环境保护科学2018，Vol.44Issue(3)：114-120,126,8.DOI:10.16803/j.cnki.issn.1004-6216.2018.03.019
基于BP神经网络的水质评价及水质时空演变趋势研究
Evaluation of Water Quality Based on BP Neural Network and Study of the Temporal and Spatial Evolution Trend of Water Quality
何钰 1唐颖 2陈兰英 2黎云祥 2敬安兵 2肖娟2
作者信息
- 1. 南充市环境工程评估中心,四川 南充 637000
- 2. 西华师范大学环境科学与工程学院,四川 南充 637000
- 折叠
摘要
Abstract
According to the monthly monitoring data of water quality from 2011 to 2015, BP neural network model and comprehensive index evaluation method were used to evaluate the water quality of Nanchong section of Jialing River, and the main influencing factors of water quality evolution were analyzed. The optimum evaluation method of surface water and the evolution laws of water quality in Nanchong section of Jialing River were discussed. The results showed that the BP neural network had the advantages of objective evaluation and convenient application compared to the comprehensive index evaluation method. From 2011 to 2015, the seasonal variation trend of water temperature, pH, total nitrogen ( TN) and Chl－a of the key rivers in Nanchong City appeared higher in summer but lower in winter, and there were obvious interannual changes in BOD5, NH+4－N and total phosphorus. From 2012, the monitoring indictors exceeding the standards declined with a stable variation trend. The correlation analysis showed that NH+4－N was the main factor affecting water quality, while water temperature, DO, BOD5, CODMn, TN and TP had strong correlation. The spatial cluster analysis showed that water pollution of the rivers along the downstream direction was aggravated. NH+4－ N, Chl － a, CODMn and BOD5 in the water quality assessment index were significantly positively correlated with the coastal urban homestead and industrial land, rural residential land and fish pond areas. Finally, pollution reduction, prevention and control strategy of ecological remediation of water pollution were proposed, providing reference for water pollution control and management of Jialing River and other rivers in China.关键词
BP神经网络/嘉陵江南充段/水质变化/演变规律/防治策略Key words
BP Neural Network/Nanchong Section of Jialing River/Water Quality Change/Evolution Law/Control Strategy分类
资源环境引用本文复制引用
何钰,唐颖,陈兰英,黎云祥,敬安兵,肖娟..基于BP神经网络的水质评价及水质时空演变趋势研究[J].环境保护科学,2018,44(3):114-120,126,8.
