Detection and attribution of nitrogen runoff trend in China's croplands. (March 2018)

• Record Type: Journal Article
• Authors: Hou, Xikang; Zhan, Xiaoying; Zhou, Feng; Yan, Xiaoyuan; Gu, Baojing; Reis, Stefan; Wu, Yali; Liu, Hongbin; Piao, Shilong; Tang, Yanhong
• Is Part Of: Environmental pollution. Volume 234(2018)
• Page Start: 270
• Page End: 278
• Publication Date: 2018-03
• Subjects: Nitrogen runoff -- Temporal trend -- Spatial pattern -- Attribution analysis -- Bayesian inference; Pollution -- Periodicals; Pollution -- Environmental aspects -- Periodicals; Environmental Pollution -- Periodicals; Pollution -- Périodiques; Pollution -- Aspect de l'environnement -- Périodiques; Pollution -- Effets physiologiques -- Périodiques; Pollution; Pollution -- Environmental aspects; Periodicals; Electronic journals; 363.73
• DOI: 10.1016/j.envpol.2017.11.052
• Languages: English
• ISSNs: 0269-7491

Abstract

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. Graphical abstract: Highlights: A data-driven upscaling model can effectively and reliably detect N runoff trends. N runoff has increased by 46% for rice paddy fields and 31% for uplands since 1990. SOM change results in inverse trend of N runoff rates between upland and rice fields. Abstract : Cropland N runoff in China increased by 30% over the past two decades mainly due to increased fertilization and decreased irrigation.