Evaluating the water resources spatial equilibrium (WRSE) is the foundation for scientifically planning the construction of an optimized water resource allocation system and achieving the high-standard development of the China Water Network Project. To elucidate the characteristics of WRSE variation in Ulanqab City, this study explored a novel WRSE assessment model based on connection number and the subtraction set pair potential method. The results indicate that: (1) there exists a mismatch between the distribution of water resources in Ulanqab City and its socio-economic development. In 2020, the Gini coefficients of water resources total quantity concerning resident population, gross domestic product (GDP), industrial output value, and irrigated land area were 0.48, 0.48, 0.51, and 0.28, respectively. (2) From 2011 to 2020, the overall WRSE level in Ulanqab City showed an increasing trend year by year. Among them, the WRSE levels in six counties improved, while Jining District consistently remained at a low equilibrium state due to the prominent contradiction between water supply and demand. (3) In the future, Ulanqab City can further enhance the WRSE level by promoting the reuse of recycled water, intensifying groundwater pollution control, and implementing a quota management system for agricultural water use.

  • The distribution of water resources in Ulanqab City is in a state of mismatch with social and economic development.

  • From 2011 to 2020, the water resources spatial equilibrium levels of six counties in Ulanqab City improved, while there was no significant change in five counties.

  • The vulnerability indicators of Ulanqab City are per capita water resources and ecological environment water demand load.

Water resources are primarily natural and strategic economic resources that concern the national economy, people's livelihood, and dominant controlling factors of the ecological environment and economic and social development (Long et al., 2020; Wang et al., 2023a, 2023b). The balanced distribution of water resources also determines the upper limit of economic and social development, and there is a complex relationship between it and territorial spatial planning (Rosa et al., 2020; Yuan et al., 2023). Low per capita consumption, uneven distribution of time and space, and the mismatch of water and soil resources are the significant characteristics of China's water resources (Wang et al., 2020). Coupled with the rapid development of some regions, the contradiction between the supply and demand of water resources has gradually developed from a local to a universal social problem (Peng et al., 2021). As a result, the contradiction between the spatial distribution of water resources in some cities and the high-intensity water demand gradually becomes prominent, seriously restricting some regions' social and economic development (Yang et al., 2019). Therefore, balancing the coordination between water resource supply and demand, population distribution, and economic development is an essential issue of common concern to society. It is also a challenge to realize the 17 Sustainable Development Goals proposed by the United Nations (Tortajada 2020).

Since the Reform and Opening Up, China's economy has made extraordinary achievements. However, some areas have problems, such as economic development restricted by water resources and low efficiency of water use (Zhang et al., 2019; Ge & Wang, 2023). In the transition towards high-quality development, dealing rationally with the relationship between water resources and economic and social development is necessary (Yan & Xu, 2022). This puts forward new requirements for alleviating the contradiction between the supply and demand of water resources in green development. According to the 2019 World Water Development Report, by 2050, more than 2 billion people will live in areas with severe water shortages, and about 4 billion will suffer severe water shortages for at least one month each year (Niu et al., 2022). China is the world's largest developing country, not only having enormous demand for water resources but also undergoing a transition in the utilization of water resources from extensive to intensive. In recent years, there has been a proactive shift towards water conservation, improving efficiency, and enhancing water usage effectiveness (Li et al., 2022a, 2022b). Aiming at the incompatibility problem between water resource distribution and social development distribution in China, the General Secretary of the Communist Party of China proposed the idea of ‘water resources spatial equilibrium (WRSE)’ as a significant development concept. Constructing the spatial allocation pattern of national water resources based on the principle of spatial equilibrium can provide a strong guarantee for promoting the domestic economic cycle and realizing the coordinated development of regions (Bian et al., 2022).

Although there is no unified cognition on the connotation of WRSE, the research content of WRSE is also relatively complex. There have been many relevant studies so far. For instance, Marin & Smith (1988) were the first to consider national and regional strategies related to the four main objectives of water policy: supply and demand balance, economic efficiency, cost recovery, and equity, and propose a spatial equilibrium approach to water resource assessment based on this. However, during the period when the dominant factors constraining regional development were predominantly related to science and technology, the contradiction between regional water resource endowment and the demand for water resource development was not particularly pronounced. This led to the spatial equilibrium theory of water resources not initially drawing significant attention from scholars when first proposed. Subsequently, Hassan & Thurlow (2011) introduced a comprehensive equilibrium model framework to analyze the overall economic impact of water resource utilization and distribution. Murray et al. (2012) proposed a spatial optimization model to study how water supply allocation plays a role in regional water resources management. In recent years, as the challenge of water use intensifies and the contradiction between limited regional water resources and the rapidly developing economy becomes increasingly acute, the research on WRSE has attracted more attention. Yang et al. (2022) proposed a framework for evaluating WRSE by coupling fuzzy sets of variables and Gini coefficient methods and applied it to the Yangtze River Economic Belt in China. Bai et al. (2022) applied the method of multi-dimensional connection cloud and coupling coordination degree to build a comprehensive evaluation model of the WRSE system.

