Using a modified DNDC biogeochemical model to optimize field management of a multi-crop (cotton, wheat, and maize) system: a site-scale case study in northern China

Zhang, Wei; Liu, Chunyan; Zheng, Xunhua; Wang, Kai; Cui, Feng; Wang, Rui; Li, Siqi; Yao, Zhisheng; Zhu, Jiang

It is still a severe challenge to optimize the field management practices for a multi-crop system when simultaneously aiming at yield sustainability and minimum negative impacts on climate as well as atmosphere and water quality. This site-scale case study was devoted to developing a biogeochemical process model-based approach as a solution to this challenge. The best management practices (BMPs) of a three-crop system growing cotton and winter wheat–summer maize (W–M) in rotation, which is widely adopted in northern China, were identified. The BMPs referred to the management alternatives with the lowest negative impact potentials (NIPs) among the scenarios satisfying all given constraints. The independent variables used to determine the NIPs and those utilized as constrained criteria were simulated by the DeNitrification-DeComposition model, which was modified in this study. Due to the unsatisfactory performance of the model in daily simulations of nitric oxide (NO) emission and net ecosystem exchange of carbon dioxide (NEE), the model was modified to (i) newly parameterize the soil moisture effects on NO production during nitrification, and (ii) replace the original NEE calculation approach with an algorithm based on gross primary production. Validation of the modified model showed statistically meaningful agreements between the simulations and observations in the cotton and W–M fields. Three BMP alternatives with overlapping uncertainties of simulated NIPs were screened from 6000 management scenarios randomly generated by Latin hypercube sampling. All of these BMP alternatives adopted the baseline (currently applied) practices of crop rotation (3 consecutive years of cotton rotating with 3 years of W–M in each 6-year cycle), the fraction of crop residue incorporation (100 %), and deep tillage (30 cm) for cotton. At the same time, these BMP alternatives would use 18 % less fertilizer nitrogen and sprinkle or flood-irrigate ∼23 % less water than the baseline while adopting reduced tillage (5 cm) for W–M. Compared with the baseline practices, these BMP alternatives could simultaneously sustain crop yields, annually enlarge the soil organic carbon stock by 4 ‰ or more, mitigate the aggregate emission of greenhouse gases, NO release, ammonia volatilization, and nitrate leaching by ∼7 %, ∼25 %, ∼2 %, and ∼43 %, respectively, despite a ∼5 % increase in N2O emission. However, further study is still necessary for field confirmation of these BMP alternatives. Nevertheless, this case study proposed a practical approach to optimize multi-crop system management to simultaneously achieve multiple United Nations Sustainable Development Goals.

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Zhang, Wei / Liu, Chunyan / Zheng, Xunhua / et al: Using a modified DNDC biogeochemical model to optimize field management of a multi-crop (cotton, wheat, and maize) system: a site-scale case study in northern China. 2019. Copernicus Publications.

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