Spatiotemporal variability and controlling factors of indirect N2O emission in a typical complex watershed

Abstract

The mechanisms of N2O emissions from inland rivers remain poorly understood because of the high variability of dissolved N2O concentration and the complexity of influencing factors. Thus, it is necessary to research the spatiotemporal patterns and influencing factors to understand the driving mechanisms of riverine N2O emissions. We combine the Soil and Water Assessment Tool (SWAT) outputs with established empirical equations to identify the spatiotemporal fluctuations of riverine N2O emissions and evaluate model performance through field measurements in a typical watershed. The spatiotemporal hotspots of N2O emissions are then determined, and the relative importance of environmental variables is further determined by correlation and attribution analysis. The results indicate that the riverine N2O emissions are relatively high from August to October, which accounted for 35.38% of the annual emissions. Temporal changes are attributed to agricultural activities and meteorological factors. Agricultural activities such as planting and fertilization lead to increased diffuse nitrogen loads on the land surface. Meantime, heavy precipitation events enhance the transport of nutrients, resulting in changes in nitrogen levels in the river. Spatial analysis shows that the urban watersheds (191.22 ± 156.19 μmol m−2 d−1) are the hotspots of riverine N2O emission, which are 1.55–3.03 times that of non-urban rivers. Spatial variations are mainly affected by riverine physicochemical indicators for different watersheds. Sewage from various sources received by urban rivers provides appropriate environmental conditions for N2O production, and transports large exogenous dissolved N2O. Furthermore, salinity (r = 0.80; p < 0.001) and nitrogen nutrients in riverine physicochemical indicators show a significant correlation with N2O fluxes. It emphasizes that N-related (TN, NH4+, NO3−) indicators are important reactants for N2O generation, which can promote nitrification and denitrification. Meanwhile, the results of structural equation modeling (SEM) also demonstrate that N2O emissions follow a similar pattern to riverine dissolved N2O concentration (r = 0.841, p < 0.001), and non-point source (r = 0.678, p < 0.001) play an important role in the changes of dissolved N2O concentrations. Our results highlight that certain hot moments and hot spots of rivers play a disproportionate role in year-round and basin-wide N2O emissions, respectively. It is necessary to implement more effective management measures by controlling key environmental factors to reduce N2O emissions.