Existing research on the understanding of WRSE, measurement methods, and policy measures generally exhibits the following characteristics. In the realm of WRSE theory, scholars commonly concur that WRSE represents the coordinated balance between water resource systems, socio-economic systems, and ecological environmental systems. However, there exists significant divergence in terms of its precise connotation. In this study, we define WRSE as a theory that investigates the distribution and regulation of water resources among different regions. Its objective is to achieve spatial balance in the supply and demand of water resources, maintain water quality, and effectively protect ecosystems by adjusting the development, utilization, distribution, and management of water resources. Regarding quantification methods for WRSE, current analyses and assessments primarily fall into three categories: match relationship evaluation, indicator system evaluation, and supply–demand quantitative relationship analysis. Research methods encompass coordination development degree, imbalance index, Gini coefficient, Lorenz curve, connection number, etc., or a combination of the above methods. Wang et al. (2023a, 2023b) employed Lorenz curves, Gini coefficients, Theil coefficients, and other measures to evaluate the spatial trends and equilibrium of the water–energy–food system in the Yellow River Basin. Zhang et al. (2023) combined the analytic hierarchy process and fuzzy comprehensive evaluation to construct an agricultural water resource carrying capacity index to quantify the spatiotemporal changes in agricultural water resources carrying capacity in Henan Province. While these methods have provided new avenues for evaluating WRSE, some, such as the Gini coefficient and coupling coordination degree, have stringent requirements for selecting evaluation indicators and grading evaluation levels. In comparison, methods such as connection number and subtraction set pair potential (SSPP) demonstrate broader applicability in the evaluation of WRSE (Zhou et al., 2022b). In terms of comprehensive research, existing achievements predominantly focus on large-scale regions or river basins as the research areas, assessing whether water resources are in equilibrium and the degree of such equilibrium. Nevertheless, these studies often overlook in-depth analysis and proposals for addressing issues of imbalance at the urban scale. Conducting WRSE research from the perspective of urban scale contributes to achieving human-centered comprehensive development of the economic, social, and resource-environmental complex system, aiming to maximize overall benefits. Simultaneously, from a research dimension perspective, static analyses are commonly employed, with a dearth of exploration into the temporal and spatial dynamics of WRSE.

Ulanqab is located in the central part of the Inner Mongolia Autonomous Region. Water resources are mainly rivers and lakes, resulting in a severe shortage of total water resources (TWRs) in Ulanqab (Chen et al., 2019). The TWRs in Ulanqab are only 0.03% of the TWRs in China. However, with the continuous development of economic construction and increasing demand for water resources, problems such as uneven spatial distribution of water resources in Ulanqab followed. Water resource conflicts between regions became increasingly severe, and most regions had higher demand for water resources. The existing problems will restrict the sustainable development of Ulanqab City, so the coordination of water resources shared between the region and water users has become the primary issue urgently to be solved by the water resources management department of Ulanqab City. However, there is currently a lack of research on WRSE in Ulanqab. As a typical water shortage area, studying water resources spatial balance assessment and regulation in Ulanqab City can provide new ideas and references for other similar areas.

From the perspective of water resource development and conservation, it is beneficial to analyze the balance between the water resource system and the ecological environment system, while from the perspective of water resource supply and demand, it is more conducive to analyzing the coordination between the water resource system and the socio-economic system. Hence, the aim of this study is to select indicators from the supply and demand perspective, construct a comprehensive assessment system for WRSE by combining subjective and objective weighting, then the connection number and set pair analysis were applied to diagnose the spatial and temporal trends of WRSE levels in the 11 counties of Ulanqab. Based on these diagnostic scenarios, corresponding regional water resource optimization strategies are proposed. This endeavor will contribute to understanding the synergistic balance in resource and environmental management and help formulate practical policies and measures, with a view to providing reference for the spatially equilibrium allocation of water resources in the basin and the optimization and adjustment of regional water network layout.

Study area

Ulanqab City is located in the semi-arid region in the north of China (110°26′–114°49′ E, 40°10′–43°28′ N), covering an area of 54,500 km2 (Figure 1). Ulanqab City governs 11 administrative divisions, including Jining District (JD), Fengzhen City (FC), Zhuozi County (ZC), Huade County (HC), Shangdu County (SC), Xinghe County (XC), Liangcheng County (LC), Qahar Right Front Banner (QRFB), Qahar Right Middle Banner (QRMB), Qahar Right Rear Banner (QRRB), Dorbod Banner (DB), and the administrative center is in Jining District (Wang et al., 2018). In recent years, the carrying capacity of water resources in some regions has reached or even exceeded its limit value. Water resources have become a vital shortboard restricting the development of local society and economy. According to the ‘Master Plan of Territorial Space of Ulanqab (2021–2035)’, significant differences in water resource endowment appear, water consumption level and economic development degree among 11 districts in Ulanqab city, and the development and utilization of water resources in most regions present an unbalanced state in space.
Fig. 1

Location map and administrative division of Ulanqab City.

