c1	Percentage of ecological water39
a2	Water resources per capita39	b2	Total population6,28,36	c2	Wastewater discharge of industrial output value of 10,000 yuan6,28,34,36
a3	Precipitation39	b3	Urbanization rate39	c3	Soil erosion treatment area39
a4	Percentage of groundwater supply	b4	Percentage of investment in water supply and drainage6,28,36	c4	Green coverage rate of built-up areas34,37
a5	Water use per capita29	b5	Total grain output	c5	NDVI39
a6	Domestic water intensity30	b6	Percentage of tertiary industry value added34	c6	Sewage treatment rate6,28,34,36
a7	Total water supply30	b7	Number of students enrolled in general higher education per 10,000 population21,35	c7	Harmless treatment rate of domestic garbage33,37
a8	Specific yield31	b8	Urban resident disposable income39	c8	Mean concentration of respirable particulate matter38
a9	Coefficient of storage31	b9	Urban road area per capita6,28,36	c9	Industrial SO2 removal rate6,28,34,36
a10	Average water consumption per mu for farmland irrigation30	b10	Population density34
a11	Water consumption per 10,000 yuan industrial added value30	b11	Health facility beds per 10,000 population39
a12	Citation to transit water39	b12	Energy consumption of 10,000 yuan of GDP6,28,36,38
a13	Water resource utilization rate32
a14	Aridity index30

Methods

Synergistic development of WEE coupling system is a hot research topic at present, but the internal relationship between its influencing factors has not been fully studied and needs further exploration. Delphi method is also called expert opinion method, which can give full play to experts ‘advantages and gather experts’ wisdom, so that the selected factors have certain credibility²². Delphi method was used to select representative experts to form scientific and reasonable expert advisory group. Experts were then invited to rate the impact of each factor on the WEE coupling system. DEMATEL-ISM-MICMAC method was used to identify the key factors, and the synergistic development relationship among water resources, economic society and ecological environment was analyzed through coupling coordination degree.

DEMATEL-ISM-MICMAC Method

Decision-Making Trial and Evaluation Laboratory (DEMATEL) is a methodology that leverages graph theory and matrix methods to elucidate the relationships between factors in intricate systems and evaluate the relative significance of each factor²³. Interpretive Structural Modeling Method (ISM) can sort out the hierarchical structure of complex systems, so that the logical structure relationship of each influencing factor can be clearly displayed in a hierarchical structure diagram²⁴. Matrix Impacts Cross-reference Multiplication Applied to a Classification (MICMAC) is a methodology that uses the driving-dependence matrix to divide factors into self-consistent factors, dependent factors, associated factors and independent factors to elucidate the critical function of each component within the system²⁵. In this study, we will first use the DEMATEL method to analyze the interaction of factors affecting the synergistic development of WEE coupling system. ISM method was used to establish the layered structure of influencing factors. Finally, MICMAC method was used to determine which factors had the greatest driving force and dependence. The flowchart is shown in Fig. 2.

Fig. 2.

Methodology flowchart.

The specific steps are as follows:

Step 1 19 experts, including experts, scholars and relevant researchers in water resources and ecology, were invited to score the mutual influence relationship among indicators according to their understanding of the three-dimensional frameworks and the symbolic meaning of indicators. Specific scores are: 0 represents no impact, 1 represents a low impact, 2 represents a medium impact, 3 represents a high impact, and 4 represents an extremely high impact.

Step 2 Collect questionnaire data, calculate average value, and construct initial direct impact matrix A.

1

where n is the number of influencing factors, indicating the degree of influence of factor i on factor j, diagonal indicates the influence of a factor on itself, and all values are 0.

Step 3 Compute normalized direct impact matrix N and synthetic impact matrix T²³

2

3

4

where E is the identity matrix.

Step 4 Calculate centrality (Z_i) and causation (D_i)²³.

5

6

7

8

where r_i denotes the degree of influence of factor i, the sum of the degrees of direct or indirect influence, the sum of the degree to which it directly or indirectly influences other factors, and c_i denotes the degree to which factor i is influence, the sum of the degree to which it is influenced by other factors.

Step 5 Constructing adjacency matrix and reachability matrix M²⁴.

9

10

where is used to eliminate some factors with small influence and is determined by debugging all values in the comprehensive influence matrix.

