The Spatial-Temporal Matching Characteristics of Water Resources and Socio-Economic Development Factors: A Case Study of Guangdong Province

Abstract

The spatial-temporal mismatch of water resources and socio-economic development in rapidly urbanized regions has been the focus of water resource management, and is one of the main limitations to sustainable development goals (SDGs). Guangdong Province is represented by a highly developed economy and society, and has been undergoing disproportionately rapid population growth during the past two decades. The uneven distribution and spatial mismatch of water resources have aggravated the contradictions between water supply demand. In this paper, we evaluate the matching degree of water resources and social economic elements, detect the spatial-temporal changing pattern of the matching degree, and reveal the changing mechanism using the combined methods of the Thiel index, the space–time Gini coefficient, and the Lorenz curve. The results show that (1) the temporal matching is relatively balanced and reasonable, while the spatial mismatch is prominent and deteriorating constantly, especially the connection between the amount of water and GDP; (2) the water volume pressure is mainly concentrated in the Peral River Delta and eastern and western Guangdong, while water consumption stress is relatively lower in northeastern Guangdong; and (3) the water volume inequality is dominated by an intercity difference and is primarily caused by regional differences. Based on the results, policy implications, such as the implementation of integrated water resource management plans, investment in the development of alternative water sources, as well as enhanced public education and the establishment of a water saving society, have been provided to alleviate the mismatch issue between water elements and socio-economic parameters, and to push the realization of water-related SDGs.

1. Introduction

Water resources are the most essential and inherently cross-sectoral component supporting the compound body of the economy, environment, and society [1,2]. They serve as an enabler for climate resilience, food and energy security, public health, and human well-being [3,4]. Among the 17 goals of the UN 2030 Agenda, SDG6 “Clean Water and Sanitation” represents an ambitious blueprint involving multi-dimensional information, including socially equitable accessibility to water, economically feasible water resources management, and environmentally integrated protection and restoration of water-related ecosystems. Water availability and management directly affect agricultural productivity, which in turn impacts food security (SDG2). Efficient irrigation systems and sustainable water use can improve crop yields and livelihoods for smallholder farmers, thereby contributing to poverty reduction and economic growth (SDG1 and SDG8). Apart from that, adequate water resources that are effectively managed and distributed are crucial for communities, cities, and public health (SDG3, 11). Sustainable water management is essential for preserving ecosystems and biodiversity, and mitigating the impacts of climate change (SDG 13, SDG 14, and SDG 15). Accordingly, water resource-related goals have been listed as the core issues that help achieve the SDGs, and move through and beyond the coronavirus pandemic [1,5]. However, it is critical to acknowledge that the realization of SDGs is increasingly challenged due to the uneven distribution of water resources in time and space, as well as the mismatch of water resources and social economic parameters. For one thing, disproportionate population growth, urbanization, and land use alterations have resulted in stronger water demand, inequity, and scarcity both globally and regionally, endangering water security and restricting socio-economic development, particularly in rapidly urbanizing regions. Furthermore, the uncertainty of climate change and hysteresis of the water cycle response necessitate the systematic inclusion of equilibrium into water decision making. Therefore, systematic research and analysis of the matching characteristics of regional water resources and socio-economic parameters, and their tempo-spatial variation are significant for reasonable water resource management and allocation. Resolving the contradiction of water supply and demand; promoting the multi-dimensional, multi-element, and multi-objective balance of water resources utilization; realizing the optimal allocation between water resources and social economic parameters; and implementing the sustainable development goal of water resources are urgently needed in water-related research and practice.

