Introduction

The 19th report of the Communist Party of China advocates adhering to the essential national policy of conserving resources and protecting the environment. It emphasizes the principle that green mountains are golden mountains, and it advocates for a path of civilized development that harmonizes production, affluent living, and ecological well-being. This guidance holds extraordinary significance for the Yellow River Basin, a region of great strategic importance. When the framework of the social-ecological system is examined, the Yellow River Basin forms a vast and complex organic social-ecological whole. Under this framework, society encompasses numerous elements, such as population growth, economic development, and structural social changes within the basin1. Among these systems, the booming tourism industry serves as a crucial driving force for the social economy. Humans carry out various production and living activities that rely on the unique ecological environment of the Yellow River Basin, from the earliest agricultural irrigation to the contemporary large-scale tourism development, which constantly transforms and utilizes nature. From the perspective of the human–land relationship, the ecological environment, as a key part of “land”, in turn, restricts or promotes the human social economy and the tourism industry2. In developing the economy and tourism, we must embrace sustainable development, which prioritizes ecological protection and balances the relationship between humans and nature. With a focus on superior ecological settings and distinctive cultural ecology, the aim is to provide enriching experiences that are visually appealing and intellectually satisfying, thereby fostering the symbiotic advancement of tourism, the regional economy, and ecological integrity. The unified development of tourism, the regional economy, and the ecological environment is therefore crucial3,4. The tourism industry has unique attributes that distinguish it from general socioeconomic industries. The non-transferability of resources, the seasonality of consumption, and the high sensitivity of the industry to the environment limit the coverage of the tourism industry by the traditional socioeconomic framework5. Therefore, separately examining the tourism industry can help us understand its interaction with other systems more accurately and can lay the foundation for formulating targeted strategies. With the rapid growth of the tourism economy, China’s domestic tourism sector is expanding and increasingly becoming a strategic cornerstone of socioeconomic development. However, alongside substantial social and economic benefits, the tourism industry and broader socioeconomic progress have triggered ecological challenges, including ecological landscape degradation, environmental pollution, and significant biodiversity loss6,7. These issues hinder the harmonious development of human activities with natural systems and impose constraints on the sustainable growth of both the social economy and the tourism industry. The interaction mechanism among the social economy, the ecological environment, and the tourism industry is illustrated in Fig. 1. Understanding and aligning the relationships among these sectors is vital for attaining high-quality, sustainable regional economic and social growth8. The term "high-quality development" describes the basic feature of China’s economic development in the new era9. This term mainly refers to the high-quality development of the economy, while ecological protection indicates an improvement in the quality of the ecological environment10. There are close connections among the high-quality development of the social economy, the ecological environment and the tourism industry. The coordinated development of these three aspects has great significance11,12,13. The development of the economic, ecological, and tourism systems in the Yellow River Basin has been upgraded to a major national strategy, and exploring the analysis and trend prediction of the coordinated development of the these systems in the Yellow River Basin is highly important14.

Fig. 1
figure 1

Mechanism of socio-economic-ecological environment-tourism industry interactions.

