Author(s): Su Han Nam; Siyooun Kwon; Young Do Kim
Linked Author(s): Young C. Kim, YongDo Kim
Keywords: Eutrophication spatial characteristics time-series characteristics total nitrogen regression analysis
Abstract: Anthropogenic activities introduce pollutants into rivers, leading to eutrophication issues. Effective river eutrophication management at the watershed level requires extensive spatial and temporal monitoring; however, traditional monitoring approaches are labor-intensive and have limitations. This study focused on predicting total nitrogen levels by incorporating spatial characteristics and temporal variability in the Nakdong River watershed. To account for these spatial and temporal dynamics within each watershed, clustering was used to form groups based on specific attributes. Subsequently, various models were compared to determine the optimal model for predicting total nitrogen levels in each cluster. The clustering-based regression model applied in this study demonstrated high potential for accurate total nitrogen prediction at the watershed scale. If applied to diverse watersheds in the future, this approach is expected to contribute to national water quality management.
Year: 2025