Using vegetation correction coefficient to modify a dynamic particulate nutrient loss model for monthly nitrogen and phosphorus load predictions: a case study in a small loess hilly watershed.

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2019
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Abstract
Vegetation is an important factor affecting nutrient enrichment ratio in runoff sediments but few studies have been examined in the effects of different vegetation scenarios on the monthly evolutions of particulate nitrogen (N) and phosphorus (P) loss. In this study, a vegetation correction coefficient was innovatively embedded in a dynamic particulate nutrient loss model to evaluate the monthly trends of particulate N and P loss in a small highly erodible watershed. Results indicate that (i) the monthly sediment yield from June to August 2013 accounted for the dominant percentage in this extreme hydrological year, which was consistent with the monthly trends of rainfall erosivity. The largest monthly sediment yield rate under four different vegetation scenarios all occurred in July with the values of 530.56, 258.09, 579.69, and 370.74 t km. (ii) Particulate N and P loss from April to September changed significantly under different vegetation scenarios, and they were mainly concentrated in June and July 2013; only the N and P loss loads in July accounted for > 70% of annual load. However, the loads in January, February, March, October, November, and December were considered as zero because there was no erosive rainfall during the above 6 months. (iii) The reduction efficiency of particulate N and P loss by scenario 1 was about 1.7 times higher than scenario 3, which shows that forestland in sediment reduction was stronger than grassland and cropland in Zhifanggou Watershed. Results provide the underlying insights needed to guide vegetation reconstruction and soil conservation planning in loess hilly regions.
Reference Key
wu2019usingenvironmental Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Wu, Lei;Li, Gouxia;Jiang, Jun;Ma, Xiaoyi;
Journal Environmental science and pollution research international
Year 2019
DOI
10.1007/s11356-019-06564-2
URL
Keywords
sediment yield loess hilly regions nitrogen and phosphorus particulate nutrient loss model vegetation scenarios

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