1. Introduction
Human society depends on water resources to survive, as water shortages compromise a sustainable societal development. In terms of water resource use, the agricultural sector (which is closely related to food supply) is the largest water consumption sector [
1,
2]. The water consumption due to agricultural production accounts for 91% of the total use of freshwater resources in the world [
3]. Therefore, the sustainable use of water resources for food production has been widely considered. China is a country with limited water resources, having a per capita share of 2000 cubic meters—approximately 28% of the world average [
4]. In recent years, with the development of China’s urbanization and the improvement of the income level of residents, the change in the income of urban residents has had a huge effect on food consumption, leading to an assignable influence on the demand for agricultural water resources [
5,
6,
7,
8].
Income growth can increase the quantity of consumed food, putting pressure on the sustainable use of water resources by stimulating the food supply [
9,
10,
11]. On the other hand, income growth can lead to significant changes in dietary patterns, with the proportion of cereal food consumption declining and the proportion of animal food consumption increasing [
12,
13]. As the water requirements for animal food production are generally higher than those for plant food, the changes in dietary structure caused by income growth may increase the water requirements for future food production [
14,
15,
16,
17]. In this paper, we use urban household data to empirically analyze the relationship between water requirements for food consumption and income using the water footprint tool, paying specific attention to the effect of changes in income distribution on the water footprint of food consumption, which is used to formulate policies based on sustainable food consumption patterns to strengthen the sustainable management of water resources in China. First, because the agricultural sector, which is closely related to food supply, is the largest sector in terms of water use in China, the water footprint of food consumption is directly related to the supply security of China’s freshwater resources. Second, the income level of the population has greatly increased with the development of urbanization in China, thus promoting the expansion and transformation of the food consumption of urban residents, putting more pressure on the sustainable use of water resources in the future.
To achieve this study’s objective, two goals were set: The first was to estimate the response of the per capita water footprint of food consumption to per capita income changes across income strata by calculating income elasticities. More specifically, in addition to total sample estimation and non-parametric estimation, we use a threshold model to scientifically classify the urban household data into low- and high-income strata, based on the characteristics of the data themselves, and then estimate the effect of household per capita income on the per capita water footprint of food consumption in different income strata. The second objective was to predict the change in the per capita water footprint of food consumption under the assumption of changes in income and income distribution by using the estimation results of income elasticity.
Hoekstra (2002) proposed the concept of the water footprint, expanding the research perspective of water resources to the consumer field [
18]. Scientifically using the water footprint tool can help to understand the complex relationships between human activities and water resources [
19,
20,
21]. The water footprint has been widely applied to the study of water requirements for food consumption, profoundly affecting the evaluation and management of water resources [
22,
23,
24,
25]. The water footprint of food consumption is defined as the freshwater resources necessary for humans to maintain a certain level of food consumption over a certain period, which is used to measure the effect of human food consumption on water resources [
26].
Some studies have been devoted to analyzing the effect of economic and social factors on the water footprint of food consumption [
27,
28,
29]. At the global scale, Yang and Cui (2014) analyzed the effects of population, diet, and agricultural practices on the water footprint of food consumption [
30]. Many studies have also analyzed the factors affecting the water footprint of food consumption in China [
8,
31,
32,
33,
34,
35,
36]. At the national level, Liu and Savenije (2016) used Chinese food consumption data provided by the Food and Agriculture Organization (FAO) of the United Nations in order to study the effect of food consumption patterns on the water footprint in China. The results of the study indicated that the increase in per capita water requirements for food in China is largely due to an increase in the consumption of animal products [
5]. Zhao and Chen (2014) used Chinese food consumption data provided by the FAO to analyze the effects of diet structure, water use efficiency, economic activity, and population factors on the water footprint of agricultural products, and believe that economic activities had a relatively significant positive effect [
37]. At the urban level, Kang et al. (2017) used the Xiamen Statistical Yearbook data to analyze the effects of population, the structure and level of food consumption, water intensity, and the population rate on the water footprint of food consumption in Xiamen [
38]. Their results showed that population factors are the leading contributors to changes in the water footprint. From the perspective of previous studies, population, diet structure, income level, and urbanization are the main driving factors of changes in the water footprint of food consumption [
39]. However, most of those studies used macro data—that is, at the national or city level—to analyze the factors affecting the water footprint of food consumption, while studies using micro household data are relatively rare. Similarly, some studies have focused on the issue of crop and livestock productivity [
40,
41,
42,
43,
44,
45,
46]; however, they ignored the nexus of income change and water footprint of food consumption.
