Water, as the vital natural resource, plays a critical supporting role in the development of human society and the maintenance of ecosystem [1
]. Currently, coping with the shortage and overexploitation of water resources has become a global challenge [5
]. Rapid urbanization has increased the demand of human society for water resources and its related ecosystem services [9
] and further increases this challenge. Metropolitan areas, as regional units which generally exist in developed nations and participate in global competition and international division of labor [14
], are the most concentrated areas of human activities. So, the sustainable utilization of water resources in such areas needs thorough specific attention.
The ecological footprint model, proposed by Rees and Wackernagel [19
], reveals the relationship between ecological carrying capacity and the consumption of natural resources based on the concept of carrying capacity. The model has been widely used to evaluate the sustainability of human society by unifying measures of different types of natural resources [23
]. Subsequently, scholars constructed the water ecological footprint (WEF) model based on the concept of ecological footprint, used the land area to represent water resources consumption and regional water resources supply capacity (i.e., the total amount of water resources within the region, consisting of precipitation and the reserves of surface water and groundwater), namely, WEF, and water ecological carrying capacity (WECC), respectively [25
]. Meanwhile, the evaluation of the sustainable utilization level of water resources based on WEF is gradually emerging. For instance, Wang et al. calculated the per capita WEF and WECC and analyzed the water resources ecological pressure index to assess the sustainable utilization level of water resources in Hubei, China [25
]. Li et al. comprehensively evaluated the utilization of water resources and the spatial and temporal evolution of WEF and WECC in the lower Yellow River [26
]. Su et al. calculated WEF and WECC of four urban areas in China and suggested that adjusting industrial structure and repairing the inequality of water resources can promote the sustainable development of social economy [27
]. As a kind of natural capital, water has two attributes of stock and flow of natural capital [28
]. In the event that the capital stock of water resources is occupied, a series of serious consequences will restrict the sustainable development of human beings, such as the depletion of water resources and the decline of groundwater levels [29
]. However, it should be noted that existing studies did not consider the occupation of natural capital stock (NCS) and the consumption of natural capital flow (NCF) by WEF.
If NCF cannot meet the demand of consumption, this would threaten sustainable development [17
]. Ecological economics has reached a consensus that increasing sustainable development as far as possible could prevent a decrease in NCS [33
]. To solve this problem, Niccolucci et al. [34
] introduced footprint size and footprint depth to the ecological footprint model to reflect the occupation of NCS and NCF consumption, respectively. Subsequently, NCS and NCF were included in the assessment of regional sustainable development. Therefore, to identify the occupation of NCS and the consumption of NCF by WEF, we need to expand the WEF model into a three-dimensional model.
China is a country with uneven distribution of water resources [36
], and water shortage is one of the major constraints to the development of many Chinese urban areas [39
]. To this end, the Chinese government has issued a series of regulations on water management, development and protection, such as the Groundwater Management Regulation issued on 15 September 2021 [41
]. Therefore, factors influencing the change in WEF need to be identified. Decomposition analysis is used to quantify changes with time for a wide range of variables [42
], and the method mainly consists of the Laspeyres Index [43
], the Adaptive Weighting Divisia Index [45
] and the Logarithmic Mean Divisia Index (LMDI) [46
]. The LMDI can effectively solve the residual term, zero data and negative value problem, and is widely applied in the analysis of factors influencing water footprint [47
], ecological footprint [48
], carbon footprint [49
Therefore, we took the Wuhan Metropolitan Area, a typical metropolitan area in central China, as the research object to achieve the following research aims: (1) construct a three-dimensional WEF model; (2) construct an evaluation index system for the regional sustainable utilization level of water resources based on the model; (3) analyze the factors influencing the change in WEF using the LMDI. This research would help to improve and supplement the theoretical system of sustainable water resources development by constructing a three-dimensional WEF model and introducing two indicators of NCF and NCS [25
]. In addition, we provide references for government policies and plans in the metropolitan area development, water resources allocation and dispatching and industrial structure adjustment by analyzing the contribution of WEF intensity, economic development, population pressure and WECC to the change in WEF based on LMDI.
