Assessing the Coordination Degree of Coupled Human–Water–Ecosystem in the Tarim River Basin of China

Abstract

To understand the current status of water resource utilization and explore the coordination degree of the coupled human–water–ecosystem in the Tarim River Basin, we used the water shortage rates and index of WUE to analyze the dynamic changes in water shortage and water use efficiency. We also applied the Gini coefficient to study the evolutionary trend of the degree of matching between water consumption and GDP in each sector. Based on the above analysis, we developed a human–water–ecosystem coupling coordination degree model incorporating various indicators relevant to the three subsystems to quantitatively assess the coupled and coordinated development status of the three subsystems of the human–water–ecosystem in the basin from 2004 to 2020. The main findings are as follows: (1) The Tarim River Basin suffers from water shortage in dry years, with a prominent supply–demand contradiction. In the severe drought years of 2009 and 2014, the water shortage rates reached 10.20% and 10.93%, respectively. (2) From 2004 to 2020, the Tarim River Basin’s water use efficiency (WUE), and its five prefectures showed a clear upward trend. On a multi-year average, Bayingol Mongolian Autonomous Prefecture had the highest WUE, while the Hotan region had the lowest. (3) The multi-year average value of the match between water consumption and GDP for the entire basin is 0.28. By industry, the primary industry’s match between water consumption and GDP is higher, while the secondary and tertiary industries have lower matches. (4) From 2004 to 2020, the coordination degree of coupled human–water–ecosystem in the five prefectures showed different degrees of upward trend, generally developing towards better coordination. In terms of multi-year averages, Bayingol Mongolian Autonomous Prefecture, located in the east, has the highest degree of coupled coordination. Meanwhile, Hotan, in the south, lags significantly behind the remaining four regions. Therefore, the Tarim River Basin should further improve and optimize the development model of sustainable water resource use.

1. Introduction

Water resources are foundational and strategic assets essential for maintaining ecological balance, ensuring human survival, and supporting economic and social development [1]. The rapid development of the economy and society drives the efficient utilization of water resources while also promoting environmental protection. However, this development also increases pressure on water supplies, with the substantial pollutants generated can severely impact regional ecosystems [2,3,4]. Environmental protection is vital for supplying water resources and supporting economic and social development. Nevertheless, issues such as environmental degradation and the over-exploitation of water resources can disrupt regional water cycles, exacerbate water shortage, hinder economic and social development, and disturb ecological balance [5,6]. There is a complex feedback relationship among economic and social development, water resource utilization, and ecological environmental protection [3,7], with each factor influencing and depending on the others. As social and economic development progresses, problems such as water shortage, supply–demand imbalance, and ecosystem degradation become increasingly prominent [8]. Achieving coordinated and sustainable development of the human–water–ecosystem complex system while ensuring steady social and economic growth has become a pressing issue and common concern for scholars worldwide [9].

In exploring and assessing the coupling coordination degree of composite systems, scholars both in domestic and international settings have employed various methodologies. These include Bayesian networks [10], hierarchical analysis [11,12], geographically and temporally weighted regression [13], system dynamics [14,15,16,17,18], coupled coordination degree models [19,20,21,22], and others. Among these, coupled coordination degree models and system dynamics stand out as the most widely utilized approaches. Despite the advantages of system dynamics models in revealing regional system evolution laws, their limitations, such as parameter setting and model complexity, cannot be overlooked. In contrast, the entropy weight method and coupling coordination degree models exhibit distinct advantages in coupling coordination degree assessment. The entropy weight method objectively determines the weights of each index, thus mitigating the influence of subjective factors and enhancing the accuracy and reliability of assessment results. Meanwhile, coupling coordination models can quantitatively analyze the coupling relationship and coordination degree between the human–water–ecosystem, furnishing a scientific basis for tailored policy formulation and implementation.

Existing research, both domestically and internationally, predominantly focuses on administrative units and urban agglomerations, with fewer studies centered on watersheds. Situated in the arid region of Northwest China, the Tarim River Basin is a crucial ecological barrier and water resource hub, where the interplay among water resources, ecosystems, and human society is complex. The Tarim River Basin is characterized by a fragile ecological environment and is predominantly reliant on glacial snowmelt from high mountain areas as its primary water source, which poses challenges for direct utilization [23]. The “oasis economy, irrigated agriculture” serves as a defining feature of the Tarim River Basin’s economy [24], with agriculture accounting for more than 90% of the total water use. The fragile ecosystem is highly sensitive to the development and utilization of soil and water resources. In recent years, exacerbated by global climate change and human interventions, the demand for water resources in the Tarim River Basin has increased dramatically. However, the irrational water use structure has resulted in severe issues, including imbalanced economic development and significant ecological function degradation [25,26,27]. The Tarim River Basin has confronted significant challenges to its water resources’ security and sustainable management. Therefore, a comprehensive study and analysis of the human–water–ecosystem feedback system are crucial for promoting ecological conservation, rational water resource utilization, and sustainable development in arid regions.

To address the inquiry regarding annual water scarcity in the Tarim River Basin, gain a comprehensive understanding of water resource utilization, and scientifically evaluate the degree of coupled and coordinated development of human–water–ecosystem, we carried out the following works: (1) We analyzed the water supply–demand balance in the Tarim River Basin based on the equilibrium relationship of water resources supply and demand, utilizing metrics such as water shortage quantity and water shortage rate. (2) We applied the methodology recommended by the Food and Agriculture Organization of the United Nations (FAO) for calculating the index of water use efficiency [28,29] to assess variations in water use efficiency in the Tarim River Basin. (3) We employed the Gini coefficient to evaluate the degree of alignment between water consumption and GDP from both a regional and sectoral perspective. (4) We constructed a comprehensive evaluation index system to assess the level of coupled and coordinated development among the human–water–ecosystem systems in the Tarim River Basin.