Fig. 1

Location map and administrative division of Ulanqab City.

Close modal

Data collection

The 11 banner counties and districts of Ulanqab City are selected as the research unit. The primary socio-economic data are obtained from the 2011–2020 ‘Statistical Yearbook of Ulanqab City’, the required resident population (RP) data comes from the seventh census data. The cultivated land area data were derived from land use changes interpreted from remote sensing images (https://www.resdc.cn). The basic data on water resources are provided by Preliminary Results of the Third Water Resources Assessment of Ulanqab, in which the water consumption data and water supply data are from the Water Resources Bulletin of Ulanqab during 2011–2020. The water conservancy project's water supply data are obtained from the Water Conservancy Statistical Annual Report of Ulanqab.

Methodology

The procedure outlined in Figure 2, which incorporates Connection number and SSPP, was used for WRSE analysis of Ulanqab City.
Fig. 2

Flow chart of the WRSE evaluation model.

Fig. 2

Flow chart of the WRSE evaluation model.

Close modal

Index of the water resources spatial equilibrium model

WRSE evaluation can be divided into supply and demand subsystems. Combining the characteristics of each subsystem and the region itself, the evaluation indicator system is constructed based on scientific and reasonable relative independence, relative completeness, and operability, aiming at obtaining accurate and objective evaluation results. According to the actual situation of Ulanqab City, 12 indicators are selected (Table 1). The WRSE was conducted for each index, and five evaluation levels were defined in succession: higher level (grade I), high level (grade II), medium level (grade III), low level (grade IV), and lower level (grade V). The evaluation levels of each indicator are shown in Table 2.

Table 1

Evaluation indicators of WRSE quality.

SubsystemAbbreviationIndicatorUnitDefinition
Supply subsystem X1 Per capita water resources m3/Person Ratio of TWRs to RP 
X2 Per capita available water supply 10,000 m3/Person Ratio of water availability to RP 
X3 Utilization rate of surface water Ratio of water consumption to TWRs 
X4 Utilization rate of groundwater Ratio of the amount of groundwater supplied to the exploitable amount of groundwater 
Demand subsystem X5 Urbanization rate Ratio of the urban population to the total RP 
X6 Population density Person/km2 Ratio of RP to administrative area 
X7 Per capita daily domestic water consumption L/(Person·d) Daily water consumption per person 
X8 Water consumption per 10,000 yuan of GDP m3/10,000 yuan Ratio of total water consumption to GDP 
X9 Water consumption per 10,000 yuan of industrial added value m3/10,000 yuan Ratio of industrial water consumption to industrial added value 
X10 Farmland irrigation quota m3/mu Ratio of farmland irrigation water consumption to ILA 
X11 Ratio of irrigated land Ratio of irrigated land to arable land 
X12 Ecological environment water demand load Ratio of ecological environment water consumption to total water consumption 
SubsystemAbbreviationIndicatorUnitDefinition
Supply subsystem X1 Per capita water resources m3/Person Ratio of TWRs to RP 
X2 Per capita available water supply 10,000 m3/Person Ratio of water availability to RP 
X3 Utilization rate of surface water Ratio of water consumption to TWRs 
X4 Utilization rate of groundwater Ratio of the amount of groundwater supplied to the exploitable amount of groundwater 
Demand subsystem X5 Urbanization rate Ratio of the urban population to the total RP 
X6 Population density Person/km2 Ratio of RP to administrative area 
X7 Per capita daily domestic water consumption L/(Person·d) Daily water consumption per person 
X8 Water consumption per 10,000 yuan of GDP m3/10,000 yuan Ratio of total water consumption to GDP 
X9 Water consumption per 10,000 yuan of industrial added value m3/10,000 yuan Ratio of industrial water consumption to industrial added value 
X10 Farmland irrigation quota m3/mu Ratio of farmland irrigation water consumption to ILA 
X11 Ratio of irrigated land Ratio of irrigated land to arable land 
X12 Ecological environment water demand load Ratio of ecological environment water consumption to total water consumption 
Table 2

Spatial equilibrium quality evaluation indicators and evaluation grades.