Step 6 According to the reachability matrix M, calculate , ²⁴.

11

12

13

14

15

Step 7 According to the hierarchical classification criteria, it is the first level, then delete the used elements and repeat the classification according to the until all elements are classified into different hierarchical levels, resulting in a multi-level ISM model.

Step 8 Calculate driving force (Qi) and dependence (Yi). Driving force indicates the degree of influence on other factors, and dependence indicates the degree of influence by other factors²⁵.

16

17

Among them, high driving force and high dependence factors belong to correlation factors; low driving force and high dependence factors belong to dependence factors; low driving force and low dependence factors belong to self-consistent factors; high driving force and low dependence factors belong to independent factors.

Step 9 Plot driving forces and dependencies in quadrant diagrams to visually represent relationships between factors.

Coupled coordinated development model

Different indexes have different influence on the system. This research utilizes the entropy method to assign weights to the index system. Its calculation is publicized as follows²⁶:

18

19

where: is the information entropy; is the proportion of the j index in the i year; is the index weight.

According to the index system of WEE, the comprehensive evaluation index of WEE is constructed, namely:

20

where: is the water resources system development index; is the weight value of each index of the water resources system; is the standardized value of each index of the water resources system in the i year; k is the number of indicators of the water resources system.

21

where: is the development index of economic and social system; is the weight value of each indicator of economic and social system; is the standardized value of each indicator of economic and social system in the i year; g is the number of indicators of economic and social system.

22

where: is the development index of ecological environment system; is the weight value of each index of ecological environment system; is the standardized value of each index of ecological environment in the i year; q is the number of indicators of ecological environment system.

According to the coupling concept in physics, WEE is regarded as the coupling systems, and the extent of coupling and the level of coordination between these three systems are assessed, which can objectively reflect the coordinated development of the systems²⁷. The coupling model is:

23

where C is the degree of coupling,. When C = 0, it indicates that the system develops into disorder state, and when C = 1, it indicates that the three systems are in the optimal coupling state.

Coupling degree can only reflect the interaction degree of the three systems, but cannot explain their coordinated development level. Thus, a coupling coordination degree model is applied to provide an objective measure of the integrated advancement among the three systems.

24

where D is the degree of coordination,.

Results

Calculation of centrality and causality of influencing factors based on DEMATEL

To guarantee the accuracy and dependability of the survey findings, SPSS software is used to test the reliability of experts’ opinions, and the Cronbach’s is 0.859, which is greater than 0.80. The reliability of the survey results is high.

The initial direct impact matrix A is obtained by calculating the average of the scoring results. According to formulas (2), (3) and (4), the comprehensive influence matrix T is obtained. The influence degree, affected degree, centre degree and cause degree calculated according to Formula (5) – Formula (8) are shown in Table 2. The scatter plot of centrality-causation of each factor is shown in Fig. 3. Factors with cause degrees greater than 0 are identified as driving factors, whereas those with cause degrees less than 0 are considered outcome factors. The higher the centrality, the more critical the factor is in the coupling system; a higher causation indicates a more significant influence of that factor on other factors.

Table 2.

Centrality and causes of factors affecting synergistic development.