2. Materials and Methods

2.1. Materials

The Tarim River Basin stands as the largest inland river basin in China, situated in the southern region of Xinjiang (73°10′~94°05′ E, 34°55′~43°08′ N), covering a total area of $1.02 \times { 10}^6$ km² [27,30]. The basin’s topography is intricate, predominantly featuring high mountains, deserts, and pre-mountain oasis zones [31], with a relatively fragile ecological environment. The Tarim Rivers’ average multi-year natural surface water runoff amounts to $398 \times { 10}^8$ m³ and is primarily replenished by snow and ice melt along with precipitation in the high mountainous regions [32,33,34,35]. It traverses five regions, namely, Bayingol Mongolian Autonomous Prefecture (Bayingol), Aksu Region, Kizilsu Kirghiz Autonomous Prefecture, (Kizilsu Kirghiz), Kashgar Region, and Hotan Region. See Figure 1.

In 2021, the total water resources of the Tarim River Basin reached $439.12 \times { 10}^8$ m³. The average multi-year per capita water availability from 2004 to 2021 stands at 4395 m³/person. Agriculture is the predominant water-consuming sector, utilizing approximately 90% of the total water consumption. Notably, the Tarim River Basin is a vital agricultural production hub for grain, cotton, and high-quality fruits and vegetables in China. Regarding economic indicators, data from the Third National Land Survey reveals that the basin boasts a cultivated area of $2.84 \times {10}^6$ hectares, accounting for approximately 40.17% of Xinjiang’s total ($7.07 \times { 10}^6$ hectares). In 2020, the basin’s population accounted for 45.49% of Xinjiang’s total population, while its gross domestic product (GDP) represented 29.91% of Xinjiang’s GDP. The per capita GDP in the basin remains significantly lower than Xinjiang’s average level. The basin experiences relatively low urbanization, and its economic and social development is generally underdeveloped.

This paper integrates literature reviews with typical surveys to gather and systematize data from the “Xinjiang Water Resources Bulletin” and “Xinjiang Statistical Yearbook” spanning 2005 to 2021. Additionally, data are sourced from the “Xinjiang National Economic and Social Development Statistical Bulletin”, “China Environmental Statistical Yearbook”, and “China Urban Statistical Yearbook”, as well as from statistical yearbooks and national economic and social development bulletins of various prefectures and cities. A comparative and analytical examination of data from diverse sources is conducted to ensure the reliability and accuracy of the data analysis. The research’s technological framework is depicted in Figure 2.

2.2. Methodology

2.2.1. The Water Shortage Quantity and Water Shortage Rate

Due to the constraints imposed by the natural environment and climatic conditions, the scarcity of water resources emerges as the primary challenge confronting the Tarim River Basin. The disparity between water resource supply and demand signifies this shortage [36,37]. A larger gap between supply and demand implies a lower risk in water resource utilization and ensures greater water security. Situated in the inland zone of Northwest Arid Zone, the Tarim River Basin encompasses vegetation as a vital component of its ecosystem. Sustaining a healthy ecological environment and rehabilitating degraded ecosystems necessitates consideration of ecological water demand. Thus, water demand encompasses not only the requirements for human socio-economic development but also the ecological water demand, which pertains to the needs of the vegetation ecosystem.

Based on this, the formula for calculating the shortage of water quantity is derived based on the equilibrium between water supply and demand [36]:

$${\mathrm{W}}_{\mathrm{S}}={\mathrm{W}}_1+{\mathrm{W}}_2-{\mathrm{W}}_3$$

(1)

where

• W_S = the shortage of water quantity;
• W₁ = human water demand;
• W₂ = ecological water demand;
• W₃ = total water resources.

The greater the water shortage quantity (W), the more severe the water shortage condition. To delve deeper into the analysis of water scarcity risk, this paper introduces the concept of water shortage rate, building upon the notion of water shortage quantity. The water shortage rate is computed using the formula:

$${\mathrm{R}}_{\mathrm{S}}={\mathrm{W}}_{\mathrm{S}}/\left({\mathrm{W}}_1+{\mathrm{W}}_2\right)$$

(2)

If the water shortage rate is below zero, it suggests no risk of water shortage, with a lower value indicating a reduced risk. Conversely, if the water shortage rate exceeds zero, it signals an impending risk of water shortage, with a higher value indicating a heightened risk.

2.2.2. Calculation of Water Use Efficiency

This paper utilizes the water use efficiency calculation index recommended by the Food and Agriculture Organization of the United Nations (FAO) [28], commonly employed for assessing the influence of economic growth on water consumption.

This metric is derived by weighting and aggregating the water use efficiency across agricultural, industrial, and service, according to the proportion of water use in each sector to the total water utilization. It signifies the value added per 1 m³ of water consumed, denoted in CNY/m³. The formula is expressed as follows [28,29]:

$$\mathrm{WUE}={\mathrm{A}}_{\mathrm{we}} \times {\mathrm{P}}_{\mathrm{A}}+{\mathrm{I}}_{\mathrm{we}} \times {\mathrm{P}}_{\mathrm{I}}+{\mathrm{S}}_{\mathrm{we}} \times {\mathrm{P}}_{\mathrm{S}}$$

(3)

where WUE represents water use efficiency (CNY/m³). ${\mathrm{A}}_{\mathrm{we}}$, ${\mathrm{I}}_{\mathrm{we}}$, and ${\mathrm{S}}_{\mathrm{we}}$ are the water use efficiency of agriculture, industry, and service, respectively. Meanwhile, ${\mathrm{P}}_{\mathrm{A}}$, ${\mathrm{P}}_{\mathrm{I}}$, and ${\mathrm{P}}_{\mathrm{S}}$ signify the proportion of water utilized in agriculture, industry, and service sectors to total water consumption. When calculating agricultural water use efficiency, it is essential to consider the ratio between the rain-fed and irrigated yields in the region and deduct the value of rain-fed agricultural output. Given the Tarim River Basin’s location in the arid northwestern zone characterized by low precipitation and high evapotranspiration, primarily focusing on oasis-irrigated agriculture, rain-fed production is deemed negligible.

