An Evaluation of the Sustainability of the Urban Water Resources of Yanbian Korean Autonomous Prefecture, China

Abstract

The availability of water resources is crucial to maintaining the sustainability of urbanization. Calculating the ecological footprint of water (EF_W) is one of the ways to realize the protection of water resources in the process of urbanization. The minor settlements in border areas have been the focus of China’s urbanization development but have rarely received research attention. The objective of this study was to develop an improved model of the ecological footprint of water (EF_W) to assess the water security status of urban areas in Yanbian Korean Autonomous Prefecture (YKAP), and to demonstrate its authenticity compared with the traditional ecological footprint of water (EF_W). The results showed that water pollution is the main reason for the increase in the EF_W in each city, and the ecological water carrying capacity (EC_W) showed strong fluctuations with the interannual variation in precipitation. Although the overall availability and quality of water resources are within safe limits, there are significant differences among cities, and water pollution poses a direct threat to the health and well-being of urban dwellers in some cities. Therefore, it is recommended that water resource management agencies adjust their water supply strategies based on the data from the EF_W model, control wastewater discharge, improve their management systems and take urban economic development into account. This will significantly improve the sustainable management of water resources and ensure the health and well-being of urban residents.

1. Introduction

Water resources are key for human survival, social development and economic growth. Most of the world’s freshwater resources are found in glaciers or permanent snow and cannot be used by humans. Only 0.26% of freshwater resources are distributed in lakes and river systems [1,2]. The available freshwater resources are limited. The global population has grown to 7.5 billion people, and the continued growth of the population and urbanization will lead to long-term water-related problems [3]. China is currently the fastest country in terms of urbanization [4]. As of 2020, the urbanization rate has reached 63.89% [5]. Household water, production water and ecological water use a higher proportion of total water consumption, so direct water often becomes the focus of public attention because it directly affects the reserves of water resources [6]. The sustainability of urban water resources affects both urban residents and the wider community, which determines the water supply strategy of the regulatory agency and affects the environmental, social and economic development of the region. Therefore, the sustainability of water resources is critical in today’s world.

The Yanbian Korean Autonomous Prefecture (YKAP) is located in the transnational urban agglomeration of the Tumen River in northeastern Asia [7]. It is adjacent to major port cities such as Vladivostok and Luojin. It is an important trade cooperation partner of Russia’s Far East and the Luoxian Economic Zone of the Democratic People’s Republic of Korea (DPRK) [8]. YKAP represents an important part of the Chinese “Belt and Road” strategy, which has also been identified as a key component of the international China–Russia–DPRK–Mongolia channel [9,10]. Therefore, the development of YKAP’s cities based on the sustainability of water resources is of great importance to three countries.

The scale of urbanization will be further expanded in the future, and the security of water quantity and water quality will face unprecedented pressure [11]. However, the lack of interactions among basic users, individual water resource managers and policy-makers has led to a decrease in water volume and an increase in water pollution, which have increased the risks to all the developmental sectors that depend upon them. There are many methods of assessing water sustainability, but most of them are not sufficient to assess the differences in water sustainability among cities caused by different environmental conditions and production activities. One of the methods identified by the European Union for effectively assessing the sustainability of water resources is the assessment of the ecological footprint of water (EF_W) [12]. The concept of the ecological footprint (EF) was proposed by William and introduced by Wackernagel in the field of assessing water resources [13,14]. The current research on EF_W has concentrated on industrial production [15,16,17,18,19,20] and agricultural security [21,22,23,24], whereas quantitative assessments of urban water security are lacking [25]. However, the problem of water loss and polluted water have received increasing attention, which have made water companies, politicians, urban planners and other stakeholders use the concept of the ecological footprint of water to determine the direction of investment and policy implementation. For these reasons, examining the impact of adjusting the urban water supply and proposed solutions from quantitative perspectives is an important task for the application of EF_W analysis in urban areas [26]. Water utilities can evaluate water consumption and the reserves of water resources as factors influencing the planning process of urban scale, land use and accommodating the population [27]. Water pollution damages aquatic ecosystems and poses a threat to residents’ health and well-being. It is necessary to adjust the water treatment technology to ensure the safety of residents’ water supply [28]. In the process of urban water management, the EF_W model, which links the water supply, water use and the amount of polluted water, can serve as a cognitive tool for decision-making departments to improve water security and ultimately affect conservation activities [26,29].