	Variables	Influence degree(ri)	Affected degree(ci)	Centre degree(Zi)	Cause degree(Di)	Type
Water resources	Total water resources(a1)	3.054	1.587	4.641	1.468	Causal factor
	Water resources per capita (a2)	2.352	2.163	4.515	0.189	Causal factor
	Precipitation (a3)	3.128	1.392	4.52	1.736	Causal factor
	Percentage of groundwater supply (a4)	2.016	2.139	4.155	-0.122	result factors
	Water use per capita (a5)	2.143	1.906	4.049	0.237	Causal factor
	Domestic water intensity (a6)	2.053	1.956	4.009	0.098	Causal factor
	Total water supply (a7)	1.987	2.132	4.119	-0.146	result factors
	Specific Yield (a8)	1.421	1.158	2.579	0.263	Causal factor
	Coefficient of Storage (a9)	1.369	1.058	2.427	0.311	Causal factor
	Average water consumption per mu for farmland irrigation (a10)	2.133	1.783	3.916	0.35	Causal factor
	Water consumption per 10,000-yuan industrial added value (a11)	2.085	1.868	3.953	0.217	Causal factor
	Citation to transit water (a12)	2.316	2.319	4.635	-0.003	result factors
	Water resource utilization rate (a13)	2.481	2.303	4.784	0.178	Causal factor
	Aridity index (a14)	1.472	1.434	2.905	0.038	Causal factor
Economy and society	GDP per capita (b1)	2.379	2.802	5.181	-0.423	result factors
	Total population (b2)	2.958	2.394	5.352	0.564	Causal factor
	Urbanization rate (b3)	3.064	3.163	6.226	-0.099	result factors
	Percentage of investment in water supply and drainage (b4)	2.676	2.953	5.629	-0.277	result factors
	Total grain output (b5)	1.926	3.205	5.13	-1.279	result factors
	Percentage of tertiary industry value added (b6)	2.255	2.549	4.804	-0.294	result factors
	Number of students enrolled in general higher education per 10,000 population (b7)	1.889	2.155	4.043	-0.266	result factors
	Urban resident disposable income (b8)	2.713	2.47	5.182	0.243	Causal factor
	Urban road area per capita (b9)	2.053	2.161	4.213	-0.108	result factors
	population density (b10)	2.771	2.789	5.56	-0.019	result factors
	Health facility beds per 10,000 population (b11)	1.541	1.879	3.42	-0.338	result factors
	Energy consumption of 10,000 yuan of GDP (b12)	1.82	2.263	4.083	-0.442	result factors
Ecological environment	Percentage of ecological water (c1)	1.902	2.623	4.524	-0.721	result factors
	Wastewater discharge of industrial output value of 10,000 yuan (c2)	1.836	2.034	3.87	-0.198	result factors
	Soil erosion treatment area (c3)	2.493	2.794	5.287	-0.3	result factors
	Green coverage rate of built-up areas (c4)	2.494	2.617	5.112	-0.123	result factors
	NDVI (c5)	2.318	2.239	4.558	0.079	Causal factor
	Sewage treatment rate (c6)	2.109	2.623	4.732	-0.513	result factors
	Harmless treatment rate of domestic garbage (c7)	2.037	2.194	4.231	-0.157	result factors
	Mean concentration of respirable particulate matter (c8)	1.256	1.477	2.733	-0.22	result factors
	Industrial SO2 removal rate (c9)	1.226	1.149	2.375	0.077	Causal factor

Fig. 3.

The scatter plot of centrality-causation of each factor.

From Table 2 and Fig. 3, the evidence shows that water resources are mostly the cause factors, and economic social factors and ecological environment systems are mostly the result factors. The top five factors of centrality are urbanization rate (b3), percentage of investment in water supply and drainage (b4), population density (b10), total population (b2) and Soil erosion treatment area (c3), showing that these five factors are at the core of the index system. The top five factors of course degree is precipitation (a3), total water resources (a1), total population (b2), average water consumption per mu of farmland irrigation (a10) and coefficient of storage (a9), demonstrating that these five factors have the strongest impact on the remaining factors. Among them, the centrality and cause of a degree of the total population are the highest, which indicates that it has strong restriction and driving, and is the most critical factor in the whole system.

Hierarchical classification of influencing factors based on ISM

After repeated debugging and calculation, determine the threshold value , construct the adjacency matrix according to formula (9), and calculate the reachable matrix M according to formula (10).

According to the reachability matrix M and formulas (11) – (15), the results of the first hierarchical processing of “water resources-economic society-ecosystem” are shown in Table 3, and ISM hierarchical division model is drawn according to the hierarchical division results as shown in Fig. 4.

Table 3.

Reachable set, antecedent set and common set.