2.2.3. Gini Coefficient

The Italian economist Gini proposed the Gini coefficient in 1912 based on the Lorenz curve, which mainly serves as an economic indicator to assess the fairness of income distribution [38]. Similar to the principle of unequal income distribution, the allocation of water resources within a region is usually unbalanced and directly affects economic development [39]. Therefore, this paper utilizes the Gini coefficient to evaluate the degree of alignment and inequality between GDP and water consumption in the Tarim River Basin [38,40].

$$\mathrm{G}=\sum _{\mathrm{i}=1}^{\mathrm{n}}({\mathrm{x}}_{\mathrm{i} }-{\mathrm{x}}_{\mathrm{i}-1})({\mathrm{y}}_{\mathrm{i}} -{ \mathrm{y}}_{\mathrm{i}-1})$$

(4)

where G is the Gini coefficient, n is the number of regions, x_i represents the cumulative percentage of water usage for a certain industry in one region, and y_i represents the cumulative percentage of GDP corresponding to that industry. The alignment between water usage and GDP is categorized into five levels [41], as shown in

Table 1. Matching level between water consumption and GDP.

Range	0	0 < G < 0.2	0.2 ≤ G < 0.3	0.3 ≤ G < 0.4	0.4 ≤ G < 0.5	0.5 ≤ G < 1	1
Matching degree	Perfect match	Significant match	Relative match	Reasonable match	Relative mismatch	Significant mismatch	Complete mismatch

, with values ranging from [0, 1]. A value closer to 0 indicates a better alignment between water usage and GDP, whereas a value closer to 1 signifies a poorer alignment.

2.2.4. Coupled Coordination Degree Model of Human–Water–Ecosystem

• Construction of evaluation index system

To quantitatively analyze the degree of coupled coordination within the human–water–ecosystem, it is imperative to comprehensively consider the principles of comprehensiveness, representativeness, scientific rigor, purposefulness, and practicality during the construction of the indicator system. Considering the water resources endowment, the level of economic and social development, and the ecological environment within the Tarim River Basin, twenty-three evaluation indices were chosen to construct the evaluation index system for the coupled human–water–ecosystem, spanning three sub-systems [3,42,43,44].

2.

Entropy Weight Method

Various methods exist for determining weights, with the entropy weight method being particularly versatile. This method primarily derives indicator weights based on the discreteness of different indicator data, objectively reflecting their variations [45]. This study’s evaluation index system encompasses multiple years, regions, and indicators. Therefore, based on panel data, the entropy weight method is used to determine the weights of indicators in assessing the coordination degree of the coupled human–water–ecosystem within the Tarim River Basin spanning 2004 to 2020 [46,47]. The selected indicators are divided into positive and negative categories. The maximum–minimum value method is employed to normalize each indicator to reduce the impact of different data dimensions.

Positive normalization is applied to the original data indicators when larger values indicate better performance [46].

$${\mathrm{u}}_{\mathrm{ij}}={\displaystyle \frac{{\mathrm{x}}_{\mathrm{ij}} -{\mathrm{x}}_{\min }}{{\mathrm{x}}_{\max } -{\mathrm{x}}_{\min }}}$$

(5)

When smaller values indicate better performance, negative normalization is applied to the original data indicators.

$${\mathrm{u}}_{\mathrm{ij}}={\displaystyle \frac{{\mathrm{x}}_{\max }-{\mathrm{x}}_{\mathrm{ij}}}{{\mathrm{x}}_{\max }-{\mathrm{x}}_{\min }}}$$

(6)

where ${\mathrm{x}}_{\mathrm{ij}}$ represents the initial value of the jth indicator in the ith region, ${\mathrm{u}}_{\mathrm{ij}}$ is the standardized value of the jth indicator in the ith region, and ${\mathrm{x}}_{\max }$ and ${\mathrm{x}}_{\min }$ are the corresponding maximum and minimum values of the respective indicators.

The entropy weight calculation formula for each indicator is [46]:

$${\mathrm{w}}_{\mathrm{j}}={\displaystyle \frac{1-{\mathrm{H}}_{\mathrm{j}}}{\mathrm{n}-{\sum }_{\mathrm{j}=1}^{\mathrm{n}}{\mathrm{H}}_{\mathrm{j}}}},\mathrm{j}=1, 2, \dots \dots , \mathrm{n}$$

(7)

where ${\mathrm{w}}_{\mathrm{j}}$ represents the weight value of the jth indicator.

${\mathrm{H}}_{\mathrm{j}}$ denotes the relative entropy value of the jth indicator in the ith region: ${\mathrm{H}}_{\mathrm{j}}=-{\displaystyle \frac{1}{\ln \mathrm{m}\times \mathrm{v}}}{\sum }_{\mathrm{t}=1}^{\mathrm{v}}{\sum }_{\mathrm{i}=1}^{\mathrm{m}}{\mathrm{f}}_{\mathrm{ij}}\ln {\mathrm{f}}_{\mathrm{ij}}$, where m is the total number of regions and v is the total number of years.

