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Mapping and Representing Soil Information and Data

Mapping and Representing Soil Information and Data. Soil and Scale. Scales and complexities range Use/application determines appropriate scale. County Soil Surveys. Inventories, descriptions, evaluations, maps of soils in a county Program established 1899 in USDA

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Mapping and Representing Soil Information and Data

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  1. Mapping and Representing Soil Information and Data

  2. Soil and Scale • Scales and complexities range • Use/application determines appropriate scale

  3. County Soil Surveys • Inventories, descriptions, evaluations, maps of soils in a county • Program established 1899 in USDA • Farmers suitable crops and management practices • Now includes evaluation for other uses: construction, septic, farm planning, tax assessment, forest management, ecological research • Originally hard copy, paperback books • Useful in the field • Now available as pdf files

  4. County Soil Surveys: • Paper copy available from County NRCS office • For counties that have been surveyed • Free to public • PDF file available on NRCS MN web http://www.mn.nrcs.usda.gov • Surveys include: -general information about the county -descriptions of all the soil types in the county -tables of information on: suitabiity, limitations, management for specific uses

  5. HOW ARE SURVEYS MADE?(Goal: map county soils) • By digging a lot of holes! to observe profiles • Observing slopes, water tables, landscape, parent material, vegetation, crops, climate • Create a conceptual model of how soils were formed • Use these models during mapping to PREDICT what kind of soil will be present in a particular landscape • Sample some soils to determine laboratory and engineering characteristics

  6. General soil map units(also called associations) • Broad areas with soils, relief and drainage • Each unit represents a particular natural landscape • Useful for general land uses; not good for a farm or field or road or building • General map units are shown as: • Soil- landscape block diagrams • Written descriptions • Color map in soil survey

  7. AITKIN COUNTY EXAMPLE • Aitkin County, Volume One • (look at general description of county, climate tables, general map unit descriptions and block diagrams) • (look at General Soil Map)

  8. Detailed soil map units • “Map unit” • Soils blend into one another; do not follow strict boundaries, therefore a challenge to map • Areas of one particular soil can hardly ever be mapped without including other soils • Map unit solves this issue by including similar soils • Named by the dominant soil in the unit • Each map unit has adominantsoil and inclusions (other similar soils) • Example: p. 43 of Aitkin survey: • #292 Alstad Loam (Map Unit) • 85% Alstad • 15% inclusions

  9. Series descriptions • Unit of taxonomy • All major horizons in a series are similar • But they can differ in some characteristics, like stoniness, texture, wetness, etc. • These allowable differences are listed as Range of Characteristics after each series description • Each series gives its taxonomic class : • “Fine-loamy mixed GlossaquicEutroboralf” • We can find a detailed description of the Alstad Series • Series descriptions are listed alphabetically • Example: Alstad series, Aitkin County • (look for series description, range in characteristics, taxonomic class)

  10. Order Suborder Great group Subgroup Family Series Alfisol Boralfs Eutroboralfs GlossaquicEutroboralf “Fine-loamy mixed GlossaquicEutroboralf” Alstad Hierarchical categories“Fine-loamy mixed Glossaquic Eutroboralf”

  11. Taxonomic class • AlstadSeries:“Fine-loamy mixed GlossaquicEutroboralf” Fine-loamy mixed frigid superactive Particle size mean annual temp <8°C; >6°C range Mixture of clay minerals High CEC

  12. Note : Series are listed alphabetically, but map unit numbers are not in order, therefore need to consult Soil Legend to look up numbers from maps

  13. “The objective of mapping is not to delineate pure taxonomic classes but rather to separate the landscape into segments that have similar use and management requirements…if intensive use of small areas is planned, onsite investigations is needed to define and locate the soils…” • Soil survey maps do not preclude field checking!!!

