Abstract
According to the current situation of water quality in drainage basin, the key to improve the prediction accuracy is to select the appropriate prediction model of water quality. The time series method excellently reflected the continuity of the future data in the case of emphasizing historical data. What’s more, the time series method has the higher short-term prediction accuracy and simple modeling process. So, the time series method was used to establish the Auto-Regressive and Moving Average (ARMA) model for the time series of the concentration of dissolved oxygen (DO), biochemical oxygen demand (BOD5), chemical oxygen demand (CODCr), ammonia nitrogen (NH3-N) and total nitrogen (TN) at the Guidu fu section of Qingyi River from January 2011 to December 2015. Then, the concentrations of the five water quality indicators from January to June 2016 were predicted, which were verified and analyzed with the measured values. The results show that the model has fine fitting effect and higher prediction accuracy, which can accurately reflect the current and future change trends of the water quality.
Highlights
The water environment problem in drainage basin is one of the most important problems faced by environmental management in China in recent years
Because the mechanism water quality prediction model uses the governing equation to describe the changing trend of water quality, it is necessary to identify the parameters with practical physical significance in the modeling process, which leads to the modeling process more complex [1]
Five water quality indicators data such as dissolved oxygen (DO), BOD5, CODCr, NH3-N and total nitrogen (TN) were selected from the Guidu fu section of Qingyi River from January 2011 to June 2016
Summary
The water environment problem in drainage basin is one of the most important problems faced by environmental management in China in recent years. The time series method has a relatively complete mathematical theory foundation, which can make full use of historical data to make quantitative predictions for future water quality, and the short-term prediction accuracy is well [11]. Time series method is a mature data processing method It analyzes and studies the corresponding time series mathematical model established by the dynamic water quality parameter data, and excavates the periodic information of the water quality change to make an accurate prediction of the data change trend. Because of the uncertainties of external factors on the water quality of Qingyi River and the insufficient information of relevant data, the prediction accuracy of long-term time scale cannot meet the requirements. In order to provide a scientific basis for local water environment management and protection
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
