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Soil Texture


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:

0 - No data
1 - Sand
2 - Loamy sand
3 - Sandy loam
4 - Silt loam
5 - Silt
6 - Loam
7 - Sandy clay loam
8 - Silty clay loam
9 - Clay loam
10 - Sandy clay
11 - Silty clay
12 - Clay
13 - Organic materials
14 - Water
15 - Bedrock
16 - Other

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.

2. Soil Texture Covering Oklahoma Basins

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

3. Soil Texture Covering Covering Western Basins

Data Blocks also cover both the American and Carson rivers

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 (Θs or SMAX) and residual volumetric water content (Θr 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.

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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.


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