Approaches and concepts of modelling denitrification: increased process understanding using observational data can reduce uncertainties

被引:35
作者
Del Grosso, Stephen J. [1 ]
Smith, Ward [2 ]
Kraus, David [3 ]
Massad, Raia S. [4 ]
Vogeler, Iris [5 ]
Fuchs, Kathrin [3 ]
机构
[1] USDA ARS, SMSBRU, Ft Collins, CO 80522 USA
[2] Agr & Agri Food Canada, Ottawa Res & Dev Ctr, Ottawa, ON, Canada
[3] Karlsruhe Inst Technol, Garmisch Partenkirchen, Germany
[4] Univ Paris Saclay, INRAE, AgroParisTech, UMR ECOSYS, F-78850 Thiverval Grignon, France
[5] Aarhus Univ, Dept Agroecol, Tjele, Denmark
关键词
NITROUS-OXIDE EMISSIONS; N2O EMISSIONS; SOIL CARBON; WATER; FLUXES; CORN; AGROECOSYSTEM; CALIBRATION; GRASSLAND; IMPACTS;
D O I
10.1016/j.cosust.2020.07.003
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Denitrification is a key but poorly quantified component of the N cycle. Because it is difficult to measure the gaseous (NOx, N2O, N-2) and soluble (NO3) components of denitrification with sufficient intensity, models of varying scope and complexity have been developed and applied to estimate how vegetation cover, land management and environmental factors such as soil type and weather interact to control these variables. In this paper we assess the strengths and limitations of different modeling approaches, highlight major uncertainties, and suggest how different observational methods and process-based understanding can be combined to better quantify N cycling. Representation of how biogeochemical (e.g. org. C., pH) and physical (e.g. soil structure) factors influence denitrification rates and product ratios combined with ensemble approaches may increase accuracy without requiring additional site level model inputs.
引用
收藏
页码:37 / 45
页数:9
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