The public’s acceptance level of recycled water use is a key factor that affects the popularization of this technology; therefore, it is critical to know the public’s attitude in order to make guiding policies effectively and scientifically. To examine the major focuses and hot topics among the public about recycled water use, one of the major platforms for social opinion in China, the micro blog, is used as a source to obtain data related to the topic. Through the “follow-be followed” and “forward-dialogue” behaviors, a network of discussion of recycled water use among micro-blog users has been constructed. Improved particle swarm optimization has been used to allow deep digging for key words. Ultimately, key words about the topic of have been clustered into three categories, namely, the popularization status of recycled water use, the main application, and the public’s attitude. The conclusion accurately describes the concerns of Chinese citizens regarding recycled water use, and has important significance for the popularization of this technology.

Large-scale water transfer projects (LWTPs) have been promoted to address rising water demands around the world. Scholars have been examining various impacts of LWTPs for decades; however, there is limited research that systematically examines the literature and synthesizes impacts and lessons learned from LWTPs. By conducting a systematic literature review, we assess the impacts of LWTP implementation on communities followed by the social, political, and economic factors that shape the implementation of LWTPs. Our review indicates that LWTPs can threaten livelihood strategies, jeopardize the sustainability of traditional cultures, and disrupt communities through resettlement. These impacts are shaped by the use of water as a political mechanism, the prioritization of economic interests, and unequal participation of stakeholders. Our review goes beyond individual studies of LWTPs to highlight the importance of using an environmental justice framework to guide LWTP assessments so that these assessments can address unique contexts of individual LWTPs.

Reuse of recycled water is very important to both the environment and economy, while the public cognition degree towards recycled water reuse also plays a key role in this process, and it determines the acceptance degree of the public towards recycled water reuse. Under the background of the big data, the Hadoop platform was used to collect and save data about the public’s cognition towards recycled water in one city and the BP neural network algorithm was used to construct an evaluation model that could affect the public’s cognition level. The public’s risk perception, subjective norm, and perceived behavioral control regarding recycled water reuse were selected as key factors. Based on a multivariate clustering algorithm, MATLAB software was used to make real testing on massive effective data and assumption models, so as to analyze the proportion of three evaluation factors and understand the simulation parameter scope of the cognition degree of different groups of citizens. Lastly, several suggestions were proposed to improve the public’s cognition on recycled water reuse based on the big data in terms of policy mechanism.

The South-to-North Water Transfer Project (SNWTP) in China which is the world’s largest water transfer project completed in 2014 is promoted as a strategy to mitigate water stresses in the northern China by the Chinese government and engineers. However, the ecological compensation of SNWTP in China has been slow and less for the people living in the water source area which was lost their opportunities to earn money; some had even lost their farmland. A key issue for SNWTP is to establish an eco-compensation system, define the compensation scheme, and make an effective economic compensation to the people living in the water source area. In this paper, we take the water source area of the Middle-Route project of SNWTP located in Southern Shaanxi including three cities called Hanzhong, Ankang and Shangluo as the research regions. Six factors are taken into consideration: (1) ecological losses, (2) economic losses and (3) ecological bonus in our eco-compensation strategy, as well as join two dynamic factors accounting in the calculation of ecological damage, (4) water quantity and (5) water quality. Besides, the total amount of compensation is changing over time. (6) Time scale factor is also used to simulate. In the article, we set three-time periods to calculate the different amount of compensation for the water source area. Finally, the Southern Shaanxi, supplied 70% water to Danjiangkou Reservoir, were analyzed by this model. We make full use of the reasonable eco-compensation strategy and try to solve actual problems of water source area and even provide a basis conception for the watershed protection and management.