Spatiotemporal monitoring of total nitrogen and ammonia nitrogen in Danjiangkou reservoir

• Main Authors: LIU Xuan, ZHAO Tongqian, CAI Taiyi, XIAO Chunyan, CHEN Xiaoshu, ZHANG Wenjing
• Format: Article
• Language: zho
• Published: Agro-Environmental Protection Institute, Ministry of Agriculture 2021-09-01
• Series: Journal of Agricultural Resources and Environment
• Subjects: danjiangkou reservoir; sentinel-2; bp neural network; total nitrogen; ammonia nitrogen; spatiotemporal change
• Online Access: http://www.aed.org.cn/nyzyyhjxb/html/2021/5/20210513.htm

The quantitative inversion of water quality index content could clarify the spatiotemporal distribution characteristics, migration, and transformation laws of water quality indexes. This study focuses on the Danjiangkou reservoir, the source of the middle route of the South-to-North Water Diversion Project. Based on the reflectance of different band combinations of Sentinel-2 remote sensing images, combined with the total nitrogen(TN) and ammonia nitrogen(NH₃-N) water quality monitoring data of the sampling points in February 2016, we established a BP neural network model to invert the TN and NH₃-N contents from 2016 to 2020 in order to analyze the characteristics of spatiotemporal changes of the TN and NH₃-N contents in the reservoir area and to explore the factors affecting the changes. Our results showed that the fitting accuracy of TN and NH₃-N in the constructed BP neural network model was relatively high, <i>R</i>²=0.863 and 0.877, respectively, which was suitable for remote sensing inversion research of TN and NH₃-N in the Danjiangkou reservoir. The water quality of the Danjiangkou reservoir had shown an overall improving trend from 2016 to 2020. The NH₃-N content had been in line with Class Ⅰ water quality standards, while the TN concentration had been between Class Ⅲ and Ⅳ water quality standards. The results show that the BP neural network model based on sentinel-2 MSI image bands is suitable for the remote sensing inversion of the TN and NH₃-N concentration. It could provide technical support for the improvement of the water ecological environment and water quality supervision of large lakes.