Gl. Velthof et al., PREDICTION OF NITROUS-OXIDE FLUXES FROM MANAGED GRASSLAND ON PEAT SOIL USING A SIMPLE EMPIRICAL-MODEL, Netherlands journal of agricultural science, 44(4), 1996, pp. 339-356
Three measurement campaigns were carried out to answer questions relat
ed to the factors controlling variations in nitrous oxide (N2O) fluxes
from intensively managed grassland on peat soil, comparison of flux m
easurements with a closed flux chamber method and a flux gradient tech
nique and the development and testing of a simple empirical model for
the estimation of N2O fluxes from intensively managed grassland on pea
t soils. Fluxes of N2O were measured with 42-48 flux chambers and rang
ed from less than 0.01 to 6.66 mg N m(-2) hr(-1). Fluxes were signific
antly correlated with denitrification activity (R-2 = 0.34-0.56). Cont
ents of nitrate (NO3-) and ammonium (NH4+) in the top soil and the wat
er-filled pore space (WFPS) explained 37-77% of the variance in N2O fl
ux. Spatial variability of N2O fluxes was large with coefficients of v
ariation ranging from 101 to 320%. Spatial variability was suggested t
o be related to distribution of mineral N fertilizer and cattle slurry
, urine and dung patches and variations in groundwater level within th
e field. Average field fluxes obtained with the closed flux chamber me
thod were about a factor 10 larger than those with the flux gradient t
echnique on one measurement day but were similar on two other measurem
ent days. The results of the measurement campaigns were used to derive
a simple empirical model including total mineral N content and WFPS.
This model was tested using an independent data set, i.e. the results
of a monitoring study of two years carried out on two other grassland
sites on peat soil. The model reasonably predicted magnitude of and te
mporal variations in N2O fluxes. It is suggested that a simple empiric
al model which requires only easily obtainable data such as mineral N
content and moisture content, in combination with a few days lasting m
easurement campaigns, may be a valuable tool to predict N2O fluxes fro
m similar sites.