Currently, the inequality of water resources and the spatially mismatch between water and other elements have been increasingly discussed at various levels, from grid to prefectural, basin, and national level [6,7,8,9]. In China, regional studies focusing on water resource equilibrium have mainly concentrated in the northern arid and semi-arid region [10,11]. Previous researchers addressed that a water inequality can aggravate the water conflicts between different sectors and regions. Although the existing studies have extensively investigated the mismatch issue from different perspectives, in terms of physical water [12], virtual water [13], and the water nexus [14], most of them have only inspected the mismatch characteristics between water and one of the socio-economic factors, and few have taken a comprehensive approach that considers the economy, society, and agriculture. However, since the main consumers of water resources are the economy, society, and agriculture, they are interconnected and have strong contradictions in water use. Furthermore, due to the complexity of the economic and social utilization of water resources, the water resource volume cannot reflect the real local water stress. More aspects of water should be involved in an equilibrium analysis. Accordingly, an integrated analysis of the matching characteristic between the water elements and the economy, society, and agriculture is of great significance for the synthetic water control under multi-objectives.

In terms of research methodology, the Lorenz curve and Gini coefficient are commonly used methods to represent the correlation ratio of the matched objects. They have been widely adopted due to their simple and convenient calculation, as well as their clear physical meaning. Meanwhile, the Lorenz curve-based Gini coefficient enables a comparison analysis between different countries or regions [15,16]. The disadvantage of the Gini coefficient lies in that it can only give one generally matching degree for the entire region, but is incapable of revealing the spatial distribution within the region [17]. To overcome this weakness, we construct a water pressure index to explain the spatial differentiation of water under various parameters. Combined with the strength of the Theil index, the tempo-spatial variation of water resource elements and socio-economic parameters, as well as the water pressure and its driving factors were discussed.

Guangdong Province has maintained its position as the top ranked in China’s economy for 34 consecutive years as off 2022. As the engine of China’s economy, Guangdong Province holds significant strategic importance in the national and regional planning. Water resources are a leading constraint for the comprehensive development of the economy, society, and eco-environment. Although the water resource endowment in Guangdong is better than that of the majority of China, unbalanced regional development remains a major obstacle to socio-economic evolvement and modernized strategic objectives. However, the water scarcity and inequality issues in Guangdong Province have long been overlooked because it is considered a water-rich region. Previous scholars have extensively discussed the water scarcity and matching problems in arid and semi-arid China, as well as the Yangtze River Basin, due to the vast regional differences and social economic contribution. The top three metropolitan regions (JingJinJi, located in northern China, and the Yangtze River Delta, located in the lower part of the Yangtze basin) have been extensively discussed referring to the local water resources and development potential, while the water resource matching condition with the social economic situation in the Greater Bay Area mainly located in Guangdong Province is far from clear [12,15,18,19]. With the continuous construction of the Guangdong Hong Kong Macao Greater Bay Area, the spatial-temporal mismatch between water resources, the economy, population, and land faced by the region will become increasingly acute. Furthermore, the significant wealth disparity, socio-economic complexity and diversity in Guangdong make it a microcosm of China’s overall development contradiction. Therefore, analyzing the coupling of water and socio-economic conditions in Guangdong Province can provide a case study and reference for China. In addition, due to the difference in the scientific and research level, the water resources exploitation capacity and utilization efficiency vary significantly between different regions, leading to an inconsistent distribution of the water endowment and water utilization. Thus, we selected the water resource amount and water utilization to represent the characteristics of the water resource. In terms of socio-economic parameters, Guangdong Province is characterized by a highly developed economy, densely distributed population, and vast cultivated farmland. All three parameters present distinct spatial distributions and are strongly dependent on water resources. Therefore, we coupled the above-mentioned water resource elements and socio-economic parameters, and investigated the match characteristics of the following six connections: water resource amount and Gross Domestic Production (WA-GDP), water resource amount and population (WA-P), water resource amount and arable land area (WA-AL), water consumption and GDP (WC-GDP), water consumption and population (WA-P), and water consumption and arable land area (WA-AL).

The objectives of this paper were as follows:

(1)

Reveal the matching degree and its temporal-spatial dynamics between water elements and socio-economic parameters in Guangdong Province.

(2)

Identify the driving factors that contribute to regional differences in spatial matching.

(3)

Provide policy recommendations to optimize the allocation of water elements and socio-economic parameters, thereby promoting the development of the regional economy.

