Prediction Studies of River Water Quality Based on Moving Average Weighted Markov Model - A Case Study of Shiwei Port, Jingjiang City

被引:2
作者
Jiao, Kuo [1 ]
Cheng, Liang [1 ]
Tao, Ya [1 ]
Chen, Peng [1 ]
Chen, Wei [2 ]
机构
[1] Minist Ecol & Environm, Environm Protect Investment Performance Managemen, Environm Planning Inst, Beijing, Peoples R China
[2] Taizhou Jingjiang Ecol & Environm Bur, Jingjiang, Jiangsu, Peoples R China
来源
3RD INTERNATIONAL CONFERENCE ON AIR POLLUTION AND ENVIRONMENTAL ENGINEERING | 2020年 / 631卷
关键词
D O I
10.1088/1755-1315/631/1/012060
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
It is of great significance to predict the change trend of river water quality and comprehensively prevent and control river pollution for the protection of water quality of the Yangtze River and the implementation of "to step up conservation of the Yangtze River and stop its over development". Shiwei Port of Jingjiang City is located in the middle of Jingjiang City. It runs from north to south, connects the Jingtai Boundary River in the north, and enters the Yangtze River in the south. It is a first-class tributary of the Yangtze River. Based on the Moving Average Weighted Markov Model, this paper conducts an applied research on the water quality of Shiwei Port flowing into the Yangtze River. It is found that with the increase of the moving step, the accuracy of the moving prediction increases gradually, and the highest accuracy of the moving prediction is 24.9% compared with the original data, which shows that the moving average is necessary for the weighted Markov water quality prediction. Finally, the problems of the prediction model are analyzed and discussed, and the corresponding suggestions for the water quality and environmental management of Jingjiang City where Shiwei port is located are put forward, which can provide reference for the water quality management of other cities on both sides of the Yangtze River.
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页数:9
相关论文
共 16 条
[1]  
Cao Qun, 2011, SCI TECHNOLOGY INNOV, P241
[2]  
Khalil Arya F, 2014, AGU FALL M AGU FALL
[3]   Chance-Constrained Dynamic Programming for Multiple Water Resources Allocation Management Associated with Risk-Aversion Analysis: A Case Study of Beijing, China [J].
Li, Wei ;
Jiao, Kuo ;
Bao, Zhe ;
Xie, Yulei ;
Zhen, Jiliang ;
Huang, Guohe ;
Fu, Lingbo .
WATER, 2017, 9 (08)
[4]   The valuation of China's environmental degradation from 2004 to 2017 [J].
Ma, Guoxia ;
Peng, Fei ;
Yang, Weishan ;
Yan, Gang ;
Gao, Shuting ;
Zhou, Xiafei ;
Qi, Ji ;
Cao, Dong ;
Zhao, Yue ;
Pan, Wen ;
Jiang, Hongqiang ;
Jing, Hong ;
Dong, Guangxia ;
Gao, Minxue ;
Zhou, Jingbo ;
Yu, Fang ;
Wang, Jinnan .
ENVIRONMENTAL SCIENCE AND ECOTECHNOLOGY, 2020, 1
[5]  
Qiu Lin, 2007, YANGTZE RIVER, P81
[6]  
Qiu Xunping, 2001, YANGTZE RIVER, P26
[7]  
Rong Jie, 2013, J WATER RESOURCES WA, P98
[8]   An anisotropic and inhomogeneous hidden Markov model for the classification of water quality spatio-temporal series on a national scale: The case of Scotland [J].
Spezia, Luigi ;
Brewer, Mark J. ;
Birkel, Christian .
ENVIRONMETRICS, 2017, 28 (01)
[9]  
Sun Leqiang, 2012, YELLOW RIVER, P28
[10]  
Wang Bei, 2009, J WATER RESOURCES RE, V12, P25