This dataset contains the common Map Unit attributes for each polygon within the gSSURGO database plus NRCS derived attributes from a data summary table called the National Valu Added Look Up (valu) Table #1. It is comprised of 57 pre-summarized or "ready to map" derived soil survey geographic database attributes including soil organic carbon, available water storage, crop productivity indices, crop root zone depths, available water storage within crop root zone depths, drought vulnerable soil landscapes, and potential wetland soil landscapes. Related metadata values for themes are included. These attribute data are pre-summarized to the map unit level using best practice generalization methods intended to meet the needs of most users. The generalization methods include map unit component weighted averages and percent of the map unit meeting a given criteria. These themes were prepared to better meet the mapping needs of users of soil survey information and can be used with both SSURGO and Gridded SSURGO (gSSURGO) datasets. Gridded SSURGO (gSSURGO) Database is derived from the official Soil Survey Geographic (SSURGO) Database. SSURGO is generally the most detailed level of soil geographic data developed by the National Cooperative Soil Survey (NCSS) in accordance with NCSS mapping standards. The tabular data represent the soil attributes, and are derived from properties and characteristics stored in the National Soil Information System (NASIS). The gSSURGO data were prepared by merging traditional SSURGO digital vector map and tabular data into State-wide extents, and adding a State-wide gridded map layer derived from the vector, plus a new value added look up (valu) table containing "ready to map" attributes. The gridded map layer is offered in an ArcGIS file geodatabase raster format. The raster and vector map data have a State-wide extent. The raster map data have a 10 meter cell size that approximates the vector polygons in an Albers Equal Area projection. Each cell (and polygon) is linked to a map unit identifier called the map unit key. A unique map unit key is used to link to raster cells and polygons to attribute tables, including the new value added look up (valu) table that contains additional derived data.VALU Table Content:The map unit average Soil Organic Carbon (SOC) values are given in units of g C per square meter for eleven standard layer or zone depths. The average thickness of soil map unit component horizons used in these layer/zone calcuations is also included. The standard layers include: 0-5cm, 5-20cm, 20-50cm, 50-100cm, 100-150cm, and 150-150+cm (maximum reported soil depth). The standard zones include: 0-5cm (also a standard layer), o-20cm, 0-30cm, 0-100cm, and 0-150+cm (full reported soil depth). Zero cm represents the soil surface.The map unit average Available Water Storage (AWS) values are given in units of millimeters for eleven standard layer or zone depths. The average thickness of soil map unit component horizons used in these layer/zone calcuations is also included. The standard layers include: 0-5cm, 5-20cm, 20-50cm, 50-100cm, 100-150cm, and 150-150+cm (maximum reported soil depth). The standard zones include: 0-5cm (also a standard layer), 0-20cm, 0-30cm, 0-100cm, and 0-150+cm (full reported soil depth). Zero cm represents the soil surface.The map unit average National Commodity Crop Productivity Index (NCCPI) values (low index values indicate low productivity and high index values indicate high productivity) are provided for major earthy components. NCCPI values are included for corn/soybeans, small grains, and cotton crops. Of these crops, the highest overall NCCPI value is also identified. Earthy components are those soil series or higher level taxa components that can support crop growth. Major components are those soil components where the majorcompflag = 'Yes' in the SSURGO component table. A map unit percent composition for earthy major components is provided. See Dobos, R. R., H. R. Sinclair, Jr, and M. P. Robotham. 2012. National Commodity Crop Productivity Index (NCCPI) User Guide, Version 2. USDA-NRCS. Available at: ftp://ftp-fc.sc.egov.usda.gov/NSSC/NCCPI/NCCPI_user_guide.pdfThe map unit average root zone depth values for commodity crops are given in centimeters for major earthy components. Criteria for root-limiting soil depth include: presence of hard bedrock, soft bedrock, a fragipan, a duripan, sulfuric material, a dense layer, a layer having a pH of less than 3.5, or a layer having an electrical conductivity of more than 12 within the component soil profile. If no root-restricting zone is identified, a depth of 150 cm is used to approximate the root zone depth (Dobos et al., 2012). The map unit average available water storage within the root zone depth for major earthy components value is given in millimeters.Drought vulnerable soil landscapes comprise those map units that have available water storage within the root zone for commodity crops that is less than or equal to 6 inches (152 mm) expressed as "1" for a drought vulnerable soil landscape map unit or "0" for a nondroughty soil landscape map unit or NULL for miscellaneous areas (includes water bodies).The potential wetland soil landscapes (PWSL version 1) information is given as the percentage of the map unit (all components) that meet the criteria for a potential wetland soil landscape. See table column (field) description for criteria details. If water was determined to account for 80 or greater percent of a map unit, a value of 999 was used to indicate a water body. This is not a perfect solution, but is helpful to identifying a general water body class for mapping.The map unit sum of the component percentage representative values is also provided as useful metadata. For all valu table columns, NULL values are presented where data are incomplete or not available. How NoData or NULL values and incomplete data were handled during VALU table SOC and AWS calculations:The gSSURGO calculations for SOC and AWS as reported in the VALU table use the following data checking and summarization rules. The guiding principle was to only use the official data in the SSURGO database, and not to make assumptions in case there were some data entry errors. However, there were a few exceptions to this principle if there was a good reason for a Null value in a critical variable, or to accommodate the data coding conventions used in some soil surveys.Horizon depths considerations:If the depth to the top of the surface horizon was missing, but otherwise the horizon depths were all okay, then the depth to the top of the surface horizon (hzdept_r) was set to zero.If the depth to the bottom of the last horizon was missing, and the horizon represented bedrock or had missing bulk density, the depth to the bottom was set to equal to the depth to the top of the same horizon (hzdepb_r = hzdept_r), effectively giving the horizon zero thickness (and thus zero SOC or AWS), but not blocking calculation of other horizons in the profile due to horizon depth errors.Other types of horizon depth errors were considered uncorrectable, and led to all horizon depths for the component being set to a NoData value, effectively eliminating the component from the analysis. The errors included gaps or overlaps in the horizon depths of the soil profile, other cases of missing data for horizon depths, including missing data for the bottom depth of the last horizon if the soil texture information did not indicate bedrock and a bulk density value was coded. The SOC or AWS values were effectively set to zero for components eliminated in this way, so the values at the map unit level could be an underestimate for some soils.Horizon rock fragment considerations:Part of the algorithm for calculating the SOC requires finding the volume of soil that is not rock. This requires three SSURGO variables that indicate rock fragments (fraggt10_r, frag3to10_r, and sieveno10_r). If the soil is not organic, and any of these are missing, then the ratio of the volume of soil fines to the total soil volume was set to “NoData†, and the SOC results were coded as “NoData†and effectively set to zero for the horizon. If the soil is organic, then it may be logical that no measurement of rock fragments was made, and default values for the “zero rock†situation was assumed for these variables (i.e., fraggt10_r = 0, frag3to10_r = 0, sieveno10_r = 100). Organic soils were identified by an “O†in the horizon designator or the texture code represented “Peat†, “Muck†or “Decomposed Plant Material†. If all three of the fragment variables were present, but indicated more than 100% rock, then 100% rock was assumed (zero volume of soil and thus zero for SOC). The rock fragment variables do not influence the AWS calculation because rock content is already accounted for in the available water capacity (awc_r) variable at the horizon level.Horizon to component summary:To summarize data from the horizon level to the component level, the evaluation proceeded downward from the surface. If a valid value for AWS could not be calculated for any horizon, then the result for that horizon and all deeper horizons was set to NoData. The same rule was separately applied to the SOC calculation, so it was possible to have results for SOC but not AWS, or vice versa.Component to mapunit summary:To summarize data from the component level to the map unit level, the component percentages must be valid. There are tests both of the individual component percentage (comppct_r) data, and also of the sum of the component percentages at the map unit level (mu_sum_comppct_r). For the gSSURGO VALU table, the following rules were applied for the individual components: 1) The comppct_r must be in the range from 0 to 100, inclusive. 2) Individual components with a comppct_r that was Null (nothing coded) were ignored. A zero comppct_r value excludes