Si	R(Si)	A(Sj)	C(Si)
1	1,2,4,5,6,7,12,13,15,16,17,18,19,20,21,22,23,24,26,27,29,30,32,33,36	1	1
2	2,36	1,2,3,12,13,15,16,17,18,20,22,23,24,29,30,31	2
3	2,3,4,5,6,12,13,15,16,17,18,19,20,21,22,23,24,27,29,30,32,33,36	3	3
4	4,36	1,3,4	4
5	5,36	1,3,5,12,13,15,16,17,18,20,22,23,24,29,30,31	5
6	6,36	1,3,6,12,13,15,16,17,18,20,22,23,24,29,30,31	6
7	7,36	1,7	7
8	8,36	8	8
9	9,36	9	9
10	10,19,36	10	10
11	11,36	11	11
12	2,5,6,12,15,16,17,18,19,20,21,22,23,24,27,29,30,32,33,36	1,3,12,13,15,16,17,18,20,22,23,24,29,30,31	12,15,16,17,18,20,22,23,24,29,30
13	2,5,6,12,13,15,16,17,18,19,20,21,22,23,24,27,29,30,32,33,36	1,3,13	13
14	14,36	14	14
15	2,5,6,12,15,16,17,18,19,20,21,22,23,24,27,29,30,32,33,36	1,3,12,13,15,16,17,18,20,22,23,24,29,30,31	12,15,16,17,18,20,22,23,24,29,30
16	2,5,6,12,15,16,17,18,19,20,21,22,23,24,27,29,30,32,33,36	1,3,12,13,15,16,17,18,20,22,23,24,29,30,31	12,15,16,17,18,20,22,23,24,29,30
17	2,5,6,12,15,16,17,18,19,20,21,22,23,24,27,29,30,32,33,36	1,3,12,13,15,16,17,18,20,22,23,24,29,30,31	12,15,16,17,18,20,22,23,24,29,30
18	2,5,6,12,15,16,17,18,19,20,21,22,23,24,27,29,30,32,33,36	1,3,12,13,15,16,17,18,20,22,23,24,29,30,31	12,15,16,17,18,20,22,23,24,29,30
19	19,36	1,3,10,12,13,15,16,17,18,19,20,22,23,24,29,30,31	19
20	2,5,6,12,15,16,17,18,19,20,21,22,23,24,27,29,30,32,33,36	1,3,12,13,15,16,17,18,20,22,23,24,29,30,31	12,15,16,17,18,20,22,23,24,29,30
21	21,36	1,3,12,13,15,16,17,18,20,21,22,23,24,29,30,31	21
22	2,5,6,12,15,16,17,18,19,20,21,22,23,24,27,29,30,32,33,36	1,3,12,13,15,16,17,18,20,22,23,24,29,30,31	12,15,16,17,18,20,22,23,24,29,30
23	2,5,6,12,15,16,17,18,19,20,21,22,23,24,27,29,30,32,33,36	1,3,12,13,15,16,17,18,20,22,23,24,29,30,31	12,15,16,17,18,20,22,23,24,29,30
24	2,5,6,12,15,16,17,18,19,20,21,22,23,24,27,29,30,32,33,36	1,3,12,13,15,16,17,18,20,22,23,24,29,30,31	12,15,16,17,18,20,22,23,24,29,30
25	25,36	25	25
26	26,36	1,26	26
27	27,36	1,3,12,13,15,16,17,18,20,22,23,24,27,29,30,31	27
28	28,36	28	28
29	2,5,6,12,15,16,17,18,19,20,21,22,23,24,27,29,30,32,33,36	1,3,12,13,15,16,17,18,20,22,23,24,29,30,31	12,15,16,17,18,20,22,23,24,29,30
30	2,5,6,12,15,16,17,18,19,20,21,22,23,24,27,29,30,32,33,36	1,3,12,13,15,16,17,18,20,22,23,24,29,30,31	12,15,16,17,18,20,22,23,24,29,30
31	2,5,6,12,15,16,17,18,19,20,21,22,23,24,27,29,30,31,32,33,36	31	31
32	32,36	1,3,12,13,15,16,17,18,20,22,23,24,29,30,31,32	32
33	33,36	1,3,12,13,15,16,17,18,20,22,23,24,29,30,31,33	33
34	34,36	34	34
35	35,36	35	35
36	36	1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36	36

S36 refers to the coordinated development goal of "water resources-economic society-ecological environment".

Fig. 4.

Hierarchical structure of influencing factors.

As shown in Fig. 4, the foundational elements of the coupling system comprising WEE include total water resources, precipitation, specific yield, coefficient of storage, average water consumption per mu for farmland irrigation, water consumption per 10,000 yuan industrial added value, aridity index, health facility beds per 10,000 population, wastewater discharge of industrial output value of 10,000 yuan, NDVI, mean concentration of respirable particulate matter and industrial SO₂ removal rate. These indexes have numerous influences on the harmonious progression of the coupling system, while they themselves remain largely unaffected by other factors. As the basic factors, total water resources and precipitation have a strong influence on almost all indexes related to economy society and ecological environment in the coupling system of WEE.

