A lagged variable model for characterizing temporally dynamic export of legacy anthropogenic nitrogen from watersheds to rivers

A lagged variable model for characterizing temporally dynamic export of legacy anthropogenic nitrogen from watersheds to rivers
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用于表征遗留人为氮从流域到河流的时间动态输出的滞后变量模型

DOI:
10.1007/s11356-015-4377-y
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发表时间:
2015-03
影响因子:
5.8
通讯作者:
y A. Dahlgren
y A. Dahlgren
中科院分区:
环境科学与生态学3区
文献类型:
--
作者:
Dingjiang Chen;Yi Guo;Minpeng Hu;R;y A. Dahlgren

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来自人类氮输入(NANI)的遗留氮源可能是许多地区河流氮输出增加的主要原因,尽管NANI显著下降。然而,关于NANI对河流氮输出的滞后效应的定量知识很少。因此,在目前的流域模型中,N淋溶滞后效应没有得到很好的体现。本研究开发了一个滞后变量模型(LVM),以解决流域NANI到河流的时间动态输出。采用Koyck变换方法在经济分析中使用的,LVM表示的不确定数量的滞后项从往年的NANI与一个滞后项,结合了前一年的河流N通量,使我们能够反向校准模型参数从可测量的变量使用贝叶斯统计。对中国东部椒江上游流域1980-2010年的调查结果表明,97%的年NANI流入河流的通量发生在当年和随后的10年(滞后时间约为11年),72%的年NANI流入河流的通量来源于前几年的NANI。现有的NANI在1993-2010年期间需要减少22%才能达到目标TN水平(1.0 mg N L−1),考虑到滞后效应,指导流域氮源控制。模型结构和参数(本研究中只有四个参数)的简约性,因此,它很容易开发和应用于其他流域。该模型为定量分析人为氮素输入对河流输出的滞后效应提供了一种简单有效的工具,为有效制定和评价流域氮素控制策略提供了支持。
Legacy nitrogen (N) sources originating from anthropogenic N inputs (NANI) may be a major cause of increasing riverine N exports in many regions, despite a significant decline in NANI. However, little quantitative knowledge exists concerning the lag effect of NANI on riverine N export. As a result, the N leaching lag effect is not well represented in most current watershed models. This study developed a lagged variable model (LVM) to address temporally dynamic export of watershed NANI to rivers. Employing a Koyck transformation approach used in economic analyses, the LVM expresses the indefinite number of lag terms from previous years’ NANI with a lag term that incorporates the previous year’s riverine N flux, enabling us to inversely calibrate model parameters from measurable variables using Bayesian statistics. Applying the LVM to the upper Jiaojiang watershed in eastern China for 1980–2010 indicated that ~97 % of riverine export of annual NANI occurred in the current year and succeeding 10 years (~11 years lag time) and ~72 % of annual riverine N flux was derived from previous years’ NANI. Existing NANI over the 1993–2010 period would have required a 22 % reduction to attain the target TN level (1.0 mg N L−1), guiding watershed N source controls considering the lag effect. The LVM was developed with parsimony of model structure and parameters (only four parameters in this study); thus, it is easy to develop and apply in other watersheds. The LVM provides a simple and effective tool for quantifying the lag effect of anthropogenic N input on riverine export in support of efficient development and evaluation of watershed N control strategies.
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