${\mathrm{f}}_{\mathrm{ij}}$ is calculated as: ${\mathrm{f}}_{\mathrm{ij}}={\displaystyle \frac{{\mathrm{u}}_{\mathrm{ij}}}{{\sum }_{\mathrm{t}=1}^{\mathrm{v}}\sum _{\mathrm{i}=1}^{\mathrm{m}}{\mathrm{u}}_{\mathrm{ij}}}}$. When computing, to avoid situations where the logarithm of zero is undefined, the data can be further shifted by adding a small constant. Thus, the calculation can be adjusted as follows: ${\mathrm{u}}_{\mathrm{ij}}={\mathrm{u}}_{\mathrm{ij}}+0.00001$.

3.

Comprehensive Evaluation Index

Based on the normalized values and weight calculation results of the aforementioned indicators, the comprehensive evaluation indices for the human, water, and ecosystem subsystems can be computed separately [48,49].

$${\mathrm{U}}_{\mathrm{i}}=\sum _{\mathrm{j}=1}^{\mathrm{n}}{\mathrm{w}}_{\mathrm{ij}}{\mathrm{u}}_{\mathrm{ij}}$$

(8)

$$\mathrm{T}={\mathsf{\beta }}_1{\mathrm{U}}_1+{\mathsf{\beta }}_2{\mathrm{U}}_2+\cdots +{\mathsf{\beta }}_{\mathrm{n}}{\mathrm{U}}_{\mathrm{n}}$$

(9)

where U_i represents the contribution of the ith subsystem to the overall system orderliness, namely the comprehensive evaluation index. T is the comprehensive evaluation index of the composite system. β₁, β₂, β_n denote the weights of each subsystem. This paper interprets β₁, β₂, β_n as indicators of the significance of water resources, socio-economic factors, and ecosystems, respectively, in regional development. Referring to existing research findings [50,51], it is generally considered that the three subsystems have equal importance. Therefore, β₁ = β₂ = β₃ = 1/3.

4.

Coupling Coordination Model

The concept of coupling degree pertains to the dynamic correlation between two or more systems, which interact and mutually influence each other to achieve coordinated development. It reflects the level of interdependence and mutual constraints among the systems [52,53]. Therefore, this study adopts the coupling degree to assess the extent of interaction and mutual influence among the three primary systems: human, water, and ecology. The calculation formula is outlined below [54]:

$$\mathrm{C}=\mathrm{n}\times {\left[{\displaystyle \frac{{\mathrm{U}}_1{\mathrm{U}}_2\cdots {\mathrm{U}}_{\mathrm{n}}}{({{\mathrm{U}}_1 {+\mathrm{U}}_2+\cdots +{\mathrm{U}}_{\mathrm{n}})}^{\mathrm{n}}}}\right]}^{{\displaystyle \frac{1}{\mathrm{n}}}}$$

(10)

where C represents the coupling degree of the n-element system, ranging from 0 to 1. A higher value of C signifies greater interconnection among the systems, indicating stronger interaction between water resources, socio-economics, and the ecological environment. Conversely, a lower value indicates weaker interaction. When C = 0, it signifies no relationship within the system, indicating a disordered state of system development. When C = 1, it indicates optimal coupling among the three systems.

The coupling degree solely assesses the interaction level among the three major systems and does not signify the extent of their coordinated development. Hence, the coupling coordination degree model is introduced to provide a more objective reflection of the coordination development level among the subsystems [55].

$$\mathrm{D}=\sqrt{\mathrm{C}\times \mathrm{T}}$$

(11)

where D represents the coupling coordination degree, with a value range of [0, 1]. Based on previous research findings [56,57], the classification standard for coupling coordination degree levels is presented in

Table 2. Classification of coupling coordination levels.

Type of Coupling Coordination	Coupling Coordination Degree(D)	Level
Imbalance recession category	(0.1~0.2]	Extreme imbalance
	(0.1~0.2]	Severe imbalance
	(0.2~0.3]	Moderate imbalance
	(0.3~0.4]	Mildly imbalance
	(0.4~0.5]	Near imbalance
Coordinated development category	(0.5~0.6]	Barely coordination
	(0.6~0.7]	Basic coordination
	(0.7~0.8]	Moderate coordination
	(0.8~0.9]	Good coordination
	(0.9~1.0]	Extreme coordination

.

3. Results and Discussion

3.1. Water Shortage Situation

Li [58] calculated the ecological water demand of vegetation in the Tarim River Basin for five representative years (2000, 2005, 2010, 2015, and 2018), using the area quota method, with an average of 102.91 × 10⁸ m³. To determine whether there was a water shortage in each year for the Tarim River Basin, we used the average ecological water demand from these representative years as the theoretical ecological water demand. This value was combined with annual water consumption for human activities to calculate the total water demand each year. By comparing this total demand with the available water resources, we calculated the annual water shortage and the corresponding shortage rate.

