Evaluating Surface Water Nitrogen Pollution via Visual Clustering in Megacity Chengdu

The current standards used for nitrogen pollution evaluation are lacking, and scientific classification methods needed to improve water quality management capabilities. This study addresses the important issue of assessing surface by utilizing two advanced multivariate statistical techniques: self-organizing maps (SOMs) obtained using K-means algorithm Hasse diagram technique (HDT). research targets this rivers megacity Chengdu, China. Samples were collected on a monthly basis in 2017–2020 from different sites along rivers, their parameters determined. grouping clustering sampling events SOMs facilitate preprocessing required HDT, wherein clusters ordered according pre-clustered events. results indicate that Chengdu River Basin, which is prominent mainly driven nitrate nitrogen, can be categorized into five levels. Tuo serious. Although degree ammonia Jin higher, range smaller. Furthermore, these evaluated HDT clear reliable. Overall, findings provide local environmental legislation.