“Invulnerability” of complex network was firstly introduced to virtual water (VW) research, aiming to broaden the scope of studies on water use and management. Beginning with the construction of China's virtual water trade networks (VWTNs) of major grain crops, Node Degree (K) and Betweenness Centrality (B) are employed to evaluate and rank the importance of China's 31 regions. Regions with high values for both indicators are identified as playing pivotal roles in the VWTNs: Jiangsu (ranking 1st for both K and B), Hubei (2nd for K, 3rd for B), Henan (3rd for K, 6th for B), Hebei (4th for K, 4th for B), Hunan (4th for K, 5th for B). Using this ranking to simulate the invulnerability of VWTNs under random and intentional attacks. The results reveal a rapid decrease in both Network Efficiency (E) and Maximum Connectivity (C) under intentional attack. In comparison to seven random attacks, E falls below 0.1 and C drops below 0.5 after only three intentional attacks, and the network completely collapsed after 10 intentional attacks. This highlights the VWTN's vulnerability in maintaining food supply and agricultural water security when key regions are subjected to man‐made destruction, such as military blockades or occupations. Future work should include integrating climate change models, crops yield models, and water resource allocation models to protect the key areas. Furthermore, interdisciplinary approaches are crucial for overcoming the limitations of VW research and these findings will provide valuable insights to enhance the optimal regulation of VWTNs.

In the Yellow River Basin, the lack of water supplies is now the largest obstacle to both environmental preservation and socioeconomic growth. The fact that inhabitants’ diets may be altered to save water, however, is gravely underappreciated. Based on the water footprint theory, we examined the water footprint structure and the dynamic evolution process of food consumption in the Yellow River Basin from 1999 to 2019 in this study. The key factors affecting the water footprint of food consumption were then identified by using the STIRPAT model modified by the partial least-squares method. The findings indicate the following: (a) There had been an increase in the Yellow River Basin’s overall water footprint of food consumption from 1999 to 2019, with the midstream region having the biggest water footprint of food consumption (410.8 billion m ³ ) and the highest percentage increase (86%). (b) In the Yellow River Basin, the water footprint of meat eating was 36% while the water footprint of grain consumption was 30%. The lower Yellow River had the greatest water impact per person due to food consumption. (c) Urbanization rate played a promoting role in the upper Yellow River provinces, and GDP and irrigated area played a promoting role in the lower Yellow River provinces. The results of this study are expected to provide scientific support for the decision-making of healthy and water-saving diets in the Yellow River basin.

Agricultural water footprint is an important indicator for assessing water-use efficiency and resource carrying capacity in agricultural systems, especially in arid regions. From the perspective of ecological function zones, this study examines the spatiotemporal dynamics of the agricultural water footprint in Xinjiang, China, and evaluates its adaptability to socioeconomic factors. The blue and green water footprints of crop production and the water footprint of animal products during 2000–2020 were quantified to estimate the total agricultural water footprint. The Gini coefficient and imbalance index were used to quantitatively evaluate the spatial adaptability between the agricultural water footprint and socioeconomic factors, including sown area, population, and agricultural Gross Domestic Product (GDP) across different ecological function zones. The results indicate that the agricultural water footprint increased from 2.54 × 10¹⁰ m³ to 5.85 × 10¹⁰ m³, with a clear spatial gradient characterized by higher values in southwestern Xinjiang and lower values in the northeastern region. Crop production accounted for more than 85% of the total footprint, with cotton as the dominant contributor, while beef consumption drove the growth in the animal product water footprint. The adaptability between the agricultural water footprint and sown area improved overall, whereas coordination with population distribution remained weak, and notable regional differences were observed in water footprint intensity relative to agricultural GDP. These findings indicate that the spatiotemporal differentiation of the agricultural water footprint is closely linked to resource endowments and development characteristics across ecological function zones, providing support for region-specific agricultural water management in arid areas.