The fourth layer is the deep factors, including the percentage of groundwater supply, total water supply, water resource utilization rate and energy consumption of 10,000 yuan of GDP. Among them, energy consumption of 10,000 yuan of GDP is an indicator closely related to resources in the “economic society” system. This layer transfers the influence of total water resources and rainfall to the third layer.

The third layer is transitional factors, including citation to transit water, GDP per capita, total population, urbanization rate, percentage of investment in water supply and drainage, percentage of tertiary industry value added, urban resident disposable income, urban road area per capita, population density, soil erosion treatment area and green coverage rate of built-up area. These factors rely on the performance and changes of deep-level factors, and transmit the influence of bottom-level factors upward to surface-level factors through a ladder relationship. These factors exhibit significant interplay with other components in the complex system.

The other factors are surface factors, including water resources per capita, water use per capita, domestic water intensity, total grain output, number of students enrolled in general higher education per 10,000 population, percentage of ecological water, sewage treatment rate and harmless treatment rate of domestic garbage. Factors directly affect the harmonious progression of the coupling system of WEE. They are the most direct influencing factors. They are also affected by bottom, deep and transitional factors. The controllability is the strongest. Among them, the total grain output is also limited by the average water consumption per mu of farmland irrigation.

MICMAC analysis of WEE coupling system

According to the accessibility matrix M and formulas (16) and (17), calculate the driving force and dependence degree of each influencing factor, and the results are shown in Table 4.

Table 4.

Dependence and driving forces of infuencing factors.

Factors	Driving force (Qi)	Dependence (Yi)	Factors	Driving force (Qi)	Dependence (Yi)	Factors	Driving force(Qi)	Dependence(Yi)
a1	24	1	a13	20	3	b11	1	1
a2	1	16	a14	1	1	b12	1	2
a3	22	1	b1	19	15	c1	1	16
a4	1	3	b2	19	15	c2	1	1
a5	1	16	b3	19	15	c3	19	15
a6	1	16	b4	19	15	c4	19	15
a7	1	2	b5	1	17	c5	20	1
a8	1	1	b6	19	15	c6	1	16
a9	1	1	b7	1	16	c7	1	16
a10	2	1	b8	19	15	c8	1	1
a11	1	1	b9	19	15	c9	1	1
a12	19	15	b10	19	15

Figure 5 shows the driving force-dependency matrix. As can be seen from Table 4 and Fig. 5, total water resources, precipitation, water resource utilization rate and NDVI are independent factors with high driving force and low dependence, and have a great influence on other factors. Among them, the total driving force of total water resources is the highest and the dependence degree is the lowest. In the harmonious progression of the coupling system, water resources protection should be paid special attention. Citation to transit water, GDP per capita, total population, urbanization rate, percentage of investment in water supply and drainage, percentage of tertiary industry value added, urban resident disposable income, urban road area per capita, population density, soil erosion treatment area, green coverage rate of built-up area are cited as correlation factors, which are poor in stability, strong driving force and dependence, belonging to transitional factors in ISM, and acting on WEE through influencing surface factors. Water resources per capita, water use per capita, domestic water intensity, total grain output, number of students enrolled in general higher education per 10,000 population, percentage of ecological water, sewage treatment rate and harmless treatment rate of domestic garbage have the lowest driving force and high dependence degree, which belong to dependent factors, indicating that other factors should be started to improve these indicators. Other factors belong to self-consistent factors, which belong to the bottom factors and deep factors in the ISM model. Their minimal driving force and reliance suggest that self-consistent factors operate with a notable degree of autonomy from the system. And their relationship with other factors in the system is weak, which belongs to lagging development type indicators.

Fig. 5.

Attribute classifcation diagram of infuencing factors.

