The importance of management information and soil moisture representation for simulating tillage effects on N2O emissions in LPJmL5.0-tillage

被引:7
|
作者
Lutz, Femke [1 ,2 ]
Del Grosso, Stephen [3 ]
Ogle, Stephen [4 ]
Williams, Stephen [4 ]
Minoli, Sara [1 ]
Rolinski, Susanne [1 ]
Heinke, Jens [1 ]
Stoorvogel, Jetse J. [2 ]
Mueller, Christoph [1 ]
机构
[1] Leibniz Assoc, Potsdam Inst Climate Impact Res PIK, POB 60 12 03, D-14412 Potsdam, Germany
[2] Wageningen Univ, Soil Geog & Landscape Grp, POB 47, NL-6700 AA Wageningen, Netherlands
[3] USDA ARS, Soil Management & Sugar Beet Res Unit, 2150 Ctr Ave Bldg D, Ft Collins, CO 80526 USA
[4] Colorado State Univ, NREL, Ft Collins, CO 80523 USA
关键词
NITROUS-OXIDE EMISSIONS; DYNAMIC GLOBAL VEGETATION; GREENHOUSE-GAS EMISSIONS; NO-TILLAGE; GENERALIZED-MODEL; REDUCED TILLAGE; ORGANIC-MATTER; SYSTEMS; DAYCENT; CARBON;
D O I
10.5194/gmd-13-3905-2020
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
No-tillage is often suggested as a strategy to reduce greenhouse gas emissions. Modeling tillage effects on nitrous oxide (N2O) emissions is challenging and subject to great uncertainties as the processes producing the emissions are complex and strongly nonlinear. Previous findings have shown deviations between the LPJmL5.0-tillage model (LPJmL: Lund-Potsdam-Jena managed Land) and results from meta-analysis on global estimates of tillage effects on N2O emissions. Here we tested LPJmL5.0-tillage at four different experimental sites across Europe and the USA to verify whether deviations in N2O emissions under different tillage regimes result from a lack of detailed information on agricultural management, the representation of soil water dynamics or both. Model results were compared to observational data and outputs from field-scale DayCent model simulations. DayCent has been successfully applied for the simulation of N2O emissions and provides a richer database for comparison than noncontinuous measurements at experimental sites. We found that adding information on agricultural management improved the simulation of tillage effects on N2O emissions in LPJmL. We also found that LPJmL overestimated N2O emissions and the effects of no-tillage on N2O emissions, whereas DayCent tended to underestimate the emissions of no-tillage treatments. LPJmL showed a general bias to overestimate soil moisture content. Modifications of hydraulic properties in LPJmL in order to match properties assumed in DayCent, as well as of the parameters related to residue cover, improved the overall simulation of soil water and N2O emissions simulated under tillage and no-tillage separately. However, the effects of no-tillage (shifting from tillage to no-tillage) did not improve. Advancing the current state of information on agricultural management and improvements in soil moisture highlights the potential to improve LPJmL5.0-tillage and global estimates of tillage effects on N2O emissions.
引用
收藏
页码:3905 / 3923
页数:19
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