This dataset is called the Gridded SSURGO (gSSURGO) Database and is derived from the Soil Survey Geographic (SSURGO) Database. SSURGO is generally the most detailed level of soil geographic data developed by the National Cooperative Soil Survey (NCSS) in accordance with NCSS mapping standards. The tabular data represent the soil attributes, and are derived from properties and characteristics stored in the National Soil Information System (NASIS). The gSSURGO data were prepared by merging traditional SSURGO digital vector map and tabular data into State-wide extents, and adding a State-wide gridded map layer derived from the vector, plus a new value added look up (valu) table containing "ready to map" attributes. The gridded map layer is offered in an ArcGIS file geodatabase raster format. The raster and vector map data have a State-wide extent. The raster map data have a 10 meter cell size that approximates the vector polygons in an Albers Equal Area projection. Each cell (and polygon) is linked to a map unit identifier called the map unit key. A unique map unit key is used to link to raster cells and polygons to attribute tables, including the new value added look up (valu) table that contains additional derived data. The value added look up (valu) table contains attribute data summarized to the map unit level using best practice generalization methods intended to meet the needs of most users. The generalization methods include map unit component weighted averages and percent of the map unit meeting a given criteria. Resources in this dataset:Resource Title: gSSURGO downloads Page. File Name: Web Page, url: https://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/survey/geo/?cid=nrcs142p2_053628#value Download gSSURGO Databases

