Department of Soil and Crop Sciences, Texas A&M University, College Station, TX 77843, USA.
Texas A&M AgriLife Research Center at Beaumont, Beaumont, TX 77713, USA.
Sci Total Environ. 2021 Feb 10;755(Pt 2):142578. doi: 10.1016/j.scitotenv.2020.142578. Epub 2020 Oct 1.
The increasing trend of adopting organic fertilization in rice production can impact grain yields and soil methane (CH) emissions. To simulate these impacts in the absence of long-term field data, a process-based biogeochemical model, Denitrification and Decomposition (DNDC version 9.5) was used. The model was calibrated against a single year greenhouse study and validated using a previously published one-year field trial from 1990, both comparing varying fertilization systems in rice production in southeast Texas, USA. In both the greenhouse and the field studies, lower grain yield and greater soil CH emissions were observed in organically fertilized systems. Calibrated model simulations of the greenhouse study correlated with the observed daily CH emissions (conventional r = 0.87; organic r = 0.91) and SOC (r = 0.83); but, the model overestimated yield of conventional systems (slope = 1.2) and underestimated yield of organic systems (slope = 0.68). For the field study, agreement between simulated and observed yields and CH emissions resulted in slopes close to 1. A simple organic system with urea and straw amendment from the field study was an input available in DNDC whereas the slow release, pelletized organic fertilizer used in the greenhouse study, Nature Safe, was not modeled well by DNDC. The validated model was used to simulate 22 years of rice production and predicted that the differences in yield and CH emissions between treatments would diminish with time. In the model simulations, the overall soil health was enhanced when managed with organic fertilization compared to conventional inorganic fertilizers. Model simulations could be improved further by including site-specific calibration of soil organic C, and soil carbon dioxide (CO) emissions.
在水稻生产中采用有机施肥的趋势不断增加，这可能会影响粮食产量和土壤甲烷（CH）排放。为了在缺乏长期田间数据的情况下模拟这些影响，使用了基于过程的生物地球化学模型——反硝化和分解（DNDC 版本 9.5）。该模型通过对一个单年温室研究进行校准，并使用以前发表的 1990 年的一年田间试验进行验证，这两个研究都比较了美国德克萨斯州东南部不同的水稻生产施肥系统。在温室和田间研究中，有机施肥系统的粮食产量较低，土壤 CH 排放量较大。温室研究中校准模型的模拟与观察到的每日 CH 排放（常规 r=0.87；有机 r=0.91）和 SOC（r=0.83）相关；但是，模型高估了常规系统的产量（斜率=1.2），低估了有机系统的产量（斜率=0.68）。对于田间研究，模拟和观察到的产量和 CH 排放之间的一致性导致斜率接近 1。田间研究中来自尿素和秸秆的简单有机系统是 DNDC 可用的输入，而温室研究中使用的缓释、颗粒状有机肥料 Nature Safe 则不能很好地由 DNDC 模拟。验证后的模型用于模拟 22 年的水稻生产，并预测处理之间的产量和 CH 排放差异会随着时间的推移而缩小。在模型模拟中，与传统无机肥料相比，采用有机施肥可以提高土壤整体健康状况。通过包括特定地点的土壤有机碳和土壤二氧化碳（CO）排放的校准，可以进一步改进模型模拟。