Figure 3 provides a detailed overview of the water shortage and shortage rate for each year between 2004 and 2020. A shortage rate ≤0 indicates no water shortage, whereas a rate >0 denotes a water shortage. During the period from 2004 to 2020, the Tarim River Basin experienced water shortages in two years: 2009 and 2014. Specifically, in 2009, the water shortage amounted to 41.33 × 10⁸ m³, with a shortage rate of 10.20%. In 2014, the water shortage was 48.56 × 10⁸ m³, with a shortage rate of 10.93%. These two years coincided with drought years in the Tarim River Basin. In 2009, the Tarim River Basin experienced abnormal climate conditions, characterized by an increased frequency of extreme weather events. From January to August, precipitation levels were consistently low, averaging only 17.4 mm—nearly 60% below the norm. This led to a 1100 km interruption in the flow of the Tarim River [59]. In 2009, the total water resources in the Tarim River Basin were at their lowest, decreasing by 16.7% compared to 2008. Precipitation in Kizilsu Kirghiz decreased by 1.8%, while in Bayingol, Aksu, Kashgar, and Hotan, it dropped by 16% to 21% compared to the previous year. Due to higher-than-usual spring temperatures, most regions in the Tarim River Basin experienced an early green-up date, necessitating earlier spring irrigation. Furthermore, factors such as strong winds, sandstorms, and reduced river and reservoir inflows contributed to varying degrees of drought in Kashgar, Hotan, and Aksu. At the peak of spring irrigation, over 4 million mu of crops could not be irrigated on time [60]. It is evident that during drought years, the available water within the basin significantly decreases, thus highlighting the risk of water scarcity.

According to the data released in the “Xinjiang Water Resources Bulletin,” the water consumption in the Tarim River Basin in 2020 was 326.45 × 10⁸ m³. Excluding ecological environmental replenishment, human activity water use accounted for 315.31 × 10⁸ m³. Both the total water consumption and the water use for human activities have exceeded the red line control indicator set by the State Council (309.4 × 10⁸ m³) [61]. This indicates that the risk of water shortage in the Tarim River Basin in the future cannot be ignored. It is imperative to strengthen the prediction research on water resources, scientifically formulate reasonable allocation of water resources within the basin, and balance ecological water use with human activity water use, while comprehensively implementing policies for water conservation and efficiency improvement.

3.2. The Temporal Variation of Water Use Efficiency

Figure 4 illustrates the temporal evolution of water use efficiency (WUE) in the Tarim River Basin and its five prefectures from 2004 to 2020. It is evident from the figure that the WUE of the Tarim River Basin and its five prefectures exhibited a clear upward trend during this period, peaking in 2020. This trend demonstrates the progress made in water resource management over the past two decades in the Tarim River Basin, contributing to mitigating the water supply–demand imbalance.

As far as the prefectures are concerned, Bayingol exhibits the highest water use efficiency, significantly surpassing the basin average. This indicates that Bayingol has achieved a leading edge in water use efficiency, serving as a benchmark for other regions. In contrast, the Hotan region demonstrates the lowest water use efficiency among the five prefectures, indicating a greater need for water inputs to generate equivalent outputs, necessitating urgent enhancements in water use efficiency. Significant funding shortages for agricultural water conservancy projects in the Hotan region have resulted in a lack of advanced irrigation equipment and a limited irrigation area, adversely affecting the region’s water use efficiency [62]. The water use efficiency of Aksu, Kizilsu Kirghiz, and Kashgar fluctuates but is relatively similar overall.

Since 2012, significant achievements have been made in conserving and utilizing water resources in the Tarim River Basin, marked by a consistent optimization of water usage structure and a gradual enhancement in water efficiency. The proportion of water used for agriculture has decreased from 97.4% in 2012 to 94.8% in 2021. This structural adjustment is of great significance in easing the pressure on water resources. However, the current pattern of water resource utilization remains suboptimal. The primary industry in the Tarim River Basin consumes a substantial amount of water while generating relatively low economic benefits, thereby placing considerable pressure on water resources. In economically developed regions like Bayingol, optimizing the industrial structure by increasing the proportion of secondary and tertiary industries could enhance water use efficiency [63]. Significant water leakage and evaporation losses occur during the water transmission process, attributed to the continued utilization of poor impermeability channels by certain farmers. Traditional flood irrigation methods also persist in certain areas, further reducing water use efficiency. If the current pattern continues, future risks in water resource utilization may become inevitable. Consequently, there is an urgent need to deepen research on the water resource utilization pattern in the Tarim River Basin and explore more efficient and sustainable methodologies. By improving water transmission methods, optimizing irrigation techniques, and enhancing water use efficiency, water resource utilization in the Tarim River Basin can be guided toward a more scientific and rational trajectory, offering robust support for regional sustainable development.

3.3. Degree of Water Consumption Matching with GDP

The water resources system and the economic system are interdependent and mutually influential. Water resources both support and constrain economic development, while economic development influences the quantity and efficiency of water resource utilization. Depending on the spatial and temporal distribution of water resources and economic development disparities, various alignment states may arise. Examples include scenarios of “high water consumption with low GDP” and “low water consumption with high GDP”. We calculate the Gini coefficient (G) to measure the alignment between water consumption and GDP in the Tarim River Basin. The results are shown in Figure 5.

Figure 5a illustrates that the Gini coefficient (G) for total water consumption and GDP fluctuated between 0.1 and 0.4 from 2004 to 2020. This indicates that each region utilized a certain proportion of water resources during production while contributing an equivalent proportion to the GDP. The G value ranges across three levels: highly matched, relatively matched, and reasonably matched, with a declining trend. This trend is attributed to economic development in the Tarim River Basin, the widespread adoption of water-saving irrigation technology in agriculture, and the adjustment of industrial structures. These factors collectively improved water use efficiency, thereby enhancing the alignment between total water consumption and GDP.

On a temporal scale, the multi-year average of the Gini coefficient (G) during the study period stands at 0.28, falling within a reasonable range. Notably, in 2008, the Gini coefficient (G) for the Tarim River Basin rose to 0.39, nearing the threshold that indicates a warning for matching status. This suggests a potential risk in matching the total water use with GDP in some specific years.