Other resources include introduction to gSSURGO, User Guide (PDF; 4.22 MB), SSURGO/gSSURGO ArcTools, Valu1 (Value Added Look Up) Table, Metadata, Recommended Data Citations, Technical Information, Sample gSSURGO Map Themes

[Metadata] This dataset (SF) is called the Gridded SSURGO (gSSURGO) Database and is derived from the Soil Survey Geographic (SSURGO) Database. Source: U.S. Department of Agriculture, Natural Resources Conservation Service, 2016.For additional information, please refer to metadata at: https://files.hawaii.gov/dbedt/op/gis/data/soils.pdf.Note: Downloaded from https://datagateway.nrcs.usda.gov, 2016For additional tables and more information, visit the following pages:https://websoilsurvey.sc.egov.usda.gov/App/WebSoilSurvey.aspx (choose Download Soils Data tab, State = Hawaii - from here, you can download all shapefiles and tabular data for each county).Tables and columns metadata:https://www.nrcs.usda.gov/wps/portal/nrcs/detail/national/soils/?cid=nrcs142p2_053631For additional information, please contact the Hawaii Statewide GIS Program at gis@hawaii.gov.

The gridded National Soil Survey Geographic Database (gNATSGO) is a USDA-NRCS (Natural Resources Conservation Service) Soil & Plant Science Division (SPSD) composite ESRI file geodatabase that provides complete coverage of the best available soils information for all areas of the United States and Island Territories. It was created by combining data from the Soil Survey Geographic Database (SSURGO), State Soil Geographic Database (STATSGO2), and Raster Soil Survey Databases (RSS) into a single seamless ESRI file geodatabase. The gNATSGO database contains a 10-meter raster of the soil map units and 70 related tables of soil properties and interpretations. It is designed to work with the SPSD gSSURGO ArcTools. Users can create full coverage thematic maps and grids of soil properties and interpretations for large geographic areas, such as the extent of a State or the conterminous United States. SSURGO is the SPSD flagship soils database that has over 100 years of field-validated detailed soil mapping data. SSURGO contains soils information for more than 90 percent of the United States and island territories, but unmapped land remains. The current completion status of SSURGO mapping is displayed (PDF). STATSGO2 is a general soil map that has soils data for all of the United States and island territories, but the data is not as detailed as the SSURGO data. The Raster Soil Surveys (RSSs) are the next generation soil survey databases developed using advanced digital soil mapping methods. The first version of gNATSGO was created in 2019. It is composed primarily of SSURGO data, but STATSGO2 data was used to fill in the gaps. Three RSSs have been published as of 2019. These were merged into the gNATSGO after combining the SSURGO and STATSGO2 data. The extent of RSS is expected to increase in the coming years. Resources in this dataset:Resource Title: Website Pointer for Gridded National Soil Survey Geographic Database (gNATSGO). File Name: Web Page, url: https://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/survey/geo/?cid=nrcseprd1464625 The gNATSGO website provides an Overview slide presentation, Download links for gNATSGO databases (CONUS or States), ArcTools, Metadata, Technical Information, and Recommended Data Citations.