The current research on the sustainability of urban water resources has focused on calculating the water footprint in central cities, such as Beijing (China) [30], Berlin (Germany) [31], Seville (Spain) [32], Dalian (China) [33] and Tehran (Iran) [34], but few reports have considered border cities. Most of the studies on the ecological footprint of water in these cities have focused on the virtual water generated by food consumption [35,36]. However, government agencies and water management units have a limited impact on virtual water, and direct water use will have a greater impact on water management. At present, decision-making units support existing water resource management models by collecting large amounts of data on water supply and water use, and applying the data to traditional models of the ecological footprint of water. This may reduce the authenticity of assessments of the sustainability of water resources because of a failure to calculate the water pollution data. This limits the wide application of models of the ecological footprint of water in urban water resource management. Therefore, the purpose of this study was to propose an improved model to improve the calculation of the water footprint of urban water pollution by adjusting the method proposed by William et al. [13]. We quantitatively assessed the amount of water consumed by water pollution by incorporating the main pollutants into the model and calculating the amount of water required to degrade them, based on available data and overall water pollution indicators. The proposed model has been designed to objectively assess the sustainability of urban water resources, support the decision-making process of urban water management units and safeguard the health and well-being of residents.

2. Materials and Methods

2.1. Study Area

The YKAP is located in the eastern part of Jilin Province, China (41°59′–44°30′ N, 127°27′–131°18′ E). It has a total land surface of about 43,300 km². The prefecture has eight cities under its jurisdiction: Yanji, Longjing, Helong, Tumen, Hunchun, Dunhua, Wangqing and Antu (Figure 1). The YKAP is situated in the moderate temperate zone and has a humid monsoon climate with an average annual amount of precipitation of about 274 × 10⁸ m³. There are four main river systems present in the prefecture: the Tumen River, the Songhua River, the Suifen River and the Mudan River [37]. According to the “Outline of China’s Tumen River Regional Cooperation and Development Plan”, the YKAP will become an important gateway for China to provide access to the Sea of Japan [38]. Evaluating the water resources based on an improved model of the ecological footprint of water (EF_W) is an important method for realizing the sustainable development of the cities of the YKAP and is an important way to ensure the implementation of the national strategy.

2.2. Data

Demographic data as well as information about the GDP of the YKAP over the period 2005–2016 were acquired from Jilin Province’s statistical yearbook and Yanbian Korean Autonomous Prefecture’s statistical yearbook [39,40]. Water resource data, including the amount of precipitation, total water consumption, per capita water consumption, total water resources, COD emissions, NH₃-N emissions and the comprehensive water consumption rate, as well as additional regional data for the period 2005–2017, were derived from Yanbian Korean Autonomous Prefecture Water Resources Bulletin [41]. However, due to the lack of data on COD emissions and NH₃-N emissions for 2017–2019, the final ecological footprint of water resources and the ecological footprint of the aquatic environment were only calculated up to 2016.

2.3. Methods

2.3.1. Traditional Ecological Footprint Model of Water Resources

The traditional ecological footprint of water resources refers to the consumption level of water resources for production and domestic use, and can be described by the following equation [42,43]:

$${EF}_W {=N\times ef}_w=N\times \gamma \times \frac{W_R}{P_W}$$

(1)

where EF_W is the ecological footprint of water resources (Appendix A) (hm²), N is the total population, ef_w is the per capita ecological footprint of water resources (hm²/per person), W_R is the per capita consumption of water resources (m³), P_w is the global average availability of water resources (m³·hm⁻²) and γ is the global equilibrium factor of water resources, which is the ratio of the average productivity of land with water resources to the average productivity of all different types of agricultural land in the world [44] (

Table 1. Changes in the global equilibrium factor of water resources.

	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019
γ	5.228	5.236	5.244	5.251	5.259	5.267	5.274	5.282	5.29	5.297	5.305	5.313	5.321	5.329	5.337

). According to previous research, the value of P_w is 3140 m³·hm⁻².

