RESUMO
Due to increasing active nitrogen pollution loads, river systems have become an important source of nitrous oxide (N2O) in many areas. Due to the lack of monitoring data in many studies as well as the difficulty in estimating intermediate parameters and expressing temporal-spatial variability in current methods, a high level of uncertainty remains in the estimates of riverine N2O emission quantity. Based on the monthly monitoring efforts conducted for 10 sampling sites across the Yonganxi River system in Zhejiang Province from June 2016 to July 2019, the temporal and spatial dynamics of riverine N2O dissolved concentrations ρ(N2O), N2O fluxes, and their influencing factors were addressed. A multiple regression model was then developed for predicating riverine N2O emission flux to estimate annual N2O emission quantity for the entire river system. The results indicated that observed riverine ρ(N2O) (0.03-2.14 µg·L-1) and the N2O fluxes[1.32-82.79 µg·(m2·h)-1] varied by 1-2 orders of magnitude of temporal-spatial variability. The temporal and spatial variability of ρ(N2O) were mainly influenced by the concentrations of nitrate, ammonia, and dissolved organic carbon, whereas the N2O emission fluxes were mainly affected by river water discharges and ρ(N2O). A multiple regression model that incorporates variables of river water discharge and ρ(N2O) could explain 90% of the variability in riverine N2O emission fluxes and has high accuracy. The model estimated N2O emission quantity from the entire Yonganxi River system of 3.67 t·a-1, with 29% from the main stream and 71% from the tributaries. The IPCC default emission factor method might greatly overestimate and underestimate N2O emission quantities for rivers impacted by low and high pressures of human activities, respectively. This study advances our quantitative understanding of N2O emission for the entire river system and provides a reference method for estimating riverine N2O emission with more accuracy.