MAPPING AND REPRESENTING SOIL INFORMATION AND DATA

 Scales and complexities range  Use/application determines appropriate scale SOIL AND SCALE

 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 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  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 COUNTY SOIL SURVEYS:

 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 HOW ARE SURVEYS MADE? (Goal: map county soils)

 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 GENERAL SOIL MAP UNITS (also called ASSOCIATIONS)

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

 “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 a dominant soil and inclusions (other similar soils)  Example: p. 43 of Aitkin survey:  #292 Alstad Loam (Map Unit)  85% Alstad  15% inclusions DETAILED SOIL MAP UNITS

 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 Glossaquic Eutroboralf”  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) SERIES DESCRIPTIONS

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

 Alstad Series:“Fine-loamy mixed Glossaquic Eutroboralf” Fine-loamy TAXONOMIC CLASS Particle size mixed Mixture of clay minerals superactive High CEC frigid mean annual temp <8°C; >6°C range

 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

 “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!!!

 Soil series descriptions  Soils Data Mart OTHER USEFUL LINKS ON MN NRCS

Soil Taxonomy Keys to Soil Taxonomy Glossary PUBLICATIONS

 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 GIS SOIL DATA

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

 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 Current state of mapping in MN SSURGO

 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 DATA USES AND SCALE

 Interface for users who do not have/use/know GIS; can access SSURGO data.  Web Soil Survey Web Soil Survey WEB SOIL SURVEY

 Include past hydrology in the MN/Model. SAMPLE PROJECT USING SSURGO DATA:

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

Soil Criteria Mn/DOT formatted soil dataset Map Unit Components Taxonomy Great Groups (18) Histosols, Aquic Suborders, Udifluvents Blue Earth example, Hennepin example Hydric Rating Drainage Classes

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

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

Identification of Historic Lake and Wetland Features Select Great Groups meeting hydric criteria Filter Hydric = “P” and not Drainage = “VP” or “P” Aggregate neighboring polygons Delete areas < 3 acres Dissolve soil polygons of same Landform together Example of Tool 1 output in Hennepin Counties with GLO surveyed features Example of Tool 1 output in Hennepin County with HCD Wetland Inventory

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

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

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

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

Identify historic riverine features tool in ArcGIS ModelBuilder Select Hydric Great Groups Subset 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

Natural Features Selection Plus RDWI Tool in ArcGIS ModelBuilder Eliminate 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

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

Demonstration of SSURGO for use in GIS Downloading data Importing ssurgo into template Shapefiles Tables Linking and Joining Tables