The ecological carrying capacity of water resources provides an estimate of the amount water resources available to sustain maximum socio-economic development [45,46,47] and is defined as

$${EC}_W {=N\times ec}_w=0.4\times \gamma \times \Phi \times \frac{W}{P_W}$$

(2)

where EC_W is the ecological carrying capacity of water resources (hm²), ec_w is the per capita ecological carrying capacity of water resources (hm²/per person), W is the total volume of water resources (m³) and Φ is the factor of water resource outputs, which is the ratio of the production capacity of regional water resources to the production capacity of global water resources [48] (

Table 2. Water resource yield factors of counties in Yanbian prefecture.

	Yanji	Tumen	Dunhua	Longjing	Helong	Wangqing	Hunchun	Antu	Yanbian
Φ	0.573	0.693	0.946	0.408	0.583	0.639	1.126	0.932	0.809

). If the utilization rate of water resources in a country or region exceeds 30–40%, deterioration in the environmental quality is likely to happen. Therefore, 60% of the total water resources were deducted from the calculation [49].

$${ED}_W{(ES}_W{) =EC}_W{-EF}_W$$

(3)

The ecological surplus (ED_W) and ecological deficit (ES_W) of water resources refer to the quantitative relationship between utilization and the available reserves of water resources [50,51,52]. An ED_W value greater than zero indicates that water resources in the region are not being depleted.

$${\mathit{EPI}}_W=\frac{{\mathit{EF}}_W}{{\mathit{EC}}_W}$$

(4)

The ecological pressure index (EPI_W) provides a measure of the ecological health and basically quantifies the ecological pressure on regional water resources [53,54]. Higher values of EPI_W are indicative of an increasing chance of deterioration in the environmental quality and ecological health. Six categories of EPI_W values can be discerned [55,56] (

Table 3. Division of water resources ecological pressure levels.

Grade	Ecological Pressure Index	Token State
1	<0.50	Very safe
2	0.51–0.80	Relatively safe
3	0.81–1.00	Slightly unsafe
4	1.01–1.50	Relatively unsafe
5	1.51–2.00	Very unsafe
6	>2.01	Extremely unsafe

).

$${\mathit{EF}}_I=\frac{{\mathit{EF}}_W}{G}$$

(5)

The utilization efficiency (EF_I) is a measure of the relationship between the ecological footprint and the value of regional unit outputs expressed in GDP (G) [57]. High EF_I values point towards a low utilization efficiency of the water resources.

The load index provides information about the development prospects of water resources in the study area [58] and is defined as

$$C=S\times \frac{\sqrt{N\times G}}{W}$$

(6)

$$S=\{\begin{array}{cc}1.0& \left(R\le 200\right)\hfill \\ 1.0-0.1\left(R-200\right)/200& \left(200<R\le 400\right)\hfill \\ 0.9-0.2\left(R-200\right)/400& \left(400<R\le 800\right)\hfill \\ 0.7-0.2\left(R-200\right)/800& \left(800<R\le 1600\right)\hfill \\ 0.5& \left(1600<R\right)\hfill \end{array}$$

(7)

where C is the load index of water resources, S is the precipitation coefficient and R is the amount of precipitation [59]. The value of C can be categorized into several classes (

Table 4. Division of the ecological load levels of water resources.

Grade	C Value	Water Consumption	Development Potential	Development Prospects
1	>10	Higher	Smaller	Very difficult
2	5–10	High	Small	Difficult
3	2–5	Medium	Large	Medium
4	1–2	Low	Larger	More suitable
5	<1	Lower	Very large	Appropriate

).

2.3.2. The Improved Ecological Footprint Model

The traditional ecological footprint model of water resources can be improved by incorporating information about water pollution. Chemical oxygen demand (COD), ammonia nitrogen (NH₃-N), sulfur dioxide (SO₂) and nitrogen oxides (NOx) are the general indicators of water pollution described in the “Water Pollution Prevention and Control Action Plan” of China’s 13th Five-Year Plan [60]. Based on the availability of water resource bulletins and water pollution data in Yanbian Prefecture, we selected chemical oxygen demand (COD) and ammonia nitrogen (NH₃-N) as the main parameters to improve the traditional ecological footprint model. The maximum pollution footprint was chosen as the most suitable indicator, as both pollutants contribute to the overall environmental impact. The improved EF model can be described as

$${\mathit{EF}}_W {=\mathit{EF}}_W{+\mathit{EF}}_{\mathit{WP}}$$

(8)

$${\mathit{EF}}_{\mathit{WP}}=\mathit{max}\left({\mathit{EF}}_N{,\mathit{EF}}_{\mathit{COD}}\right)$$

