Exploring the Spatiotemporal Heterogeneity of Stream Nitrogen Concentrations in a Typical Human-Activity-Influenced Headwater Watershed in South China

Abstract

Stream nitrogen concentrations significantly impact nitrogen loads and greenhouse gas emissions, but their spatiotemporal heterogeneity and human influences remain highly uncertain. This study thoroughly explored the spatiotemporal variations in stream nitrogen concentrations in a typical headwater watershed in South China. Spatially distributed measurements were conducted during 2020–2022, and mathematical modeling was implemented based on incorporating these data. More than 4,400 data points were collected for water temperature and concentrations of ammonium nitrogen (NH₄-N), nitrate nitrogen (NO_x-N), dissolved total nitrogen (DTN), total nitrogen (TN), and dissolved oxygen. Results showed that NO_x-N was the largest component of TN, with average concentrations of 1.20 and 1.66 mg L⁻¹, respectively. The stream N₂O concentration could be predicted using NH₄-N and NO_x-N concentrations via the Michaelis-Menten equation. Significant downstream decreases in NH₄-N, NO_x-N, DTN, and TN concentrations were identified in the largest river in the watershed, and clear spatial differences in these nitrogen concentrations existed among the three main rivers. Clear seasonal and annual variations in stream nitrogen concentrations were observed. NH₄-N, NO_x-N, DTN, and TN concentrations correlated with cumulative precipitation from the preceding 8–12 days, while stream N₂O concentrations correlated over 13–20 days. Stream N₂O concentrations and emissions averaged 12.77 nmol L⁻¹ and 1.12 nmol m⁻² s⁻¹, respectively, and were lower in summer than in other seasons. Upstream tea plantations, villages, and adjacent agricultural lands significantly affected nitrogen concentrations, while overflow dams did not. These findings highlight nitrogen cycle's complexity and the need for high-resolution data to guide effective watershed management.