China's water policies in the past decades have relied heavily on the construction of massive water conservancy projects in the form of dams and reservoirs, water transfer projects, and irrigation infrastructure. These facilities have brought tremendous economic and social benefits but also posed many adverse impacts on the eco-environment and society. With the intensification of water scarcity, China's future water conservancy development is facing tremendous challenge of supporting the continuous economic development while protecting the water resources and the dependent ecosystems. This paper provides an overview of China's water conservancy development, and illustrates the socioeconomic, environmental and ecological impacts. A narrative of attitude changes of the central government towards water conservancy, as well as key measures since the 1950s is presented. The strategic water resources management plan set by the central government in its Document No. 1 of 2011 is elaborated with focus on the three stringent controlling “redlines” concerning national water use, water use efficiency and water pollution and the huge investments poised to finance their implementation. We emphasize that realizing the goals set in the strategic plan requires paradigm shifts of the water conservancy development towards maximizing economic and natural capitals, prioritizing investment to preserve intact ecosystems and to restore degraded ecosystems, adapting climate change, balancing construction of new water projects and rejuvenation of existing projects, and managing both “blue” (surface/groundwater) and “green” water (soil water)

China’s increasingly urbanized and wealthy population is driving a growing and changing demand for food, which might not be met without significant increase in agricultural productivity and sustainable use of natural resources. Given the past relationship between lack of access to affordable food and political instability, food security has to be given a high priority on national political agendas in the context of globalization. The drive for increased food production has had a significant impact on the environment, and the deterioration in ecosystem quality due to historic and current levels of pollution will potentially compromise the food production system in China. We discuss the grand challenges of not only producing more food but also producing it sustainably and without environmental degradation. In addressing these challenges, food production should be considered as part of an environmental system (soil, air, water, and biodiversity) and not independent from it. It is imperative that new ways of meeting the demand for food are developed while safeguarding the natural resources upon which food production is based. We present a holistic approach to both science and policy to ensure future food security while embracing the ambition of achieving environmental sustainability in China. It is a unique opportunity for China to be a role model as a new global player, especially for other emerging economies.

A comprehensive and reliable assessment of the water resources in China's transboundary river basins is vital for water resources management and peaceful development. In this study, we built machine learning (random forest, gradient boosting, and stacking) and traditional linear models to identify the relation between the runoff coefficient and its influencing factors, including topography, climate, land cover, and soil. The cross‐validation results show that the machine learning models greatly outperform the traditional linear model in predicting runoff coefficient. High‐resolution (0.1°) runoff coefficient and runoff maps for the China's transboundary river basins riparian countries were produced and compared with other estimates at the country level. The best water resources estimates achieved from the machine learning model are consistent with the Food and Agriculture Organization of the United Nations AQUASTAT database (root‐mean‐square error = 76.97 km³/year, normalized root‐mean‐square error = 12%) at the country level. This outperformed two currently available runoff products: the UNH/GRDC Global Composite Runoff Fields and the Global Streamflow Characteristics Dataset. The study also demonstrated that accurate precipitation data can improve runoff and water resources estimation accuracy and that climate and topographic factors have a controlling role in prediction, whereas the influences of land cover and soils are weak. Finally, China's transboundary water resources were calculated and thoroughly assessed at basin and country levels.