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In recent years, with the process of modernization, the economic, ecological, and tourism systems have undergone rapid development in many places. The coordinated development of various regions and industries has also attracted the attention of many people. In particular, in the Yangtze River Delta (YRD) region, the coordinated development of socioeconomics, the ecological environment and the tourism industry has received considerable attention. Zhang Hong and others studied the spatiotemporal evolution and its influencing factors in the social economy, the ecological environment and the tourism industry in the central cities of the YRD region through the spatial econometric analysis of panel data. They noted that there is a certain mismatch among the tourism industry, regional economy and ecological environment in the Yangtze River Economic Belt region and that coordinated development needs to be further strengthened15. Xiang Li and others studied this topic from the perspective of spatiotemporal differentiation and concluded that the degree of coordinated development of the social economy, the ecological environment and the tourism industry in the central cities of the YRD region is relatively high16,17. With the gradual increase in the number of studies on tourism development and ecological environment protection in the Yellow River Basin, aspects of tourism eco-efficiency, the green development of the tourism industry, and the tourism eco-network have increased4,6,18,19. However, few comprehensive analyses and prediction studies have focused on the level of coordinated development of the socioeconomic-ecological environment-tourism coupling in the Yellow River Basin. Mu Xueqing et al. identified and detected the spatial and temporal dynamics of tourism eco-efficiency in the Yellow River Basin and reported that tourism eco-efficiency varies spatially and temporally and that the driving factors include mainly tourism investment, the quality of the ecological environment, and the level of regional economic development7. In research on the relationships among the tourism industry, the regional economy and the ecological environment, a certain coordination relationship exists in the coupling coordination, but there is also the problem of unbalanced development20. Miao Xinping et al. analysed the coordinated development trends and obstruction levels of provincial-level regional economies, the ecological environment, and the tourism industry. The findings indicated that the level of regional economic development ranks among the primary factors that influences coordinated development19,21. Moreover, numerous studies have been dedicated to examining the coupling coordination relationships among the tourism industry, the economy, and the ecological environment across diverse regions. For example, Zhao Hulan et al. investigated the coupling trends of the tourism industry, economic development, and the regional ecological environment in Xinjiang and conducted relevant predictive analyses. They discovered that the coupling trends of these aspects in Xinjiang are relatively favourable22. To explore the coordinated development dynamics among different subsystems in a region, the coupling coordination model aptly quantifies their coupling intensity and coordination level. Researchers have used comprehensive evaluation methods, coupled coordination models and other approaches to establish a comprehensive evaluation index system. They have analysed the degree of regional coupling and coordination from the dimensions of regional distribution and coordinated development by comparing the coordinated development of the ecological environment, economy and tourism11,12,23,24. Xue Huaju et al. applied coupling theory in physics to analyse the relationships among the coordinated development of tourism, the economy and the environmental system in Qinghai Province. Consequently, the comprehensive evaluation level of the ecosystem in Qinghai Province has greatly improved25. With respect to the evaluation of regional coupled coordinated development, the international research literature is extremely rich. In 1977, Wall G and Wright C integrated the tourism economy and the ecological environment to explore their coupled coordinated relationships26. Stephen’s research indicated that the tourism economy and the ecological environment interact27. A multivariate evaluation method has been proposed for the index system. By combining coupling analysis with sequential relationship analysis, an objective coupling weighting method has been suggested. Compared with the urban coordination level calculated by the entropy value method, this approach can guide the coordinated development of the urban economy, society, and the environment26,28,29. The coupled coordination degree model and the spatial autocorrelation statistical model have also been utilized to assess the spatiotemporal coupled interaction of coordinated development in the process of urbanization, thus enhancing regional sustainability30,31,32,33. These efforts have broadened the research perspectives for evaluating the coordinated development of the urban economy, society, and environment34,35,36,37. In terms of forecasting the trend of regional coupling and coordination, the relevant literature is relatively scarce. Most studies have adopted grey prediction models to predict the degree of system coupled coordination and to propose specific and replicable countermeasures38,39,40,41,42. Additionally, based on grey prediction theory, an objective prediction model of the spatial land use structure of urban agglomerations has been established to calculate and measure the spatial land use structure of urban agglomerations43,44,45.

Overall, under the wave of development in the current era, the exploration of the coordinated development of the ecological environment, economy and tourism has already shifted from the purely theoretical stage to practical operations at the regional level. Because of its unique and complex characteristics, the Yellow River Basin has naturally become a key research area that has drawn much attention in this practical process. When the complex development situation of the Yellow River Basin is analysed, the coupling coordination degree model can capture complex interaction relationships and perform dynamic monitoring. It can track the coupling coordination situations of the three systems at different stages and reveal their development trends. However, when examined from the perspective of the coupling of the human–land system, the existing research still has several limitations, which include the following. (1) In terms of the regional scale, most studies have focused on the eastern coastal regions with extremely dense populations and highly developed social economies. However, there is still room for further research in the central and western regions of China, especially in the Yellow River Basin. (2) In terms of the elements of coupling coordination, relatively few studies have examined the degree of coupling coordination among the social economy, the ecological environment and the tourism industry simultaneously, and the theoretical support is insufficient. (3) From the perspective of predictive research, relatively little international research has focused on predicting the coupling coordination relationship. Therefore, it is necessary to form predictions by following ideas similar to those in this paper and propose corresponding reasonable suggestions for future development.

Overview of the study area

The Yellow River Basin is one of the important geographical and ecological regions in China, spanning from west to east across four geomorphological units, namely, the Tibetan Plateau, the Inner Mongolian Plateau, the Loess Plateau and the Yellow-Huai-Haihai Plain, and flowing through nine provinces (districts), namely, Qinghai, Sichuan, Gansu, Ningxia, Shaanxi, Shanxi, Henan, Inner Mongolia and Shandong. The terrain of the Yellow River Basin is high in the west and low in the east, and the average altitude of the source area in the west is above 4000m, consisting of a series of high mountains, with year-round snow and glacial landforms; the central area, with an altitude of 1,000-2,000m, has loess landforms and serious soil erosion; and the eastern part is mainly made up of the Yellow River Alluvial Plain, as shown in Fig. 2.

Fig. 2
figure 2

Overview of the location of the Yellow River Basin (Note: This map is based on the standard map with the serial number GS (2020) 4631 downloaded from the standard map service website of the Bureau of Surveying, Mapping and Geographic Information of China (http://bzdt.ch.mnr.gov.cn/), and it was produced through ArcGIS 10.6 software (https://support.esri.com/en/download/7583). No modification has been made to the boundaries of the base map, and it does not require any permission from any source. The production methods of Figs. 5 and 6 below are the same as that of this map).

