Urbanization is an engine of economic development, but this process is often constrained by increasingly scarce water resources. A model predicting the drag effect of water consumption on urbanization would be useful for future planning for sustainable water resource utilization and economic growth. Using panel data from 11 provinces in China’s Yangtze River economic belt (YREB) from 2000 to 2015, we apply Romer’s growth drag theory with spatial econometric models to quantitatively analyze the drag effect of water consumption on urbanization. The results show the following. (1) The drag effect of water consumption on urbanization has significant spatial correlation; the spatial Durbin model is the best model to calculate this spatial connection. (2) The spatial coefficient is 0.39 and the drag that is caused by water consumption on urbanization in the YREB is 0.574, which means that when spatial influences are considered, urbanization speed slows by 0.574% due to water consumption constraints. (3) Each region in the YREB has different water consumption patterns and structure; we further calculate each region’s water consumption drag on urbanization. We find that areas with high urbanization levels, like Shanghai (average 84.7%), have a lower water consumption drag effect (0.227), and they can avoid the “resource curse” of water resource constraints. However, some low-level urbanization provinces, like Anhui (average 39.3%), have a higher water consumption drag effect (1.352). (4) Our results indicate that the water drag effect is even greater than the drag effect of coal and land. Therefore, policies to increase urbanization should carefully consider the way that water constraints may limit growth. Likewise, our spatial model indicates that policy makers should work with neighboring provinces and construct an effective regional water cooperation mechanism.

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Affected by global climate change and water shortages, food security continues to be challenged. Improving agricultural water use efficiency is essential to guarantee food security. China has been suffering from water scarcity for a long time, and insufficient water supply in the agricultural sector has seriously threatened regional food security and sustainable development. This study adopted the super-efficiency slack-based model (SBM) to measure the provincial agricultural water use efficiency (AWUE). Then, we applied the vector autoregression (VAR) Granger causality test and social network analysis (SNA) method to explore the spatial correlation of AWUE between different provinces and reveal the interprovincial transmission mechanism of spillover effects in AWUE. The results show the following: (1) In China, the provincial AWUE was significantly enhanced, and the gaps in provincial AWUE have widened in the past 20 years. (2) There were apparent spatial heterogeneity and correlations of provincial AWUE. The provinces with higher AWUE were mainly located in economically developed and coastal areas. (3) The correlation of AWUE between provinces showed significant network structure characteristics. Fujian, Hebei, Jiangsu, Shandong, and Hubei Qinghai were central to the network, with high centrality. (4) The AWUE spatial correlation network could be divided into four blocks. Each block played a different role in the cross-provincial transmission of spillover effects. Therefore, it is necessary to manage the agricultural water resources and improve water use efficiency from the perspective of the network.

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