SubsystemIndicatorPropertyGrade criteria
Grade IGrade IIGrade IIIGrade IVGrade V
Supply subsystem X1 Positive >2000 1500 ∼ 2000 1000 ∼ 1500 500 ∼ 1000 <500 
X2 Positive >600 450 ∼ 600 300 ∼ 450 150 ∼ 300 <150 
X3 Negative <40 40 ∼ 60 40 ∼ 60 80 ∼ 100 >100 
X4 Negative <55 55 ∼ 70 70 ∼ 85 85 ∼ 100 >100 
Demand subsystem X5 Negative <40 40 ∼ 55 55 ∼ 70 70 ∼ 85 >85 
X6 Negative <100 100 ∼ 400 400 ∼ 700 700 ∼ 1000 >1000 
X7 Negative <80 80 ∼ 120 120 ∼ 160 160 ∼ 200 >200 
X8 Negative <30 30 ∼ 70 70 ∼ 110 110 ∼ 150 >150 
X9 Negative <10 10 ∼ 20 20 ∼ 30 30 ∼ 40 >40 
X10 Negative <100 100 ∼ 150 150 ∼ 200 200 ∼ 250 >250 
X11 Negative <20 20 ∼ 30 30 ∼ 40 40 ∼ 50 >50 
X12 Positive >10 7 ∼ 10 4 ∼ 7 1 ∼ 4 <1 
SubsystemIndicatorPropertyGrade criteria
Grade IGrade IIGrade IIIGrade IVGrade V
Supply subsystem X1 Positive >2000 1500 ∼ 2000 1000 ∼ 1500 500 ∼ 1000 <500 
X2 Positive >600 450 ∼ 600 300 ∼ 450 150 ∼ 300 <150 
X3 Negative <40 40 ∼ 60 40 ∼ 60 80 ∼ 100 >100 
X4 Negative <55 55 ∼ 70 70 ∼ 85 85 ∼ 100 >100 
Demand subsystem X5 Negative <40 40 ∼ 55 55 ∼ 70 70 ∼ 85 >85 
X6 Negative <100 100 ∼ 400 400 ∼ 700 700 ∼ 1000 >1000 
X7 Negative <80 80 ∼ 120 120 ∼ 160 160 ∼ 200 >200 
X8 Negative <30 30 ∼ 70 70 ∼ 110 110 ∼ 150 >150 
X9 Negative <10 10 ∼ 20 20 ∼ 30 30 ∼ 40 >40 
X10 Negative <100 100 ∼ 150 150 ∼ 200 200 ∼ 250 >250 
X11 Negative <20 20 ∼ 30 30 ∼ 40 40 ∼ 50 >50 
X12 Positive >10 7 ∼ 10 4 ∼ 7 1 ∼ 4 <1 

Index weight calculation

Considering the impact of different indicators on the assessment of water resources spatial balance, it is vital to determine the weight of each indicator reasonably. The widely used analytic hierarchy process (AHP) can reasonably compare indicators based on expert experience and the actual situation of the problem (Murmu et al., 2019), however, the disadvantage is that it may ignore individual subjective arbitrariness. The variation coefficient method (VCM) has absolute objectivity. However, the calculated weight value will also deviate from the actual importance, leading to an immense weight value of individual indicators with apparent differences. Therefore, the combination weighting method of the AHP and the coefficient of variation method is applied to assign weights to each index of WRSE evaluation to make up for the errors and deficiencies of unilateral weighting.
formula
(1)
where represents the combined weight of the index; is the objective weight vector obtained by the VCM; and is the subjective weight vector obtained by the AHP. The comprehensive weight reweighting of WRSE evaluation indicators is shown in Table 3.
Table 3

Weights of spatial equilibrium quality evaluation indicators.

SubsystemIndicatorAHP weightVCM weightComprehensive weight
Supply subsystem X1 0.108 0.292 0.066 
X2 0.187 0.189 0.074 
X3 0.293 0.362 0.223 
X4 0.412 0.157 0.136 
Demand subsystem X5 0.098 0.051 0.018 
X6 0.113 0.273 0.122 
X7 0.060 0.039 0.010 
X8 0.156 0.068 0.043 
X9 0.208 0.204 0.167 
X10 0.135 0.093 0.046 
X11 0.173 0.075 0.048 
X12 0.058 0.198 0.046 
SubsystemIndicatorAHP weightVCM weightComprehensive weight
Supply subsystem X1 0.108 0.292 0.066 
X2 0.187 0.189 0.074 
X3 0.293 0.362 0.223 
X4 0.412 0.157 0.136 
Demand subsystem X5 0.098 0.051 0.018 
X6 0.113 0.273 0.122 
X7 0.060 0.039 0.010 
X8 0.156 0.068 0.043 
X9 0.208 0.204 0.167 
X10 0.135 0.093 0.046 
X11 0.173 0.075 0.048 
X12 0.058 0.198 0.046 

Connection number

Connection number theory is a mathematical model and a system analysis method used to deal with uncertainty problems. When establishing the evaluation model of the linkage number system, the dimension of the linkage number is determined according to the order of the evaluation grade, which is usually three, four and five. This study's evaluation level is divided into five levels, so the five-element connection number method is adopted. For the five-element connection number, the relation degree between the sample value and the evaluation criteria is shown in formulas (2)–(3).

When the evaluation index is negative, the correlation degree between the value xl of a specific index and the evaluation standard corresponding to the index is expressed as:
formula
(2)
where S1S2S3S4S5.
formula
(3)
where S1S2S3S4S5.
According to the confidence criterion, the grade result of couplet coefficient is judged:
formula
(4)
where, hk is the sum of k components of the five-element connection number, ; is the weight of each indicator and is confidence level, which is taken as 0.6 in this study.

