For convenience, this page provides extracts from the data developed by Miller and White (1998) and available from the Penn State Center for Environmental Informatics Database http://dbwww.essc.psu.edu/. The extracted grids contain the dominant soil texture class for each of 11 standard soil layers derived from State Soil Geographic (STASGO) soil data compiled by the Natural Resources Conservation Service (NRCS) of the U.S. Department of Agriculture. Texture grids covering CONUS and clipped grids covering DMIP areas are provided for those who prefer to download smaller data files. The spatial resolution of the grids is 30 arc-seconds (~ 1 km).

The 11 standard layers defined by Miller and White (1998) are: 0-5 cm, 5-10 cm, 10-20 cm, 20-30 cm, 30-40 cm, 40-60 cm, 60-80 cm, 80-100 cm, 100-150 cm, 150-200 cm, 200-250 cm. For many STASGO components, a depth-to-bedrock value of 152 cm was used to indicate that the soil was sampled only to this depth, and no bedrock was encountered. As a result, for many mapunits a soil texture of 'bedrock' for the two lowest standard layers (150cm to 250cm) may actually indicate 'no data'. Definition of soil texture classes:

For more information on these gridded products derived from STATSGO, please visit PSU STATSGO Soil Website.

All files are provided in a gzipped ASCII format. The first several lines of the ASCII files give spatial reference information such as:

nrows = number of rows
ncols = number of columns
xllcorner, yllcorner = coordinater for the lower left corner of the lower left cell
cellsize (units are decimal degrees)
NODATA_value

Data following the header information are listed in row-major order with the top (northernmost) row on the first line.

For users of ESRI software, data can be imported into Arc/Info using the "asciigrid" command or imported in to the ArcView Spatial Analyst using the File --> Import Data Source option.

1. Soil Texture Covering CONUS

Soil texture grids covering the conterminous US are provided below in ascii format. The next section provides clipped versions of these grids covering DMIP study areas for those who prefer to download smaller files.

Layer 1
Layer 2
Layer 3
Layer 4
Layer 5
Layer 6
Layer 7
Layer 8
Layer 9
Layer 10
Layer 11

2. Soil Texture Covering Oklahoma Basins

For Illinois River Basins (Data Blocks also cover Blue and Elk Rivers)

Illinois_005
Illinois_010
Illinois_020
Illinois_030
Illinois_040
Illinois_060
Illinois_080
Illinois_100
Illinois_150
Illinois_200
Illinois_250

3. Soil Texture Covering Covering Western Basins

Data Blocks also cover both the American and Carson rivers

western_layer1.asc.gz
western_layer2.asc.gz
western_layer3.asc.gz
western_layer4.asc.gz
western_layer5.asc.gz
western_layer6.asc.gz
western_layer7.asc.gz
western_layer8.asc.gz
western_layer9.asc.gz
western_layer10.asc.gz
western_layer11.asc.gz

4. Soil texture and properties on the HRAP grid

A grid of dominant soil texture is provided on the HRAP grid. This grid was derived in the process of determining a-priori model parameters for the Sacramento soil moisture accounting model (Koren et al., 2002). Each grid cell contains a value (from 1-12) corresponding to the dominant soil texture (using the same soil texture code definitions defined above). Horizontally, the dominant texture is representative of the HRAP cell area and vertically it is representative of the upper zone of the Sacramento model, which most often corresponds to a physical depth somewhere between 0-20 and 0-30 cm.

stxt.asc.gz: Soil texture grid covering all of CONUS.
stxtclip.asc.gz: Soil texture grid clipped to the soil moisture modeling area for DMIP2 (see modeling instructions).

Grids of saturation volumetric water content (Θ_s or SMAX) and residual volumetric water content (Θ_r or SWLT) were inferred from the STATSGO-based texture grids. These grids are provided to assist modelers in completing the soil moisture section of the modeling instructions. Please see the modeling instructions for more details.

smax.asc.gz (clipped to DMIP2 soil moisture modeling area)
smin.asc.gz (clipped to DMIP2 soil moisture modeling area)

The file format for these grids is the same gzipped grid ASCII format described above for the soil texture data, except these data are in the HRAP projection (same projection as the precipitation data). Therefore, the cellsize for these data is 1 HRAP unit.

Reference

• Miller, D.A., White, R.A., 1998. A conterminous United States multi-layer soil characteristics data set for regional climate and hydrology modeling, Earth Interactions 2, (available at http://EarthInteractions.org).


• Koren, V., Smith, M., Duan, Q. (2002). Use of a priori parameter estimates in the derivation of spatially consistent parameter sets of rainfall-runoff models. In: Calibration of Watershed Models, Water Science and Application 6 (ed. by Q. Duan, S. Sorooshian, H. Gupta, A. Rosseau & R. Turcotte), AGU, Washington DC, USA, 239-254.