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引用本文:明晓星,杨平恒,谢世友,盛婷,罗丹.金佛山世界遗产地岩溶地下河系统硝酸盐来源与转化.湖泊科学,2019,31(5):1299-1309. DOI:10.18307/2019.0521
MING Xiaoxing,YANG Pingheng,XIE Shiyou,SHENG Ting,LUO Dan.Sources and transformations of nitrate of the subterranean river system in Jinfoshan Karst World Heritage. J. Lake Sci.2019,31(5):1299-1309. DOI:10.18307/2019.0521
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金佛山世界遗产地岩溶地下河系统硝酸盐来源与转化
明晓星, 杨平恒, 谢世友, 盛婷, 罗丹
西南大学地理科学学院, 岩溶环境重庆市重点实验室, 自然资源部岩溶生态环境-重庆南川野外基地, 重庆 400715
摘要:
地下水硝酸盐污染已成为一个普遍的环境问题.为研究重庆金佛山水房泉岩溶地下河系统的硝酸盐来源与转化,于2017年4-10月每24 d左右对地下河系统内的某酒店自来水、化粪池、1#落水洞、水房泉4个采样点开展监测,进行水化学和δ15Nnitrate、δ18Onitrate同位素分析.某酒店污水经化粪池处理后,由1#落水洞排入地下河,最后在水房泉排泄.结果表明:①水房泉NO3-浓度范围为4.65~10.20 mg/L,相对于我国生活饮用水标准处于较低水平;化粪池、1#落水洞、水房泉3个采样点电导率和NO3-、Cl-浓度的高值期与游客人数增多对应关系较好.②某酒店自来水δ15Nnitrate值为3.7‰~5.8‰、δ18Onitrate值为1.6‰~2.7‰,说明硝酸盐主要来源为土壤有机氮,处于自然背景值;1#落水洞δ15Nnitrate值为14.4‰~21.1‰、δ18Onitrate值为3.5‰~11.2‰,显示硝酸盐主要来源为粪肥污水;化粪池和水房泉的δ15Nnitrate值为3.7‰~17.0‰、δ18Onitrate值为-9.0‰~7.3‰,表明硝酸盐主要来源为土壤有机氮与粪肥污水,显示其硝酸盐主要污染源是酒店生活废污水.③某酒店自来水、水房泉地下水的硝酸盐转化过程以同化作用为主;化粪池污水以硝化作用为主,是岩溶地下河系统硝酸盐的重要来源之一;1#落水洞污水表现为反硝化作用.④基于SIAR模型对水房泉的硝酸盐来源进行定量解析,发现大气降水、土壤有机氮和粪肥污水的贡献率分别为28%、36%和36%左右.
关键词:  地下河  硝酸盐  氮氧同位素  来源与转化  SIAR模型  金佛山
DOI:10.18307/2019.0521
分类号:
基金项目:国家自然科学基金项目(41103068)和中央高校基本科研业务费专项(XDJK2018AB002)联合资助.
Sources and transformations of nitrate of the subterranean river system in Jinfoshan Karst World Heritage
MING Xiaoxing, YANG Pingheng, XIE Shiyou, SHENG Ting, LUO Dan
School of Geographical Sciences, Southwest University, Chongqing Key Laboratory of Karst Environment, Field Scientific Observation & Research Base of Karst Eco-environments at Nanchuan in Chongqing, Ministry of Nature Resources of the People's Republic of China, Chongqing 400715, P. R. China
Abstract:
Nitrate pollution in groundwater has become a common environmental problem. From April to October in 2017, four sampling sites (a hotel's tap water, septic system, Sinkhole 1# and Shuifang spring) in Jinfoshan Karst, Chongqing were monitored every 24 days to investigate the sources and transformations of nitrate. The hydrochemistry and δ15Nnitrate, δ18Onitrate isotopic analyses were carried out. The sewage from hotel was degraded in the septic system, then discharged into the subterranean river by the Sinkhole 1#, and finally drained at Shuifang spring. Results showed that the concentrations of nitrate ranged from 4.65 to 10.20 mg/L at Shuifang spring, which was at a low level comparing with the standard of drinking water in China. The three high-value periods of the electrical conductivity and concentrations of nitrate and chloride at septic system, Sinkhole 1# and Shuifang spring corresponded well to the increase in the number of tourists. The isotopic nitrate compositions of hotel's tap water were found to range from 3.7‰ to 5.8‰ for δ15Nnitrate and from 1.6‰ to 2.7‰ for δ18Onitrate, indicating that the nitrate mainly originated from soil organic nitrogen maintaining at a natural background value. The δ15Nnitrate and δ18Onitrate at Sinkhole 1# varied from 14.4‰ to 21.1‰, and from 3.5‰ to 11.2‰, respectively, revealing that manure & sewage was the main source of nitrate at Sinkhole 1#. The δ15Nnitrate and δ18Onitrate at septic system and Shuifang spring varied between 3.7‰ and 17‰ for δ15Nnitrate value, and -9.0‰ and 7.3‰ for δ18Onitrate value, suggesting that soil organic nitrogen and manure & sewage were the major sources of nitrate which was dominantly derived from the domestic sewage of the hotel. In hotel's tap water and groundwater from Shuifang spring, assimilation is the main process of nitrate transformation. While effluent in septic system, one of the important sources of nitrate in the subterranean river system was affected by nitrification. The wastewater at Sinkhole 1# was characterized by denitrification. A SIAR model was used to estimate the contribution of each nitrate source to total nitrate at Shuifang spring, which indicated that the contribution rate of atmospheric precipitation, soil organic nitrogen and manure & sewage were roughly 28%, 36% and 36%, respectively.
Key words:  Subterranean river  nitrate  dual isotopes of nitrogen and oxygen  sources and transformations  SIAR model  Jinfoshan
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