RUSLE A Value Metadata
GEODATASET NAME: LMR_RUSLEA
IDENTIFICATION INFORMATION
Description:
The A value (tons/acre/year soil erosion) as estimated from the Revised
Universal Soil Loss Equation (RUSLE) for the Little Miami River watershed
(HUC catalog unit 05090202) in southwestern Ohio
Abstract:
USLE A value in tons/acre/year as estimated from the five RUSLE component
factor grids, for the Little Miami River watershed
Data Type:
Grid
Data Originators:
USDA Agricultural Research Service
National Sedimentation Laboratory
Oxford, MS
and
USDA Natural Resources Conservation Service
National Cartography and GIS Center
P.O. Box 6567
Fort Worth, TX 76115-0567
and
U.S. Geological Survey
National Elevation Dataset
Sioux Falls, SD
and
Rick Van Remortel
Lockheed Martin Environmental Services
980 Kelly Johnson Drive
Las Vegas, NV 89119
(702)897-3295
rvanremo@lmepo.com
Data Processor:
Rick Van Remortel
Lockheed Martin Environmental Services
980 Kelly Johnson Drive
Las Vegas, NV 89119
(702)897-3295
rvanremo@lmepo.com
Data Provider:
Bernie Daniel
U.S. Environmental Protection Agency
National Exposure Research Laboratory
26 W. Martin Luther King Dr. MS-785
Cincinnati OH 45268
(513)596-7401
daniel.bernie@epamail.epa.gov
Keywords:
watershed, soils, RUSLE, erosion, A value
Version:
N/A
Status:
Interim
Revision Number:
0
Series Name:
Online Link (URL):
Time Period of Content:
Use Constraints:
This grid contains uncertainty specific to a given location on a landscape,
so users should exercise caution when applying results to local situations.
The component K-factor grid values used in creating the A-value grid were
developed by area-weighting the array of individual STATSGO soil
components within a series of soil map units delineated within each
state, then joining the states to the EPA region level. STATSGO is a
state-level database. As such, the specific K-factor value of a given
point on the landscape cannot be known with certainty because the
distribution of soil components within each map unit is variable
across a state. Finer resolution data can be derived from the SSURGO
database (for soil survey areas) where such data have been released by
NRCS. However, SSURGO data only has improved resolution and still is not
point-specific. Caution must be exercised with the interpretations drawn
from STATSGO and SSURGO applications. The present version of this grid
should be considered Draft, for internal use only at this time.
Purpose:
Little Miami River geodata browser website
Date of metadata entry/update:
6/15/2000
No Publication Information Available
No File Security Information Available
DATA QUALITY INFORMATION
Cloud Cover:
Not applicable
Software:
Arc/Info 7.2
Operating System:
Unix
Path Name:
/gis8/l_miami/data/ned/lmr_ruslea
Logical Consistency Report:
Not presently available
Completeness Report:
Not presently available
Horizontal Positional Accuracy:
Not presently available
Vertical Positional Accuracy:
Not presently available
Attribute Accuracy:
Not presently available
Procedures:
The A-value grid is a multiplicative composite of five input RUSLE
factor grids, where A is expressed in tons/acre/year. Because
of file storage considerations, the input factor grids were modified
from floating point to integer grids, thus carrying with them an
expansion coefficient that would have to be applied to the data to put
the factors in proper units. For example, a K-factor of '0.32'
became '32' with an expansion coefficient of '100'. In this way, the
input factor grids were multiplied together and then divided by the
total number of power-of-10 exponents to put the A-value grid into its
proper reporting units (t/a/y). The LMR boundary grid (lmr_bnda27g) was
used as a mask during the processing. Also see the individual metadata
files describing the input factors for more information.
Reviews Applied to Data
Lockheed Martin internal review
Related Spatial Data Files:
All geodatasets with *usle* within the name
Other References Cited:
Renard, K.G., G.R. Foster, G.A. Weesies, D.K. McCool, and D.C. Yoder.