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In the socio-economic aspect, the economic output value of the nine provinces in the Yellow River Basin grows continuously, and the industrial structure tends to be rationalized gradually. The economy, as the basis of social development and industrial progress, provides sufficient technical support and financial guarantee for the ecological development and tourism industry.The Yellow River Basin has been written into the government work report for three consecutive years, and "the Yellow River Basin ecological protection and high-quality development" has gradually risen to a national strategy. In 2022, while implementing the normalized epidemic prevention and control work, the nine provinces and regions in the Yellow River Basin achieved fruitful results in sustaining economic growth at the same time.Among them, Shandong has the highest annual gross domestic product (GDP), exceeding 8 trillion yuan and being substantially higher than that of other provinces and regions in the basin. Henan and Sichuan are the second and third respectively. Shaanxi, Shanxi and Inner Mongolia have exceeded the 2 trillion yuan mark. Gansu’s GDP is 1.02433 trillion yuan. Ningxia and Qinghai have the lowest GDPs, at 452.23 billion yuan and 334.663 billion yuan respectively, and there is a large gap between them and those of other provinces and regions in the basin. Ecological construction has become the top priority in building a beautiful China. The nine provinces and regions in the Yellow River Basin have actively implemented all the tasks of the Outline. The provinces and regions through which the upper reaches of the main stream flow focus on protecting important water supply sites and intensifying sand management. The regions in the middle reaches are focusing on enhancing the capacity of soil and water conservation. The downstream wetland protection and ecological governance are accelerating. The upper, middle and lower reaches are coordinated in policy implementation. As a result, the ecological environment of the Yellow River Basin has improved significantly, with the solution of ecological problems being a crucial prerequisite for promoting economic development. In the development of tourism industry, relying on the unique natural and humanistic tourism resources, the tourism industry in the Yellow River Basin has developed rapidly, and the proportion of total tourism income in GDP has increased from 8.13% to 18.35%, with an increase of about 10% in 10 years. The development of socio-economic, ecological environment and tourism industry has become an important driving force for the national strategy of high-quality development of the Yellow River Basin.

Data processing and research methodology

Data sources and processing

The data used in this paper mainly include raster data, socio-economic data, etc. The raster data mainly involves land use data, which comes from the Resource and Environment Science and Data Centre of the Chinese Academy of Sciences (http://www.resdc.cn/), with a resolution of 30 × 30; the socio-economic data comes from the 2010–2020 China Urban Statistical Yearbook, China Environmental Yearbook, China Tourism Yearbook and Yellow River Yearbook. China Tourism Yearbook and the Yellow River Yearbook. In view of the missing relevant data in individual years, this study also refers to the 2010–2021 Statistical Yearbook and 2010–2021 Statistical Bulletin of some central cities, as well as data published publicly and released on official websites of the state, provinces and regions (Table1).

Table 1 Data Sources.
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Research methodology

Evaluation model for the level of system development

Due to the large differences in the unit and size of the original data, it is necessary to carry out the polar deviation standardization and dimensionless processing of the original data by referring to the research of related scholars25. In this paper, the entropy weight method is used to determine the weight of each evaluation index, and then the comprehensive development evaluation model of each subsystem is constructed based on the linear weighting function. The comprehensive evaluation index of the three major subsystems of the Yellow River Basin: social economy, ecological environment and tourism industry:

$$U_{i} = \sum\limits_{i = 1}^{m} {B_{ij} } ,\left( {U_{i} = E_{i} ,H_{i} ,L_{i} } \right)$$
(1)

where: Ui is the comprehensive evaluation index of the three major systems, and Ei, Hi, Li are the evaluation values of the social economy, ecological environment and tourism industry of the Yellow River Basin respectively.

Coupling coherence model

Coupling originates from the concept of physics and refers to the phenomenon of two or more systems or forms of motion influencing each other through various interactions. There is a dynamic relationship of mutual connection and mutual influence among the economic and social systems, ecological environment and tourism industry in the Yellow River Basin. “Coordinated development” particularly emphasizes that within the coupling relationship network of social economy, ecological environment, and tourism industry, each system strives to achieve a balanced and harmonious state via mutual support and complementary advantages. When the system or elements within the system are well coordinated and developed, it is called benign coupling, and vice versa, it is called malignant coupling. The degree of coupling is used to measure the strength with which the system or elements influence each other, while coordination is the relationship between the system or elements to coordinate and form a virtuous cycle. The specific steps are as follows:

  1. (1)

    With the help of the coupling coordination degree model in physics, the coupling degree formula of the three major systems of socio-economic-ecological environment-tourism industry in the Yellow River Basin is obtained:

    $$C_{i} = \left\{ {\frac{{E_{i} \times H_{i} \times L_{i} }}{{\left[ {\left( {E_{i} + H_{i} + L_{i} } \right)/3} \right]^{3} }}} \right\}^{1/3}$$
    (2)

    where: Ci is the degree of coupling, when Ci=1, it means that the three systems are in the optimal coupling state; Ci=0, it indicates that the internal elements of the system have nothing to do with each other, and the system develops in the direction of disorder.

