China is increasingly facing water-related problems, such as water scarcity, pollution, and overexploitation of groundwater. This paper discusses the water status in China and claims that governance is the cause of water-related problems. The structure of the current water management is analyzed to conclude that the control-command is a static approach which is less capable of dealing with the uncertainty in the water resources system. An adaptive governance frame is introduced, which highlights the learning process and participation. The learning process avoids making the same mistake twice and the participation ensures the diversity of information, which are both necessary for water resources management.

A water resource allocation model coupling quantity and quality is a topic of concern in China. The water resources supply modelling is set up according to the water quality, and water quality has been emulated under the program of water resources allocation. It analysed the effect to water resources allocation which was caused by water quality and researched the technology of pollutants reduction under the protection target of water quality in water functional zone. Such a methodology can be used by basin managers in decision making and provides better performance in terms of both water resources and the environment. The methodology of water resource allocation model coupling quantity and quality is applied to the Huntai River Basin in China, under different scenarios. The results show that it is possible to reduce future water scarcity problems and improve the water environment. In addition, an optimal water resource allocation model can be useful for water saving and protection.

The main purpose of this study is to investigate the effects of aquatic plants with no leaves (L0), 4 leaves (L4), 8 leaves (L8), and 12 leaves (L12) on the mean streamwise velocity, turbulence structure, and Manning’s roughness coefficient. The results show that the resistance of submerged aquatic plants to flow velocity is discontinuous between the lower aquatic plant layer and the upper free water layer. This leads to the difference of flow velocity between the upper and lower layers. An increase of the number of leaves leads to an increase in the flow velocity gradient in the upper non-vegetation area and a decrease in the flow velocity in the lower vegetation area. In addition, aquatic plants induce a momentum exchange near the top of the plant and increase the Reynold’s stress and turbulent kinetic energy. However, because of the inhibition of leaf area on the momentum exchange, the Reynold’s stress and turbulent kinetic energy increase first and then decrease with the increase in the number of leaves. Quadrant analysis shows that ejection and sweep play a dominant role in momentum exchange. Aquatic plants can also increase the Reynold’s stress by increasing the ejection and sweep. The Manning’s roughness coefficient increases with the increasing number of leaves.