To sum up, the influencing factors of the harmonious progression of WEE can be constructed into a five-level hierarchical structure, which can be divided into four categories: independent factors, associated factors, dependent factors and self-consistent factors. Combined with the centrality of the influencing factors and the size of the driving force, the role of the influencing factors can be visually reflected in the hierarchical structure for easy observation. In the bottom layer factors, total water resources, NDVI and precipitation centrality are stronger, and driving force is higher as the most fundamental factors. Among them, precipitation and total water resources have higher cause degree, which indicates that they have greater influence on other factors. Among the surface factors, the centrality of total grain output is the highest, and it plays the most critical role in the system. The absolute value of the cause of percentage of ecological water is the highest, which is an important result factor characterizing the ecosystem. The cause degree of water use per capita is the highest, which exerts a more significant direct influence on the system. The driving force of water resources per capita is the largest, so these three factors are the most direct factors. The urbanization rate and population density rank high to influence and being influenced, with a high degree of centrality and a strong driving force, making these two factors important transition factors.

Example analysis

From the preceding analysis, we selects the total water resources, precipitation, water use per capita and water resources per capita in the water resources system; urbanization rate, total grain output, population density and the percentage of tertiary industry value added in the economic and social system; percentage of ecological water and NDVI in the ecological environment system. The harmonious progression of WEE in CPUA from 2011 to 2020 is analyzed by using the system comprehensive development evaluation index, as shown in Fig. 6.

Fig. 6.

2011–2020 System coupling harmonization.

Through the analysis of the CPUA, we found that the key influencing factors we identified can well analyze the changes in the harmonious progression of water resources, economic and social, and ecological systems from 2011 to 2020. Figure 6 shows the overall trend of WEE system coupling coordination in CPUA. During the study period, the coupling coordination increased from a low of 0.324 in 2011 to a high of 0.978 in 2020. In some years, the coupling degree and the coupling coordination degree are quite different because the coupling degree describes the interaction degree between the systems, while the coupling coordination degree considers the holistic development level within the system based on the coupling degree and emphasizes the synergistic overall effect among the various parts within the system. For example, in 2012, although the indicator gap between the three systems narrowed, the overall coordination status was still at a low level because it was in the early stage of development. Different from the existing research, the system coupling coordination degree appears inflection point in 2019, the overall index of water resources system decreases obviously, and the system coupling degree and coordination degree decrease obviously. It is observed that the primary factor hindering the harmonious progression of WEE system in CPUA is the unbalanced development among the three systems, among which the old problems of water resources system need to be solved, and the new issues such as water scarcity, ecological damage and pollution to water systems become more and more prominent and urgent. Therefore, the healthy development of water resources system is crucial for the coupling system of CPUA. In 2020, the CPUA has made significant breakthroughs in water resources and ecological environment protection, and the water ecological conditions of most cities have been significantly improved, realizing benign interaction between ecological and economic development. Among the three subsystems, the water resources system is restricted by natural conditions, the development status is the most unstable, the coupling degree of the system fluctuates to a certain extent because of the disturbance of the water resources system, the economic society and ecological environment show a significant growth trend, and the water resources system is still the key to harmonious progression.

Discussion

Based on the systematic view, this paper divides the influencing factors of the harmonious progression of WEE into three dimensions. According to each subsystem, and further explores the influencing factors of the harmonious progression of WEE by using DEMATEL-ISM-MICMAC method and taking the CPUA as an example. It can provide more pertinent reference for government departments to formulate policies to promote the harmonious progression of WEE.

Water resource factors are mostly causative factors, socio-economic factors and ecological environment system are mostly outcome factors. Water resources system has increasingly become the dominant factor limiting the harmonious progression of WEE. This is consistent with Zhu’s findings³⁹. Water resources are the basic foundation of city growth and acting as the vital connection between the economy, society, and the ecological environment. Considering the multi-level structural model, the surface factors directly promote the harmonious progression of WEE and are affected by various factors. These factors are mainly related to the level of social development and environmental governance capacity, because achieving high-quality economic development requires not just an ample supply of water resources, but also the maintenance of robust and healthy ecosystems⁴⁰. The transition factors are mainly economic and social systems, because the improvement of urbanization level is conducive to promoting the implementation and effective progress of water conservation and environmental protection policies, and further affecting the sustainable development of coupled systems⁴¹.The deep factors are the factors that characterize resource dependence, while the bottom factors are mainly water resources system and ecological environment system factors. This indicates that in the WEE system, resources and ecological environment factors are essential, because the present socio-economic continues to be heavily dependent on the depletion of natural resources and the encroachment on the ecological environment⁴².