When examining the alignment between water consumption and gross product across different industries, significant disparities become evident. Figure 5b demonstrates that in the primary sector, the alignment between water consumption and gross product is high and relatively stable. This stability is due to the arid climate and limited precipitation in the Tarim River Basin, leading to over 90% of water resources being consistently allocated for agriculture. However, variability in water resource endowment leads to uncertainty in total water resources and consumption over time. As a result, water consumption in the secondary and tertiary sectors is low and experiences significant inter-annual fluctuations. Concurrently, the gross product of each region within the basin has experienced rapid growth. Consequently, the divergence between gross product and water consumption has resulted in fluctuating variations in alignment (Figure 5c,d). In some years, the degree of matching exceeded the warning threshold of 0.4, indicating a relative mismatch.

Further analysis reveals that various factors influence the alignment between water consumption and gross product. Firstly, abundant water resources directly impact its utilization efficiency and distribution fairness. Increased water shortages lead to reduced water availability, which in turn affects how water is allocated and utilized across industries. In 2009 and 2014, when the water shortage rate was more significant than 0, the Gini coefficient G value in the Tarim River Basin was lower compared to adjacent years, indicating an improved alignment between water consumption and gross product. This suggests that in response to water shortages, regions effectively implemented inter-regional water transfers and optimized usage to meet essential living and production needs, leading to improved alignment between water consumption and gross product.

Furthermore, the structure of water allocation, namely the water use pattern, is also a key factor influencing the degree of matching between water consumption and Gross Domestic Product (GDP) in the Tarim River Basin. There are differences in the proportion of the three major industries across regions, leading to disparities in economic development and influencing the water usage patterns within each region. As the economy continues to evolve, these disparities will grow accordingly. Agriculture occupies an important position among the three major industries in the Tarim River Basin. Regardless of whether there is a water shortage in the basin, the water consumption of agriculture remains above 90% of the total and at the same time, brings about a steady increase in food production and gross product. Therefore, the water consumption of the primary sector consistently aligns with its gross product, maintaining a high level of stability over time. However, the situation differs in the secondary sector. Products in the secondary industry have higher added value and generate substantial economic returns. Additionally, a significant portion of the water used in production is recycled and reused, leading to relatively low overall water consumption [64]. For instance, in Bayingol from 2004 to 2009, the secondary sector contributed approximately 70% of the basin’s secondary sector GDP, despite utilizing only 20% of the total water consumption in that sector. This disparity between water consumption and gross product results in a decreased alignment. Similarly, the tertiary sector encounters analogous challenges. In 2015, the tertiary sector in Bayingol consumed a large amount of water resources in the basin, accounting for 52% of the total water usage in the tertiary sector. However, its output value was only 25% of the total tertiary sector’s output value in the basin. This mismatch between water consumption and gross product persisted from 2015 to 2017. It adversely impacted the alignment between water consumption and gross product in the tertiary sector of the Tarim River Basin.

In recent years, measures such as inter-regional water transfers and localized water resource allocation have alleviated significant differences in water consumption among various regions to a certain extent. Nonetheless, achieving sustainable development requires further enhancing water resource utilization efficiency through rational management and industrial restructuring. This includes fostering a positive interplay between water resource utilization and economic development, thereby establishing a solid foundation for sustainable development in the Tarim River Basin.

3.4. Assessing the Coordination Degree of Coupled Human–Water–Ecosystem in the Tarim River Basin

3.4.1. Analysis of Indicator Weights

Using the entropy weight method with panel data, the weights of each evaluation index are calculated, as shown in

Table 3. Assessment Index System of the coordination degree of coupled human–water–ecosystem in the Tarim River Basin.

Subsystem		Index	Unit	+/−	Weight
Human	Economy	Per capita GDP	CNY per capita	+	0.2070
		Grain yield per unit area	Kg/hm2	+	0.0445
		Proportion of industrial output value	%	+	0.2053
		Proportion of tertiary industry output value	%	+	0.0678
	Society	Urbanization rate	%	+	0.0769
		Urban registered unemployment rate	%	−	0.0235
		Rural electricity consumption	10,000 kWh	+	0.1737
		Population density	people/km2	+	0.2013
Water	Background conditions	Total water resources	100 million m3	+	0.1776
		Water production modulus	10,000 m3/km2	+	0.1797
		Per capita water resources	m3 per capita	+	0.2680
	Development level	The utilization ratio of water resources	%	−	0.0971
		Groundwater extraction rate	%	−	0.0282
		Per capita water consumption	m3 per capita	−	0.1081
	Utilization efficiency	Water consumption per CNY 10,000 GDP	m3/CNY 10,000	−	0.0438
		Irrigation water consumption per mu of farmland	m3/mu	−	0.0975
Ecosystem		Total afforested area	hectare	+	0.1951
		Per capita park green space area	m3	+	0.1034
		Fertilizer application intensity	t/ha	-	0.0894
		Proportion of ecological water use	%	+	0.3664
		Desertification control area	hectare	+	0.1990
		Sewage treatment rate	%	+	0.0145
		Urban waste disposal rate	%	+	0.0323

. In the human subsystem, per capita GDP (0.2070) and the proportion of industrial output value (0.2053) hold significant weights, underscoring their substantial impact on the basin’s economic and social advancement. These two indicators not only gauge the region’s economic prosperity but also reflect the impact of industrialization on economic and social development. In the water resources subsystem, the weight of background conditions is as high as 0.6253, which is far more than other factors in the water resources subsystem, illustrating the core position of background conditions in the comprehensive development of the Tarim River Basin. The weight of per capita water resources (0.2680) is particularly notable because it is directly related to the abundance or shortage of water resources and has a decisive influence on the sustainable development of the basin. In the ecosystem subsystem, the weights of the ecological water use ratio (0.2143), and sewage treatment ratio (0.2432) are relatively high, indicating that they play an important role in maintaining the health of the ecological environment. The ecological water use ratio reflects the rational allocation of water resources in the basin for ecological preservation, whereas the sewage treatment ratio gauges the basin’s effectiveness in environmental management. Comparatively, the weights of per capita green space in parks (0.0605) and fertilizer application intensity (0.0294) are lower, suggesting their lesser impact on comprehensive ecosystem development, but they are still factors that should not be ignored.