This paper fills a gap in our theoretical understanding of the intricate relationship between water resources and socio-economic factors in a highly developed and water-rich region. It not only integrates water resource management with socio-economic development, but also provides valuable insights into specific implementation strategies for attaining the regional targets of SDGs2030 by identifying water resource management variations and disparities. On a practical level, this research informs policymaking and interventions designed to optimize the planning and allocation of water resources in Guangdong Province.

2. Material and Methodology

2.1. Study Area

Guangdong Province is located on the southeastern coast of China, between 109.65–117.32° E and 20.22–25.52° N, bordering the South China Sea. The vast majority of the province is controlled by subtropical humid monsoon climate with abundant rainfall (Figure 1). During the 24 years from 1997 to 2020, the average annual total water resources of the province reached 187.3 billion m³, while the total water consumption decreased from 43.95 billion m³ in 1997 to 40.51 billion m³ in 2020, indicating an inverted V-shaped trend [20]. The proportion of water consumption of various sector has changed dramatically. Since 1989, Guangdong’s gross domestic production (GDP) has ranked first in the country, accounting for 1/8 of the country’s total economic output [21]. According to the seventh national population census, there are up to 126 million permanent population living in Guangdong Province, mainly concentrated in the Pearl River Delta. This number continues to grow due to the continuous immigration. In recent years, with the increase in the intensity of development and construction and the intensification of urbanization, the cultivated land area in Guangdong Province has shown a distinct reduction.

2.2. Data Source

The water-related data from 2000 to 2020 were collected from the Water Resources Bulletin of Guangdong Province and the Statistical Yearbook of Guangdong Province of the corresponding year. The multi-phase remote sensing monitoring data of land use with 30 m resolution were gathered from the Data Center for Resources and Environmental Sciences Chinese Academy of Sciences (https://www.resdc.cn (accessed on 11 December 2023)) with 5-year temporal slice in 2000, 2005, 2010, 2015, and 2020, based on which the agricultural land was extracted. Meanwhile, the urbanization rate represented by the urbanization ratio was estimated based on the socio-economic statistic data.

2.3. Method

2.3.1. Lorenz Curve

Lorenz curve was first introduced by the American statistician Lorenz Gurves (Lorenz) in 1905. It was first used to intuitively depict the inequality degree of income distribution on the graph. Specifically, in the two-dimensional coordinates, if we plot the cumulative percentage of population (P) as the x-axis, the cumulative proportion of income (L) is projected to the y-axis (Figure 2) [22]. The estimated line formed by the corresponding scattered points is the Lorenz curve (line M), while the Line N represents the absolute mean curve of the distribution. The farther the curve M deviates from N, the larger the area surrounded by the two (S_A) is, and the worse the matching degree of the two resources is. In the field of water resources, the cumulative percentage of socio-economic elements can be plotted along x-axis, while the cumulative percentage of water resource elements can be plotted along y-axis, to obtain the corresponding Lorenz curve of various pairs, characterizing the degree of inequality between water resource elements and socio-economic elements.

2.3.2. Gini Coefficient

The Gini coefficient was proposed by Italian economist Gini Conrado to evaluate the inequality in the distribution a particular parameter in a given population. Due to the uneven distribution of water resources in time and space, they follow a very similar mathematical law to that of income distribution, Therefore, Gini coefficient, in conjunction with the Lorenz curve, is widely adopted in the matching degree analysis between water resources and social economic factors.

The Gini coefficient can be expressed as [23]

$$G=S_A/\left(S_A+S_B\right)$$

(1)

$$S_A=0.5-S_B$$

(2)

$$S_B={\int }_0^{1}Mdx$$

(3)

where G means the Gini coefficient; S_A refers to the extent enclosed by Lorenz curve (M), L, and the absolute mean curve (N); while S_B indicates the area fenced by Lorenz curve, x-axis, and x = 1 line.

