Long-term riverine nitrogen dynamics reveal the efficacy of water pollution control strategies
Long-term riverine nitrogen dynamics reveal the efficacy of water pollution control strategies
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长期河流氮动态揭示水污染控制策略的有效性
DOI：
10.1016/j.jhydrol.2022.127582
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发表时间：
2022-02
影响因子：
6.4
通讯作者：
Dingjiang Chen
中科院分区：
文献类型：
--
作者：
Kaibin Wu;Minpeng Hu;Yufu Zhang;Jia Zhou;Hao Wu;Mingfeng Wang;Dingjiang Chen
确定流域人为干预的长期水质趋势对于制定和调整水污染控制战略至关重要。该研究首次使用时间、流量和季节加权回归（WRTDS）模型评估了中国东部永安江流域1980-2019年期间河流氮（N）水平的趋势和来源。WRTDS模型对河流总氮（TN）、氨氮（NH 4+）和硝态氮（NO3−）日浓度/负荷的预测精度令人满意（R2> 0.55，n = 366）。模拟的流量标准化河流NH 4+浓度从1980年到2009年增加了789%，然后在2010-2019年下降了63%。河流NH 4+浓度的变化趋势主要归因于2010-2019年由于在城市地区建立了三个新的污水处理厂和加强农村生活污水收集/处理，废水NH 4+排放量减少了43%。尽管在2000-2019年期间，化学氮肥的使用量减少了49%，家畜数量减少了73%，但在1980-2019年期间，流量标准化的河流TN和NO3−浓度分别增加了161%和232%。减少氮输入和增加河流TN/NO3−浓度之间的矛盾归因于来自土壤和地下水的遗留氮的输入。1980-2019年，河流NO3−浓度增加了3.8倍，（2000-2019年增加86%），10天无降水后（代表地下水对基流的贡献）和1980-2019年河流NO3−浓度增加4.1倍（2000-2019年增加91%）在10天无降水（代表土壤冲刷）后的第一场暴雨之后。这些结果表明，点源污染控制的努力是有效的，而从非点源污染控制的好处被掩盖的输入遗留的N污染。WRTDS模型被证明是一个有用的工具，用于评估长期河流N污染动态和来源，从而为决策者提供关键信息，以指导流域N污染控制策略。
Identification of long-term water quality trends in response to watershed anthropogenic interventions is crucial for developing and adapting water pollution control strategies. This study represents the first use of the Weighted Regressions on Time, Discharge, and Season (WRTDS) model to evaluate trends and sources of riverine nitrogen (N) levels over the 1980–2019 period in the Yongan River watershed of eastern China. The WRTDS model showed satisfactory accuracies for predicting daily riverine total N (TN), NH4+and NO3−concentrations/loads (R2> 0.55, n = 366). Modeled flow-normalized riverine NH4+concentration increased by 789% from 1980 to 2009 and then decreased by 63% in 2010–2019. This changing trend for riverine NH4+concentration was mainly attributed to a 43% decrease of wastewater NH4+discharge load in 2010–2019 due to establishment of three new WWTPs in urban areas and enhanced rural domestic sewage collection/treatment. Although chemical N fertilizer use decreased by 49% and domestic animal numbers decreased by 73% in 2000–2019, flow-normalized riverine TN and NO3−concentrations progressively increased by 161% and 232% in 1980–2019, respectively. The paradox between decreasing N inputs and increasing riverine TN/NO3−concentrations is attributed to inputs of legacy N from soil and groundwater. This is supported by the 3.8-fold increase of riverine NO3−concentration in 1980–2019 (86% increase in 2000–2019) following 10-days with no-precipitation (representing groundwater contributions to baseflow) and a 4.1-fold increase of riverine NO3−concentration in 1980–2019 (91% increase in 2000–2019) following the first rainstorm after 10-days of no-precipitation (representing soil flushing). These results document that point-source pollution control efforts were effective, whereas benefits from nonpoint-source pollution control were masked by inputs from legacy N pollution. The WRTDS model was demonstrated to be a useful tool for assessing long-term riverine N pollution dynamics and sources, thereby providing decision-makers with critical information to guide watershed N pollution control strategies.
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影响因子：
12.8
作者：
Shejiang Liu;Zhijiang Zhao;Jie Li;Juan Wang;Yun Qi
通讯作者：
Shejiang Liu;Zhijiang Zhao;Jie Li;Juan Wang;Yun Qi
影响因子：
5.2
作者：
K. Meter;N. Basu;P. Cappellen
通讯作者：
K. Meter;N. Basu;P. Cappellen
影响因子：
8.7
作者：
Zhang, Kun-min;Wen, Zong-guo
通讯作者：
Wen, Zong-guo
影响因子：
3.1
作者：
Duan Shuiwang;Zhang Shen;Hu Hongyu
通讯作者：
Duan Shuiwang;Zhang Shen;Hu Hongyu
影响因子：
4.9
作者：
Hirsch, Robert M.;Archfield, Stacey A.;De Cicco, Laura A.
通讯作者：
De Cicco, Laura A.