Modeling forest/agricultural and residential nitrogen budgets and riverine export dynamics in catchments with contrasting anthropogenic impacts in eastern China between 1980–2010
Modeling forest/agricultural and residential nitrogen budgets and riverine export dynamics in catchments with contrasting anthropogenic impacts in eastern China between 1980–2010
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对 1980 年至 2010 年间中国东部流域的森林/农业和住宅氮预算和河流出口动态进行建模，对比人为影响
DOI：
10.1016/j.agee.2016.01.037
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发表时间：
2016-04
影响因子：
6.6
通讯作者：
y A. Dahlgren
中科院分区：
文献类型：
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作者：
Dingjiang Chen;Minpeng Hu;Yi Guo;R;y A. Dahlgren
本研究量化了中国东部三个受低（LD）、中（MD）和高（HD）人类影响的流域的河流总氮（TN）输出对森林/农业（NANIFA）和住宅（NANIR）系统人为氮净输入变化的长期响应。1980-1999年NANIFA年增长63-87%，2000-2010年NANIFA年变化为0%（LD），-23%（MD）和-40%（HD），导致1980-2010年NANIFA净增长56-78%。1980-2010年，三个集水区的年NANIR增加了101-152%。土地利用显示，在研究期间，已开发土地面积（D%）增加了58-65%，排水系统得到改善的农业用地（AD%）增加了96-108%。在过去的31年中，在NANIFA，NANIR和土地利用的变化，河流TN通量持续增加3.0至6.1倍，在三个集水区。对于每个流域，建立了一个经验模型，该模型将年NANIFA、NANIR、排水量、D%和AD%结合起来，用于预测和量化河流TN通量的来源（R2= 0.93 − 0.97）。该模型估计，NANIFA，NANIR和其他N源（例如，自然背景、历史遗留和工业氮源分别占河流总氮通量的27- 90%、0- 45%和10-28%。模型结果与河流氯、铵、硝酸盐、溶解氧和pH值的时空变化以及农业土壤有效氮水平的变化相一致。在氮源管理方面，LD流域NANIFA和HD流域NANIR的减少对减少河流TN通量的影响最大。此外，在制定氮污染控制策略时，应考虑土地利用和气候的变化以及遗留氮。
This study quantified the long-term response of riverine total nitrogen (TN) export to changes in net anthropogenic nitrogen inputs to forest/agricultural (NANIFA) and residential (NANIR) systems across three catchments affected by low (LD), medium (MD), and high (HD) human impacts in eastern China. Annual NANIFAincreased by 63–87% in 1980–1999, followed by 0% (LD), −23% (MD) and −40% (HD) changes of NANIFAin 2000–2010, resulting in a net increase of 56–78% in NANIFAin 1980–2010. Annual NANIRincreased by 101–152% in the three catchments in 1980–2010. Land-use showed a 58–65% increase in developed land area (D%) and a 96–108% increase in agricultural lands with improved drainage systems (AD%) over the study period. In response to changes in NANIFA, NANIRand land-use, riverine TN flux continuously increased 3.0- to 6.1-fold in the three catchments over the past 31 years. For each catchment, an empirical model incorporating annual NANIFA, NANIR, water discharge, D%, and AD% was developed (R2= 0.93 − 0.97) for predicting and quantifying sources of annual riverine TN fluxes. The model estimated that NANIFA, NANIRand other N sources (e.g., natural background, legacy, and industrial N sources) contributed 27–90%, 0–45%, and 10–28% of riverine TN fluxes, respectively. Model results were consistent with spatio-temporal changes of riverine chloride, ammonium, nitrate, dissolve oxygen and pH, as well as changes in available N levels in agricultural soils. In terms of N source management, reduction of NANIFAin catchment LD and NANIRin catchment HD would have the greatest impact on reducing riverine TN fluxes. Furthermore, changes in land use and climate as well as legacy N should be considered in developing N pollution control strategies.
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影响因子：
3.7
作者：
Sheng W;Yu G;Fang H;Jiang C;Yan J;Zhou M
通讯作者：
Zhou M
影响因子：
2.8
作者：
D. Swaney;Bongghi Hong;A. P. Selvam;R. Howarth;R. Ramesh;R. Purvaja
通讯作者：
D. Swaney;Bongghi Hong;A. P. Selvam;R. Howarth;R. Ramesh;R. Purvaja
DOI：
10.1016/j.agee.2009.06.011
发表时间：
2009-12
期刊：
Agriculture, Ecosystems & Environment
影响因子：
--
作者：
Dingjiang Chen;Jun Lu;Ye-na Shen;R. Dahlgren;Shu-quan Jin
通讯作者：
Dingjiang Chen;Jun Lu;Ye-na Shen;R. Dahlgren;Shu-quan Jin
影响因子：
6.5
作者：
Ju, XT;Liu, XJ;Roelcke, M
通讯作者：
Roelcke, M
影响因子：
11.4
作者：
H. Jarvie;A. Sharpley;J. Thad Scott;B. Haggard;M. Bowes;L. B. Massey
通讯作者：
H. Jarvie;A. Sharpley;J. Thad Scott;B. Haggard;M. Bowes;L. B. Massey