Membrane and Water Treatment

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Water quality big data analysis of the river basin with artificial intelligence ADV monitoring

  • Chen, ZY (School of Science, Guangdong University of Petrochemical Technology) ;
  • Meng, Yahui (School of Science, Guangdong University of Petrochemical Technology) ;
  • Wang, Ruei-yuan (School of Science, Guangdong University of Petrochemical Technology) ;
  • Chen, Timothy (California Institute of Technology)
  • Received : 2019.09.15
  • Accepted : 2022.08.30
  • Published : 2022.09.25
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Abstract

5th Assessment Report of the Intergovernmental Panel on Climate Change Weather (AR5) predicts that recent severe hydrological events will affect the quality of water and increase water pollution. To analyze changes in water quality due to future climate change, input data (precipitation, average temperature, relative humidity, average wind speed, and solar radiation) were compiled into a representative concentration curve (RC), defined using 8.5. AR5 and future use are calculated based on land use. Semi-distributed emission model Calculate emissions for each target period. Meteorological factors affecting water quality (precipitation, temperature, and flow) were input into a multiple linear regression (MLR) model and an artificial neural network (ANN) to analyze the data. Extensive experimental studies of flow properties have been carried out. In addition, an Acoustic Doppler Velocity (ADV) device was used to monitor the flow of a large open channel connection in a wastewater treatment plant in Ho Chi Minh City. Observations were made along different streams at different locations and at different depths. Analysis of measurement data shows average speed profile, aspect ratio, vertical position Measure, and ratio the vertical to bottom distance for maximum speed and water depth. This result indicates that the transport effect of the compound was considered when preparing the hazard analysis.

Keywords

Acknowledgement

The authors are grateful for the research grants given to Ruei Yuan Wang from GDUPT talent introduction, Peoples R China under Grant No. 702 519208, the Projects of Talents Recruitment of GDUPT (NO. 2019rc098), and the research grants given to ZY Chen from the Projects of Talents Recruitment of GDUPT (NO. 2021rc002) in Guangdong Province, Peoples R China.

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