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引用本文:崔玉环,王杰,郝泷,董斌,高祥.长江中下游平原升金湖流域硝酸盐来源解析及其不确定性.湖泊科学,2021,33(2):474-482. DOI:
Cui Yuhuan,Wang Jie,Hao Shuang,Dong Bin,Gao Xiang.The contribution rates of nitrate sources and their uncertainties in Shengjin Lake Basin, middle and lower reaches of the Yangtze River Plain. J. Lake Sci.2021,33(2):474-482. DOI:
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长江中下游平原升金湖流域硝酸盐来源解析及其不确定性
崔玉环1, 王杰2,3, 郝泷1, 董斌1, 高祥1
1.安徽农业大学理学院, 合肥 230036;2.安徽大学资源与环境工程学院, 合肥 230601;3.安徽大学湿地生态保护与修复安徽省重点实验室, 合肥 230601
摘要:
考虑流域地理特征的空间分异,以升金湖流域人口/农业集约区大渡口(DDK)与森林子流域唐田河(TTH)为研究区,利用贝叶斯同位素混合模型分别解析这2个子流域硝酸盐来源的贡献率,并分析其不确定性.研究表明:(1)地下水中,DDK、TTH硝酸盐均主要来源于粪便/污水,贡献率可达65%以上,粪便/污水通过土壤下渗导致地下水硝酸盐富集.(2)地表水中,DDK硝酸盐主要来源于化学肥料,贡献率约为56%;而TTH主要来源于土壤,贡献率为44%;化肥和粪便/污水在DDK的贡献率要高于TTH.(3)无论是地表水还是地下水,贡献率大的硝酸盐来源,其不确定性较大,这与流域土地利用方式、生活污染源以及土壤理化特性等因素的空间差异有关.
关键词:  硝酸盐氮氧同位素  贝叶斯混合模型  硝酸盐源解析  不确定性  升金湖流域
DOI:
分类号:
基金项目:国家自然科学基金项目(41401022,41801332)、安徽高校自然科学研究项目(KJ2019A0045)和精准林业北京市重点实验室项目(2015ZCQ-LX-01)联合资助.
The contribution rates of nitrate sources and their uncertainties in Shengjin Lake Basin, middle and lower reaches of the Yangtze River Plain
Cui Yuhuan1, Wang Jie2,3, Hao Shuang1, Dong Bin1, Gao Xiang1
1.School of Science, Anhui Agricultural University, Hefei 230036, P. R. China;2.School of Resources and Environmental Engineering, Anhui University, Hefei 230601, P. R. China;3.Anhui Province Key Laboratory of Wetland Ecosystem Protection and Restoration, Anhui University, Hefei 230601, P. R. China
Abstract:
Considering the spatial differentiation of geographical characteristics in the basin, the population/agricultural intensive watershed (DDK) and a forest sub-watershed (TTH) in Shengjin Lake Basin selected as study areas, Bayesian isotope mixed models is used to analyse the contribution rates and uncertainties of potential nitrate sources in surface water and groundwater. For the groundwater type in the basin, nitrate in DDK and TTH are mainly comes from manure and sewage, with the contribution rate more than 65%, which is caused by the infiltration of manure and sewage through soil. For the surface water type, nitrate in DDK mainly comes from chemical fertilizer, with a contribution rate of 56%, while that in TTH mainly comes from soil with a contribution rate of 44%. The contribution of chemical fertilizer and manure and sewage in DDK is significantly higher than that that in TTH. Whether for surface water or groundwater, the nitrate sources with the larger contribution rate have greater uncertainties, which are related to spatial differentiation in factors such as land use patterns, domestic pollution sources, and soil physicochemical characteristics.
Key words:  Nitrate isotopes  Bayesian mixed model  nitrate source identification  uncertainty  Shengjin Lake Basin
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