[Nitrate-Nitrogen Pollution Sources of an Underground River in Karst Agricultural Area Using N and O Isotope Technique].

The objectives of this study were to reveal the sources of nitrate and the ratio of karst in an agricultural basin based on a N and O isotope technique and quantitative calculation of the IsoSource model. From May to October 2017, six sampling points in the Qingmuguan river basin, Chongqing, were monitored every 24 d. Results showed that there was a great risk of nitrate pollution in the underground river system, because most NO-N concentrations of the sampling points exceeded the threshold. Spatially, NO-N concentrations in the underground river increased from upstream to downstream. Temporally, NO-N concentrations of Fishpond and Yankou Ponor upstream and Jiangjia Spring downstream were impacted by agricultural fertilizer from May to June and fluctuated from June to September due to precipitation. With decreased agricultural activities, NO-N concentrations gradually decreased after September. NO-N concentrations were high in midstream soil water. Daluchi, in the middle and lower reaches, maintained relatively low NO-N concentrations with stable fluctuations. Dual N and O isotopic compositions suggested that the upstream nitrates were derived from soil organic nitrogen and a mixture of manure and sewage. The midstream nitrates originated from soil organic nitrogen and NH from fertilizer and rain. Nitrates in the middle and lower reaches were derived from the mixing of manure and sewage, soil organic nitrogen, and NH from fertilizer and rain. Jiangjia Spring, the outlet of the underground river, was seriously polluted by nitrates. It is believed that soil organic nitrogen, NH in fertilizer and rain, the mixing of manure and sewage, and NO in precipitation were the main nitrate sources in the outlet. Nitrate source contribution of the outlet was calculated with the IsoSource model. The calculation results showed that manure and sewage, soil organic nitrogen, NH in fertilizer and rain, and NO in precipitation contributed 46.4%, 32.6%, 18.6%, and 2.4%, respectively.