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• W2337522059 abstract "The apportionment of riverine dissolved inorganic nitrogen (DIN) load to individual land use on a watershed scale demands the support of accurate DIN load estimation and differentiation of point and non-point sources, but both of them are rarely quantitatively determined in small montane watersheds. We introduced the Danshui River watershed of Taiwan, a mountainous urbanized watershed, to determine the export coefficients via a reverse Monte Carlo approach from riverine DIN load. The results showed that the dynamics of N fluctuation determines the load estimation method and sampling frequency. On a monthly sampling frequency basis, the average load estimation of the methods (GM, FW, and LI) outperformed that of individual method. Export coefficient analysis showed that the forest DIN yield of 521.5kg-Nkm(-2)yr(-1) was ~2.7-fold higher than the global riverine DIN yield (mainly from temperate large rivers with various land use compositions). Such a high yield was attributable to high rainfall and atmospheric N deposition. The export coefficient of agriculture was disproportionately larger than forest suggesting that a small replacement of forest to agriculture could lead to considerable change of DIN load. The analysis of differentiation between point and non-point sources showed that the untreated wastewater (non-point source), accounting for ~93% of the total human-associated wastewater, resulted in a high export coefficient of urban. The inclusion of the treated and untreated wastewater completes the N budget of wastewater. The export coefficient approach serves well to assess the riverine DIN load and to improve the understanding of N cascade." @default.
• W2337522059 created "2016-06-24" @default.
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• W2337522059 date "2016-08-01" @default.
• W2337522059 modified "2023-10-16" @default.
• W2337522059 title "Apportioning riverine DIN load to export coefficients of land uses in an urbanized watershed" @default.
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• W2337522059 doi "https://doi.org/10.1016/j.scitotenv.2016.04.055" @default.
• W2337522059 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/27093117" @default.
• W2337522059 hasPublicationYear "2016" @default.
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