When rain falls over land a portion of it runs off into stream channels and storm water systems while the remainder is absorbed into the soil or returns to the atmosphere directly through evaporation.Physical properties of soil affect the rate that water is absorbed and the amount of runoff produced by a storm. Hydrologic soil group provides an index of the rate that water infiltrates a soil and is an input to rainfall-runoff models that are used to predict potential stream flow.For more information on using hydrologic soil group in hydrologic modeling see the publication Urban Hydrology for Small Watersheds (Natural Resources Conservation Service, United States Department of Agriculture, Technical Release–55).Dataset SummaryThis layer provides access to an image service with a cell size of 30 meters. It is derived from the 2014 version of the gSSURGO 30m raster (contiguous 48 States and Washington D.C.) and 10m raster (all other regions) produced by the Natural Resources Conservation Service (NRCS). The value for hydrologic soil group was derived from the gSSURGO Map Unit Aggregate Attribute table field Hydrologic Group - Dominant Conditions (hydgrpdcd).This 30m resolution layer covers most of the continental United States, portions of Alaska, and Hawaii, Puerto Rico, the U.S. Virgin Islands, and several Pacific Islands including Guam and Saipan. The layer was created from the 2014 SSURGO snapshot.The seven classes of hydrologic soil group are:Group A soils have a high infiltration rate and low runoff. These soils consist of deep, well drained sands or gravelly sands and have a high rate of water transmission.Group B soils have a moderate infiltration rate. This group consists chiefly of deep well drained soils with a moderately fine to moderately coarse texture and a moderate rate of water transmission.Group C soils have a slow infiltration rate. This group consists of soils with a layer that impedes the downward movement of water or fine textured soils and a slow rate of water transmission.Group D soils have a very slow infiltration rate and high runoff potential. This group is composed of clays that have a high shrink-swell potential, soils with a high water table, soils that have a claypan or clay layer at or near the surface, and soils that are shallow over nearly impervious material. These soils have a very slow rate of water transmission.If a soil is placed in group D because of a high water table it may be assigned to a dual hydrologic group: A/D, B/D, or C/D. The first letter of the pair represents the soil’s group if drained and the D represents the natural condition.For more information on soil hydrologic groups see the Natural Resources Conservation Service's National Engineering Handbook.The original gSSURGO dataset is available from the NRCS’s Geospatial Data Gateway.Link to source metadata

[Metadata] This feature class represents the special soil features that are delineated as one or more points. Downloaded statewide dataset from USDA/NRCS (https://www.nrcs.usda.gov/resources/data-and-reports/gridded-soil-survey-geographic-gssurgo-database) 11/28/23. It is generally the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The features are linked to attributes in the featdesc attribute table. The map data are in a state-wide extent format.

For more information, see metadata at https://files.hawaii.gov/dbedt/op/gis/data/soils.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

[Metadata] Hawaii Digital Soil Survey special soil feature lines for the State of Hawaii. Downloaded statewide dataset from USDA/NRCS (https://www.nrcs.usda.gov/resources/data-and-reports/gridded-soil-survey-geographic-gssurgo-database) 11/28/23. This feature class represents the special soil features that are delineated as one or more lines. It is generally the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The features are linked to attributes in the featdesc attribute table. The map data are in a state-wide extent format.For more information, see metadata at https://files.hawaii.gov/dbedt/op/gis/data/soils.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