Gini coefficient ranges from 0 (total equality) to 1 (complete inequality). A smaller G suggests a higher level of balance between water resources and social economic level, and vice versa. According to the matching degree division criteria stipulated by the United Nations Program, we can divide the match state into 5 groups (

Table 1. Matching degree division criteria.

G Range	(0, 0.2)	[0.2, 0.3)	[0.3, 0.4)	[0.4, 0.5)	[0.5, 1)
Match status	Balanced	Relatively balanced	Reasonable	Relatively uneven	Uneven

).

When this method is used to calculate the Gini coefficients of water resources and social economic parameters, the specific calculation formula is as follows [23]:

$$G_N={\sum }_{i=1}^n(W_i{R}_{i+1}-W_{i+1}{R}_i)$$

(4)

where W_i refers to the cumulative percentage of water resources on the ith region in the total provincial water resources, for example, water resources amount; R_i refers to the cumulative percentage of social economic parameter, for example, GDP of the ith region in the total regional amount.

2.3.3. Theil Index

Theil index originated in 1967, when the concept of entropy in information theory was adopted to measure income inequality [24]. The greater the deviation from the average, the stronger the inequality of the income. According to the principle of Theil index, the overall difference (T) can be decomposed into inter-regional difference (T₁) and intra-regional difference between different cities (T₂), and the contribution of T₁ and T₂ to the overall difference can be estimated by their ratio to the overall difference. The expression of Theil index is as follows [8]:

$$T=T_1+T_2$$

(5)

$$T_1=\sum _{i=1}^n{W}_i\ln \frac{W_i}{P_i}$$

(6)

$$T_2=\sum _{i=1}^n{W}_i\left(\sum _{j=1}^m{W}_{\mathit{ij}}\ln \frac{W_{ij}}{P_{ij}}\right)$$

(7)

$$F_1=\frac{T_1}{T}$$

(8)

$$F_2=\frac{T_2}{T}$$

(9)

where n and m represent the number of economic regions and subregions, respectively; W_i and P_i mean the proportion of water resources and social economic parameter of region i; and W_ij and P_ij indicate the proportion of subregion j in total water resource and social economic parameter of Guangdong. A larger Theil index denotes higher regional difference and inequality of the water resource and social economic parameter. F₁ and F₂ reveal the contribution rate of different sources between regions and subregions.

3. Results

3.1. Temporal Match Characteristics

According to the results of the Gini coefficient and the Lorenz curve, the time matching between water resources and socio-economic factors in Guangdong Province from 2000 to 2020 ranged generally from a balanced to a reasonable level. No distinct change was detected during the study period (

Table 2. Temporal averaged Gini coefficient between water resources and socio-economic factors in Guangdong Province from 2000 to 2020.

Match Object	Temporal Averaged Gini	Level
WA-P	0.108	Balanced
WA-GDP	0.339	Reasonable
WA-AL	0.100	Balanced
WC-P	0.089	Balanced
WC-GDP	0.368	Reasonable
WC-AL	0.020	Balanced

, Figure 3 and Figure 4). Among them, the matching degree between the water resource elements and GDP showed the highest uneven status, with Gini coefficients valued at 0.368 (water amount–GDP) and 0.339 (water use–GDP), respectively. Meanwhile, the farthest Lorenz curve from the absolute average could be witnessed. During the study period, the total GDP of Guangdong Province increased from 108.1021 billion yuan in 2000 to 1107.6094 billion yuan in 2020, with an average annual growth rate of 10.94%. The climate and hydrological conditions, however, were relatively stable. For example, the total water resources fluctuated between 1500 and 2500 × 10⁸ m³, while the water consumption decreased year on year. Therefore, the contradiction between water consumption and GDP was more prominent.

3.2. Spatial Match Characteristics

Compared with the temporal distribution of water resources, the spatial balance of the matching between water resources and social economic factors was in a poor situation (

Table 3. Spatial Gini coefficient between water resources and socio-economic factors in Guangdong Province in 2000, 2010, and 2020.

