Literature DB >> 25225934

Quantitative identification of riverine nitrogen from point, direct runoff and base flow sources.

Hong Huang1, Baifa Zhang1, Jun Lu2.   

Abstract

We present a methodological example for quantifying the contributions of riverine total nitrogen (TN) from point, direct runoff and base flow sources by combining a recursive digital filter technique and statistical methods. First, we separated daily riverine flow into direct runoff and base flow using a recursive digital filter technique; then, a statistical model was established using daily simultaneous data for TN load, direct runoff rate, base flow rate, and temperature; and finally, the TN loading from direct runoff and base flow sources could be inversely estimated. As a case study, this approach was adopted to identify the TN source contributions in Changle River, eastern China. Results showed that, during 2005-2009, the total annual TN input to the river was 1,700.4±250.2 ton, and the contributions of point, direct runoff and base flow sources were 17.8±2.8%, 45.0±3.6%, and 37.2±3.9%, respectively. The innovation of the approach is that the nitrogen from direct runoff and base flow sources could be separately quantified. The approach is simple but detailed enough to take the major factors into account, providing an effective and reliable method for riverine nitrogen loading estimation and source apportionment.

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Year:  2014        PMID: 25225934     DOI: 10.2166/wst.2014.303

Source DB:  PubMed          Journal:  Water Sci Technol        ISSN: 0273-1223            Impact factor:   1.915


  2 in total

1.  Water quality trend and change-point analyses using integration of locally weighted polynomial regression and segmented regression.

Authors:  Hong Huang; Zhenfeng Wang; Fang Xia; Xu Shang; YuanYuan Liu; Minghua Zhang; Randy A Dahlgren; Kun Mei
Journal:  Environ Sci Pollut Res Int       Date:  2017-05-23       Impact factor: 4.223

2.  Assessment of Long-Term Watershed Management on Reservoir Phosphorus Concentrations and Export Fluxes.

Authors:  Xiaolin Huang; Han Chen; Fang Xia; Zhenfeng Wang; Kun Mei; Xu Shang; Yuanyuan Liu; Randy A Dahlgren; Minghua Zhang; Hong Huang
Journal:  Int J Environ Res Public Health       Date:  2018-10-02       Impact factor: 3.390

  2 in total

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