  2. (2)

    The coupling degree can only explain the system interaction, but cannot reflect the level of coupling coordination, this paper introduces the coupling coordination degree model to determine the degree of coupling development of the three major systems of the Yellow River Basin: socio-economic, ecological environment and tourism industry:

    $$D_{i} = \sqrt {C_{i} \times T_{i} }$$
    (3)
    $$T_{i} = \alpha E_{i} + \beta H_{i} + \delta L_{i}$$
    (4)

    where: Di is the degree of coupling coordination; Ti is the comprehensive evaluation index of the three systems; α,β,δ is the coefficient to be determined; considering the tourism industry is an important part of regional economic activities, this paper refers to the international and domestic related research literature, this paper classifies the coupling coordination degree, as shown in Table 2. Setting α=0.4,β=0.4,δ=0.2.

    Table 2 Classification of coupling coordination levels.
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Construction of the indicator system

The scope of the watershed determined in this paper refers to the natural watershed scope delineated by the Yellow River Water Conservancy Commission of the Ministry of Water Resources, and 78 prefecture-level cities are selected as the research scale.In order to highlight the important coordinating and connecting role that the tourism industry in the Yellow River Basin plays in the regional economy and ecological environment, the three major subsystems of it, namely, regional economy, ecological environment and tourism industry, are placed at the same level for research. Considering that the tourism industry is an important part of the socio-economic activities, the analysis needs to focus on considering the relationship of the three degrees of affiliation and the size of the weights.When taking into account the relative and absolute differences between the levels of urban development, a comprehensive and reasonable evaluation system is the premise of the coupling and coordination analysis among the three. In accordance with the principles of data availability, representativeness of the indicators and systematic relevance, and with reference to the relevant research results, firstly, we center around the three major aspects of economy, ecology and tourism. Secondly, we select 30 tertiary indicators in detail from nine perspectives, including total economic scale, economic structure characteristics, social and economic construction, ecological environment endowment, current state of environmental pollution, and results of environmental governance. Finally, we take full account of the horizontal and vertical comparability of the indicators, so as to establish an evaluation model for the coupled and coordinated development of the socio-economic, ecological environment, and tourism industries in the Yellow River Basin (Table 3).

Table 3 Calculation results of the weights of indicators of coordinated development of socio-economic-ecological environment-tourism industry in the Yellow River Basin.
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As an objective assignment method, the entropy value method determines the weight of indicators based on the degree of variation of various indicators. It can have higher credibility and accuracy than the subjective assignment method and comprehensively reflect the amount of information contained in the indicators. In the evaluation indicators related to the three subsystems of socio-economic-ecological environment-tourism industry in the Yellow River Basin, the entropy value method is applied to calculate the weights, as shown in Table 3. And for the comparability of the indicators, firstly, the indicators are standardized by the extreme value standardization method to eliminate the shielding effect and the difference in the scale between the indicators. Then, in order to avoid the bias caused by human factors, the entropy value method is used to determine the weights of the indicators. Lastly, the linear weighting method is applied to comprehensively evaluate the development level of the three major subsystems of the regional economy, the ecological environment and the tourism industry. The steps are as follows:

  1. (1)

    With m evaluation objects (represented here as research periods) and n evaluation indicators, the original data matrix of the evaluation system X = (xij) is obtained, where i = 1,2,…,m;j = 1,2,…,n.

    $$\left\{\begin{array}{cccc}{\text{X}}_{11}& {\text{X}}_{12}& \cdots & {\text{X}}_{1\text{n}}\\ {\text{X}}_{21}& {\text{X}}_{22}& \cdots & {\text{X}}_{2\text{n}}\\ \cdots & \cdots & \cdots & \cdots \\ {\text{X}}_{\text{m}1}& {\text{X}}_{\text{m}2}& \cdots & {\text{X}}_{\text{mn}}\end{array}\right\}$$
    (5)

    where xij denotes the value for year i on the jth evaluation indicator.

  2. (2)

    The raw data are standardised to obtain the standardised matrix X′ = (y′ij), where i = 1,2,…,m;j = 1,2,…,n. In order to avoid the standardised values being zero and the subsequent calculations being meaningless, the standardised values are uniformly added with 0.001.The positive indicator is then:

    $${\text{y}}_{\text{ij}}=\frac{{x}_{ij}-min{x}_{ij}}{max {x}_{ij}-min{x}_{ij}}+0.001$$
    (6)

    Negative indicators are:

    $${\text{y}}_{\text{ij}}=\frac{{\text{maxx}}_{\text{ij}-}{\text{x}}_{\text{ij}}}{\text{max }{\text{x}}_{\text{ij}}-{\text{minx}}_{\text{ij}}}+0.001$$
    (7)
  3. (3)

    The weight of the value of the jth evaluation indicator in year i is:

    $${\text{P}}_{\text{ij}}=\frac{{y}_{ij}}{{\sum }_{i=1}^{m}{y}_{ij}}$$
    (8)
  4. (4)

    The entropy value of the information of the jth evaluation indicator is:

    $${\text{e}}_{\text{j}}=-\text{k}{\sum }_{\text{i}=1}^{\text{m}}{\text{p}}_{\text{ij}}{\text{lnp}}_{\text{ij}},\text{k}>\text{0,0}\le {\text{e}}_{\text{ij}}\le 1$$
    (9)
  5. (5)

    Calculation of the redundancy of the entropy values of the indicators.