Match Object	2000	2010	2020	Averaged Gini	Level
WA-P	0.477	0.528	0.585	0.518	Uneven
WA-GDP	0.683	0.736	0.736	0.725	Uneven
WA-AL	0.220	0.211	0.241	0.213	Relatively balanced
WC-P	0.224	0.215	0.238	0.231	Relatively balanced
WC-GDP	0.433	0.457	0.459	0.453	Relatively uneven
WC-AL	0.298	0.351	0.361	0.353	Reasonable

, Figure 5). Similar to the temporal match, among all the connections, the spatial match between the water resource amount and GDP showed the largest disequilibrium condition, with a spatial Gini as high as 0.736 in 2020. A second unbalanced connection was in the match between the water resource amount and the population, and its spatial Gini in 2020 reached 0.585. This indicates a high imbalance between the economic and population pattern and the natural distribution of water resources. When it comes to the match between water consumption, GDP, and population, the spatial Gini coefficients were between 37% and 60% lower compared with their connections with the water resource amount, respectively. Higher water use efficiency, efficient water allocation strategies, and better water saving and treatment technologies incorporated with the economic developed and populous region alleviated the local water shortage limitation, and therefore improved the match pattern between water consumption and the two parameters. The spatial Gini coefficients of total water resources and arable land, and water consumption and arable land were 0.241 and 0.361, respectively, and were evaluated as “relatively balanced” and “reasonable” levels in 2020.

The temporal dynamics of the spatial match was analyzed and the results are shown in Figure 6. A clear trend of deterioration is revealed along the study period, especially the match between the water resource amount and population. The spatial match of water resource elements and GDP distinctly decreased.

The water consumption and cultivated land had an obvious change point on the Lorenz curve, while the total water resources and cultivated land curve was smooth and the slope change was small. Both these results indicate that water resources and cultivated land have a strong match in natural endowment, but human activities are intensifying the contradiction between water resources and cultivated land. The cultivated land distribution pattern and water resources distribution pattern in Guangdong Province matched each other. In 2020, the cultivated land area of five cities in western Guangdong accounted for 37.75% of Guangdong Province, while the nine cities in the Pearl River Delta accounted for only 29.39%. In terms of water resources distribution, there are more water resources in northern and western Guangdong, so the spatial matching between total water resources and cultivated land is the highest.

Taking 2020 as an example, the total GDP of the Pearl River Delta region accounted for 80% of the total economic volume of Guangdong Province, and the total population accounted for 61.97% of the total population of Guangdong Province, while the total economic volume of eastern Guangdong, western Guangdong, and northern Guangdong accounted for 6.67%, 7.73%, and 6% of the total, respectively, and the population accounted for 12.92%, 12.5%, and 12.61%, respectively. At the same time, the total water resources of the five cities in northern Guangdong accounted for 44.58% of the total water resources of Guangdong Province, while the total water resources of the nine cities in the Pearl River Delta was only 31.76% of the total.

3.3. Water Pressure

The single-point slope (k) of a Lorenz curve can reflect how much water is allocated to different cities to support its socio-economic factors. The smaller the slope is, the smaller the amount of water resources consumed by each portion of socio-economic factors is, and the stronger the water resource intensity the region is confronting because the region has to manage the same task with a relatively smaller water resource. Taking Shenzhen as an example, the slope of Shenzhen’s water resource amount–GDP Lorenz curve in 2020 was 0.20, indicating that Shenzhen used 0.20 units of water resources to support the production of 1 unit of GDP, showing extremely high water pressure. According to this theory, the water resource pressure in various cities in Guangdong Province in 2020 was estimated and is shown in Figure 7. The core cities of the Pearl River Delta—Guangzhou, Shenzhen, Dongguan, Foshan, etc., tend to bear the highest pressure in the perspective of the water resources amount (Figure 7a–d). The water pressure caused by the GDP displayed a similar spatial pattern with that caused by population, except for part of western Guangdong. The water amount pressure in the core area of the Pearl River Delta and eastern Guangdong was higher than that of other prefecture-level cities in Guangdong Province, which is closely related to the population siphon effect of the Pearl River Delta and the traditional concept of people returning to their hometown in eastern Guangdong. The water amount pressure caused by cultivated land tended to be high in eastern and western Guangdong, and the western part of the Pearl River Delta. In terms of water consumption, the water pressure in the core areas of the Pearl River Delta was relatively low compared with that of the rest of Guangdong Province (Figure 7e–h). Although the water consumption pressure related to GDP and population tended to be higher in the Pearl River Delta region, the arable land elevated the water consumption pressure of the surrounding region.