Subtraction set pair potential

SSPP is used to judge the changing trend of WRSE evaluation index (Zhou et al., 2022a).
formula
(5)
Since b1 and b3 will have different impacts on the positive and negative trends of the spatial equilibrium state of water resources, the formula is improved by analyzing the meaning of each connection number component and the degree of influence of the development trend of the equilibrium state. Introducing the influence coefficient λ of the different degree sub-items, the obtained formula is:
formula
(6)

Based on the equipartition principle, is divided into five levels: when ∈ [−1, −0.6) is a negative potential, it means that the changing trend of WRSE is negative; when ∈ [−0.6, −0.2) is a partial negative potential, it means that the changing trend of WRSE is negative; when ∈ [−0.2, 0.2) is an equilibrium potential, it means that the trend of spatial equilibrium change of water resources is stable. When ∈ [0.2, 0.6] is homogenous, it means that the trend of spatial equilibrium change of water resources is positive; when ∈ [0.6, 1.0], the trend of spatial equilibrium change of water resources is positive.

When the SSPP of the whole system is in reverse potential or partial reverse potential, it indicates that its state develops in an unfavorable direction; when the SSPP of the sample value is in reverse potential or partial reverse potential, it indicates that the sample is a vulnerability index affecting the spatial equilibrium state of water resources.

Water resources and economic and social development in Ulanqab City

Lorentz curve and Gini coefficient were used to characterize the matching relationship between water resources and socio-economic development in Ulanqab. Based on the spatial and temporal distribution of water resources and the status of economic and social development, there may be a variety of matching conditions, such as ‘abundant water resources but low level of economic and social development’ and ‘scarce water resources but high level of economic and social development’. In order to reflect the matching relationship between the above two systems, representative factors can be selected respectively for quantitative analysis of matching, and the matching degree can be expressed through the spatiotemporal inhomogeneity of water resources distribution and economic and social development level. The closer the Gini coefficient is to 0, the more matched the factors are. The closer the Gini coefficient is to 1, the more mismatched they are.

The Lorenz curves for the TWRs of Ulanqab City from 2011 to 2020, as associated with the RP, GDP, industrial added value (IAV), and irrigated land area (ILA), are illustrated in Figure 3. Overall, except for irrigated land, the Gini coefficients of all the indicators exhibited a significant increasing trend in relation to water resources during this period. Notably, the population has shown a considerably higher level of imbalance since 2015. In the case of GDP and industrial added value, the Gini coefficient remained relatively stable from 2011 to 2015, but then increased between 2015 and 2020. This suggests that during the ‘Thirteenth Five-Year Plan’ period, with the implementation of a series of technological innovation and reform policies in Ulanqab, the industrial economy gradually expanded, exacerbating the inequality in resource allocation within this sector. Furthermore, in 2020, the Gini coefficients for the TWRs in relation to the RP, GDP, industrial added value, and ILA were 0.48, 0.48, 0.51, and 0.28, respectively (Table 4). Therefore, the distribution of water resources in Ulanqab City is in a state of mismatch with social and economic development overall, and it is urgent to comprehensively evaluate the spatial equilibrium of water resources in this region.
Table 4

Gini coefficient of Ulanqab from 2011 to 2020.

Gini coefficientYear
201120152020
TWR-RP 0.20 0.47 0.48 
TWR-GDP 0.42 0.40 0.48 
TWR-IAV 0.36 0.33 0.51 
TWR-ILA 0.26 0.33 0.28 
Gini coefficientYear
201120152020
TWR-RP 0.20 0.47 0.48 
TWR-GDP 0.42 0.40 0.48 
TWR-IAV 0.36 0.33 0.51 
TWR-ILA 0.26 0.33 0.28 
Fig. 3

Lorenz curve of TWRs and representative indicators of Ulanqab from 2011 to 2020.

Fig. 3

Lorenz curve of TWRs and representative indicators of Ulanqab from 2011 to 2020.

Close modal

Spatial and temporal variation characteristics of water resources spatial equilibrium

From 2011 to 2020, the spatial equilibrium quality of water resources was improved in six banner counties, namely Zhuozi County, Fengzhen City, Xinghe County, Liangcheng County, Qahar Right Middle Banner, and Dorbod Banner. Zhuozi County, Dorbod Banner, and Qahar Right Middle Banner gradually improved from medium-level equilibrium to high-level equilibrium; Liangcheng County was in a medium equilibrium state from 2011 to 2013, a low equilibrium state from 2015 to 2016, and gradually improved to a high equilibrium state from 2018 to 2020. Xinghe County went from a lower-level equilibrium state to a low-level equilibrium state. Fengzhen City improved from a low equilibrium state to a high equilibrium state. Jining District has been in a low-level equilibrium state and Huade County was always in a medium-level equilibrium state during this period. Shangdu County was in a low equilibrium state in 2011 and 2013 and in a medium equilibrium state in other years. The Qahar Right Rear Banner has been in a medium-level equilibrium for 10 years. The Qahar Right Front Banner was in a high-level equilibrium in 2020 and a medium-level equilibrium in other years (Figure 4).
Fig. 4

Spatial equilibrium evolution of water resources in Ulanqab from 2011 to 2020.