3.1. Per Capita Water Ecological Deficit and Surplus
The per capita WEF, per capita WECC, per capita WED and WES of the Wuhan Metropolitan Area from 2010 to 2019 were calculated according to Equations (4) and (8) (Figure 2
). For the Wuhan Metropolitan Area, the per capita WEF was always within the range of the per capita WECC and there was no deficit (Figure 2
a). In 2016, per capita WES was the highest during the period 2010–2019. This is because the range in the per capita WEF was small, and 2016 was a wet season in the metropolitan area, resulting in sufficient water resources supply (Appendix A Table A2
). However, per capita WED and WES of urban areas within the metropolitan area was quite different. The cumulative WED of Ezhou was highest at 5.02 ha/cap from 2010 to 2019, which indicated that Ezhou had the highest per capita WEF (Appendix A Table A3
) in the metropolitan area with a smaller WECC (Figure 2
c). Xianning and Huanggang had no WED, and Huangshi, with a higher WECC, only had a deficit in 2019. Overall, the sustainable utilization level of regional water resources is more affected by WECC and leads to regional differences. However, to realize the sustainable utilization of water resources and sustainable development of the social economy, it needs to be carried out within the scope of WECC. Therefore, the composition of WEF needs to be further analyzed.
PWEF was the chief component of WEF of the Wuhan Metropolitan Area and its inner urban areas (Figure 2
b). Among the nine urban areas, Wuhan had the smallest proportion of PWEF in WEF, and also had the smallest per capita WEF and PWEF (Appendix A Table A3
and Table A4
). This is because although Wuhan had the highest GDP, its low proportion of secondary industry inhibited the growth of WEF (Figure 1
d). However, the emergence of its WED emphasizes that it still needs to further improve the efficiency of water resources utilization.
At the same time, the spatial distribution of the per capita WECC was mainly concentrated in the southeast of the metropolitan area. For urban areas without WED, the industrial scale could be appropriately increased to develop GDP, but it still needs to be carried out within the scope of WECC and improve the utilization efficiency of water resources.
3.2. Water Resources’ Sustainable Utilization Level Assessment
Equation (9) was used to calculate the WPI of the Wuhan Metropolitan Area from 2010 to 2019 (Figure 3
The WPI of the metropolitan area fluctuated between 0.31 and 0.96 from 2010 to 2019, and the WPI was always lower than 1. In 2011 and 2019, the WPI was the highest at 0.96 and was the lowest in 2016 at 0.31. The level of water resources’ sustainable utilization reached level 3 (relatively unsustainable) in 2011 and 2019, it was in the state of relatively sustainable in the periods 2012–2015 and 2017–2018, and the state of very sustainable in 2010 and 2016. When WECC was smaller, the grade of water resources’ sustainable utilization level was higher. However, overall, the metropolitan area was still in the state of sustainable development of water resources consumption.
In terms of the inner urban areas of the metropolitan area, the WPI of each urban were showed the same dynamics and there was a significant difference between those urban areas. The WPI of Huanggang and Xianning was always lower than 0.5, and it was always the lowest in Xianning. During the period 2010–2012, the WPI in Xiaogan was the highest; and in 2011 and 2012, Xiaogan was in the state of completely unsustainable. Excluding 2014, the WPI in Ezhou was the highest.
3.3. Natural Capital Occupation Analysis
reflect the NCS occupation and NCF consumption by WEF, respectively, and the result is shown in Figure 4
. In terms of the Wuhan Metropolitan Area, WEFsize
did not substantially change and only fluctuated around 0.87 (ha/cap) and WEFdepth
was always 1 from 2010 to 2019. Thus, the NCF is used first, the NCS is not occupied and the supply capacity of water resources is unaffected.
However, in terms of inner urban areas in the metropolitan area, WEFsize
of Ezhou was the highest during the periods 2010–2012 and 2014–2016, and excluded 2010 and 2016, WEFdepth
of Ezhou was greater than 1. In 2019, WEFdepth
was the highest and reached 2.73, suggesting that 2.73-fold the current area was required to support the water resources consumption of Ezhou. In terms of the urban areas which consumed water resources NCF and occupied water resources NCS, water resources utilization was unsustainable. The reason is that the supply of NCF would decrease over the following year, and reduce WECC by the accumulative nature of WED [10
]. Adverse effects on local water environment, such as aquifer depletion [31
], are caused. Therefore, these urban areas must develop their industries within the scope of region’s WECC, and determine the scale of industries and urban areas by setting production and people based on WECC.
3.4. Factors Influencing Water Ecological Footprint Change
Considering that WEF is more easily affected by human production and management activities. In this paper, WEF increment of the Wuhan Metropolitan Area in China from 2010 to 2019 was decomposed into four effects—WEFI effect, ED effect, PP effect and WECC effect (Figure 5
). The change in their values is shown in Appendix A Table A5
, Table A6
, Table A7
and Table A8
. Both ED and PP were effects that lead to the increase in WEF of the metropolitan area and nine urban areas within it, while WEFI effect and WECC effect had the opposite effect.
