While tourism generates economic benefits at destinations, it also creates certain environmental pressures. In the global context of water scarcity, the spatial and temporal differentiation characteristics of water consumption at tourism destinations have become a focus of attention. Based on panel data, the present study calculates the change trends in China’s tourism water footprint (TWF) in the 2013–2018 period using input-output analysis, analyses the regional differences in TWF changes using kernel density estimation and the Theil index, and investigates the driving factors of the spatial and temporal differentiation of the TWF using the logarithmic mean Divisia index model. The results indicate that (1) the tourism water consumption in China increased year-by-year but that the tourism water use efficiency improved; (2) the proportion of the TWF for accommodation and food in the total TWF gradually increased, while the proportion of the TWF for transportation continuously decreased; (3) the TWF of each region increased continuously, with the absolute difference between regions gradually increasing and the difference in the TWF intensity gradually decreasing; and (4) decomposition analysis showed that the TWF in China was positively driven by per capita expenditure and the number of tourists, with the role of TWF intensity shifting from inhibition to promotion, and that each driving force changed with time. Based on the spatial and temporal differences in the TWF, the provinces in China are divided into five categories, and targeted countermeasures and suggestions are proposed.

Tourism development consumes ecological resources to varying extents while bringing economic benefits; tourism eco-efficiency (TEE) assessment has thus become an area of major focus in destination sustainability research. This paper intends to examine the spatiotemporal characteristics and driving factors of eco-efficiency changes in 36 tourist cities on the Chinese mainland from 2010 to 2019, using a super-slacks-based measure (SBM) model, the data envelopment analysis (DEA)–Malmquist index, spatial correlation, and regression analysis. In contrast to the previous work, this work explores TEE among major tourist cities in China by considering the undesirable outputs of carbon emissions and sewage. The results show that (1) the TEE of most cities during the study period was low but increasing; there were significant spatial differences among different cities, and the eco-efficiency of the same city fluctuated over time. (2) The TEE was globally uncorrelated, but low-eco-efficiency areas were adjacent to each other and formed agglomerates, enhancing the negative spillover effect. (3) Despite fluctuations, the Malmquist indices exhibited positive trends, which resulted from the technical progress index rather than the technical efficiency index. (4) Socioeconomic development significantly promoted TEE. This research reveals the evolutionary law of TEE on the urban scale and explores the impact of social and economic development on TEE, which can provide a reference for policymaking and enrich research on destination sustainability.