Nitrogen removal in the Chaohu Lake, China: Implication in estimating lake N uptake velocity and modelling N removal efficiency of large lakes and reservoirs in the Changjiang River network
Li, Qingqian1,2; Yu, Qibiao1,3; Wang, Fang1; Yan, Weijin1; Wang, Jianing4
刊名ECOLOGICAL INDICATORS
2021-05-01
卷号124页码:12
关键词Denitrogen Nitrogen removal efficiency Uptake velocity Shallow eutrophic lake Reservoirs Changjiang River network
ISSN号1470-160X
DOI10.1016/j.ecolind.2021.107353
通讯作者Yan, Weijin(yanwj@igsnrr.ac.cn)
英文摘要Lakes and reservoirs are important inland waterscapes in linking nitrogen (N) transport and removal from the terrestrial to marine ecosystems. N removal processes eliminate N permanently from lakes and reservoirs, including denitogen, permanent burial and biomass harvest. The N removal efficiency (R-_removal, i.e. the fraction of N removal amount against total N loads to the lake) is an important parameter for the quantification of N removal from lakes and reservoirs. Intrinsically, R-_removal depends on hydrologic load and total N uptake velocity (V-f_removal). However, it is a challenge in determining Vf_removal which can be used to model R-_removal of lakes and reservoirs. Furthermore, there is less studies in distinguishing the N uptake velocity of individual processes from each other. Here, we estimated the magnitude of each uptake velocity of N removal processes with field observed data, and further presented an integrated V-f_removal to estimate R-_removal of a typical eutrophic lake (the Chaohu Lake) in Eastern China. The mean dinitrogen emission rate was 1.23 +/- 0.83 mg N m(-2) h(-1) in Chaohu Lake in 2016. The uptake velocity of denitrogen, permanent N burial and biomass harvest was 2.67 m yr(-1), 0.25 m yr(-1) and 0.23 m yr(-1), respectively. The removal efficiency of denitrogen, permanent N burial and biomass harvest was 26.14%, 2.76% and 2.56%, respectively. The integrated value of V-f_ removal was 3.33 m yr(-1). We finally compiled hydrological data of 566 large reservoirs in Changjiang River network, and modelled the N removal by combining our estimated value of V-f_removal with hydrological data. We found a significant power relationship between N removal and the reservoir discharge, which can predict the variation of N removal of each reservoir in Changjiang River network. Our research helps to understand N removal in lakes and reservoirs at an entire river network scale.
资助项目National Natural Science Foundation of China[41371454] ; National Natural Science Foundation of China[42077304] ; National Key Research and Development Program of China[2016YFA0601004]
WOS研究方向Biodiversity & Conservation ; Environmental Sciences & Ecology
语种英语
出版者ELSEVIER
WOS记录号WOS:000624330900002
资助机构National Natural Science Foundation of China ; National Key Research and Development Program of China
内容类型期刊论文
源URL[http://ir.igsnrr.ac.cn/handle/311030/162098]  
专题中国科学院地理科学与资源研究所
通讯作者Yan, Weijin
作者单位1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
2.Chinese Acad Sci, Grad Univ, Beijing 100049, Peoples R China
3.Xiamen Univ, Coll Environm & Ecol, Fujian Prov Key Lab Coastal Ecol & Environm Studi, Key Lab Coastal & Wetland Ecosyst, Xiamen 361102, Peoples R China
4.Chinese Acad Environm Planning, Beijing 100012, Peoples R China
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GB/T 7714
Li, Qingqian,Yu, Qibiao,Wang, Fang,et al. Nitrogen removal in the Chaohu Lake, China: Implication in estimating lake N uptake velocity and modelling N removal efficiency of large lakes and reservoirs in the Changjiang River network[J]. ECOLOGICAL INDICATORS,2021,124:12.
APA Li, Qingqian,Yu, Qibiao,Wang, Fang,Yan, Weijin,&Wang, Jianing.(2021).Nitrogen removal in the Chaohu Lake, China: Implication in estimating lake N uptake velocity and modelling N removal efficiency of large lakes and reservoirs in the Changjiang River network.ECOLOGICAL INDICATORS,124,12.
MLA Li, Qingqian,et al."Nitrogen removal in the Chaohu Lake, China: Implication in estimating lake N uptake velocity and modelling N removal efficiency of large lakes and reservoirs in the Changjiang River network".ECOLOGICAL INDICATORS 124(2021):12.
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