In terms of the metropolitan area, WEF increased by 1.67 million ha from 2010 to 2019, ED effect was the main effect of WEF and resulted in an increased WEF of 27.65 million ha. On the contrary, WEFI effect was the chief negative effect that inhibited the increase in WEF. This is consistent with previous research conclusions [47
]. Meanwhile, we found that PP effect had a positive effect on the increase in WEF, which was second only to ED effect. This is because the increase in population not only reduces WECC by occupying wetlands through urban expansion [56
] but improves WEF by expanding the industrial scale, thus showing a positive driving effect on the change in WEF. However, WECC effect inhibited the change in WEF, which may be because the reduction in WECC forces water-consuming industries to improve the utilization efficiency of water resources and reduce the consumption of water resources, that is, to use WECC to limit the industrial scale.
In terms of the inner urban areas of the metropolitan area, the contribution of the four effects to the change in WEF was significantly different, but the relative relationship between each effect and WEF change was consistent with that of the metropolitan area.
5. Conclusions and Implications
To identify the occupancy of natural capital stock and the consumption of natural capital flow by water resources consumption in the Wuhan Metropolitan Area, we extended the water ecological footprint model into a three-dimensional water ecological footprint model. By analyzing the relationship between the supply and demand of water resources in the metropolitan area and its inner urban areas, the sustainable utilization level of water resources was evaluated, and the stock occupancy and flow consumption of natural capital were integrated into the evaluation system of the sustainable utilization level of water resources. The three-dimensional water ecological footprint model provided a new perspective for the assessment of sustainable utilization level of water resources.
During the period 2010–2019, the change in water ecological carrying capacity was larger than water ecological footprint, and there was no water ecological deficit in the Wuhan Metropolitan Area. Water ecological deficit and surplus were different for inner urban areas of the metropolitan area, Ezhou had the highest cumulative water ecological deficit with 5.02 ha/cap. Water ecological footprint of production was the main component of the water ecological footprint of the metropolitan area. The spatial distribution of per capita water ecological carrying capacity was mainly concentrated in the southeast of the metropolitan area. In general, although there was no water ecological deficit in the metropolitan area, there were great differences in water ecological footprint and water ecological carrying capacity of the inner urban areas, leading to different degrees of deficit.
The level of water resources’ sustainable utilization level in the Wuhan Metropolitan Area was relatively unsustainable in 2011 and 2019. Xianning was the most sustainable urban area in terms of water resources utilization among the nine urban areas within the metropolitan area. In the periods 2011–2012 and 2018–2019, the sustainable utilization level of water resources in some urban areas was in the state of completely unsustainable.
Regarding the natural capital flow consumption and the natural capital stock occupancy in the Wuhan Metropolitan Area, there was never occupancy of natural capital stock. In the periods 2011–2015 and 2017–2019, there were always some urban areas occupying on natural capital stock, and Ezhou was always one of them. This indicates that the natural capital flow cannot meet the water resources consumption demand, and that the high occupation of the natural capital stock would seriously hinder the recovery of water ecological carrying capacity.
The factors affecting the change in water ecological footprint were divided into four effects—water ecological footprint intensity effect, economic development effect, population pressure effect and water ecological carrying capacity effect—and the relative contribution of each effect was determined using the Logarithmic Mean Divisia Index. Economic growth effect and population pressure effect had a positive driving effect on the change in water ecological footprint, while the intensity effect of water ecological footprint and water ecological carrying capacity effect had the opposite effect.
This paper suggests that the local government should strengthen control of water resources consumption in the production sector, and take the annual average water ecological carrying capacity of the region as the upper limit of production, living and ecological water consumption in the region. Therefore, the metropolitan area should be encouraged to eliminate or upgrade systems with low water resources utilization efficiency; apply strict restrictions at the industrial scale, the population scale and the city scale based on water resources supply capacity; and improve water efficiency.
Second, the protection of water sources should be strengthened, the scale of urban expansion should be carefully planned, and the natural capital flow of water resources in the dry season should be ensured to meet the production, living and ecological needs of the region. Further, the occupation of natural capital stock of water resources should be reduced.
Thirdly, it is suggested that based on the market economy, methods such as water ecological compensation could be used to restrain the consumption of water resources and realize the allocation of water resources in areas with high water consumption and promote differentiated regional development models and water policy.