Geology Reference
In-Depth Information
channel transferring water down from the ter-
race/diversion to the hillslope bottom. This chan-
nel can currently be modelled to cause deposition,
but cannot currently be modelled as experiencing
erosion. The ability to easily add or remove ter-
races for the hillslope description is important
because it allows these to be approached as
another management alternative, rather than
requiring redefinition by the user of the hillslope
profile itself.
elevation on erosivity was reflected by defining
precipitation zones within counties of 11 moun-
tainous western US states. The erosivity density
approach allows geographically consistent ero-
sion predictions needed for a conservation/ero-
sion planning tool, and maximizes information
that can be extracted from available 15-min pre-
cipitation data.
(ii) Changes in the soil description
Changes in
the soil description and
K
-factor computations
include the development of a modified nomo-
graph for highly disturbed soils, the development
of new routines to describe time-variation in the
K
factor based on location temperature and pre-
cipitation data, and the ability to reflect the
impact of subsurface drainage by specifying a soil
hydrological class. RUSLE2 contains equations
representing both the standard nomograph (Fig.
8.2) and a modified nomograph that applies to
disturbed soils such as construction sites or
reclaimed mine soils. The modified nomograph
is the same as the standard nomograph for fine
granular soils (
S
(i) Changes in the climate description
The cli-
mate data required to calculate soil loss in
RUSLE2 are monthly averages for precipitation,
temperature and erosivity, plus the desired loca-
tion's ten-year 24-h precipitation amount (
P
10y,24h
).
Climate description changes from RUSLE1 to
RUSLE2 include: specification of
P
10y,24h
rather
than the ten-year
EI
event; updating the underly-
ing record to the period from 1960 to 1989 (1960
to 1999 in many cases); and development of the
erosivity density concept. Specification of
monthly average precipitation and monthly aver-
age erosivity density is the preferred way of
describing monthly erosivity in RUSLE2, and
these values are contained in all the NRCS loca-
tion climate files (USDA-NRCS, 2008). Erosivity
density is defined as the amount of rainfall ero-
sivity per unit of precipitation. Erosivity density
has units of energy per unit area per unit time
(e.g. MJ ha
−1
h
−1
), and when multiplied by the
depth of precipitation over an interval (event, day,
month, year) yields the appropriate average ero-
sivity value. Using erosivity density has several
advantages over directly calculated rainfall ero-
sivity: (1) because it is the ratio of storm erosivity
to storm precipitation, missing data have less
impact on monthly means; (2) a shorter period of
record is needed to arrive at a stable value of this
ratio than a stable absolute value of erosivity;
(3) because erosivity density was found to be rela-
tively independent of elevation up to 3000 m, it
was possible to interpolate a smoothly-varying
erosivity density surface for the entire nation,
making it possible to calculate erosivity for each
county (common use in the US) or each precipita-
tion zone (USDA-ARS, 2008a,b). The effect of
2), but the structural trend in
erodibility is reversed in the modified nomo-
graph, so that erodibility decreases as structure
varies from very fine granular to massive. In the
modified nomograph, the labels for class 1 and 3
structures would be exchanged and the line for
class 4 structure would be to the left of all struc-
ture lines shown in Fig. 8.2. The modified nomo-
graph is recommended for highly disturbed lands
such as reclaimed mined land and construction
sites, whereas the standard nomograph is recom-
mended for agricultural soils because of its
empirical support. For equivalent soil properties,
both the standard and modified nomograph
return a base
K
factor for Columbia, MO, which
is a reference location and the centre of the
RUSLE2 domain.
RUSLE1 included a time-varying
K
factor
that was based on a few data points collected in
the central US that indicated a time-varying
change in Unit Plot erosion from storms with
similar erosivity. New relationships in RUSLE2
capture the effect of temperature and precipita-
tion on the likelihood of runoff and hence the
K
=
