Simulating soil carbon sequestration, yield, and N2O fluxes with DayCent under long-term no-till and cover crop-based cotton cropping system

IF 6.4 1区 农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY
Jashanjeet K. Dhaliwal , Stephen J. Del Grosso , Debasish Saha
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引用次数: 0

Abstract

Cover crops are widely promoted for improving soil health through carbon sequestration and show promise as a natural climate solution by reducing greenhouse gases through atmospheric carbon dioxide storage. However, their effect on nitrous oxide (N₂O) emissions is more variable and contrasting compared to their influence on soil organic carbon (SOC) changes. To effectively represent cover crop systems and estimate the associated N₂O emissions, process-based models must be rigorously evaluated. This study aims to assess the ability of DayCent to simulate cotton lint yield, SOC, and N₂O emissions in long-term no-till (NT) cotton cropping systems with cover crops in the Southeastern US. The model was evaluated using long-term data on cotton lint yield and SOC and short-term data on soil mineral N, and N₂O emissions from NT cotton plots with two N rates (0 kg N ha⁻¹, NF, and 67 kg N ha⁻¹, F) and two cover crop treatments (hairy vetch, HV, and no cover crop, NC). DayCent accurately simulated the effect of N fertilizer on cotton lint yield but underestimated yield in non-fertilized treatments, failing to capture the impact of cover crops in these systems. The model accurately captured the long-term impact of cover crops on SOC in non-fertilized treatments but overestimated SOC in fertilized treatments, regardless of cover crop inclusion. Simulated mean soil ammonium levels were overestimated in fertilized treatments and underestimated in non-fertilized treatments, while nitrate levels were consistently lower than measured values across all treatments. Regardless of cover crop presence, DayCent accurately predicted cumulative N₂O emissions in unfertilized treatments but overestimated N₂O in fertilized treatments. DayCent performance in cover cropping systems could be improved by reducing denitrification rates and enhancing its ability to simulate soil mineral N.
利用DayCent模拟长期免耕覆盖棉花种植制度下土壤固碳、产量和N2O通量
覆盖作物因其通过固碳来改善土壤健康而得到广泛推广,并有望通过大气二氧化碳储存来减少温室气体,成为一种自然的气候解决方案。然而,与它们对土壤有机碳(SOC)变化的影响相比,它们对一氧化二氮(N₂O)排放的影响更为多变和鲜明。为了有效地表示覆盖作物系统并估计相关的N₂O排放,必须严格评估基于过程的模型。本研究旨在评估DayCent模拟美国东南部有覆盖作物的长期免耕(NT)棉花种植系统中皮棉产量、有机碳和N₂O排放的能力。该模型使用两种氮肥处理(0 kg N ha⁻¹,NF和67 kg N ha⁻¹,F)和两种覆盖作物处理(毛豆,HV和无覆盖作物,NC)的NT棉花田的棉花产量和有机碳的长期数据和土壤矿质氮和N₂O排放的短期数据进行评估。DayCent准确模拟了氮肥对棉绒产量的影响,但低估了未施肥处理的产量,未能捕捉覆盖作物在这些系统中的影响。该模型准确地反映了未施肥处理下覆盖作物对有机碳的长期影响,但在不考虑覆盖作物的情况下,高估了施肥处理下的有机碳。在施肥处理中,模拟平均土壤铵水平被高估,而在未施肥处理中被低估,而硝酸盐水平在所有处理中始终低于测量值。无论覆盖作物是否存在,DayCent准确地预测了未施肥处理的累积二氧化碳排放量,但高估了施肥处理的二氧化碳排放量。通过降低反硝化速率和增强其模拟土壤矿质氮的能力,可以改善覆盖作物系统的DayCent性能。
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来源期刊
Agriculture, Ecosystems & Environment
Agriculture, Ecosystems & Environment 环境科学-环境科学
CiteScore
11.70
自引率
9.10%
发文量
392
审稿时长
26 days
期刊介绍: Agriculture, Ecosystems and Environment publishes scientific articles dealing with the interface between agroecosystems and the natural environment, specifically how agriculture influences the environment and how changes in that environment impact agroecosystems. Preference is given to papers from experimental and observational research at the field, system or landscape level, from studies that enhance our understanding of processes using data-based biophysical modelling, and papers that bridge scientific disciplines and integrate knowledge. All papers should be placed in an international or wide comparative context.
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