(9)

$$\begin{gathered} {\mathit{EF}}_N=\gamma \times \frac{C_N}{P_N} \\ {\mathit{EF}}_{\mathit{COD}}=\gamma \times \frac{C_{\mathit{COD}}}{P_{\mathit{COD}}} \end{gathered}$$

(10)

where EF_w is the overall ecological footprint of water resources (hm²); EF_WP is the ecological footprint of water pollution (hm²); EF_N is the ecological footprint of ammonia nitrogen water pollution; EF_COD is the ecological footprint of organic matter water pollution; C_N and C_COD are the amounts of ammonia nitrogen and organic matter discharged into the water in the study area, respectively; and P_N and P_COD are the global average degradation capacities of ammonia nitrogen and chemical oxygen demand in water, respectively.

The global average degradation capacity of ammonia nitrogen and organic matter in the aquatic environment was calculated using the upper limit of ammonia nitrogen concentrations (NH₃-N ≤ 1.0 mg/L) and chemical oxygen demand (COD ≤ 20 mg/L) for the Class III water standard of China’s Surface Water Environmental Quality Standard (GB3828-2002) and the global average production capacity of water resources. The values of P_N and P_COD were 3.145 × 10⁻³ t/hm² and 6.2893 × 10⁻² t/hm², respectively.

$${\mathit{EC}}_W {=\mathit{EC}}_W {+\mathit{EC}}_{\mathit{WE}}$$

(11)

$${\mathit{EC}}_{\mathit{WE}}=\mathit{min}\left({\mathit{EC}}_N{,\mathit{EC}}_{\mathit{COD}}\right)$$

(12)

$$\begin{gathered} {\mathit{EC}}_N=0.88{ \times \gamma \times U}_N\times \frac{{W-C}_W\times K}{P_N} \\ {\mathit{EC}}_{\mathit{COD}}=0.88{ \times \gamma \times U}_{\mathit{COD}}\times \frac{{W-C}_W\times K}{P_{\mathit{COD}}} \end{gathered}$$

(13)

where EC_W represents the ultimate ecological carrying capacity of water resources (hm²), EC_WE represents the ecological carrying capacity of the aquatic environment (hm²), EC_N and EC_COD are the environmental carrying capacity of water polluted by ammonia nitrogen and organic matter (hm²), U_N and U_COD are the upper concentration limits of ammonia nitrogen and organic pollutants (t/m³) that are considered safe for the environment, C_w is the water consumption (m³) and K is the comprehensive water consumption rate. A factor of 0.88 is introduced as the bearing capacity coefficient to prevent the loss of biodiversity [46].

$${\mathit{ED}}_W\left({\mathit{ES}}_W\right)=\mathit{EC}{·}_W{-\mathit{EF}}_W$$

(14)

$${\mathit{ED}}_{\mathit{WE}}\left({\mathit{ES}}_{\mathit{WE}}\right){=\mathit{EC}}_{\mathit{WE}}{-\mathit{EF}}_{\mathit{WP}}$$

(15)

where ED_W and ES_W as well as ED_WE and ES_WE are in line with the ultimate ecological surplus or deficit of water resources and the aquatic environment.

$$\mathit{EPI}{·}_W=\frac{\mathit{EF}{·}_W}{\mathit{EC}{·}_W}$$

(16)

$${\mathit{EPI}}_{\mathit{WE}}=\frac{{\mathit{EF}}_{\mathit{WP}}}{{\mathit{EC}}_{\mathit{WE}}}$$

(17)

where EPI·_W represents the ultimate pressure index of the aquatic ecosystem, and EPI_WE represents the ecological pressure index of the aquatic environment.

3. Results

3.1. The Ultimate Ecological Footprint of Water Resources

The ultimate per capita ecological footprint (ef_w) calculated using the improved EF model varied from 2.868 to 4.044 hm². The values showed an increase at an average annual rate of 2.86% from 2005 to 2011, which was then followed by a decrease at an average annual rate of 6.63%. The calculated values of the ultimate per capita ecological carrying capacity (ec·_w) fluctuated between 6.707 hm² and 16.064 hm² as a result of annual variations in the amount of precipitation (Appendix B). The trend of the values of ed·_w was similar to that of ec·_w. The values of epi·_w and C were between 0.216 and 0.571, and between 1.143 and 4.278, respectively. In other words, it was in a safe condition, but there is much room for improvement in the future. Although the water use efficiency has increased over the years as a result of changes in industrial water use and the implementation of water-saving policies (

Table 5. Changes in the ultimate ecological footprint of water resources.

