Predicting Soil Carbon Sequestration and Harvestable C-Biomass of Rice and Wheat by DNDC Model

GM crops Pub Date : 2023-08-30 DOI:10.3390/crops3030021
M. Shaukat, A. K. Hoshide, S. Muhammad, I. Arshad, Muhammad Mushtaq, D. C. de Abreu
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Abstract

Several biogeochemical models have been applied to understand the potential effects of management practices on soil organic carbon (SOC) sequestration, crop growth, and yield. In this study, the denitrification and decomposition (DNDC) model was used to simulate soil SOC dynamics and harvested C-biomass in rice–wheat rotation under organic/inorganic fertilization with conventional tillage (CT) and reduced tillage (RT). Before calibration, DNDC underpredicted harvestable grain C-biomass of rice where percent difference (PD) varied from 29.22% to 42.14%, and over-simulated grain C-biomass of wheat where PD was −55.01% with 50% nitrogen–phosphorus–potassium (NPK) and 50% animal manure applied under the CT treatment. However, after calibration by adjusting default values of soil and crop parameters, DNDC simulated harvestable grain C-biomass of both crops very close to observed values (e.g., average PD ranged from −2.81% to −6.17%). DNDC also predicted the effects of nutrient management practices on grain C-biomass of rice/wheat under CT/RT using d-index (0.76 to 0.96) and the calculated root mean squared error (RMSE of 165.36 to 494.18 kg C ha−1). DNDC simulated SOC trends for rice–wheat using measured values of several statistical indices. Regression analysis between modeled and observed SOC dynamics was significant with R2 ranging from 0.35 to 0.46 (p < 0.01), and intercept ranging from 0.30 to 1.34 (p < 0.65). DNDC demonstrated that combined inorganic and organic fertilization may result in higher C-biomass and more SOC sequestration in rice–wheat systems.
利用DNDC模型预测水稻和小麦土壤固碳和可收获碳生物量
几种生物地球化学模型已被应用于了解管理实践对土壤有机碳(SOC)固存、作物生长和产量的潜在影响。本研究采用反硝化与分解(DNDC)模型,模拟了常规耕作(CT)和免耕(RT)有机/无机施肥条件下稻麦轮作土壤有机碳动态和收获碳生物量。在校正前,DNDC低估了水稻的可收获粒碳生物量,其百分比差异(PD)在29.22% ~ 42.14%之间;在CT处理下,当氮磷钾(NPK)用量为50%、动物粪便用量为50%时,DNDC过度模拟了小麦的可收获粒碳生物量,其百分比差异为- 55.01%。然而,通过调整土壤和作物参数的默认值进行校准后,DNDC模拟的两种作物的可收获谷物c -生物量非常接近观测值(例如,平均PD范围为- 2.81%至- 6.17%)。DNDC还利用d指数(0.76 ~ 0.96)和计算均方根误差(RMSE为165.36 ~ 494.18 kg C ha−1)预测了不同营养管理措施对CT/RT条件下水稻/小麦籽粒C生物量的影响。DNDC利用多个统计指标的实测值模拟稻麦有机碳变化趋势。模型与实测SOC动态之间的回归分析具有显著性,R2范围为0.35 ~ 0.46 (p < 0.01),截距范围为0.30 ~ 1.34 (p < 0.65)。研究表明,有机无机配施可提高水稻-小麦系统的碳生物量和固碳量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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