This is a MD iMAP hosted service layer. Find more information at http://imap.maryland.gov. This data layer is a compilation of the MUPOLYGON feature class - muaggatt table and component table of the Gridded Soil Survey Geographic (gSSURGO) Database for Maryland. United States Department of Agriculture - Natural Resources Conservation Service. Under the direction of the Watershed Resources Registry (WRR) Technical Advisory Committee (TAC) this data has been altered from its original state. A reclassification of the hydric classification field was performed which classifies all soil map units consisting of less that 40% total hydric soils as not hydric - all soil map units from 41% - 79% as partially hydric and all soil map units 80% and greater as hydric. This reclassification was performed to provide a more refined input for modeling purposes. A full version of this database is available at: http://datagateway.nrcs.usda.gov/. Last Updated: 01/15/2014 Feature Service Layer Link: https://mdgeodata.md.gov/imap/rest/services/Geoscientific/MD_Geology/MapServer ADDITIONAL LICENSE TERMS: The Spatial Data and the information therein (collectively "the Data") is provided "as is" without warranty of any kind either expressed implied or statutory. The user assumes the entire risk as to quality and performance of the Data. No guarantee of accuracy is granted nor is any responsibility for reliance thereon assumed. In no event shall the State of Maryland be liable for direct indirect incidental consequential or special damages of any kind. The State of Maryland does not accept liability for any damages or misrepresentation caused by inaccuracies in the Data or as a result to changes to the Data nor is there responsibility assumed to maintain the Data in any manner or form. The Data can be freely distributed as long as the metadata entry is not modified or deleted. Any data derived from the Data must acknowledge the State of Maryland in the metadata.

[Metadata] Hawaii Digital Soil Survey polygons for the State of Hawaii. Downloaded statewide dataset from USDA/NRCS (https://www.nrcs.usda.gov/resources/data-and-reports/gridded-soil-survey-geographic-gssurgo-database) 11/28/23. This dataset is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information.This dataset consists of georeferenced digital map data and computerized attribute data. The map data are in a state-wide extent format and include a detailed, field verified inventory of soils and miscellaneous areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties.For more information, see metadata at https://files.hawaii.gov/dbedt/op/gis/data/soils.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

Input data, executable computer program, output data, and metadata of a Soil-Water-Balance (SWB) model for the Glacial Ridge National Wildlife area, northwestern Minnesota during the years 2002 through 2015. Also included is a data set of selected hourly precipitation totals for six ditch basins used in HEC/HMS ditch-flow modelling in the the Glacial Ridge National Wildlife area, 2004–2006 and 2013–2015 described in the associated report. A soil-water balance model (SWB) was developed to estimate evapotranspiration in six ditch basins of the Glacial Ridge National Wildlife Refuge area, northwestern Minnesota, during 2002–2015. The model was used to estimate evapotranspiration in water balances in six ditch basins as part of the associated report, U.S. Geological Survey Scientific Investigations Report 2019-5041 (http://dx.doi.org/10.3133/SIR20195041). This SWB model was derived from the statewide Minnesota SWB potential recharge model, described, calibrated, and documented as part of U.S. Geological Survey Scientific Investigations Report 2015-5038 (http://dx.doi.org/10.3133/sir20155038). The data sets and calibrations from the Minnesota statewide model were used without modification except for the more detailed precipitation, water capacity, and land use input data. In this model, precipitation data were interpolated from local raingages. Water capacity data were taken from the gSSURGO soils data base. Land-use data were compiled from three sources using the most detailed data: the National Land Cover Database, the Cropland Data Layer and data from the local Natural Resources Conservation Service office. Details of the procedures used to produce these three detailed data sets can be found in U.S. Geological Survey Scientific Investigations Report 2019-5041 (http://dx.doi.org/10.3133/SIR20195041). This model was not recalibrated. All calibrated parameters remain the same as those in the statewide Minnesota SWB model. The areal resolution of this model was increased to a 60-meter square grid and the temporal period was extended through 2015 relative to the statewide SWB model. Daymet (version 2) daily surface temperature data necessary to run this SWB model are available upon request through the following link: https://doi.org/10.3334/ORNLDAAC/1219.