    $${g}_{j}=1-{e}_{ij}$$
    (10)
  6. (6)

    The evaluation indicators are weighted:

    $${w}_{j}=\frac{{g}_{j}}{\sum_{j=1}^{n}{g}_{j}}$$
    (11)
  7. (7)

    Calculation of the composite development index for each city for each year.

    $${C}_{\lambda i}={p}_{\lambda ij}\times {w}_{ij}$$
    (12)

GM(1,1) grey prediction method

Grey system theory is widely used in engineering control, economic management, social systems and other fields. The grey prediction method based on grey system theory can be divided into the types of series prediction, catastrophe prediction, seasonal catastrophe prediction, topological prediction, and system integrated prediction according to the characteristics of the prediction object. In this paper, we adopt the method of series prediction, that is, to make quantitative prediction on the development and change of a certain indicator, and its prediction result is the specific value of the indicator in the future moments.The specific operation steps of GM(1,1) prediction method are as follows:

  1. (1)

    Let the time series \(X_{0} = \left\{ {x_{0} \left( 1 \right),x_{0} \left( 2 \right),...,x_{0} \left( n \right)} \right\}\) have observations, and generate a new time series \(X_{1} = \left\{ {x_{1} \left( 1 \right),x_{1} \left( 2 \right),...,x_{1} \left( n \right)} \right\}\) by accumulating the original series, then the corresponding differential equation for the GM(1,1) model is:

    $$\frac{{dX_{1} }}{{d_{t} }} + aX_{1} = \mu$$
    (13)

    where: \(\alpha\) is the developmental grey count; μ is the endogenous control grey count.

  2. (2)

    Let \(\hat{a}\) be the parameter vector to be estimated, \(\hat{a} = \left( {\frac{a}{\mu }} \right)\) can be solved by the least squares method, and the solution is \(\hat{a} = \left( {B^{T} B - 1} \right)B^{T} Y_{n}\), and the prediction model can be obtained by solving the differential equation:

    $$x_{1}^{T} X_{1} \left( {k + 1} \right) = \left[ {x_{0} (1) - \frac{\mu }{a}} \right]e^{ - ak} + \frac{a}{\mu },k = 1,2,...,n$$
    (14)
  3. (3)

    The accuracy test of the grey prediction formula is generally given by the following Table 4, if the probability of small error P and the ratio of the posterior difference C are within the permissible limits, the predicted value of the indicator can be calculated, otherwise it is necessary to re-correct the formula by analysing the sequence of residuals.

    Table 4 Grey prediction accuracy test level criteria.
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Results and analyses

Analysis of spatial and temporal differences in coupling coordination

Temporal variation of the coupling coordination degree.

Based on the comprehensive development indices of the three subsystems, the coupling degree and the coupling coordination degree of these systems in the Yellow River Basin are derived. The coupling coordination level and type are obtained by combining the division standard. In the past ten years, the overall degree of coupling among the social economy, ecological environment, and the tourism industry in the Yellow River Basin has been relatively moderate (Table 5). From 2010 to 2020, the degree of coupling coordination changed from 0.622 to 0.468. During this period, the coupling grade experienced an evolution from primary coordination to barely coordinated and then to on-the-verge-of-dissonance. These findings indicate that these three systems in the Yellow River Basin tend to be independent. Over the years, the degree of coupling and the mutual influence have decreased, and their independence has become stronger, which makes them easier to maintain and expand. In the late stage of study, the tourism industry and the socioeconomic system were overdeveloped, while the ecological environment lagged behind. This reflects that excessive development through construction and tourism damage the ecological environment to a certain extent and then constrain its benign development. From 2010 to 2020, the development levels of these three major systems in the Yellow River Basin, clearly decreased (Fig. 3). In 2010, the sum of the development levels of each system was relatively high, and the socioeconomic system accounted for a relatively large proportion. From 2011 to 2012, the development levels of each system remained relatively high, and the proportions of each were relatively balanced. From 2013 to 2020, the development levels of each system declined further. Especially in 2019 and 2020, the development levels of each system decreased to their lowest level.

Table 5 Calculation results of time-averaged coupling coordination degree of the three major systems in the Yellow River Basin, 2010–2020.
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Fig. 3
figure 3

System comprehensive evaluation value.