3.4.2. Comprehensive Evaluation Index

Compute the comprehensive evaluation indices of subsystems and the human–water–ecosystem composite system in the Tarim River Basin each year. The results are shown in Figure 6.

Figure 6a depicts that the human subsystem’s comprehensive evaluation index (U1) is highest in Bayingol and lowest in Hotan. This disparity correlates with economic development levels, evidenced by Bayingol’s multi-year average GDP per capita is CNY 56,289, significantly higher than Hotan’s CNY 7644. Furthermore, Bayingol’s industrial output value accounted for 52.29% of the basin’s multi-year average, contrasting with Hotan, where the primary industry dominates, with industrial output value accounting for only 6.08% of the basin’s multi-year average. These two key indicators fully illustrate Bayingol’s economic and social development achievements, thereby explaining why the comprehensive evaluation index of its economic and social subsystems is much higher than that of the Hotan region. For the underdeveloped Hotan region, it is essential to reform the economic and social development model according to local conditions, optimize the industrial structure, and appropriately increase the share of the tertiary sector.

Due to background conditions, the weight of per capita water resources within the water resources system is significant. Consequently, its comprehensive evaluation index (U2) closely correlates with the extent of water resource shortage. Figure 6b depicts a significant drop in the comprehensive evaluation index of the different regions in 2009 and 2014, compared to other years. This decline is attributed to the drought conditions prevalent in these two years. The substantial reduction in the incoming water volume led to a considerable decrease in the per capita water resources across the regions, an increase in groundwater extraction rates, and the utilization ratio of water resources, consequently resulting in a notable decline in the comprehensive evaluation index of the water resources subsystem [27].

In Figure 6c, the comprehensive evaluation index (U3) for each region within the ecosystem subsystem generally remains below 0.4, indicating the need for further enhancement in the coordinated ecosystem development across the states. In terms of temporal changes, Hotan exhibits a relatively stable comprehensive evaluation index, consistently hovering around 0.2 with minor fluctuations. Conversely, the comprehensive evaluation index of the other four regions displays significant fluctuations, closely linked to interannual variations in ecological indicators, such as water usage for ecological purposes and total afforested area. Therefore, sustained attention to ecological water use, bolstered desertification control, urban greening initiatives, and similar efforts are imperative for ensuring the benign and stable development of the ecological environment.

Figure 6d displays the comprehensive evaluation index (T) of the coupled human–water–ecosystem complex system in the Tarim River Basin. Overall, the index remains relatively stable, demonstrating an upward trend across all regions due to economic and social development, enhanced water resource utilization, and the implementation of ecological protection policies. From a temporal standpoint, particularly after 2012, each region has experienced a noticeable increase in the comprehensive evaluation index of the coupled system. Spatially, Bayingol exhibits the highest comprehensive development level, with its index rising from 0.33 in 2004 to 0.48 in 2020.

3.4.3. The Degree of Coupling Coordination

The coupling degree (C) of the human–water–ecosystem complex system for each year between 2004 and 2020 in every region of the Tarim River Basin was computed based on the comprehensive evaluation index of the three subsystems. The results are mostly above 0.7, indicating strong coupling, which suggests a strong coupling relationship of interdependence, mutual constraints, and mutual influence among the three subsystems of human, water, and ecosystem.

According to Equation (11), the coupled coordination degree (D) of the human–water–ecosystem complex system in the Tarim River Basin was calculated for each year from 2004 to 2020, and the results are depicted in Figure 7.

By examining the data presented in Table 2 and Figure 7, we can discern the degree of coupling coordination within the human–water–ecosystem composite system in the Tarim River Basin. Under the influence of the comprehensive evaluation indices for each subsystem improving year by year, the coupling coordination degree of the system ranged between 0.4 and 0.7 from 2004 to 2020, indicating a mid-low level of coordination, oscillating between near imbalance, barely coordination, and basic coordination. The upward trend in the coupling coordination degree across the regions of the Tarim River Basin from 2004 to 2020, is influenced by advancements in water use technology, economic and social development, and ecological environmental protection efforts. All five regions are generally developing in the direction of harmonization, which aligns with previous research [3,27]. After 2012, the growth rate of the coupling coordination degree across various regions accelerated significantly, likely due to the implementation of more stringent water resources management policies [3]. Among them, Bayingol exhibits the highest degree of coupling coordination, with a significant increase from 0.55 to 0.67 between 2004 and 2020, fluctuating between barely and basic coordination. This enhancement is attributed to rapid development in its economic, social, and ecosystem subsystems. From 2004 to 2020, Bayingol underwent industrial upgrades, resulting in reduced water consumption per unit of GDP and ongoing improvements in water use efficiency. Economic and social development, coupled with improvements in the ecological environment, led to a steady increase in the coupling coordination degree among the human–water–ecosystem. In 2018, Bayingol’s coupling coordination degree peaked, primarily because ecological water usage in the region reached its highest level in recent years. In comparison, the Aksu, Kizilsu Kirghiz, Kashgar, and Hotan regions started from a disadvantaged position, experiencing relatively minor changes in coupling coordination throughout the study period. However, these regions demonstrate a stable upward trend, progressing from near imbalance in 2004 to basic and barely coordination by 2020. This suggests that despite starting from a disadvantaged position, these regions have made commendable advancements in enhancing the degree of coupled coordination within the human–water–ecosystem complex system.