Year	ef·w	ec·w	ed·w	epi·w	C	EFI
2005	3.413	11.386	7.973	0.299	1.143	3.500
2006	3.422	6.569	3.147	0.520	2.259	3.039
2007	3.316	8.828	5.512	0.375	1.788	2.352
2008	3.299	7.148	3.849	0.461	2.608	1.861
2009	3.105	6.707	3.602	0.462	2.849	1.500
2010	3.509	14.767	11.258	0.237	1.281	1.439
2011	4.044	7.081	3.037	0.571	3.564	1.355
2012	3.915	11.375	7.460	0.344	1.977	1.116
2013	3.811	16.064	12.253	0.237	1.343	0.965
2014	3.583	6.620	3.037	0.541	4.278	0.908
2015	3.618	8.114	4.496	0.445	3.216	0.899
2016	2.868	13.231	10.363	0.216	1.663	0.694

), the current values indicate that further improvements are still needed.

Considerable differences in the values of ef·_w and ec·_w were observed among cities in the YKAP. Some cities, such as Yanji, Tumen and Longjing, showed higher ef·_w values, which were influenced by political functions and the industrial structure (Figure 2a). However, the values of ec·_w were lower than those of other cities as a result of the regional water resource reserves (Figure 2b). Water resource deficits have been a major problem in these cities (Figure 2c). Compared with other cities, Yanji had the highest epi·_w values, with a maximum of 13.082 in 2011 (Figure 2d).

3.2. The Traditional Ecological Footprint of Water Use

The values of ef_w in the YKAP varied between 0.475 and 0.800 hm², and showed an average annual growth rate of 2.74%. The values of ec_w ranged from 1.831 hm² to 4.421 hm², and the annual variation was similar to that of ec·_w. The values of ef_w generally showed an upward trend but have been decreasing year by year since 2016 and are significantly different from the values of ec_w. The trend of ed_w was in accordance with the ecological carrying capacity (1.085–3.650 hm²). The values of epi_w varied between 0.152 and 0.422 with a fluctuating but upward trend (

Table 6. Changes in the traditional ecological footprint of water use.

Year	efw	ecw	edw	epiw
2005	0.475	3.125	2.650	0.152
2006	0.500	1.831	1.331	0.273
2007	0.498	2.437	1.939	0.204
2008	0.510	1.989	1.479	0.256
2009	0.541	1.873	1.332	0.288
2010	0.637	4.047	3.410	0.157
2011	0.758	1.997	1.239	0.379
2012	0.754	3.154	2.400	0.239
2013	0.771	4.421	3.650	0.174
2014	0.792	1.877	1.085	0.421
2015	0.800	2.284	1.484	0.350
2016	0.794	3.662	2.868	0.216
2017	0.767	3.310	2.544	0.232
2018	0.727	3.475	2.748	0.209
2019	0.693	3.278	2.585	0.211

).

The values of ef_w in the different cities showed an overall upward trend (Figure 3a), while the values of ec_w showed large internal variations as well as significant differences among cities as a result of varying amounts of precipitation (Figure 3b). An ecological water deficit is prevalent in Yanji, Tumen, Longjing and Helong (Figure 3c), and the ecological pressure on water resources in these cities was substantially higher than that of other cities in the YKAP (Figure 3d).

3.3. The Ecological Footprint of the Aquatic Environment

The maximum ecological footprint and the minimum ecological carrying capacity of the aquatic environment in the YKAP over the years were mostly related to ammonia nitrogen emissions. These emissions have resulted in ef_wp values as high as 2.074–3.285 hm² and ec_we values as high as 4.737–11.642 hm². The environmental quality of water always showed a surplus (1.798–8.602 hm²). The values of epi_we ranged between 0.216 and 0.646, with an average annual decline of 4.4% (

Table 7. Changes in the ecological footprint of water pollution.

