4.7 Article

Quantifying nitrogen leaching response to fertilizer additions in China's cropland

Journal

ENVIRONMENTAL POLLUTION
Volume 211, Issue -, Pages 241-251

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.envpol.2016.01.010

Keywords

Nitrogen leaching; Nonlinearity; Variability; Spatial pattern; Bayesian inference

Funding

  1. National Natural Science Foundation of China [41201077, 71103186, 41561134016]
  2. Research Fund for the Doctoral Program of Higher Education of China [20120001120129]
  3. 111 Project [B14001]

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Agricultural soils account for more than 50% of nitrogen leaching (L-N) to groundwater in China. When excess levels of nitrogen accumulate in groundwater, it poses a risk of adverse health effects. Despite this recognition, estimation of L-N from cropland soils in a broad spatial scale is still quite uncertain in China. The uncertainty of L-N primarily stems from the shape of nitrogen leaching response to fertilizer additions (N-rate) and the role of environmental conditions. On the basis of 453 site-years at 51 sites across China, we explored the nonlinearity and variability of the response of L-N to N-rate and developed an empirical statistical model to determine how environmental factors regulate the rate of N leaching (LR). The result shows that L-N-N-rate relationship is convex for most crop types, and varies by local hydro-climates and soil organic carbon. Variability of air temperature explains a half (similar to 52%) of the spatial variation of LR. The results of model calibration and validation indicate that incorporating this empirical knowledge into a predictive model could accurately capture the variation in leaching and produce a reasonable upscaling from site to country. The fertilizer-induced L-N in 2008 for China's cropland were 0.88 +/- 0.23 TgN (1 sigma), significantly lower than the linear or uniform model, as assumed by Food and Agriculture Organization and MITERRA-EUROPE models. These results also imply that future policy to reduce N leaching from cropland needs to consider environmental variability rather than solely attempt to reduce N-rate. (C) 2016 Elsevier Ltd. All rights reserved.

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