Fig. 4

Spatial equilibrium evolution of water resources in Ulanqab from 2011 to 2020.

Close modal

The indicator of surface water utilization rate is closely related to the spatial equilibrium of water resources. On the one hand, the decrease in surface water utilization rate means the conservation and protection of water resources, which is conducive to maintaining the natural cycle and ecological balance of water resources. On the other hand, the increase in the surface water utilization rate may lead to the concentration of resources in some areas, while other areas may face water shortage problems, reflecting the imbalance of water supply and demand. The overall surface water utilization rate of Ulanqab City is not high and shows a downward trend, decreasing from 45% in 2011 to 36% in 2020, which reduces the imbalance to some extent. During the 12th and 13th Five-Year Plan periods, Ulanqab City has implemented a series of water-saving measures, such as strengthening the control of total water consumption intensity, enhancing water management in key industries, and promoting the utilization of unconventional water sources. Furthermore, specific water control targets for each region have been established, achieving a more rational allocation of water resources. Therefore, despite the increase in the regional Gini coefficient, the spatial balance of water resources has improved. For local areas, Jining District has always been at a high level, increasing from 146% in 2011 to 281% in 2020, indicating that the water resources development degree of Jining District exceeds its water resources development limit, resulting in overexploitation of groundwater and more prominent water supply and demand contradiction. The surface water utilization rate of other banners and counties did not show obvious changes during this period.

Analysis of spatial equilibrium situation of water resources

The SSPP was used to judge the development trend of the WRSE quality level. According to the connection number of WRSE quality evaluation in Ulanqab City from 2011 to 2020, the corresponding SSPP value was calculated by the formula (6); thereby, the potential level (PL) analysis was carried out. The results show that during the study period, the SSPP values of the whole water resources system, supply subsystem, and demand subsystem of Ulanqab were positive. Except for the symmetrical potential state in 2011, they were all in the state of identical potential or partially identical potential from 2012 to 2020. The quality level of each system presents a trend of improvement year by year, consistent with the state change judged by the five-element correlation number (Table 5).

Table 5

2011–2020 Ulanqab City WRSE quality evaluation subtraction set pairs.

YearWhole system
Supply subsystem
Demand subsystem
SSPPPLSSPPPLSSPPPL
2011 0.10 Symmetrical potential 0.18 Symmetrical potential 0.04 Symmetrical potential 
2012 0.40 Partial identical potential 0.46 Partial identical potential 0.35 Partial identical potential 
2013 0.45 Partial identical potential 0.52 Partial identical potential 0.37 Partial identical potential 
2014 0.35 Partial identical potential 0.33 Partial identical potential 0.36 Partial identical potential 
2015 0.35 Partial identical potential 0.29 Partial identical potential 0.40 Partial identical potential 
2016 0.40 Partial identical potential 0.33 Partial identical potential 0.47 Partial identical potential 
2017 0.54 Partial identical potential 0.48 Partial identical potential 0.60 Identical potential 
2018 0.66 Identical potential 0.63 Identical potential 0.69 Identical potential 
2019 0.66 Identical potential 0.64 Identical potential 0.69 Identical potential 
2020 0.67 Identical potential 0.68 Identical potential 0.66 Identical potential 
YearWhole system
Supply subsystem
Demand subsystem
SSPPPLSSPPPLSSPPPL
2011 0.10 Symmetrical potential 0.18 Symmetrical potential 0.04 Symmetrical potential 
2012 0.40 Partial identical potential 0.46 Partial identical potential 0.35 Partial identical potential 
2013 0.45 Partial identical potential 0.52 Partial identical potential 0.37 Partial identical potential 
2014 0.35 Partial identical potential 0.33 Partial identical potential 0.36 Partial identical potential 
2015 0.35 Partial identical potential 0.29 Partial identical potential 0.40 Partial identical potential 
2016 0.40 Partial identical potential 0.33 Partial identical potential 0.47 Partial identical potential 
2017 0.54 Partial identical potential 0.48 Partial identical potential 0.60 Identical potential 
2018 0.66 Identical potential 0.63 Identical potential 0.69 Identical potential 
2019 0.66 Identical potential 0.64 Identical potential 0.69 Identical potential 
2020 0.67 Identical potential 0.68 Identical potential 0.66 Identical potential 

Similarly, the SSPP values of units in lousy states in Ulanqab City from 2011 to 2020 were analyzed. For the whole system unit, there are four units with a bad situation. Among them, Jining District has been in a state of inverse potential or partial inverse potential in the past 10 years, indicating that the level of Jining District has gradually deteriorated; Fengzhen City and Shangdu County were in a partial inverse potential only in 2011; Xinghe County was on the partial inverse potential only in 2011 and 2012, and in other years it was in a good situation, indicating that the overall level of other regions except Jining District has been improving by years. For the supply subsystem, seven units have a bad situation. The SSPP values of Jining District in the past 10 years are all −1, indicating that the supply level of Jining District continues to deteriorate; Huade County was in a state of partial reverse potential or reverse potential in other years except 2012. Shangdu County and Qahar Right Front Banner were in bad condition for 7 years, Xinghe County and Fengzhen City were in reverse state in the early stage, and the supply level was improved in the late stage. For the demand subsystem, there are three units with lousy situations, indicating that the water level of the demand side is good.

