Identifying spatiotemporal hotspots and sources of small-middle riverine nitrogen pollution using intensive field sampling and export coefficient model.

Terrestrial pollution discharge induces spatiotemporal heterogeneity in riverine nitrogen dynamics. Accurately identifying sensitive temporal phases, spatial hotspots, and primary pollution sources is essential for effective riverine environmental management. This study developed an identification framework to delineate spatiotemporal pollution hotspots and source contributions in the Dai River basin by coupling intensive monitoring with the export coefficient method. The results indicated that the flood season was a critical period for increased total nitrogen (TN) pollution. Approximately 60% of the annual rainfall occurred in July and August, resulting in a 2.5-fold increase in TN concentrations in August compared to June. Moreover, rainfall events exceeding 100 mm/day led to 2- to 3.5-fold increases in TN concentrations relative to pre-event levels, with maximum increases surpassing 14-fold. Automatic monitoring data revealed a decreasing trend in TN concentrations from upstream to downstream. Intensive monitoring identified the Yu, Xidai, and Sha rivers at the headwaters as pollution hotspot zones, characterized by higher nitrogen concentrations and larger basin areas. The export coefficient model results showed that urban domestic wastewater and livestock farming were the dominant sources, accounting for 35.87% and 35.55% of total discharges, respectively. Yuguan town exported 33.34 t of nitrogen, contributing 47% of the total discharges. Based on hotspot identification, we proposed differentiated and integrated management measures for each town.