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The distribution of the values of the coupled coordination degree of the social economy, ecological environment and tourism industry of the 78 prefecture-level cities in the Yellow River Basin from 2010 to 2020 can be divided into three stages in terms of time (Fig. 4). The first stage is the rising coupling stage (2010–2011). In 2011, the coupling coordination degree of these three systems (0.622) in the nine provinces of the Yellow River Basin was in the primary coordination state. At that time, the construction of “Beautiful China” was written into the report of the 18th National Congress of the Communist Party of China. Relying on steady economic development, the tourism industry was on the rise, and it was experiencing the final stage of the integration strategy with the economic and social sectors. The second stage is the stable coupling stage (2015–2019). Beginning in 2015, this degree of coupling coordination of the Yellow River Basin reached the barely coordinated state and remained at this level for four years. During the processes proposed and implemented in important meetings such as the 18th and 19th National Congresses of the Communist Party of China, the national policies on ecological civilization construction and tourism development increased the importance of the Yellow River Basin for the development of these three systems. Under important strategic initiatives for the high-quality development of the Yellow River Basin, economic and social development, ecological environment protection, and the prosperity of the tourism industry have been placed in more prominent positions. As a result, the mutual influence among these systems gradually decreased while their independence increased. The third stage is the plummeting coupling stage (2020). In 2020, the coupling coordination degree of these systems in the Yellow River Basin (0.278) was in a state of moderate dissonance. Moreover, the outbreak of the COVID-19 pandemic comprehensively affected the coupling development among these three major systems in the Yellow River Basin. In particular, the indicators of the tourism industry dropped to their lowest values in the past ten years, and the economic output value was sluggish. Although the achievements in ecological environment protection were remarkable, the impact of the epidemic on the economy and the tourism industry was obvious, which caused the coupling coordination degree of these three systems to suddenly decrease to a state of moderate dissonance.

Fig. 4
figure 4

Line graph of coupled economic society-ecological environment-tourism industry coordination degree in the Yellow River Basin from 2011 to 2020.

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Spatial differentiation of coupling coordination degrees

To further explore the spatial differences in the social economy, ecological environment, and tourism industry in the Yellow River Basin from 2011 to 2020, cross-sectional data from four years—2010, 2013, 2016 and 2020—were selected, and the spatial distribution of the degree of coupling coordination among these three systems was plotted with ArcGIS software (Fig. 5). The coupling coordination degree of 78 prefecture-level cities in the Yellow River Basin was also plotted (Fig. 6). The spatial coupling degree of the three major systems in the Yellow River Basin was classified into low, medium and high levels, and the coupling coordination degree was evaluated. In terms of the spatial distribution of the average coupling coordination degree among the social economy, the ecological environment and the tourism industry in the Yellow River Basin from 2011 to 2020, Shandong Province, Shanxi Province, Henan Province, Shaanxi Province, and the Inner Mongolia Autonomous Region had high levels of coupling coordination. In contrast, Qinghai Province, the Ningxia Hui Autonomous Region and Gansu Province had a low level of coupling coordination. The distributions of the spatial coupling and coordination of these three systems in the Yellow River Basin are highly compatible with the degree of economic development in East China, Central China and West China and are essentially coupled with the distributions of the geographic locations in the upper, middle and lower reaches of the Yellow River Basin. These distributions are basically positively related to the degree of development in the basin.

Fig. 5
figure 5

Distribution of spatial coupling coordination degree of 78 cities in the Yellow River basin (The map was generated by the authors with the help of ArcGIS 10.6 (https://support.esri.com/en/download/7583) and does not require any permission from anywhere.)

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Fig. 6
figure 6

Coupling coordination degree of 78 prefecture-level cities in the Yellow River basin (The map was generated by the authors with the help of ArcGIS 10.6 (https://support.esri.com/en/download/7583) and does not require any permission from anywhere.)

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Spatially, the cities of Shandong Province had a relatively high degree of coupling and coordination over the decade. The high-quality development of the Yellow River Basin is in a very special position. The development of the Shandong Peninsula city cluster in the Yellow River Basin plays a leading role, and the cities of Qingdao and Jinan are particularly prominent. In the central region, Shanxi Province, Henan Province, the Inner Mongolia Autonomous Region, and Shaanxi Province have not only a large degree of coordination changes but also current development of social economy, ecological environment, and tourism industry clusters. Moreover, Zhengzhou and Luoyang as the centre of the Central Plains city cluster and Taiyuan as the centre of the Taiyuan city cluster are on the rise, and megacity clusters are taking shape in the development strategy. However, because of the imperfect urban infrastructure system, the ecological environment protection that can support investment is not enough, and the tourism industry belongs to the new development stage; thus, it is not yet possible to form an arrangement in which the three systems support one another. Notably, Henan Province has an intermediate coordination relationship among the three systems. Henan Province is the heart of the central development of large provinces adjacent to Shandong Province, and in recent years, Henan Province’s GDP has been close to Shandong’s GDP. The development of the tourism industry has increased substantially, and the depth of its immersive tourism has become a model for the whole country. In addition, the future of the three systems in the Yellow River Basin is highly coupled with the development of this important province. Gansu Province, Qinghai Province and the Ningxia Hui Autonomous Region in the western region are the typical areas with low coupling and coordination relationships among the three systems in the Yellow River Basin, and these three provinces are the western provinces of China with fragile ecological environments and slower economic development, which corresponds to a lower degree of tourism resource development. Economic development here cannot provide better infrastructure construction and financial support for environmental protection and tourism development, and the support of ecological policies for the construction of a beautiful China has resulted in a relatively weak capacity for tourism industry development, which cannot form a state of system development.

Correlation analysis

The development status of the three systems in the Yellow River Basin is the result of the combined action of multiple factors. Therefore, its spatial distribution should be comprehensively explored from multiple perspectives (Fig. 7).

