Open AccessProcess‐based TRIPLEX‐GHG model for simulating N 2 O emissions from global forests and grasslands: M odel development and evaluation
Author(s) -
Zhang Kerou,
Peng Changhui,
Wang Meng,
Zhou Xiaolu,
Li Mingxu,
Wang Kefeng,
Ding Juhua,
Zhu Qiuan
Publication year - 2017
Publication title -
journal of advances in modeling earth systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.03
H-Index - 58
ISSN - 1942-2466
DOI - 10.1002/2017ms000934
Subject(s) - environmental science , atmospheric sciences , nitrous oxide , grassland , nitrification , greenhouse gas , ecology , chemistry , biology , nitrogen , physics , organic chemistry
The development of the new process‐based TRIPLEX‐GHG model derives from the Integrated Biosphere Simulator (IBIS), which couples nitrification and denitrification processes to quantify nitrous oxide (N 2 O) emissions from natural forests and grasslands. Sensitivity analysis indicates that the nitrification rate coefficient (COE NR ) is the most sensitive parameter to simulate N 2 O emissions. Accordingly, we calibrated this parameter using data from 29 global forest sites (across different latitudes) and grassland sites. The average nitrification rate coefficient gradually increases in the order of tropical forest to grassland to temperate forest to boreal forest, and giving means of 0.009, 0.03, 0.04, and 0.09, respectively. This study validated the mean value for each ecosystem at 52 sites globally. Calibration results both indicate the good performance of the model and its suitability in capturing seasonal variation and magnitude of N 2 O flux; however, it is limited in modeling N 2 O uptake and increments during periods of snowmelt. Additionally, validation results indicate that simulated and observed annual or seasonal N 2 O fluxes are highly correlated (R 2 = 0.75; P < 0.01). Consequently, our results suggest that the model is suitable in simulating N 2 O emissions from different forest and grassland land types under varying environmental conditions on a global scale.