The relationship between income and the water footprint is an important aspect of the sustainable management of water resources. In terms of research in developed countries, Feng et al. (2011) studied the relationship between income level and the water footprint of residents in different regions of the U.K. and found a linear relationship between them [
47]. Longo and York (2009) found that developed countries with higher per capita income had a relatively higher water footprint of food consumption [
48]. Similarly, Ivanova believed that the consumptive water footprint was unevenly distributed across regions and found that the per capita water footprint was the greatest in rich countries [
49]. In terms of research in China, many studies have found regional differences in the effect of income on the water footprint of food consumption [
6,
50]. Huang et al. (2012) studied the effect of local grain consumption on the water resources in Beijing and found that income growth significantly increased the water footprint of food consumption and increased the pressure on water resources [
51]; however, only a few previous studies have focused on the effect of income changes on the water footprint of food consumption in different income groups. Research on the effect of income distribution on the water footprint of food consumption is also relatively limited. Therefore, it is necessary to study the effect of the income changes of different income groups on the water footprint of food consumption, thus providing a reference for a more effective guidance of water resource management.
4. Discussion and Conclusions
In this paper, we calculated the per capita water footprint of food consumption based on data of urban households in Guangdong Province. The influence of income change on the per capita water footprint of food consumption was analyzed by calculating the elasticity. We projected the per capita water footprint of food consumption under hypothetical changes in income and income distribution.
The income growth of urban residents had a significant positive effect on the per capita water footprint of food consumption, where the effect varied by income stratum. The income elasticity of the per capita water footprint of food consumption for the total sample was 0.45, while the income elasticity of the low-income group (0.75) was greater than that of the high-income group (0.23), indicating that the change in income in the low-income group had a greater effect on water resources. Previous studies have confirmed the effects of food consumption patterns, population size, and urbanization on the per capita water footprint of food consumption. The difference of income elasticity was closely related to the change of food consumption structure in different income groups. Increasing income can push the food consumption pattern of low-income groups in the direction of higher water consumption due to a higher animal food consumption. The water footprint of food consumption in the high-income group had already reached a very high level, and the growth rate was small. Therefore, in order to reduce the effect of food consumption on the environment, sustainable food consumption management should consider group differences. We should correctly guide all kinds of groups to carry out sustainable consumption, advocate healthy and reasonable diet models, reduce animal food consumption, avoid the excessive consumption of food, and strengthen the management of food waste. In future research, we should explore the relationship between income and the water footprint of specific food, as well as study sustainable food consumption management from the perspective of the water footprint.
The simulation results for Scenarios A and B showed that the increase in the per capita water footprint of food consumption for the total sample of households would be considerably larger if the total increase in income was received by the low-income stratum, rather than a uniform percentage distribution of the additional income across each income stratum. Therefore, revenue growth by narrowing the income gap will considerably increase the water footprint of food consumption for the whole society. Meanwhile, the simulation results for Scenario D showed that the redistribution of income would significantly increase the per capita water footprint of food consumption, even if there was no increase in the average per capita income. However, the simulation results of Scenario C showed that the income growth pattern of the widening income gap would slightly increase the per capita water footprint of food consumption for all sample households. At present, China is in a period of rapid economic growth and urbanization, a period of profound change and sensitive response to the income level of urban and rural residents. The simulation results showed that increasing the income of residents, especially of low-income groups, will significantly increase the water footprint of food consumption of the whole society. This prospect is expected to have an effect on the sustainable food consumption and water resources management in China. In future research, when analyzing the water demand due to food consumption in China, the expected changes in income growth and income distribution should be fully considered.
This paper analyzed the effect of income on water resources for food consumption from the perspective of the water footprint, which is of great significance to promote sustainable food consumption and sustainable water resources management. The research results showed that changes in income and income distribution can affect the water footprint of food consumption of urban households in China. In this paper, the complex relationship between human activities and natural resources was simplified by using the water footprint tool, which has some limitations. First, we estimated the amount of water resources needed to produce food, according to the amount of food consumed, and failed to consider the environment, location, and other factors of food production. Future food water footprint research should consider the regional distribution of food production and the flow of water footprint among regions. Second, we analyzed the relationship between income growth and water footprint of food consumption at the micro level using household data, which has certain limitations when used as a reference in formulating macro policies at the national scale. In the future, we should strengthen the macro level research and carry out research on the differences and flows of water footprint among regions, countries, and provinces, which will be more conducive to the formulation of macro policies at the national scale.