Growing evidence demonstrated that human has dramatically altered the global environment. Identifying the human factors driving environmental impacts is a hot topic in the field of sustainable development. One key limitation to a precise understanding of anthropogenic impacts is the absence of a set of refined analytic tools. The water footprint index has been used as a comprehensive impact measure of water use in relation to consumption of people, which indirectly reflect anthropogenic pressure on the environment. Using techniques of spatial econometrics, we study the water footprint of 31 provincial regions in China. The spatial linkage of provinces and cities is described with a spatial weights matrix. With a view to dismantling the anthropogenic driving forces of water footprint, the modified IPAT-called STIRPAT(Stochastic impacts by regression on Population (P), Affluence (A) and Technology (T))-has been employed as a common analytic framework. It is evident that the spatial dependence across regions is strong enough to distort the ordinary least squares (OLS) algorithm. This paper analysis Chinese provincial water footprint based on the traditional STIRPAT model through spatial econometric analysis as spatial lag model and spatial error model. Our analyses show that population is a major driver of water footprint, and it has a proportional effect on water footprint, and affluence monotonically increased the water footprint with a relative less degree than population. Changing the traditional mode of economic growth and taking the path to new industrialization, appeared to affect the water footprint. Urbanization has no distinct impact on environment. Economic growth in itself did not offer a solution to environmental problems. Our results indicate that, when affluence approached about 10560.92 RMB in GDP under the precondition of controlling the population′s impact, environmental stresses tend to fall below a strict proportionality. The productivity of (virtual) water in Hainan is the highest, but the lowest in Qinghai and Inner Mongolia.