Literature DB >> 21555173

Spatio-temporal variations of nitrogen in an agricultural watershed in eastern China: catchment export, stream attenuation and discharge.

Dingjiang Chen1, Jun Lu, Yena Shen, Dongqin Gong, Ouping Deng.   

Abstract

Using the monthly hydrogeochemical data of ChangLe River system from 2004 to 2008, total nitrogen (TN) export load (S(n)) from nonpoint sources (NPS) to stream and in-stream attenuation load (A(L)) was estimated by the inverse and forward format of an existing in-stream nutrient transport equation, respectively. Estimated S(n) contributed 96 ± 2% of TN entering the river system, while A(L) reduced the input TN by 23 ± 14% in average. In-stream TN attenuation efficiency in high flow periods (10 ± 5% in average for the entire river system) was much lower than that in low flow periods (39 ± 17%). TN attenuation efficiency in tributaries (28 ± 16% in average) was much higher than that in mainstream (11 ± 8%). Hydrological conditions are important in determining the spatio-temporal distributions of NPS TN export, stream attenuation and discharge. Increasing the water residence time might be a practical method for mitigating stream TN.
Copyright © 2011 Elsevier Ltd. All rights reserved.

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Year:  2011        PMID: 21555173     DOI: 10.1016/j.envpol.2011.04.023

Source DB:  PubMed          Journal:  Environ Pollut        ISSN: 0269-7491            Impact factor:   8.071


  5 in total

1.  Stream nitrogen sources apportionment and pollution control scheme development in an agricultural watershed in eastern China.

Authors:  Dingjiang Chen; Jun Lu; Hong Huang; Mei Liu; Dongqin Gong; Jiabo Chen
Journal:  Environ Manage       Date:  2013-08       Impact factor: 3.266

2.  Nutrient concentrations and fluxes in the upper catchment of the Miyun Reservoir, China, and potential nutrient reduction strategies.

Authors:  Jian Jiao; Pengfei Du; Cong Lang
Journal:  Environ Monit Assess       Date:  2015-02-12       Impact factor: 2.513

3.  Forecasting riverine total nitrogen loads using wavelet analysis and support vector regression combination model in an agricultural watershed.

Authors:  Xiaoliang Ji; Jun Lu
Journal:  Environ Sci Pollut Res Int       Date:  2018-07-07       Impact factor: 4.223

4.  Support vector machine-an alternative to artificial neuron network for water quality forecasting in an agricultural nonpoint source polluted river?

Authors:  Mei Liu; Jun Lu
Journal:  Environ Sci Pollut Res Int       Date:  2014-06-05       Impact factor: 4.223

5.  Effects of land use, topography and socio-economic factors on river water quality in a mountainous watershed with intensive agricultural production in East china.

Authors:  Jiabo Chen; Jun Lu
Journal:  PLoS One       Date:  2014-08-04       Impact factor: 3.240

  5 in total

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