3.4. Water Equality

The Theil index between water resource elements and socio-economic elements in Guangdong Province is given in

Table 4. Theil index and the contribution of the regional and subregional difference in 2000, 2010, and 2020.

Match Object	Year	T	Intercity Difference		Regional Difference
			T1	F1/%	T2	F2/%
WA-GDP	2000	0.75	0.47	62	0.29	38
	2010	1.08	0.74	69	0.34	31
	2020	1.11	0.77	69	0.34	31
WC-GDP	2000	0.32	0.18	57	0.14	43
	2010	0.35	0.22	62	0.13	38
	2020	0.36	0.22	62	0.13	38
WA-P	2000	0.37	0.2	55	0.17	45
	2010	0.47	0.26	56	0.21	44
	2020	0.6	0.36	60	0.24	40
WC-P	2000	0.08	0.02	23	0.07	77
	2010	0.07	0.02	29	0.05	71
	2020	0.09	0.04	41	0.05	59
WA-AL	2000	0.08	0.05	64	0.03	36
	2010	0.08	0.04	50	0.04	50
	2020	0.10	0.05	51	0.05	49
WC-AL	2000	0.18	0.08	47	0.09	53
	2010	0.28	0.11	41	0.16	59
	2020	0.33	0.12	38	0.20	62

. The overall difference (T) between each group of elements generally rose from 2000 to 2020, indicating the deterioration of equality. The water equality of GDP was at the lowest level, with the overall difference increasing from 0.70 in 2000 to1.15 in 2020, followed by that of population, rising from 0.37 to 0.60 during the same period. The water equality of arable land was relatively higher, especially the match between the amount of water and the arable land.

The intercity difference dominated the inequality in the match of the water amount and water consumption with GDP, and the controlling force became stronger. In the connections between water elements and population, the intercity difference tended to increase and become more influential to the water amount, while regional differences played a dominant role in water consumption, but with decreasing controlling force. The intercity difference used to lead the WA–AL inequality in 2000, but its contribution decreased rapidly. In fact, the intercity and regional differences have become of comparable strength in 2010 and 2020. The WC–AL inequality was mainly induced by a regional difference, and the regional difference became more and more dominant.

4. Discussion

4.1. Regional Matching Degree

According to the physical landscape and economic characteristics, Guangdong Province can be divided into four parts: the highly developed Pearl River Delta region, northern mountainous and hilly Guangdong, western Guangdong mesa, and eastern mountainous and coastal Guangdong. The comparative analysis of the proportion of water elements and socio-economic parameters in the four regions of Guangdong are given in Figure 8. As the growth capital of the regional economy and population, the total amount of water resources in the Pearl River Delta region is relatively low, while the economic development level in the eastern, western, and northern regions of Guangdong, which have rich water resources, is relatively low. Spatially, the Pearl River Delta has the largest water resources burden, with only 32% of water resources supporting nearly 81% of the province’s GDP, 62% of the population, and 37% of the cultivated land of the entire province in 2020. On the contrary, northern Guangdong demonstrates the most prominent water advantage in 2020, using 41% of water to produce only 5% of GDP, feed 11% of the population, and irrigate 18% of the arable land. Compared with northern Guangdong, the advantages of water resources in western and eastern Guangdong are relatively small. One proportion of water in eastern Guangdong sustained a 1.6 proportion of the population and 0.75–0.88 proportion of the economy and agriculture, while in western Guangdong one proportion supported 0.42, 0.74, and 1 proportion of the economy, population, and arable land, respectively, in 2020.