  14. Other useful links on MN NRCS • Soil series descriptions www.soils.usda.gov/technical/classification/osd • Soils Data Mart www.soildatamart.nrcs.usda.gov

  15. Publications www.soils.usda.gov Soil Taxonomy Keys to Soil Taxonomy Glossary

  16. GIS Soil data • Spatially referenced • GIS-compatible format • Geographic Information Systems Data sets identify soils with similar characteristics and tables describe attributes (characteristics) of each delineated soil type • STATSGO • SSURGO

  17. STATSGO • State Soil Geographic database • More generalized than SSURGO • 1;250,000 • For land use planning over large areas • Need GIS or Web Soil Survey

  18. SSURGO • Soil Survey Geographic database • “SSURGO-certified” • National cartographic standards • More detail than STATSGO • 1:12,000 to 1:63,360 • Landowners and county-level planning • Need GIS or Web Soil Survey • Current state of mapping in MN

  19. DATA USES AND SCALE • Site-Level Management: • Detailed applications: • Precision agriculture, UMD farm recommendations, septic mound location • On-site investigation by soils person to augment info in county survey (if one is available) • Up to 1: 5000 • Local Planning: • Residential and commercial development, transportation, recreation, open space and natural areas • County soil surveys: 1:20,000 • Generalized characterization of Landscape: • Broad management and ecological research • Statewide data sets

  20. Web soil survey • Interface for users who do not have/use/know GIS; can access SSURGO data. • Web Soil Survey

  21. Sample Project Using SSURGO data: • Include past hydrology in the MN/Model.

  22. Mn/Model 2002 • Archaeological predictive model used by Mn DOT to avoid destroying or disturbing archaeological sites during road construction projects. • GIS statistical model of High, Medium, Low likelihood • Important input to model is landscape • Lacked past hydrology

  23. Soil CriteriaMn/DOT formatted soil datasetMap Unit ComponentsTaxonomyGreat Groups (18)Histosols, Aquic Suborders, UdifluventsBlue Earth example, Hennepin exampleHydric RatingDrainage Classes

  24. existing lakes, streams, and wetlands county SSURGO soils data 30m elevation data / geomorphology General Land Office survey maps Existing GIS data used to derive historic water features

  25. Landform Sediment Assemblages Identify riverine features Input GIS dataset Tool output dataset Final model output dataset GLO lakes Tool in ModelBuilder GLO wetlands Potential historic lake / wetland areas with source field populated 2. GLO lakes and wetlands Correspondence Potential Historic Lake / Wetland areas derived from soil polygons Use if GLO delineations are not available 1. select great groups and eliminate_less_3acres Mn/DOT soils Derived from SSURGO All historic water features Potential historic riverine features 5. Combine all potential historic water features 3. Identify historic riverine features Select great groups for riverine features Identify fluvial features Identify perennial features Identify riverine features MN DNR Geomorphology MN DNR Streams NWI wetlands Selected natural palustrine, Lacustrine features And areas derived from RDWI 4. NWI natural feature selection plus RDWI RDWI wetlands only if available Conceptual Model to Create Historic Water Features layer for Mn/Model Phase 4.

  26. Identification of Historic Lake and Wetland Features Select Great Groups meeting hydric criteriaFilter Hydric = “P” and not Drainage = “VP” or “P”Aggregate neighboring polygonsDelete areas < 3 acresDissolve soil polygons of same Landform togetherExample of Tool 1 output in Hennepin Counties with GLO surveyed features Example of Tool 1 output in Hennepin County with HCD Wetland Inventory

  27. Figure 6. Historic features illustrating Great Group selection in Blue Earth County

  28. Figure 7. Historic features illustrating Great Group selection in Hennepin County

  29. Figure 8. Example of Tool 1 output in Hennepin Counties with GLO surveyed features

  30. Figure 9. Example of Tool 1 output in Hennepin Counties with HCD Wetland Inventory

  31. Identify historic riverine features tool in ArcGIS ModelBuilder Select Hydric Great GroupsSubset Great Groups that intersect Fluvial Geomorphology (set 1) Select Riverine Features from NWI (set 2) Combine Set 1, Set 2, and Set 3 for Historic Riverine Features Historic riverine features and associated data in Blue Earth County

  32. Natural Features Selection Plus RDWI Tool in ArcGIS ModelBuilderEliminate artificial wetlands from NWI (Wreg = K, artificial; Spec_mod1 = b [beaver], h [impounded], or x [excavated])Select NWI that corresponds with RDWI, populate RDWI field = ‘y’Combine RDWI and NWI features

  33. Combine all potential historic water features Compare to General Land Office data? Other studies in other counties (Hennepin)

  34. Demonstration of SSURGO for use in GIS http://soildatamart.nrcs.usda.gov/ http://www.lmic.state.mn.us/chouse/soil.html Downloading data Importing ssurgo into template Shapefiles Tables Linking and Joining Tables

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