SSURGO-QT - released June 1, 2022

Soil Survey Geographic Query Tool

by Paul R. Finnell, Prairie Hills Soils Consulting

Have you ever wondered where all the deep soils are in your county? Or the salt-affected soils within your state? Or soils that have layers that will restrict root growth within your regional area??The Soil Survey Geographic Query Tool, “SSURGO-QT” (www.ssurgoqt.com), is the newest web-based tool (officially released Jun 1, 2022) accessing the USDA NRCS soil survey database.?SSURGO-QT joins the Web Soil Survey (2004 Web Soil Survey - Home (usda.gov)) that was designed to replace hard copy reports with a digital report and SoilWeb (2010 SoilWeb: An Online Soil Survey Browser | California Soil Resource Lab (ucdavis.edu)) that was designed to access soils maps and data via a smartphone.?SSURGO-QT is designed to query and analyze soil survey data on a regional basis.?The USDA SSURGO database is a United States treasure valued in the billions of dollars and freely accessible to all through these and other web-based applications.?The soil survey inventory is mapped from coast to coast and border to border, digitized at scales of 1:12,000 and 1:24,000, with a massive soils database supporting the maps.?SSURGO-QT accesses the most recently certified national soil survey database using a drop-down menu system allowing the user to filter the soils data to meet their needs.?

SSURGO-QT was developed in cooperation with Stone Environmental, Inc. under a NRCS CEAP-Grazing Lands agreement.?This web-based tool was designed to group landscapes for modeling purposes, provide management-pertinent soils data for more efficient conservation planning, link research-scale data to soils data, and to aid users with identification of soil/ecological site concepts.?Data is displayed within the user selected NRCS Major Land Resource Area (MLRA), allowing the user to then select different soil physical and chemical characteristics (derived from specified depths or thicknesses in the profile) for soils that exist within the chosen MLRA. The output soil map unit component data allows the user to more efficiently group soil components for modeling, aid conservation planners, ranchers and government agencies to develop conservation and monitoring plans, and display, create or refine ecological site concepts.?Users, such as academia, engineers, researchers, agricultural industry, and reclamation specialists, will all find the ability to query and analyze soils on a regional basis to aid their programs as well.?Additionally, NRCS soil scientists will have the ability to identify and rectify the quality of the soil survey database.?Data can be viewed on screen or downloaded for further analysis in tabular and spatial formats.?The user guide can be read at: SSURGO-QT App User Guide.pdf (ssurgoqt.com).?

The home page has a simple regional interface allowing the user to identify the MLRA region of interest.?The user selects the MLRA via a choice list, or types in their MLRA selection (Figure 1).?If the user isn’t sure of the MLRA for their area of interest, an address or known location can be input and then the user can change the scale of the map until the MLRA is identifiable on the map. At that point, the MLRA needs to be entered to use the filter.

Figure 1. Initial screen upon entering the SSURGO-Query Tool online application (https://ssurgoqt.com/). Enter the desired MLRA (or choose from the dropdown list) in the left pane to begin the soil property filtering process.

The map will then focus and zoom into the MLRA chosen, and the user can begin the process of choosing soil properties of interest within the MLRA (Figure 2).?This is a key feature of this tool, and how it is unique when compared to the existing soil querying tools: the user will query data based on soil properties and characteristics of soil components important to their needs. They will not be looking at aggregated or interpreted soil mapunit data (as in Web Soil Survey).

Figure 2. The user selected MLRA 103, and the map refreshed, the soil property selection categories appeared, and now the user can filter the visible soils within MLRA 103 based on specific soil properties that are of interest.

Fourteen soil property categories are available for selection.?The visual map data is filtered with each soil property selection. The categories contain choice lists for Soil Moisture/Temperature, Surface Texture, Surface Cover of Coarse Fragments (eg, rocks), Coarse Fragments within the Top Horizon, Soil Depth, Soil Water, Hydrologic Group, Slope Class, Available Water, Chemical Characteristics, Restrictions, Diagnostic Features, Soil Component name, and Ecological site (Figure 2).?Each category has nested choice lists allowing the user to narrow their search criteria. Each selected criteria influences the choice list available in the next category – the filter is designed to be used from the top down. If the user begins at the bottom and then enters a choice from a category above, the map will update to reflect the top-most selection, and the user will have to re-enter any criteria they selected that is beneath the top-most selection. For example, choosing the Soil Water Characteristics category allows the selection of average water table depth during April to September to identify those soils that meet the criteria. After selection, the map is updated to reflect the selected choice(s) (Figure 3). The user can view the data on the MLRA scale or zoom into their area of interest.?The map will update after each additional category and choice list selection within the area of interest.

Figure 3. Here, the user selected soils with an average depth to water that is greater than 10cm and less than or equal to 20cm during any month from April through September. The map view displays the distribution of soil map units which have soil components meeting that selection criteria.

?SSURGO-QT will nest the search criteria allowing the user to tailor the map. For example, as seen below (Figures 4, 5 and 6), the user could create a map for MLRA 103 (Central Iowa and Minnesota Till Prairies) of soils with silt loam surface soil textures that are very deep?and have??surface pH ranges of 5 to 6. The user could refine the filter further to include, for instance, soil taxonomic data or simply jump to the list of soil components that meet the criteria. ?

Figure 4. User selected all soils in MLRA 103 with a silt loam surface texture, and the map displays the results (779 total records).

Figure 5. User further chooses only Very Deep silt loams in MLRA 103, and the map displays the results (757 total records).

Figure 6. User added the pH desired range (5 to 6), so the map updated to show only very deep silt loams with pH between "very strongly acid" and "moderately acid" in MLRA 103 (63 records).

The potential of SSURGO-QT is unlimited.?Conservation planners and land users now have a way to identify existing and potential concerns related to soils, and they can identify areas with a high likelihood of success when any number of conservation practices are implemented. Academia has a new tool to teach soil formation and properties on a regional scale.?Researchers have a tool to identify soil properties impacting chemical, irrigation, fertilizer, or other applications.?Ecologists can identify soil properties impacting plant communities.?Engineers can identify local and regional soil properties impacting structure design.?State and local governments can identify the soil properties and the impact soils will have on decision making.?The agricultural industry now has another tool available to identify how and where soil properties can be found when determining agricultural decisions.?The casual user has an educational tool learning about the soils in their area. And NRCS soil scientists can use this as a quality control tool to focus work to maintain the 120-year-old soil survey.?

The USDA NRCS is continually maintaining the soil survey database. ?As the NRCS Soil and Plant Sciences Division updates their work annually, there will also be an annual refresh to match the new data in SSURGO-QT (the tool currently uses SSURGO 2021 data) . ?What began in 1899 by Congress as an inventory of the farmable soils in the country has evolved into a digital product that is used for far more applications than originators ever dreamed.?SSURGO-QT is yet another web-based application that puts the power of the soil survey database into an easy-to-use format for many users.?SSURGO-QT is located at www.ssurgoqt.com.

Comments or questions can be directed to the lead developers of SSURGO-QT, Loretta Metz ([email protected]) or Carrie-Ann Houdeshell ([email protected]).