Official Series Description


Lab Data Summary

Aggregate lab data for the GILBOA soil series. This aggregation is based on all pedons with a current taxon name of GILBOA, and applied along 1-cm thick depth slices. Solid lines are the slice-wise median, bounded on either side by the interval defined by the slice-wise 5th and 95th percentiles. The median is the value that splits the data in half. Five percent of the data are less than the 5th percentile, and five percent of the data are greater than the 95th percentile. Values along the right hand side y-axis describe the proportion of pedon data that contribute to aggregate values at this depth. For example, a value of "90%" at 25cm means that 90% of the pedons correlated to GILBOA were used in the calculation. Source: KSSL snapshot . Methods used to assemble the KSSL snapshot used by SoilWeb / SDE

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Pedons used in the lab summary:

MLRALab IDPedon IDTaxonnameCINSSL / NASIS ReportsLink To SoilWeb GMap
111D06N0638S05IN007001Gilboa7Primary | Supplementary | Taxonomy | Pedon | Water Retention | Correlation | Andic Soil Properties40.5512326,-87.3396857

Water Balance

Monthly water balance estimated using a leaky-bucket style model for the GILBOA soil series. Monthly precipitation (PPT) and potential evapotranspiration (PET) have been estimated from the 50th percentile of gridded values (PRISM 1981-2010) overlapping with the extent of SSURGO map units containing each series as a major component. Monthly PET values were estimated using the method of Thornthwaite (1948). These (and other) climatic parameters are calculated with each SSURGO refresh and provided by the fetchOSD function of the soilDB package. Representative water storage values (“AWC” in the figures) were derived from SSURGO by taking the 50th percentile of profile-total water storage (sum[awc_r * horizon thickness]) for each soil series. Note that this representation of “water storage” is based on the average ability of most plants to extract soil water between 15 bar (“permanent wilting point”) and 1/3 bar (“field capacity”) matric potential. Soil moisture state can be roughly interpreted as “dry” when storage is depleted, “moist” when storage is between 0mm and AWC, and “wet” when there is a surplus. Clearly there are a lot of assumptions baked into this kind of monthly water balance. This is still a work in progress.

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Sibling Summary

Siblings are those soil series that occur together in map units, in this case with the GILBOA series. Sketches are arranged according to their subgroup-level taxonomic structure. Source: SSURGO snapshot , parsed OSD records and snapshot of SC database .

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Select annual climate data summaries for the GILBOA series and siblings. Series are sorted according to hierarchical clustering of median values. Source: SSURGO map unit geometry and 1981-2010, 800m PRISM data .

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Geomorphic description summaries for the GILBOA series and siblings. Series are sorted according to hierarchical clustering of proportions and relative hydrologic position within an idealized landform (e.g. top to bottom). Most soil series (SSURGO components) are associated with a hillslope position and one or more landform-specific positions: hills, mountain slopes, terraces, and/or flats. Proportions can be interpreted as an aggregate representation of geomorphic membership. The values printed to the left (number of component records) and right (Shannon entropy) of stacked bars can be used to judge the reliability of trends. Small Shannon entropy values suggest relatively consistent geomorphic association, while larger values suggest lack thereof. Source: SSURGO component records .

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There are insufficient data to create the 3D mountains figure.

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Competing Series

Soil series competing with GILBOA share the same family level classification in Soil Taxonomy. Source: parsed OSD records and snapshot of the SC database .

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Select annual climate data summaries for the GILBOA series and competing. Series are sorted according to hierarchical clustering of median values. Source: SSURGO map unit geometry and 1981-2010, 800m PRISM data .

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Geomorphic description summaries for the GILBOA series and competing. Series are sorted according to hierarchical clustering of proportions and relative hydrologic position within an idealized landform (e.g. top to bottom). Proportions can be interpreted as an aggregate representation of geomorphic membership. Most soil series (SSURGO components) are associated with a hillslope position and one or more landform-specific positions: hills, mountain slopes, terraces, and/or flats. The values printed to the left (number of component records) and right (Shannon entropy) of stacked bars can be used to judge the reliability of trends. Shannon entropy values close to 0 represent soil series with relatively consistent geomorphic association, while values close to 1 suggest lack thereof. Source: SSURGO component records .

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There are insufficient data to create the 3D mountains figure.

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Click the image to view it full size.

Soil series sharing subgroup-level classification with GILBOA, arranged according to family differentiae. Hovering over a series name will print full classification and a small sketch from the OSD. Source: snapshot of SC database .

Block Diagrams

Click a link below to display the diagram. Note that these diagrams may be from multiple survey areas.

  1. IN-2012-01-19-06 | Benton County - 1989

    Pattern of soils and parent material in the Corwin-Odell-Chalmers association (Soil Survey of Benton County, Indiana; 1989).

Map Units

Map units containing GILBOA as a major component. Limited to 250 records.

Map Unit Name Symbol Map Unit Area (ac) Map Unit Key National Map Unit Symbol Soil Survey Area Publication Date Map Scale
Gilboa silt loam, 0 to 2 percent slopesGlA151061645735j7tin00719851:15840
Gilboa silt loam, 2 to 4 percent slopesGlB41231645745j7vin00719851:15840
Gilboa-Odell complex, 0 to 2 percent slopesGbA53601635805h6sin11119901:15840
Gilboa silt loam, 0 to 2 percent slopesGgA41961631125gqpin17119871:15840

Map of Series Extent

Approximate geographic distribution of the GILBOA soil series. To learn more about how this distribution was mapped, or to compare this soil series extent to others, use the Series Extent Explorer (SEE) application. Source: generalization of SSURGO geometry .