Official Series Description


Lab Data Summary

Aggregate lab data for the OPTIMA soil series. This aggregation is based on all pedons with a current taxon name of OPTIMA, 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 OPTIMA 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
77A93P0110S1992OK139001Optima6Primary | Supplementary | Taxonomy | Pedon | Water Retention | Correlation | Andic Soil Properties36.6991653,-100.9811096
77A05N0686S2005KS129003Optima6Primary | Supplementary | Taxonomy | Pedon | Water Retention | Correlation | Andic Soil Properties37.2219429,-101.5977783

Water Balance

Monthly water balance estimated using a leaky-bucket style model for the OPTIMA 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 OPTIMA 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 OPTIMA 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 OPTIMA 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 .

There are insufficient data to create the 2D hillslope position figure.

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

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

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

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Competing Series

Soil series competing with OPTIMA 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 OPTIMA 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 OPTIMA 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 OPTIMA, 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

No block diagrams are available.

Map Units

Map units containing OPTIMA 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
Optima-Eva complex, 1 to 15 percent slopes5934105913817372w84rks02519801:24000
Eva-Optima-Dalhart complex, 0 to 5 percent slopes523159913817362w84qks02519801:24000
Eva-Optima-Dalhart complex, 0 to 5 percent slopes5231213804592w84qks05719621:24000
Eva-Optima complex, 5 to 15 percent slopes5236163524233352rgf6ks06719651:24000
Optima loamy sand, 5 to 20 percent slopes52574224233382rgfhks06719651:24000
Eva-Optima complex, 5 to 15 percent slopes523628524418212rgf6ks08119651:24000
Eva-Optima-Dalhart complex, 0 to 5 percent slopes52312514587452w84qks08119651:24000
Optima-Eva complex, 1 to 15 percent slopes59343252613818102w84rks11919731:24000
Eva-Optima-Dalhart complex, 0 to 5 percent slopes52312521113818092w84qks11919731:24000
Optima fine sand, 10 to 25 percent slopes5249289113817992rgffks11919731:24000
Optima loamy sand, 5 to 20 percent slopes5253112313818002rgfhks11919731:24000
Eva-Optima complex, 5 to 15 percent slopes52361715713825972rgf6ks12919951:24000
Optima loamy sand, 5 to 20 percent slopes52571171213826062rgfhks12919951:24000
Optima loamy fine sand, 1 to 5 percent slopes5256651213826052rgfgks12919951:24000
Eva-Optima-Dalhart complex, 0 to 5 percent slopes52313715813826242w84qks17519631:24000
Eva-Optima complex, 5 to 15 percent slopes52363416916904852rgf6ks17519631:24000
Optima fine sand, 10 to 25 percent slopes5249467013826582rgffks17519631:24000
Optima loamy sand, 5 to 20 percent slopes5253182213826592rgfhks17519631:24000
Eva-Optima complex, 5 to 15 percent slopes5236483059168112rgf6ks18920051:24000
Optima loamy sand, 5 to 20 percent slopes525769969168212rgfhks18920051:24000
Optima loamy fine sand, 1 to 5 percent slopes525694310175812rgfgks18920051:24000
Optima-Eva complex, 1 to 15 percent slopesOpEF1567531012892w84rok00720211:24000
Optima loamy sand, 5 to 20 percent slopesOptF538531564962rgfhok00720211:24000
Optima loamy fine sand, 1 to 5 percent slopesOptC216731564952rgfgok00720211:24000
Eva-Optima complex, 3 to 5 percent slopesVb67811325534330qg0ok02519581:20000
Dalhart-Optima complex, 1 to 5 percent slopesDoB627194844423dj1tx19520071:24000

Map of Series Extent

Approximate geographic distribution of the OPTIMA 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 .