Due to the rapid development and the siphon effect of the Pearl River Delta, the water pressure has been booming in the Pearl River Delta, while the other three regions have been experiencing water stress remission during the study period.

4.2. Urbanization Level and Spatial Matching Degree

The spatial matching characteristics of the six groups were plotted against the urbanization level and are shown in Figure 9. Here, the urbanization development level is characterized by the urbanization rate of the urban population in the total population. Generally, the urbanization level was inversely proportional to the matching degree, except for the WA–AL and WC–AL connections. A higher urbanization level is represented by the unbalanced corporation of water elements and socio-economic parameters. This is particularly true for the water resource amount and GDP matching pattern. In the early stage of urbanization, the spatial matching degree decreased significantly with the urbanization process. However, when the urbanization rate reached 70%, the deterioration rate of the spatial matching degree slowed down, indicating the marginal effect of urbanization development in the water mismatch with the economy and population. The improved water-saving technology hatched by the high scientific and research investment during the highly developed urbanization stage promoted water efficiency. Urbanization tends to relieve the water stress of agriculture (Figure 9e,f), mainly because the expansion of land used for construction occupied the agricultural land, resulting in lower agricultural water needs. In addition, the progress in irrigation techniques along with urbanization caused water consumption to decline in agriculture, and mitigated the water stress.

4.3. Water Sustainability

The spatially uneven distribution of water resources has become a key global issue threatening the water-related SDGs (Sustainable Development Goals) and restricting the sustainable development of society and the economy. Guangdong has been the largest economy of China for more than 30 consecutive years. The spatial distribution of matching characteristics, pressure, and inequality between water elements and socio-economic parameters can provide valuable advice on the allocation and management of water resources, which would then promote the water-related SDGs (SDGs 1, 2, 3, 6, and 8), sustainable cities and communities SDGs (SDGs 11), and SDGs related to ecosystems, biodiversity, and mitigating the impacts of climate change (SDG 13, SDG 14, and SDG 15). Apart from the mismatch of water and socio-economic parameters, Guangdong has been suffering from severe water scarcity and pollution [25,26]. In general, the water resources security situation is relatively severe in the relatively developed core area of the Pearl River Delta, as well as the eastern and western coastal areas of Guangdong. The huge wastewater discharge and harmful discharge relationships from primary industry are the main reasons for the local and seasonal water scarcity, especially in the coastal Guangdong region [7,27]. Strictly controlling the water consuming industry, improving water saving technology, and promoting scientific and research investment in professional treatment techniques should be adopted to effectively mitigate the wastewater problem. Additionally, although the water utilization efficiency has been increasing in the last decade, the treated and reclaimed water is mainly used for recharging the water environment, while the industrial and municipal use is supposed to be upgraded [28,29].

As shown in the results, the spatial equilibrium of water consumption is much more robust than the water amount. This is mainly because the potential of water consumption stemmed from the higher water use efficiency and improved technique of water application [28]. The water resource amount, however, is relatively spatially stable. Thus, strengthening the water use efficiency is the most effective way to improve water equality and sustainability.

4.4. Policy Implications

The imbalance between water resources and social economic parameters highlights the development of scientifically sound policy implications to address the challenges. One potential solution is the implementation of integrated water resource management plans that account for the complex interplay between water resources and economic growth. These plans should incorporate comprehensive assessments of the quantity and quality of available water resources, as well as the economic needs of the region. To achieve sustainable water management, such plans should also consider the impacts of economic activities on the local water supply, and the promotion of measures to promote water conservation, reuse, and recycling. For example, as the main water provider to the Great Bay Area, Dongjiang River Basin is confronting unprecedented water pressure. Dongjiang holds 18% of the total water resources of the province but supports 28% of the water consumption and 48% of the GDP. The utilization rate of water resources continuously challenges the internationally recognized alert line of 40%. On the contrary, the water volume of Xijiang River is approximately 10 times that of Dongjiang River, and the utilization rate of water resources is only approximately 1.3% [20]. Transferring water from Xijiang River would highly relieve the water pressure of the Greater Bay Area. The water transfer program plays an important role in optimizing the alignment of water resources with economic and social factors. What quantity and scale of water resource allocation is needed to achieve fairness in water resources at the economic and social levels? This study has provided an estimation and scientific references for this issue, and serves as an evaluation tool for water transferring projects.