It is found that the total water resources is the most fundamental factor. They are the basic material condition to maintain the stability of society, economy and ecosystem, and supply essential raw materials for production and life for social and economic development⁴³. At present, numerous scholars study the change of total water resources and how to improve the resilience from various angles. Scanlon’s review of existing literature shows that human activities influence total water resources in two primary ways: directly via water usage and indirectly through land-use alterations, such as agriculture and urban expansion.⁴⁴. However, in this study, total water resources are an indispensable key factor in resident production and life, economic development and ecosystem stability, and occupy a central position in coping with climate change and social and economic development. Total water resources affect the coupling system of WEE by affecting water resources per capita, water use per capita, urbanization rate, total grain output and NDVI. In the ISM model of this study, precipitation and NDVI belong to the same hierarchy and interact and couple with each other. This is consistent with the results of the study. Precipitation is one of the main ways of water supply, forest transformation and landscape pattern optimization make vegetation index increase, ecological environment has been restored⁴⁵. Ecosystems are vital for bolstering the resilience of water resources and managing waste produced by development, thereby sustaining the overall stability of the system⁴⁶. Related studies have found that precipitation is the main meteorological control factor affecting the change of vegetation index, and the increase of rainfall will also lead to the increase of normalized vegetation index⁴⁷.

At various stages, social and economic development can exert both beneficial and detrimental effects on water resources and ecosystems⁴⁸. On the positive side, economic and social progress offers the crucial technological tools and material infrastructure needed for the development and exploitation of resources and the environment.⁴⁹; On the negative side, rapid development will lead to prominent contradictions between water supply and demand, and the ecological environment will be seriously threatened⁵⁰. Urbanization rate matters in economy and society. It is in a transition layer in the whole system and affects other system. Xu et al.⁵¹ similar to the study, urbanization leads to the expansion of construction land and the decline of ecosystem services in urban–rural transition areas. The acceleration of urbanization has also had a greater impact on the regional natural environment and industrial economic development⁵². There is no similar literature on the impact of total grain output. However, studies have found that apple marketing stimulates large-scale expansion of orchard land and increases groundwater and surface water withdrawals to meet irrigation needs in agricultural areas⁵³. These changes have led to a significant reduction in regional water resources. In addition, the government will promote economic development by increasing agricultural production. More production requires more arable land and more water intake. The expansion of arable land to ensure food security is at the expense of grassland encroachment⁵⁴. In the economic society, the talent policy attracts high-quality population, which brings about the improvement of innovation ability and changes the production mode and other methods to act on water resources, economic society and ecological environment. Zameer et al.⁵⁵ thinks the role of cleaner production technology was emphasized. The government and enterprises optimize the industrial structure through capital allocation, rationally allocate funds, and improve ecological efficiency⁵⁶. The percentage of tertiary industry value added chosen in this paper is a transitional layer factor, which indicates the degree of industrial transformation. With the further development of the economy, it is believed that the vegetation state and ecological environment are better because of the rapid transformation and upgrading of industrial structure, and the tertiary industry has become the focus of economic development⁵⁷. Through the study of policy impact, it is found that although the industrial structure dominated by tertiary industry accounts for a small proportion,it significantly enhances ecological efficiency⁵⁸. The government implements policies and regulations aimed at high energy-consuming, highly polluting, and low-efficiency industries. These measures are designed to guide enterprises in upgrading or transforming their technologies, thereby effectively reducing resource consumption and mitigating environmental pollution.

The analysis of the Central Plains Urban Agglomeration reveals an overall positive trend in the coupling and harmonization of the “water resources-economy-economy-ecology” system from 2011 to 2020. This is consistent with the reality of urban development. The inflection point of the system coupling coordination degree in 2019 is shown in Fig. 6, which shows that the comprehensive development index of the water resources system decreases. In 2019, the Central Plains Urban Agglomeration suffered from severe water logging because of the impact of heavy rainfall, which led to a threat to the water resources system⁵⁹. Compared with existing studies, the influencing factors we identified show the water resources system changes through the comprehensive development index, which can be more detailed to find the fluctuation of the water resources system in the Central Plains Urban Agglomeration in the overall positive trend.