Analysis of the optimal scheme of water resources regulation and control in the planning year

According to the Overall Territorial Space Plan of Ulanqab (2021–2035), 2035 is selected as the planning year to forecast and evaluate the spatial equilibrium state of water resources. The main measures include agricultural water-saving, paddy field to dry land, and internal and external water transfer. Since Ulanqab has consistently implemented the agricultural water-saving square array, the following six schemes are determined after combining the above measures (Table 6). In addition, according to a series of vision planning policy documents issued by the city of Ulanqab, the development degree of some important indicators for the planning year was determined. For the urbanization rate, Jining District will reach 95%; other counties will reach about 70%; Ulanqab's GDP will grow at an average annual rate of about 7% in 2035. Water consumption per 10,000 yuan of industrial added value should be reduced by 10% every five years.

Table 6

2035 Water resources regulation plan set.

PlanMeasures
Agricultural water-savingPaddy field to dry landInternal water transferExternal water transfer
√    
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PlanMeasures
Agricultural water-savingPaddy field to dry landInternal water transferExternal water transfer
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The quantitative and qualitative evaluation of WRSE for plans 1–6 showed that plans 2, 5, and 6 eliminated the mild water shortage imbalance in Shangdu County, Dorbod Banner, and Qahar Right Middle Banner. Still, program 6 eliminated the water shortage imbalance in Jining District. The system equilibrium coefficients of schemes 1–6 are 0.152, 0.119, 0.125, 0.135, 0.086, and 0.061, respectively, so schemes 7 and 8 are preliminarily judged to be better. The evaluation results of WRSE quality showed that: plans 1, 2, 3, and 5 worsened the quality level of supply and demand of some units, plans 4 and 6 improved the quality level of supply and demand equilibrium of some units, but only plan 6 improved the quality level of Jining District to a higher level of equilibrium (Figure 5).
Fig. 5

Characteristics of WRSE under different schemes in 2035.

Fig. 5

Characteristics of WRSE under different schemes in 2035.

Close modal

Therefore, based on the two evaluation results, scheme 6 (agricultural water-saving + paddy field to dry land + internal water transfer + external water transfer) is the optimal regulation scheme. The imbalance of water resources in some areas of Ulanqab cannot be fundamentally reversed only by relying on agricultural water-saving, water conversion to drought, and water transfer within the system. In the future, it is necessary to continuously reduce the ILA in overloaded areas, accelerate the construction of the Yellow River diversion project, and accelerate the planning, implementation, and landing of water transfer projects within the system based on agricultural water-saving to improve the spatial equilibrium state of water resources in Ulanqab City.

Diagnostic identification and countermeasures of current situation

In water shortage areas, WRSE theory has become a key concept for water resource allocation (Li et al., 2022a, 2022b). Therefore, the SSPP method was used to identify the WRSE evaluation indicators of Ulanqab City in 2020 (Figure 6), and to identify the key factors affecting WRSE in each region from the perspective of regional classification. When the SSPP value calculated by the correlation number of the sample value of an indicator is judged to be in the inverse potential or partial inverse potential, the index is considered to be the main reason leading to the low level of the overall evaluation level of the system, and can be diagnosed and identified as the vulnerability index of the evaluation unit, and will be the main regulatory factor in the future development process. If the index is determined to be identical potential or partial identical potential, it is considered that the index can be used as a favorable factor for future development.
Fig. 6

SSPP value of WRSE evaluation indicators in Ulanqab in 2020.

Fig. 6

SSPP value of WRSE evaluation indicators in Ulanqab in 2020.

Close modal

In Ulanqab, only water resources per capita and the water demand load of the ecological environment are in the partial reverse state. Regarding per capita water resources, seven regions (Jining District, Fengzhen City, Huade County, Shangdu County, Xinghe County, Qahar Right Front Banner, and Qahar Right Rear Banner) were in a state of inverse potential or partial inverse potential. In the recent 10 years, the population of Ulanqab, except Jining District has shown a declining trend. This result is similar to that of Liu et al. (2023), which investigated that Ulanqab City's economic and social development coordination level showed a downward trend during this period. The lower the level of WRSE, the less coordinated the development of social-economic and environmental systems that are supported by water resources. This uncoordinated development, in turn, leads to inefficient water use, which affects the level of WRSE (Yue et al., 2021). Hence, under the current direction, the per capita water resources of other regions except Jining District may increase slowly. Considering that Ulanqab is located in a semi-arid region, it is difficult to control the water resource index. In addition, with the popularity of ecological civilization, more and more attention has been paid to ecological environmental water consumption, and the ecological environmental water demand load has become an expected and controllable indicator.

