Review of social water cycle research in a changing environment

Lu, Shilei; Zhang, Xiaoling; Bao, Haijun; Skitmore, Martin

doi:10.1016/j.rser.2016.04.071

Cited by 61 publications

(19 citation statements)

References 38 publications

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“…HDFS has adopted the classic Master/Slave system structure after referring to the structure of the GFS Master-Chunk Server. The entire HDFS consists of a name node, data node, 2 Complexity and client; except for the name node, the quantity of the remaining two can be multiple ones. The name node is the system administrator that is responsible for namespace maintenance and block [16].…”

Section: Hadoop Cloud Computationmentioning

confidence: 99%

“…Recycled water reuse has brought huge social and environmental benefits in terms of improvement of water resource utilization and economic efficiency in cities [1]. Meanwhile, it can also promote the sustainable development of water resource [2]. However, the publicity of recycled water reuse in China is far behind the level of developed countries at the same period because of a late start.…”

Section: Introductionmentioning

confidence: 99%

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Big Data Digging of the Public’s Cognition about Recycled Water Reuse Based on the BP Neural Network

Liu

Wang

et al. 2018

Complexity

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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.

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Section: Hadoop Cloud Computationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Big Data Digging of the Public’s Cognition about Recycled Water Reuse Based on the BP Neural Network

Liu

Wang

et al. 2018

Complexity

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“…In the past 100 years, the demand of for water has increased by nearly 8 times [1]. Human activities have become the most important factor affecting the natural water cycling system, and its influence has exceeded the limit of ecological bearing capabilities, thus causing irreversible damage [2,3]. In urban areas with relatively dense industries and population, the supply-demand conflict of water resources is extremely significant, making water resources an important factor that restricts the development of the social economy in the 21st century [4].…”

Section: Introductionmentioning

confidence: 99%

Research on Big Data Digging of Hot Topics about Recycled Water Use on Micro-Blog Based on Particle Swarm Optimization

Liu

et al. 2018

Sustainability

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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.

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“…The system can analyze the droughts probabilities at different degrees in each period. Passing through the use of Markov chain method, we can get the stability of the drought transition probability [23]. Therefore, probability in the next period can be found in the drought probability transition matrix based on the drought situations of this period.…”

Section: Introductionmentioning

confidence: 99%

Evaluation on Early Drought Warning System in the Jinghui Channel Irrigation Area

Shang

Zhang

2020

IJERPH

Self Cite

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With the economic growth, continuous global environment deterioration, and increasingly serious water resources shortage, droughts have become more and more serious and produced great impacts on both the regional ecology and sustainable economic development. This paper has established the “green, blue, yellow, orange, and red lights” as the early warning grades for agricultural droughts. By using the two influencing factors, namely precipitation and soil moisture, this paper has established the drought assessment index evaluation model using weighted coupling method. It has carried out the analogue simulation of the early drought warning based on the Jinghui Channel’s 2013 water source situations. The soil moisture in January and February is relatively ideal, and the actual early drought warning is expressed by the “green light”. The soil moisture deficit is comparatively serious in March, but the situation concerning water inflow is ideal with the “green light”. Actually, the early warning signal is basically consistent with the soil moisture drought degree between April and August. The actual early warning is expressed by the “green light” as well, but the soil moisture is not so ideal, however, this is the seeding time of the winter wheat so the lack of soil moisture has no impact on the crops output. In November and December, the winter wheat is at the growth and development stage and does not need much moisture. At this stage, the soil moisture is relatively poor. By integrating the time effects into the early drought warning system, this paper provides administrators of irrigation areas with a scientific decision-making based on the drought control measures.

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Review of social water cycle research in a changing environment

Cited by 61 publications

References 38 publications

Big Data Digging of the Public’s Cognition about Recycled Water Reuse Based on the BP Neural Network

Big Data Digging of the Public’s Cognition about Recycled Water Reuse Based on the BP Neural Network

Research on Big Data Digging of Hot Topics about Recycled Water Use on Micro-Blog Based on Particle Swarm Optimization

Evaluation on Early Drought Warning System in the Jinghui Channel Irrigation Area

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