Year	efwp	ecwe	edwe	epiwe
2005	2.938	8.261	5.323	0.355
2006	2.922	4.737	1.815	0.616
2007	2.818	6.390	3.572	0.441
2008	2.789	5.158	2.369	0.540
2009	2.563	4.834	2.271	0.530
2010	2.872	10.719	7.847	0.267
2011	3.285	5.083	1.798	0.646
2012	3.160	8.221	5.061	0.384
2013	3.040	11.642	8.602	0.261
2014	2.790	4.742	1.952	0.588
2015	2.818	5.830	3.012	0.483
2016	2.074	9.568	7.494	0.216

).

The values of ef_wp in the different cities showed an overall fluctuating but declining trend, with the per capita contribution to water pollution in Yanji and Tumen being the highest (Figure 4a). The values of ec_we in Yanji, Tumen and Longjing amounted to 0.714, 2.573 and 1.920 hm², respectively (Figure 4b), thus demonstrating the large regional differences (Figure 4c). The ecological safety of water has been facing serious threats (Figure 4d).

4. Discussion

4.1. Evaluation of the Improved EF Model

Compared with other indicators, the EPI·_W is more suitable for evaluating the sustainable use of water resources [61]. Because traditional EF models only consider the impact of water consumption, earlier calculations have suggested that the water resources in the cities of the YKAP were within safe limits. Deterioration in the water quality caused by increased urbanization and economic activities was therefore underestimated. The improved EF model presented in this study accounted for the impact of water consumption as well as the negative effects of water pollution on the aquatic environment. The results showed that the EPI_W of Yanji (Figure 5a), Tumen (Figure 5b), Dunhua (Figure 5c), Longjing (Figure 5d), Helong (Figure 5e), Hunchun (Figure 5g), Antu (Figure 5h) and Yanbian (Figure 5i) were higher than their EPI_W. This was particularly evident in Yanji (Figure 5a) and Tumen (Figure 5b), where the ecological pressure status of water resources (Table 3) has escalated directly to very unsafe and extremely unsafe levels. The results are more in agreement with the actual state of water resource utilization, and can provide a reference for government departments to help them formulate policies (Figure 5).

4.2. Contribution of the Ecological Footprint of the Aquatic Environment

Regarding changes in the values, the ultimate ecological footprint of water resources (EF_W) consists of the traditional ecological footprint of water resources (EF_W) and the ecological footprint of the water environment (EF_WP). A comparison of the three graphs (Figure 2, Figure 3 and Figure 4) shows that the ecological footprint of the water environment had a greater impact, as can be clearly seen in the values of ef_w, ec_w, ed∙_w, es∙_w and epi_w. On the other hand, the magnitude of the change in the ecological footprint of the water environment can be easily seen as an important part of the ultimate ecological footprint of water resources (EF_W).

Regarding the impact on ranking, the ecological footprint of the aquatic environment (EF_WP) had a greater impact on the ranking among cities than the traditional ecological footprint of water resources (EF_W). This was especially reflected in the value of ef_w, as the ranking in terms of the ultimate ecological footprint of water resources for Yanji and Tumen changed directly from seventh and fourth (Figure 3a) to third and first (Figure 2a), respectively. The rankings of other the cities also changed.

The contribution of the ecological footprint of the aquatic environment to the ultimate ecological footprint of water resources was clearly demonstrated by the changes in the values and rankings.

