Water Footprint of Food Consumption by Chinese Residents

Water shortages are a worldwide problem. Virtual water and the water footprint link water resources, human beings and agricultural products, and are effective tools to alleviate water-resources stress. The production of agricultural products consumes a large amount of water, and food is the most basic consumer good for human survival, so it is very necessary to study the water footprint of residents’ food consumption, which is also the weak point of current research on virtual water and the water footprint. This paper aimed to conduct a comprehensive analysis on the water footprint of food consumption in China from the perspectives of urban and rural residents, per capita water footprint, water footprint structure and food consumption structure. The results revealed that the average water footprint of residents’ food consumption was 605.12 billion m3/year, basically showing an upward trend. Guangdong residents had the highest water footprint for food consumption due to the highest population and higher consumption of water-intensive foodstuffs such as grain and meat in their diet. The water footprint of Xizang residents’ food consumption was the lowest followed by Ningxia and Qinghai due to having the least population. The water footprint of food consumption consumed by urban residents was on the rise while that consumed by rural residents was on the decline in China, which was consistent with the changing trend of population. On the whole, the rural population consumed more virtual water embedded in food than the urban population. From the water footprint structure point, the contribution rate of the green water footprint is the largest, reaching 69.36%. The second is the gray water footprint and then the blue water footprint, accounting for 18.71% and 11.93%, respectively. From the perspective of the food consumption structure, grain and pig, beef and mutton consumption contributed significantly to the total water footprint of residents’ food consumption, contributing 37.5% and 22.56%, respectively. The study is helpful for water management and water allocation in rural and urban areas, improving agricultural technology to reduce the gray water footprint and optimizing food consumption structure, such as reducing the consumption of grain and meat.