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首页> 外文期刊>Environmental Science and Pollution Research >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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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

机译:利用植被校正系数来改变每月氮和磷荷载预测的动态颗粒营养损失模型:小型黄土丘陵流域的案例研究

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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(-2). (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.
机译:植被是影响径流沉积物但很少有研究养分富集比在不同的植被情景对颗粒氮(N),磷(P)的损失每月变阵效果已审查的一个重要因素。在这项研究中,植被校正系数被创造性地嵌入在动态微粒营养损失模型来评估在小高度侵蚀流域微粒氮磷损失每月的趋势。结果表明:(一)月度泥沙从六月到2013年8月的产量占这种极端水文年的主要比例,这与降雨侵蚀力的月度趋势是一致的。在四个不同的植被情景的最大月度产沙率都发生在7月,530.56,258.09,579.69和370.74吨公里(-2)的值。 (ⅱ)颗粒N与四月至九月磷流失下不同植被场景显著改变,并且它们主要集中在6和7月2013;仅在七月的氮磷流失负荷占全年负荷> 70%。然而,因为当时在6个月以上无侵蚀性降雨在一月,二月,三月,十月,十一月和十二月的负荷被视为零。 (ⅲ)的微粒n中的还原效率和P损失由方案1为约比方案3的1.7倍更高,这表明,在林地减沙比在纸坊流域草原和耕地更强。结果提供在黄土丘陵地区需要引导植被重建和水土保持规划的基本见解。

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