Root depth with time
5. Actions of overburden and water droplets on
Borg and Grimes (1986) developed a model to
water-weakened aggregates during rainfall;
simulate actual root depth as a function of time.
6. Frost heave actions.
For a given crop and location, the model requires
Physicalimpedance can be measured with pene-
an estimate of the maximum rooting depth to be
trometers, shear vanes, shear rings, triaxial shear
achieved and the number of days to reach matur-
cells, and unconfined compression cells. As far as
ity.
we know, no mathematical model is available to
predict soil yielding under load using fundamental
Root depth with temperature
parameters.
The model is two-dimensional and was devel-
oped from data that explain the effect of root zone
Spatial variability
temperature on soybean root development (Stone
Considerable research has been reported in
et al. 1983). The model predicts the extension of the
the literature during the past decade on the spa-
taproot and ten primary lateral roots for two
tial variability of soil physical properties. How-
groups of soybean cultivars. The simulation em-
ever, in cold environments a computer literature
phasizes the importance of soil temperature, but
search has revealed limited published studies on
ignores many other factors responsible for root
the spatial variability of solute and temperature,
elongation.
and none with respect to root water uptake.
Therefore, this section is limited to reporting sol-
Carbon partition models
ute and temperature-related variability studies
Carbon partition models are complex compared
from cold environments.
to simple models. These models partition carbon
Spatial variability has a significant effect on
between the above- and below-ground biomass.
field-scale solute movement through the unsat-
The partitioning coefficient is assumed to be a con-
urated zones. The effect of spatial variability in
stant fraction of the daily photosynthetic produc-
soil hydraulic properties has been investigated
tion. Following are a few examples of carbon parti-
using either parametric models (Dagan and Bres-
tion models.
ler 1979, Bresler and Dagan 1981, Amoozegar-
Fard et al. 1982, Simmons 1982, Destouni and
Root:shoot ratios
Cvetkovic 1989) or transfer function models (Jury
Numerous studies have shown that plants tend
et al. 1986, Butters and Jury 1989). Few workers
to adjust their root:shoot ratio to maintain an inter-
studied the temperature spatial variability in re-
nal carbon-nitrogen balance favorable for growth
lation to soil water content (Vauclin et al. 1982,
(Davidson 1969, Reynolds and Thornley 1982,
Davidoff et al. 1986).
Skiles et al. 1982, Johnson 1983, Coughenour et al.
1984, Fishman et al. 1984). Davidson (1969) devel-
OVERVIEW OF ROOT GROWTH MODELS
oped a model based on a hypothesis that a func-
tional balance exists between the size and activity
Several root growth models were developed
of the shoot (which supplies carbohydrates) and
during the past decade, but none is geared to the
the size and activity of the root (which supplies
problems associated with root growth in cold re-
water and essential nutrients). His model suggest-
gions. The models reported in the literature are
ed the partitioning of photosynthates.
classified as simple models, carbon-partition
Partition models were reviewed by Reynolds
models, growing degree day-based models, soil
and Thornley (1982). They developed a model
parameter-based models, and arctic plant growth
based on the assumption that the partition of new
models.
growth is controlled by whole-plant substrate con-
centrations. Their model partitioned the photo-
Simple models
synthates between root and shoot on the basis of
the nitrogen:carbon ratio in the plant's labile pool.
Root distribution with depth
In spite of good features and the high complexity
The model of Gerwitz and Page (1974) is em-
of the model, however, it has the following draw-
pirical in nature and simulates root density as a
backs:
function of soil depth. The model makes no
1. The carbon:nitrogen (C:N) substrate concen-
attempts to define the relative age classes of the in-
tration ratio is always considered a fixed value
dividual root axes in each layer or the proportion of
not influenced by the external environment;
those axes that are first- or second-order laterals.
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