4.3. Relationships with Influencing Factors

The relationships between the ultimate ecological footprint of water resources and the influencing factors (Appendix B) were explored. The ultimate ecological footprint of water resources (EF·_W) was positively correlated to EF_WP (r > 0; p < 0.001) and Cn (r > 0; p < 0.001); the traditional ecological footprint (EF_W) was positively correlated to Wr (r > 0; p < 0.001) and negatively related to EF_I (r < 0; p < 0.001) and N (r < 0; p < 0.05); the ecological footprint of the aquatic environment (EF_WP) was positively correlated to Cn (r > 0; p < 0.001) and N (r > 0; p < 0.05). This shows that pollutants had a significant impact on the ultimate ecological footprint of water resources, that water consumption has a strong impact on the traditional ecological footprint of water resources and that the ecological footprint of the aquatic environment is closely correlated to pollutants. The relationships between the ultimate ecological carrying capacity of water resources and the influencing factors were also examined. The ultimate ecological carrying capacity of water resources (EC·_W) was positively correlated with EC_W (r > 0; p < 0.001), EC_WE (r > 0; p < 0.001), W (r > 0; p < 0.001), pre (r > 0; p < 0.001), sur (r > 0; p < 0.001) and gro (r > 0; p < 0.01); the carrying capacity of water resources (EC_W) was positively correlated with EC_WE (r > 0; p < 0.001), W (r > 0; p < 0.001), pre (r > 0; p < 0.001), sur (r > 0; p < 0.001) and gro (r > 0; p < 0.01); the ecological carrying capacity of the aquatic environment (EC_WE) was positively correlated with W (r > 0; p < 0.001), pre (r > 0; p < 0.001), sur (r > 0; p < 0.001) and gro (r > 0; p < 0.01). All of these findings indicate that the total amount of water resources made a significant contribution to the ultimate ecological carrying capacity of water resources, the ecological carrying capacity of water resources and the ecological carrying capacity of the aquatic environment.

4.4. Recommendations for Improving the Health and Well-Being of Local Residents

Shortages of water resources and increasing water pollution are posing serious threats to the health and well-being of urban residents. According to a study published by the World Meteorological Organization in 2021, 5 billion people worldwide are expected to face water scarcity by 2050 [62], and about 1.4 million people die of preventable diseases every year because of lack of access to safe drinking water. Without the implementation of effective measures against drug resistance, this will become an important cause of death from infectious diseases worldwide by 2050 [63].

The Chinese government has formulated a number of policies and regulations at all levels to ensure the supply and quality of water in the YKAP through the implementation of the “Water Pollution Prevention and Control Law of the People’s Republic of China” in 2008, the revision of the “Water Law of the People’s Republic of China” in 2016, the review of the “Work Program for Fully Implementing the River Length System in Jilin Province” in 2017, the implementation of the “Regulations on Environmental Protection of Drinking Water Sources in YKAP” in 2017 and the adoption of the “Collaborative Mechanism on the Establishment of River and Lake Chiefs plus River and Lake Sheriffs plus Procurators plus Court Presidents: Guiding Opinions” in 2021.

Increasing urbanization and expansion of the tourism industry have, however, led to increased pressure on the water resources in the area. The increase in both industrial as well as urban sewage discharge has resulted in further pollution of the surface water as well as groundwater. In addition, inefficient urban and agricultural use has caused large-scale water losses. It is suggested that the government should use data based on the EF·_W models, refine the relevant laws and regulations, and adjust the water supply strategies and increase the sewage treatment methods, considering social and economic development and the protection of water resources to realize the sustainability of water resources.

4.5. Limitations and Future Outlook

The improved EF model described in this study still has various limitations. It only describes the consumption and pollution of water resources on a macroscopic level by selecting two main parameters, but did not give specific details of the specific water consumption sources such as production, life, ecology, etc. In addition, other major pollution parameters were not added because of a lack of data, and the model could provide more information on the ecological pressure of the aquatic environment over a longer period of time. Nevertheless, the results showed that the ecological footprint of human water consumption in the YKAP increased from 2006 to 2019, in line with earlier findings by Zhao [64].

To better understand the factors influencing the overall ecological footprint of water resources in the YKAP, we will provide a more detailed account of the various sources in future research [65]. In addition, we will try to collect basic data on water resources at the township level, and carry out assessments of the water resources and the ecological environment.

5. Conclusions

This study has presented an improved water ecological footprint model, providing a reference for the formulation of urban water management strategies and various solutions through quantitative evaluations of water consumption and water pollution. Although pollution data for 2017–2019 were lacking, it is not difficult to conclude that the ecological footprint of water resources in the YKAP increased between 2005 and 2019, mainly through increased water pollution. Because of annual fluctuations in the amount of precipitation, the values of EC·_W showed strong fluctuations. Although the overall availability and quality of water resources was within safe limits, there were large differences among cities, and in some cities, water pollution could pose a direct threat to the health and well-being of local residents. It is recommended that water resource management agencies adjust their water supply strategies based on data from the EF_W model, control wastewater discharge, improve their management systems and take urban economic development into account. The findings will significantly improve the sustainable management of water resources and ensure the health and well-being of urban residents.