Optimization of Monitoring Indexes of Nitrogen and Phosphorus in Rice Fields in the Lower Reaches of the Yangtze River Based on Cluster Analysis and Principal Component Analysis
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Abstract
Pollution from nutrients in rice production can affect water quality. To generate a nitrogen and phosphorus index for the surface water and leaching water from rice paddy fields in the lower reaches of the Yangtze River, samples were collected in the modern agricultural park of the Qingpu District, Shanghai in 2018 over the whole period of paddy growth. Leaching water was sampled at depths of 30 and 60 cm. Principal component analysis (PCA) and cluster analysis (CA) were used to optimize the monitoring indexes and to establish the minimum data set (MDS) for the monitoring indicators of nitrogen and phosphorus in rice paddy fields in this region. The comprehensive scores of water quality index (WQI) of the MDS and the comprehensive scores of water quality index of the total data set (WQI-TDS) based on different analysis methods were compared. The results show that: (1) a minimum data set composed of 3-4 indicators could be selected from eight monitoring indexes of the surface water and leaching water at depths of 30 and 60 cm in paddy fields by principal component analysis and cluster analysis. (2) The comprehensive scores of water quality in paddy fields based on different data sets were significantly different. The range and mean value of comprehensive scores of water quality show that WQI-PCA was closer to WQI-TDS than WQI-CA, and the Nash effective coefficient and correlation of WQI-PCA and WQI-TDS were higher than WQI-CA. This indicates that MDS-PCA is more suitable than MDS-CA to replace WQI-TDS as the monitoring and evaluation index for rice paddy water pollution.
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