Fig. 7
figure 7

Results of the interactive detection of the coupling coordination degree between the social economy—ecological environment—tourism industry and the systems in the Yellow River Basin.

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The economic subsystem has a relatively high impact on the coupled and coordinated development of the three major systems. Among them, the interaction effect between the disposable income of urban residents and the development levels of the three systems is the most significant. When the disposable income of urban residents increases, residents’ requirements for the ecological environment also increase, which is conducive to the development of relevant industries in the Yellow River Basin, promotes the prosperity of the economic system, and directly or indirectly supports the development of the tourism industry in the Yellow River Basin. The number of unemployed people has a significant negative correlation with coordinated development, and an increase in the number of unemployed people will lower this level. In the ecological subsystem, factors such as the urban green space area, the green coverage rate of the built-up area, and investment in research and development also have relatively prominent impacts on the coordinated development among the systems. The increase in the urban green space area and the green coverage rate of the built-up area helps enhance the stability of the urban ecosystem, improve a city’s image, and adds green charm to tourism development in the Yellow River Basin. In the tourism industry, factors such as the number of employees in the tertiary industry, the total number of tourists, and per capita tourism consumption have relatively large impacts. An increase in the number of personnel and per capita consumption means an improvement in the quality of tourism services and reflects tourists’ pursuit of tourism quality.

Notably, the interaction between natural factors and social factors is greater than the impact of individual factors. The Yellow River Basin combines its unique natural scenery with local folk culture to form a distinctive tourism experience, attracting many tourists. This integration not only promotes the development of the tourism industry but also drives local economic growth. Moreover, this integration has prompted people to attach greater importance to ecological protection, resulting in the coordinated development of the ecological, economic, and tourism systems. This indicates that there are situations such as synergy effects or mediation effects that influence these systems, which fully demonstrates the intricate yet closely intertwined relationships among them.

Grey model forecasting analysis

The grey prediction error test of GM (1,1) for the degree of coupling coordination of the economic, ecological and tourism systems in the Yellow River Basin from 2010 to 2020 is shown in Table 6. The predicted future values of the coupled coordination degree of the three major systems in the Yellow River Basin from 2026 to 2030 are presented in Table 7.

Table 6 Grey prediction accuracy test level criteria.
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Table 7 Forecast value of coupled economic development-ecological environment-tourism industry coordination in the Yellow River Basin, 2026–2030.
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Table 6 shows that the model is constructed to obtain the development coefficient a, the grey role quantity b, the value of the a posteriori ratio C and the probability of small error through the p value; the value of the a posteriori difference ratio C of 0.1396 ≤ 0.35 implies that the model accuracy grade is good. In addition, the small error probability p value is 0.800 < 0.95, which means that the model accuracy is sufficient. The predicted values of the coupled coordination degree of the economic, ecological and tourism systems for the 78 prefecture-level cities in the Yellow River Basin from 2026 to 2030 and the future coupled coordination degree of the three major systems in the Yellow River Basin will be in a moderately coordinated stage of epidemic recovery. During the epidemic period, the ecological environment in the Yellow River Basin was relatively less affected. However, the tourism industry suffered severe impacts. In the post-epidemic era, many tourism practitioners became unemployed. Moreover, the epidemic prevention and control policies restricted travel, resulting in a slow recovery of the output value of the tourism industry and further affecting the recovery process of the economy. The economy, ecology and tourism will remain in a barely coordinated state of development in the short term. Therefore, it is necessary to focus on restoring the recovery of the tourism industry by reducing the unemployment rate of residents working in tourism, increasing the per capita income of tourism, and stimulating tourism consumption to promote economic growth and social stability. The high-quality development of the economic, ecological, and tourism systems in the Yellow River Basin is imperative, and economic construction as the foundation will not waver but will adhere to the ecological bottom line and build a beautiful China while promoting the accelerated revival of the tourism industry.

Discussion and conclusions

Discussion

This study evaluates the coupling and coordination relationships among the three major systems of the social economy, the ecological environment, and the tourism industry in the Yellow River Basin from the perspective of the city domain in both temporal and spatial dimensions through the coupling and coordination development model. This research has important practical significance and theoretical potential for application in other similar river basins. Research has revealed that the coupling and coordination development of the social economy, the ecological environment, and the tourism industry in the Yellow River Basin has a continuous downwards trend. In the long run and overall, problems such as ecological destruction, unsustainable economic development, and the contraction of the tourism industry are likely to occur46,47. The development of the coupling and coordination degree shows a decreasing trend from east to west, which is highly consistent with the degree of economic development in the eastern, central, and western regions of China, and has a positive correlation with the development degree of the Yellow River Basin. This also confirms that all regions in the Yellow River Basin are gradually moving towards high-quality development47,48. Compared with the one-way interaction perspective, coupling research can reveal the dynamic mechanism of the internal nonlinear correlation of the social economy, ecological environment and tourism industry in the Yellow River Basin more deeply from the perspective of system integration to analyse the complex human‒land relationship49,50,51,52,53. Furthermore, it is easier to clarify the evolution process of the spatial heterogeneity and the key elements formed by coupling, which helps to intuitively explain the complex interaction of the three systems. In the relevant research fields of the Yellow River Basin, the focus is often on the binary relationship between a single industry and the ecological environment where the internal correlations between pairs are explored. However, relatively few systematic investigations have organically integrated these three key fields. This paper places the social economy, ecological environment, and tourism industry under a unified framework, which helps to intuitively explain the complex interactions among them and can thus provide practical response strategies for the high-quality development of the Yellow River Basin.

