Abstract:
Accurate prediction of soil- gas
diffusivity (Dp/Do: where Dp and Do are gas
diffusion coefficients in soil and free air,
respectively) and its variation with air-filled
porosity (ε) is important for understanding soil
aeration and subsurface greenhouse gas
emissions and thereby to characterize essential
soil functional services in terrestrial ecosystems.
Since measuring Dp/Do is instrumentally
challenging and requires maintaining
controlled boundary conditions, different
predictive models have been developed to
estimate Dp/Do from easily measurable soil
properties such as air-filled porosity (ε) and soil
total porosity (Ф). In this study, a total of 593
gas diffusivity measurements conducted on 150
data from differently characterized
undisturbed Danish soils were used to evaluate
the performance of five prospective predictive
models developed over the period of 1904 -2013.
The selected soils represent agricultural soils,
forest soils, urban soils, and landfill cover soils
and measurements were within a selected range
of matric potentials (−10 to −500 cm H2O)
typically occurring in subsurface. Results of the
model comparison made using two statistical
indices (RMSE and Bias) showed that widely
used model for repacked soils made a significant
overprediction of undisturbed data. This study
clearly distinguished the effect of soil structure
status on soil gas diffusivity as demonstrated by
the best performance of SWLR model over the
other predictive models by yielding minimum
RMSE and bias.
