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首页> 外文期刊>The Science of the Total Environment >Quantitative identification of nitrate sources in the surface runoff of three dominant forest types in subtropical China based on Bayesian model
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Quantitative identification of nitrate sources in the surface runoff of three dominant forest types in subtropical China based on Bayesian model

机译:基于贝叶斯模型的亚热带亚热带三种主要森林类型硝酸盐源的定量鉴定

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Nitrate pollution is a global environmental issue. Forests play an important role in altering hydrological processes and purifying water pollutants in rainfall and runoff. The quantitative identification of nitrate concentration and sources in surface runoff is of great significance for watershed management and water environment improvement. In this study, water quality of surface runoff was monitored in three typical forest types in subtropical eastern China: Phyllostachys pubescens, Cunninghamia lanceolate, and Cyclobalanopsis glauca. Combined with hydrochemical analysis, we adopted the dual isotope approach (δ~(15)N-NO_3~- and δ~(18)O-NO_3~-) and Bayesian model (SIAR) to identify nitrate sources in forests that are subject to low anthropogenic disturbance. Results showed that the temporal variability of NO_3-N concentrations was similar for all forest types, with higher values in periods of low rainfall and lower values in heavy rainfall periods. The NOi-N concentration in runoff was much higher in C. glauca forests relative to P. pubescens and C. lanceolata. Both the Cl~- concentrations and NO_3~-/Cl~- molar ratio suggested the fertilizer inputs was the dominant source of nitrate in surface runoff. In agreement, δ~(15)N-NO_3~- and δ~(18)O-NO_3~- values inferred atmospheric deposition and chemical fertilizers to be the main sources of nitrate in all forest types. The Bayesian model outputs demonstrated that atmospheric deposition was the main source in the runoff in P. pubescens and C. lanceolate forests, contributing 28.83% and 35.08% to the total nitrate, respectively. In contrast, chemical fertilizers were identified as the main source in C. glauca forests, with NH_4~+ fertilizers and NO_3~- fertilizers accounting for 27.07% and 24.83%, respectively. Both chemical and isotopic analysis indicated that nitrification had little contribution to nitrate concentrations in runoff. Our results suggest that, even in forests with low anthropogenic disturbance, the application of fertilizer in surrounding agricultural regions should be effectively managed to minimize watershed nitrogen contamination.
机译:硝酸盐污染是一个全球环境问题。森林在改变水文过程中发挥着重要作用,在降雨和径流中净化水污染物。硝酸盐浓度和表面径流源的定量鉴定对于流域管理和水环境改善具有重要意义。在这项研究中,在亚热带东部的三种典型的森林类型中监测了表面径流水质:Phyllostachys Pubescens,Cunninghamia披针形和Cyclobalanopsis Glauca。结合水化学分析,我们采用了双同位素方法(δ〜(15)N-NO_3〜 - 和δ〜(18)O-NO_3〜 - )和贝叶斯模型(SIR),以识别受到约束的森林中的硝酸盐来源低人为干扰。结果表明,对于所有森林类型,NO_3-N浓度的时间变异性相似,具有较高的降雨量的值较高,降低降雨周期的较低值。径流中的Noi-n浓度在C.Glauca森林中相对于P. Pubescens和C. Lanceolata的林。 Cl〜浓度和NO_3〜/ CL〜 - 摩尔比表明肥料输入是表面径流中硝酸盐的主要源。在一致语中,Δ〜(15)n-no_3〜 - Δ〜(18)O-NO_3〜 - 值推断大气沉积和化学肥料是所有森林类型中的硝酸盐的主要来源。贝叶斯模型产出证明,大气沉积是P. Pubescens和C.披针形森林的径流中的主要来源,分别为总硝酸盐贡献28.83%和35.08%。相比之下,化肥被鉴定为C.Glauca森林的主要来源,NH_4〜+肥料和NO_3〜 - 肥料分别占27.07%和24.83%。化学和同位素分析都表明硝化对径流浓度几乎没有贡献。我们的研究结果表明,即使在具有低人为干扰的森林中,应有效地设法应用肥料在周围的农业区域中的应用,以最大限度地减少流域氮污染。

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