Utilizing the calculated results of the coupling coordination within the human–water–ecosystem complex system, combined with the ArcGIS 10.5 software, we selected the years 2004, 2010, 2015, and 2020 for analysis. We generated a spatial distribution map depicting the coupling coordination within the human–water–ecosystem complex system in the basin of the Tarim River, which is presented in Figure 8. From a perspective of spatial distribution, the coupling coordination of the Tarim River Basin from 2004 to 2020 shows an upward trend. Bayingol in the eastern part of the basin exhibits the highest level of coupling coordination within human–water–ecosystem systems, whereas Aksu, Hotan, Kashgar, and Kizilsu Kyrgyz in the central and western parts of the basin exhibit relatively lower levels of coordination. In 2004, Bayingol barely reached coordinated levels, while other regions were nearly imbalanced. Over time, the coupling coordination levels of Aksu and Kashgar improved to barely coordinated levels in 2010 from the near imbalance, with Bayingol further progressing from barely coordinated to basic coordination. By 2015, Kashgar achieved basic coordination levels, while Kizilsu Kirghiz and Hotan saw an improvement in their coupling coordination levels within the human–water–ecosystem system from near imbalance to barely coordinated levels. By then, all five regions in the Tarim River Basin had reached the category of coordinated development. By 2020, except for Hotan, which remained at barely coordinated levels, the other regions had all achieved basic coordination levels. In summary, the coordination degree of the coupled human–water–ecosystem in the Tarim River Basin is closely linked to geographic location, with the eastern region showing a higher level of coupling coordination compared to the central and western regions.

The achievement of coordinated development in complex systems is influenced by numerous factors, where the rational utilization of water, high-quality economic and social development, and ecological protection are complementary. When the mutual negative influences among these three factors are minimized, the state of coordination can be optimal [44,65]. Unlike humid regions, the Tarim River Basin relies heavily on irrigated agriculture, resulting in disproportionately high agricultural water usage, causing significant structural water shortage issues in the basin. However, with the implementation of the nation’s most stringent water resources management system and the widespread application of water-saving irrigation technologies, water use efficiency in this basin has significantly increased. Specifically, the per mu irrigation water use in farmland, which is one of the main evaluation indicators for the water subsystem, decreased from 926.17 m³ in 2004 to 602.03 m³ in 2020. This decrease has not only alleviated pressure on the water subsystem but also fostered favorable conditions for the coordinated development of the entire human–water–ecosystem complex system, thus laying a solid foundation for the basin’s sustainable development.

On the other hand, water shortage is another significant factor affecting the coordinated development of the human–water–ecosystem system in the Tarim River Basin. In 2009 and 2014, years marked by drought, the per capita water resources were 5602.8 m³/person and 5092.8 m³/person, respectively. The decrease in per capita water resources highlights the risk of water scarcity within the basin, which consequently reduces the coupling coordination. In dry years, there is a significant increase in water pressure in the Tarim River Basin, significantly impacting industries dependent on water resources. Agricultural irrigation, ecological conservation, and residential water usage all exert considerable pressure. Moreover, the increasing water costs due to scarcity could lead to higher operating costs for businesses, thereby reducing profitability. Therefore, careful attention to climate change and water resource dynamics is crucial for addressing future challenges and risks. In this process, regions with higher coupling coordination, such as Bayingol, should leverage their higher influential role by sharing successful experiences in water resource management and water-saving irrigation technology applications to help other regions enhance the coupling coordination of complex systems, achieve harmonious coexistence of human, water, and ecosystem, and promote the sustainable development in the basin.

4. Conclusions

This paper examines water resource utilization in the Tarim River Basin by calculating the water shortage rate and water use efficiency. Furthermore, we examine variations in the alignment between water consumption and the gross product in each industry. Additionally, we develop a coupling coordination degree model to evaluate the level of coordinated development within the human–water–ecosystem complex system in the Tarim River Basin from 2004 to 2020. The principal findings are as follows:

(1)

Between 2004 and 2020, the Tarim River Basin faced severe water shortages in drought years, resulting in a significant imbalance between water supply and demand. While there was a general upward trend in water use efficiency, certain regions, notably the Hotan region, showed lower efficiency levels. Over the study period, the agricultural sector in the basin exhibited greater alignment between water consumption and gross product compared to the secondary and tertiary industries.

(2)

The coupled coordination degree of the human–water–ecosystem composite system in the basin is generally improving, although with spatial disparities. Bayingol exhibits higher coordination, while Hotan shows lower levels. Overall, the Tarim River Basin has made progress in water management over the past two decades. However, the current usage pattern needs optimization to mitigate future water risks. Therefore, future development efforts should prioritize adjusting the water usage structure and implementing comprehensive water conservation and efficiency strategies. This approach aims to alleviate the constraints of the water subsystem on other subsystems and enhance the sustainability of water resource utilization.

(3)

The assessment results of the coupled human–water–ecosystem coordination degree in the Tarim River Basin demonstrate the feasibility and effectiveness of the constructed evaluation index system and quantitative method. These findings hold both theoretical and practical significance for fostering the harmonious and coordinated development of water resources, the economy, society, and the ecological environment in the basin. However, the evaluation index system encompasses numerous indicators, demanding comprehensive and accurate basic data. Therefore, the indicators used to assess each subsystem need further research and enhancement.