However, this study also has certain limitations. First, the COVID-19 pandemic swept across the world in 2020, and it had a significant impact on the tourism industry. In the next few years, a difficult recovery period will occur in the post-pandemic era. This causes the theoretical results based on the existing data to have errors and affects the accuracy and reliability. Second, the grey prediction model may itself have the randomness of time series in its predictions, resulting in relatively low prediction accuracy. Therefore, how to further reduce these errors in the post-pandemic era will be an important issue and the direction of our efforts in the future. Subsequently, we plan to introduce means such as multisource data cross-validation and correction and the in-depth optimization of model parameters to refine the research methods and provide a reliable decision-making basis for the development of river basins. Third, this study has relatively broad geographical coverage, and a detailed description of microregional differences and changes is still insufficient. In the future, we will be committed to deepening the research on a microscale by combining the uniqueness of each region and thoroughly exploring the correlations among the three systems.

Conclusion

This study conducts in-depth research concerning the Yellow River Basin. By constructing a three-dimensional index system that includes the social economy, the ecological environment, and the tourism industry and applying the coupling coordination development model, the coupling coordination relationships among the three major systems in the basin are analysed in both the temporal and spatial dimensions from 2010 to 2020. Moreover, with the help of the GM (1,1) grey prediction model, this study preliminarily predicts the coupling coordination trend of 78 prefecture-level cities in the Yellow River Basin from 2026 to 2030. Based on the comprehensive research results and discussion, the following conclusions are drawn.

  1. (1)

    Exploration of the coupling coordination development of the social economy, ecological environment, and tourism industry in the Yellow River Basin: Based on the comprehensive weight information obtained by the entropy method and relevant analyses, in promoting the high-quality development process of the Yellow River Basin, in terms of the social economy, efforts should focus on solving employment problems, reducing the unemployment rate, and improving the income levels of urban and rural residents. It is expected that by considering improvements in people’s quality of life and consumption level as opportunities, an impetus can be injected into economic growth. In terms of ecological environment protection, when pursuing improvements in economic efficiency, continuous attention should be given to the construction visions of "lucid waters and lush mountains" and “Beautiful China”. Emphasis should be placed on reducing the emissions of the “three wastes” (waste gas, waste water, and industrial residues), increasing investment in ecological governance, expanding the per capita green area, and adhering to the "ecological red line" to help transform ecological advantages into economic advantages. In the tourism industry, continuously cultivating high-quality professional talent, rectifying industry chaos, and strengthening the supervision of tourism enterprises are crucial for optimizing the quality of tourism services and enhancing tourists’ immersive experiences.

  2. (2)

    Evaluation of the coupling coordination development of the social economy, ecological environment, and tourism industry in the Yellow River Basin: With the help of the coupling coordination model, from the perspective of the time dimension, the average coupling coordination degree of the Yellow River Basin generally showed a downward trend from 2010 to 2020 and transitioned from primary coordination to moderate imbalance. In 2020, affected by the impact of the epidemic, various indicator data, especially those related to the tourism industry, decreased significantly, which to some extent reflects the vulnerability and instability of the development of the three major systems in the Yellow River Basin when addressing sudden external shocks. From the perspective of the spatial dimension, the coupling coordination degree in the Yellow River Basin shows a decreasing trend from east to west. In view of this, strengthening the effectiveness of leading cities in Shandong Province, solidifying the foundation of the construction of the central urban agglomeration, jointly promoting the coupling coordination development of the economic, ecological, and tourism systems, and cultivating the awareness of the river basin community are highly important for achieving sustainable and high-quality development in the upper, middle, and lower reaches of the Yellow River Basin.

  3. (3)

    Prediction of the coupling coordination development of the social economy, ecological environment, and tourism industry in the Yellow River Basin: According to the preliminary prediction of the GM (1,1) grey prediction model, there is a risk of a continuous decline in the coupling coordination degree in the Yellow River Basin from 2026 to 2030. In this context, placing the development of the tourism industry in an important position in the future construction of the Yellow River Basin may become a key focus for stimulating economic growth, ensuring employment and residents’ income, and improving living standards. This strategy will help to achieve stable and healthy development of the industry, society, economy, and ecology. However, because of certain limitations of the grey prediction model itself, such as the interference of the randomness of time series, the prediction results are only for reference, and it is still necessary to combine more actual situations for improvement in the future.

Accordingly, the conclusions of this study are drawn by integrating multiple factors. However, in view of the uncertainties in the research process, such as the impact of the epidemic and model limitations, further in-depth research is still needed in the future to optimize relevant strategies and serve the development practice of the Yellow River Basin more accurately.