Official Series Description


Lab Data Summary

Aggregate lab data for the MERETA soil series. This aggregation is based on all pedons with a current taxon name of MERETA, 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 MERETA 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
78B11N8870S10TX3999007Mereta8Primary | Supplementary | Taxonomy | Pedon | Water Retention | Correlation | Andic Soil Properties31.7689171,-100.0761642
81B09N0840S09TX307004Mereta7Primary | Supplementary | Taxonomy | Pedon | Water Retention | Correlation | Andic Soil Properties31.2077637,-99.2266464

Water Balance

Monthly water balance estimated using a leaky-bucket style model for the MERETA 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 MERETA 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 MERETA 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 MERETA 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 MERETA 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 MERETA series and competing. Series are sorted according to hierarchical clustering of median values. Source: SSURGO map unit geometry and 1981-2010, 800m PRISM data .

There are insufficient data to create the annual climate figure.

Geomorphic description summaries for the MERETA 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 .

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.

There are insufficient data to create the 3D flats position figure.

Soil series sharing subgroup-level classification with MERETA, 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. TX-2010-11-03-75 | Mason County -

  2. TX-2012-03-21-46 | McCulloch County - November 1974

    Pattern of soils in Rowena-Mereta association (Soil Survey of McCulloch County, TX; 1974).

  3. TX-2012-03-21-65 | Runnels County - March 1970

    Soils formed in plains outwash (Soil Survey of Runnels County, TX; 1970).

  4. TX-2012-03-21-67 | Shackelford County - February 1990

    Typical pattern of soils and parent material in the Lueders-Throck-Nukrum map unit (Soil Survey of Shackelford County, TX; 1990).

  5. TX-2012-03-21-69 | Shackelford County - February 1990

    Typical pattern of soils and parent material in the Rowena-Leeray-Nuvalde map unit (Soil Survey of Shackelford County, TX; 1990).

Map Units

Map units containing MERETA 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
Mereta clay loam, cool, 1 to 3 percent slopesMeB69903627232wt7btx02319711:24000
Mereta clay loam, 3 to 5 percent slopesMeC2192362724d5fstx02319711:24000
Mereta clay loam, cool, 1 to 3 percent slopes2432063635982wt7btx05919791:24000
Mereta clay loam, dry, 1 to 3 percent slopesMcB152743639802t268tx08119681:24000
Mereta clay loam, dry, 0 to 1 percent slopesMcA83603639792t26ctx08119681:24000
Mereta-Nuvalde complex, 0 to 1 percent slopesMeA70113639812t0r5tx08119681:24000
Mereta-Nuvalde complex, 1 to 3 percent slopesMeB21463639822t0r8tx08119681:24000
Cho and Mereta soils, undulatingKMB12424364014d6sdtx08319681:24000
Mereta clay loam, cool, 1 to 3 percent slopesMrB72773640232wt7btx08319681:24000
Mereta clay loam, 1 to 3 percent slopesMeB492883644392t267tx09519851:24000
Mereta clay loam, 0 to 2 percent slopesMeA178643644382t269tx09519851:24000
Mereta clay loam, dry, 1 to 3 percent slopesMeB91653662412t268tx17319741:31680
Mereta-Nuvalde complex, 1 to 3 percent slopesMnB181153679612t0r8tx23519821:31680
Mereta-Nuvalde complex, 0 to 1 percent slopesMnA65893679602t0r5tx23519821:31680
Mereta clay loam, moist, 1 to 3 percent slopesMeB9943688652szprtx28119901:24000
Mereta clay loam, 1 to 3 percent slopesMeB360463699512t267tx30719701:24000
Cho-Mereta association, gently undulatingCMB29776369937ddygtx30719701:24000
Mereta clay loam, 0 to 2 percent slopesMeA116033699502t269tx30719701:24000
Nuvalde-Mereta complex, 2 to 5 percent slopesNvC6619369955ddz1tx30719701:24000
Mereta-Cho-Sunev complex, 0 to 5 percent slopes, rockyMSC19751370430dfgctx31920111:24000
Mereta clay loam, 0 to 2 percent slopesMrA38643706102t269tx32719651:20000
Mereta clay loam, dry, 1 to 3 percent slopesMmB95213707282t268tx33519651:20000
Mereta clay loam, dry, 0 to 1 percent slopesMmA29283707272t26ctx33519651:20000
Mereta clay loam, 1 to 3 percent slopes19112403709862t267tx35319791:24000
Mereta clay loam, 0 to 2 percent slopes1823303709852t269tx35319791:24000
Mereta clay loam, cool, 1 to 3 percent slopesMcB565993717752wt7btx39919651:20000
Mereta clay loam, 0 to 1 percent slopesMcA11811371774dgvqtx39919651:20000
Mereta clay loam, moist, 1 to 3 percent slopesMeB33763719562szprtx41119801:24000
Valera-Mereta-Kavett association, nearly level11142026371991dh2qtx41319771:31680
Mereta silty clay, 1 to 3 percent slopesMeB10364372067dh55tx41719851:24000
Mereta clay loam, dry, 1 to 3 percent slopesMeB328903722472t268tx43119741:31680
Mereta clay loam, dry, 0 to 1 percent slopesMeA39903722462t26ctx43119741:31680
Mereta clay loam, 1 to 3 percent slopesMrB86963915292t267tx44119711:20000
Mereta clay loam, 0 to 1 percent slopesMrA1238391528f4dytx44119711:20000
Mereta clay loam, 3 to 5 percent slopesMrC935391530f4f0tx44119711:20000
Mereta clay loam, dry, 0 to 1 percent slopesMeA387303727482t26ctx45119711:20000
Mereta clay loam, dry, 1 to 3 percent slopesMeB334753727492t268tx45119711:20000
Mereta-Urban land complex, 0 to 3 percent slopesMuB1471372750dhw6tx45119711:20000
Mereta clay loam, moist, 1 to 3 percent slopes5036423910272szprtx60219751:24000
Mailtrail-Mereta complex, 0 to 5 percent slopesMmC32035374303dkh9tx60720001:31680
Mereta clay loam, dry, 1 to 3 percent slopesMeB36503747122t268tx61819891:31680
Mereta clay loam, dry, 0 to 1 percent slopesMeA32213747112t26ctx61819891:31680

Map of Series Extent

Approximate geographic distribution of the MERETA 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 .