4.7 Article

Exploring management strategies to improve yield and mitigate nitrate leaching in a typical radish field in northern China

期刊

JOURNAL OF ENVIRONMENTAL MANAGEMENT
卷 290, 期 -, 页码 -

出版社

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jenvman.2021.112640

关键词

DNDC model; Radish yield; Nitrate leaching; Drainage; Sensitivity analysis; Optimized management practice

资金

  1. National Key Research & Development Program of China [2016YFD0200103]
  2. Fundamental Research Funds for Central Nonprofit Scientific Institution [1610132019047]
  3. Reform & Development Fund of Beijing Academy of Agriculture and Forestry Sciences [YZS201905]

向作者/读者索取更多资源

The study evaluated the performance of the DNDC model in simulating crop growth and nitrate leaching in a radish system, showing good to excellent performance in simulating radish yield, N uptake, and soil temperature while exhibiting fair performance in estimating soil moisture and drainage. The model also showed good performance in predicting nitrate leaching. Sensitivity analyses indicated that optimized management practices could significantly reduce N usage, irrigation amount, and nitrate leaching in radish production systems.
It is currently uncertain whether process-based models are capable of assessing crop yield and nitrogen (N) losses while helping to investigate best management practices from vegetable cropping systems. The objectives of this study were to (1) calibrate and evaluate the Denitrification-Decomposition (DNDC) model in simulating crop growth and nitrate leaching in a typical field radish system; (2) optimize management practices to improve radish yield and mitigate nitrate leaching under 20-year climate variability. A five-season in-situ field experiment of spring and autumn radish in northern China was established in the autumn of 2017 and measurements of radish yield, N uptake, soil temperature, soil moisture, drainage, and nitrate leaching were obtained under different N usage. DNDC overall demonstrated good to excellent performance in simulating radish yield, total biomass, N uptake, and soil temperature across all treatments (6.4% < normalized root mean square error (nRMSE) < 15.5%; 0.12 < Nash-Sutcliffe efficiency (NSE) < 0.88; 0.80 < index of agreement (d) < 0.97). DNDC generally exhibited fair performance in estimating soil moisture and drainage (10.9% < nRMSE < 27.2%; -0.18 < NSE < 0.37; 0.69 < d < 0.82) and good performance when predicting nitrate leaching (12.4% < nRMSE < 26.7%; -0.59 < NSE < 0.51; 0.68 < d < 0.90). Sensitivity analyses demonstrated that optimized management practices (planting dates, irrigation amount, fertilization rate and timing) could substantially reduce N usage by 40%-50%, irrigation amount by 33%-50%, and nitrate leaching by 86%-95% compared to farmers' practice in radish planting system. This study indicated that a modelling method is helpful for evaluating the biogeochemical effects of management alternatives and identifying optimal management practices in radish production systems of China.

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