In this study, we not only analyze the key factors affecting the harmonious progression of WEE, but also reveal the complex relationship between them. By establishing multi-layer model, the relationship between deep factors and surface factors is clearly presented, and the hierarchical relationship of these factors is vividly explained. Based on the existing research, this study analyzed the key factors and paths affecting the coordinated development of water resources, economy, society and ecological environment. This research provides new insights for sustainable development of water resources, economic and ecological environmen. More importantly, identifying these influencing factors lays the groundwork for informed decision-making by policymakers and practitioners to assist in making more rational policy and strategic decisions. There are some limitations to this paper. First, this study takes the Central Plains urban agglomeration as the study area for expert interviews. Therefore, this study does not fully consider the impact of heterogeneity of the ecological environment and economic society in different countries and regions on sustainable development. Future research should consider the different development plans of different regions when selecting influencing factors, and reveal the driving factors of coordinated development of WEE and their changes under different scenarios.

Conclusion

This paper uses the DEMATEL-ISM-MICMAC combination model to study the key factors affecting the coordinated development of WEE by taking the CPUA as an example. The conclusions are as follows:

1. Total water resources, precipitation and total population are important cause factors, while total grain output, percentage of ecological water and sewage treatment rate are important result factors. Water resources system factors are mostly causative factors, socio-economic systems and ecological environment systems are mostly outcome factors. Among them, the driving force and dependence degree of economic and social system factors are strong, which are not only affected by other factors but also have a strong influence on other factors.

2. The influence factor system of WEE is composed of four levels, among which, the total water resources, precipitation and NDVI are at the bottom, and their driving forces are strong, which are the basic factors of the coupling system. Percentage of groundwater supply, total water supply, water resource utilization rate and energy consumption of 10,000 yuan of GDP are deep-seated factors, among which water resource utilization rate is highly dependent and should be treated as special factors. The driving force and dependence degree of transition layer factors are strong, and the surface layer factors are directly affected by the joint effect of the transition layer, among which the total grain output, water resources per capita and water use per capita are the direct factors.

3. In the CPUA, water resources system is still the key to coordinated development. The water resources system is restricted by natural conditions, the development status is the most unstable, the system coupling degree fluctuates to a certain extent because of the disturbance of the water resources system, the economic society and ecological environment show a significant growth trend, and the water resources system is pivotal for ensuring the coordinated development.

Building on the above research findings, the following countermeasures and suggestions are proposed: (1) to formulate comprehensive water resources management strategy, optimize water resources allocation, strengthen water resources monitoring and early warning system, ensure sustainable utilization and protection of water resources, and timely respond to water resources changes and challenges in dry season. (2) Consider the capacity and quality of water supply in the process of urbanization, promote urban rainwater utilization and water resource recycling, reduce over-exploitation of surface and groundwater resources, and ensure the safety and sustainability of urban water use. (3) Promote water-saving irrigation technology and efficient agricultural production mode, strengthen the combination of science and technology and management, establish digital management platform, and realize refined and intelligent management. (4) In order to increase food production and guarantee food security, it is recommended that the process of agricultural modernization be accelerated, including the improvement of the application of agricultural science and technology, the improvement of irrigation systems, and the increased use of agricultural machinery, etc., in order to increase production per unit area and to cope with the pressures brought about by population growth. (5) Based on the improvement of the water environment, further enhance the systematic, holistic and synergistic nature of ecological protection and governance, with the protection and restoration of water ecology as the core, giving full consideration to the basic ecological water needs, and maintaining the healthy ecology of rivers and lakes.

Author contributions

Conceptualization, writing—original draft, S.R.; writing—review and editing, P.L,H.Z..; funding acquisition, supervision, F.W.,H.Z(zhaoheng); investigation, supervision, L.C. All authors have read and agreed to the published version of the manuscript. The authors would like to express their sincere gratitude to the anonymous reviewers for their constructive comments and useful suggestions that helped us improve this study.

Funding

The project was financially supported by the National Natural Science Foundation of the People’s Republic of China (U2443203, 52279014), Major agricultural science and technology projects (NK202319020506).

Data availability

Data sets generated during the current study are available from the corresponding author on reasonable request.

Declarations

Competing interests

The authors declare no competing interests.