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中国农田氮径流趋势的检测与归因。

Detection and attribution of nitrogen runoff trend in China's croplands.

机构信息

Sino-France Institute of Earth Systems Science, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, PR China.

Sino-France Institute of Earth Systems Science, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, PR China.

出版信息

Environ Pollut. 2018 Mar;234:270-278. doi: 10.1016/j.envpol.2017.11.052. Epub 2017 Dec 21.

Abstract

Reliable detection and attribution of changes in nitrogen (N) runoff from croplands are essential for designing efficient, sustainable N management strategies for future. Despite the recognition that excess N runoff poses a risk of aquatic eutrophication, large-scale, spatially detailed N runoff trends and their drivers remain poorly understood in China. Based on data comprising 535 site-years from 100 sites across China's croplands, we developed a data-driven upscaling model and a new simplified attribution approach to detect and attribute N runoff trends during the period of 1990-2012. Our results show that N runoff has increased by 46% for rice paddy fields and 31% for upland areas since 1990. However, we acknowledge that the upscaling model is subject to large uncertainties (20% and 40% as coefficient of variation of N runoff, respectively). At national scale, increased fertilizer application was identified as the most likely driver of the N runoff trend, while decreased irrigation levels offset to some extent the impact of fertilization increases. In southern China, the increasing trend of upland N runoff can be attributed to the growth in N runoff rates. Our results suggested that increased SOM led to the N runoff rate growth for uplands, but led to a decline for rice paddy fields. In combination, these results imply that improving management approaches for both N fertilizer use and irrigation is urgently required for mitigating agricultural N runoff in China.

摘要

可靠地检测和归因农田氮(N)径流的变化对于设计未来高效、可持续的 N 管理策略至关重要。尽管人们认识到过量的 N 径流会对水生富营养化构成威胁,但在中国,大规模、空间详细的 N 径流趋势及其驱动因素仍未得到充分理解。本研究基于中国农田 100 个站点 535 个站点年的数据,开发了一个数据驱动的放大模型和一种新的简化归因方法,以检测和归因 1990-2012 年期间的 N 径流趋势。结果表明,自 1990 年以来,稻田和旱地的 N 径流分别增加了 46%和 31%。然而,我们承认放大模型存在较大的不确定性(N 径流的变异系数分别为 20%和 40%)。在国家尺度上,增加肥料施用量被认为是 N 径流趋势的最可能驱动因素,而灌溉水平的降低在一定程度上抵消了施肥增加的影响。在中国南方,旱地 N 径流的增加趋势可归因于 N 径流率的增长。结果表明,增加的 SOM 导致旱地的 N 径流率增加,但导致稻田的 N 径流率下降。总的来说,这些结果表明,需要紧急改进氮肥料使用和灌溉的管理方法,以减少中国农业 N 径流。

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