Further analysis of the remaining 10 indicators except per capita water resources and ecological environmental water demand. For per capita daily domestic water consumption: Dorbod Banner, Zhuozi County, and Huade County are in a negative or slightly negative trend. These areas should actively promote various water-saving measures to strengthen daily water-saving. For the proportion of irrigated land: Jining District, Liangcheng County, Qahar Right Front Banner, and Qahar Right Rear Banner are in the reverse state, which was consistent with the research findings by Chen et al. (2019). The utilization rate of groundwater development in Jining District is in a reverse condition, while Huade County and Shangdu County are in a partial reverse state. Similarly, the per capita available water supply in Jining District is in a reverse state, while Huade County is in a partial reverse potential state. Regarding water resources utilization, urbanization rate, and population density, only Jining District was in a reverse form. Dorbod Banner and Zhuozi County were, respectively, in the state of partial reverse for the water consumption of 10,000 yuan GDP and farmland irrigation quota. For 10,000 yuan industrial added water consumption value: only Liangcheng County is in the state of the reverse trend.

Suggestions and limitations

Based on the above analysis and the ‘14th Five-Year Plan’ development plan for Ulanqab City, categorized recommendations for water resource regulation measures are provided. For Jining District, it is imperative to strengthen the conservation and utilization of water resources through rigid constraints. Adhering to a strategy that aligns urban planning, land use, population distribution, and industrial development with water availability, Jining District aims to achieve dual control over the total consumption and intensity of water resources. Zhuozi County can incorporate recycled water into the unified water resource allocation system and vigorously promote the utilization of recycled water. Huade County and Shangdu County's vulnerability indicator is the utilization rate of groundwater. In the future, it is essential to establish a robust groundwater environmental monitoring system, intensify efforts in preventing and controlling groundwater pollution, and facilitate a gradual rise in the groundwater table. Liangcheng County needs to enhance the deep treatment of industrial wastewater and the recycling of treated water, striving to achieve comprehensive coverage of industrial water reuse. Qahar Right Front Banner and Qahar Right Rear Banner should have a clear understanding of the fundamental situation of overall water scarcity in the entire banner. It is crucial to implement a total control and quota management system for agricultural irrigation water use. These measures aim to enhance the overall agricultural production efficiency of the watershed's water resources (Wang et al., 2021). Dorbod Banner can implement a tiered water pricing approach with progressive surcharges for residential water use, and comprehensively promote the construction of water-efficient cities to meet standards.

Compared to existing research, this research innovates in two main aspects: The research scope has expanded from assessing the spatiotemporal evolution patterns of WRSE to identifying critical vulnerable factors. The study area has shifted from large-scale economically developed regions to urban areas characterized by water scarcity and ecological vulnerability. This advancement applies to both the research subjects and the domains explored. Research limitations do exist for this study. For instance, as Ulanqab City is located in a semi-arid region, the indicators selected in determining the WRSE quality evaluation system are targeted (Mirdashtvan et al., 2021). However, if applied to other regions, there may be some uncertainties. Therefore, the evaluation index system should be adjusted accordingly when the method proposed in this paper is carried out in other regions. Besides, this study is an evaluation and analysis of WRSE under the condition of a multi-year average. Future studies may consider the influence of wet and dry years. Finally, the impact of external water transfer on the whole system needs to be further studied, such as what new implications will be brought to the overall balance of the system and whether the balance of the water source transfer system will fluctuate (Zhang et al., 2020).

Achieving the goal of WRSE is an inevitable requirement in the current integrated management practices of water resources in China. Based on defining the conceptual framework of WRSE, this study, taking the urban scale perspective, employs the connection number and SSPP method to analyze the spatiotemporal variation process of WRSE status in Ulanqab City. It further identifies the development trends and key influencing factors within different regions. The main conclusions are as follows:

  • (1) The distribution of water resources in Ulanqab City is in a state of mismatch with social and economic development. The Gini coefficients of TWRs and RP, GDP, industrial output value, and ILA are 0.483, 0.481, 0.506, and 0.279, respectively.

  • (2) From 2011 to 2020, the level of WRSE has improved in six counties and has not changed significantly in five counties, among which Jining District has been in a low-level equilibrium state due to its lower resource endowment.

  • (3) By 2035, under the scenario of a combination of measures such as agricultural water conservation, paddy field drought reduction, internal water transfer, and external water transfer, the WRSE status in Ulanqab City reaches its optimum. This should be complemented by the construction of the Yellow River Diversion Project and agricultural water conservation to promote the efficient and intensive use of water resources in the region.

  • (4) The vulnerability indicators of Ulanqab City are per capita water resources and ecological environment water demand load. In the future, the government needs to formulate region-specific water-saving strategies by promoting the reuse of reclaimed water, intensifying prevention of groundwater pollution, and implementing a quota management system for agricultural water use based on the characteristics of each region.

We are grateful for financial support from the National Natural Science Foundation of China (52279005) and Jinan Water Science and Technology Project (JNSWKJ202101). We thank reviewers and editors for very helpful comments and suggestion of the manuscript.

Data cannot be made publicly available; readers should contact the corresponding author for details.

The authors declare there is no conflict.

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