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

文献类型： 外文期刊

第一作者： Hou, Xikang

作者： Hou, Xikang;Zhan, Xiaoying;Zhou, Feng;Wu, Yali;Piao, Shilong;Tang, Yanhong;Yan, Xiaoyuan;Gu, Baojing;Reis, Stefan;Liu, Hongbin;Reis, Stefan

作者机构：

关键词： Nitrogen runoff;Temporal trend;Spatial pattern;Attribution analysis;Bayesian inference

期刊名称：ENVIRONMENTAL POLLUTION （ 影响因子：8.071； 五年影响因子：8.35 ）

ISSN： 0269-7491

年卷期： 2018 年 234 卷

页码：

收录情况： SCI

摘要： 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. (C) 2017 Elsevier Ltd. All rights reserved.

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