1997. Predicting soil erosion by water: A guide to conservation
planning with the Revised Universal Soil Loss Equation (RUSLE).
Agriculture Handbook No. 703. U.S. Dept. Agr., Agric. Res. Serv.
Van Remortel, R.D., M.E. Hamilton, and R.J. Hickey. In press. Estimating
the LS factor for RUSLE through iterative slope length processing of
digital elevation data. Cartography.
Wischmeier, W.H., and D.D. Smith. 1968. Predicting Rainfall Erosion
Losses: A Guide to Conservation Planning. USDA Handbook No. 537.
U.S. Department of Agriculture, Washington, DC.
Notes:
Update Frequency:
As needed
SPATIAL REFERENCE INFORMATION
Description of Grid lmr_ruslea
Cell Size = 30.000 Data Type: Integer
Number of Rows = 3919 Number of Values = 416
Number of Columns = 2248 Attribute Data (bytes) = 12
BOUNDARY STATISTICS
Xmin = 984724.688 Minimum Value = 0.000
Xmax = 1052164.688 Maximum Value = 791.000
Ymin = 1828894.625 Mean = 5.199
Ymax = 1946464.625 Standard Deviation = 6.547
COORDINATE SYSTEM DESCRIPTION
Projection ALBERS
Datum NAD27
Units METERS Spheroid CLARKE1866
Parameters:
1st standard parallel 29 30 0.000
2nd standard parallel 45 30 0.000
central meridian -96 0 0.000
latitude of projection's origin 23 0 0.000
false easting (meters) 0.00000
false northing (meters) 0.00000
ENTITY AND ATTRIBUTE INFORMATION
Annotation Name:
ATTRIBUTE LISTING FOR: LMR_RUSLEA.VAT
COLUMN ITEM NAME WIDTH OUTPUT TYPE N.DEC ALTERNATE NAME INDEXED?
1 VALUE 4 10 B - Indexed
5 COUNT 4 10 B - -
9 A_VALUE_TAY 4 4 I - -
METADATA REFERENCE SECTION
FGDC Content Standards for Digital Geospatial Metadata
FGDC Standards Version 6/98 / metadata.aml ver. 1.3 5/21/99
SUPPLEMENTAL METADATA (where available)
Abstract:
The Universal Soil Loss Equation (USLE) is designed to predict
long-term average annual soil loss. It was developed primarily for
agricultural situations, but has been more widely applied. The equation
is based on the concept that rainfall patterns across a region set up
characteristic erosion conditions that are mitigated or exacerbated by
soil type, slope, and land cover conditions. The basic equation is:
A = R * K * LS * C * P
where A is long-term average annual soil loss (tons/acre/year), R is
the rainfall erosivity factor, K is the soil erodibility factor, LS is
the length-slope factor, C is cover and management factor, and P is
the support management factor (e.g., strip cropping, buffer-strip
cropping). Over the eastern U.S. R ranges between 75 and 450, and
the other factors typically range between 0 and 1. Conceptually, USLE
estimates soil erosion as a reduction in potential erosion from rainfall
due to soil, slope, and land cover characteristics.
USLE and RUSLE are experiencing a resurgence because of growth in
GIS-based analysis and better availability of digital data. The slope
length and steepness factor (LS) can now be reasonably estimated from digital
elevation model (DEM) data, in this case 30-meter NED DEM data using a custom
LS-factor AML (Van Remortel et al., in press). The soil erodibility factor (K)
is estimated as part of the Natural Resources Conservation Service (NRCS)
digital STATSGO or SSURGO soils databases. The basic soil map unit components
are associated phases of soils series. Each soil series typically has a
unique K factor, and the K factor for each map unit was calculated as a
weighted average. The cover factor (C) can be estimated for land cover
classes derived from 30-m satellite data. The support management factor
(P) only applies to intensive agricultural land cover classes and a constant
factor of contour strip cropping was assumed. C and P were estimated as the
middle or average value from a range of values derived from different land
cover types and slope gradient ranges. R-factor values were taken from an
interpolated grid of values derived from a RUSLE isoline map.
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