Moreover, to address the water resource mismatch, investment in the development of alternative water sources, such as desalination and wastewater treatment, should also be considered. In this way, additional water resources can be generated, helping to alleviate the pressure on existing resources and support economic growth. As environmental protection gains increasing attention in China, wastewater treatment and reuse have emerged as crucial industries, occupying a position similar to that of tap water production and supply. However, despite the growth of these industries, many areas in Guangdong remain underdeveloped and lack investment, resulting in low rates of wastewater treatment and reuse compared to rates in developed countries.

The enhancement of public education and the establishment of a society focused on water conservation and reduced pollution would be another policy implication. This is highly dependent on the public’s understanding of the value of water and their willingness to acknowledge its scarcity. Thus, it is critical for the government to prioritize efforts to improve public education, encourage modifications in water usage behavior, and thoroughly examine all aspects of the water crisis. Given that the public has already established water consumption patterns, it is crucial for the government to adopt economic, political, and technological countermeasures to motivate the public to conserve water. An effective campaign for water saving should highlight the positive impacts of the government’s decisions. Additionally, the water market and pricing system can serve as powerful incentives to encourage the public to conserve water, as many people are more concerned with their water bills than water waste. For example, previous research investigated the potential of water pricing mechanisms to incentivize conservation and reduce water waste, and found that such measures could be effective in promoting more sustainable water use practices [30]. By regulating their water consumption and trading their surplus water, the public can save money and earn additional income, thereby stimulating their enthusiasm for water conservation [31,32]. As such, promoting public enthusiasm for water saving should be a key objective of the government’s initiatives.

The implementation of these measures can enable the government at different levels to more effectively address issues related to water saving, wastewater treatment, and reuse, etc. By improving policy frameworks and investing in these industries, Guangdong can improve its water management capabilities, reduce water pollution, and alleviate the mismatch problem between water resource elements and socio-economic parameters, and can promote the sustainable development of the compound water–economy–ecology system.

5. Conclusions

Based on the characteristics of the tempo-spatial match between water resource elements (water resource amount, water consumption) and socio-economic parameters (population, GDP, and arable land area), this paper analyzed the water pressure and equality in Guangdong Province from 2000 to 2020, and results clearly showed the following.

Firstly, the temporal match between water resources and socio-economic indicators was found to be relatively balanced and reasonable. On the other hand, the spatial mismatch was in a poor situation, although it has been decreasing over time. It is important to note that the spatial match between the water amount and GDP showed the worst status, indicating a mismatch between economic development and water resource availability.

Secondly, in terms of the spatial distribution of the amount of water resources, the pressure was mainly concentrated in the Pearl River Delta due to economic and demographic pressure. In contrast, the water consumption stress in northeastern Guangdong was relatively higher, suggesting variations in water usage patterns across different regions.

Furthermore, this study highlighted the presence of significant spatial inequalities, particularly in the matches between the amount of water and the GDP, as well as the amount of water and the population. Inter-city differences predominantly drive the water volume inequality, whereas regional disparities play a more significant role in shaping water consumption inequalities.

These findings underscore the necessity for targeted policies and interventions to address the imbalanced spatial distribution of water resources and promote sustainable water management practices, such as water transfer projects and water resource guarantee engineering. Additionally, efforts should be made to reduce the disparities in water consumption patterns and ensure equitable access to water resources across different regions, to facilitate the harmonious and sustainable development of water resources and the social/economic development in Guangdong.