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Titel Estimating net anthropogenic nitrogen inputs (NANI) in the Lake Dianchi basin of China
VerfasserIn W. Gao, R. W. Howarth, B. Hong, D. P. Swaney, H. C. Guo
Medientyp Artikel
Sprache Englisch
ISSN 1726-4170
Digitales Dokument URL
Erschienen In: Biogeosciences ; 11, no. 16 ; Nr. 11, no. 16 (2014-08-28), S.4577-4586
Datensatznummer 250117568
Publikation (Nr.) Volltext-Dokument vorhandencopernicus.org/bg-11-4577-2014.pdf
 
Zusammenfassung
Net anthropogenic nitrogen inputs (NANI) with components of atmospheric N deposition, synthetic N fertilizer, agricultural N fixation and N in net food and feed imports from 15 catchments in the Lake Dianchi basin were determined over an 11-year period (2000–2010). The 15 catchments range in size from 44 km2 to 316 km2 with an average of 175 km2. To reduce uncertainty from scale change methodology, results from data extraction by area-weighting and land use-weighting methods were compared. Results show that the methodology for extrapolating data from the county scale to watersheds has a great influence on NANI computation for catchments in the Lake Dianchi basin, and that estimates of NANI between the two methods have an average difference of 30% on a catchment basis, while a smaller difference (15%) was observed on the whole Lake Dianchi basin basis. The riverine N export has a stronger linear relationship with NANI computed by the land use-weighting method, which we believe is more reliable. Overall, nitrogen inputs assessed by the NANI approach for the Lake Dianchi basin are 9900 kg N km−2 yr−1, ranging from 6600 to 28 000 kg N km−2 yr−1 among the 15 catchments. Synthetic N fertilizer is the largest component of NANI in most subwatersheds. On average, riverine flux of nitrogen in catchments of the Lake Dianchi basin averages 83% of NANI, far higher than generally observed in North America and Europe. Saturated N sinks and a limited capacity for denitrification in rivers may be responsible for this high percentage of riverine N export. Overall, the NANI methodology should be applicable in small watersheds when sufficiently detailed data are available to estimate its components.
 
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