Developing a Taxonomic Soil Dataset from SSURGO for Hydrological and Water Quality Modeling

The file provided has two R scripts that can be used to aggregate SSURGO map units up to their subgroup taxonomic level. The script divides the soils listed in the SSURGO data into five classes: soils having fragipan, wet soils, wet soils having fragipan, soils having shallow bedrock (lithic), and soils that do not exhibit any of these four characteristics (general).The first script, 'fun_standerdise_layers.R’ extracts the soil mukey data from 'SoilDB' R package (Beaudette et al., 2021), connects it with the SSURGO soil data obtained from the SWAT website (https://swat.tamu.edu/data/), and standardizes the soil data with uniform soil layer depths considering depth-weighted average. The second script, 'create_taxonomy_soils.R' reads this data and first classifies it into taxonomic groups and then clusters it for each of the four hydrologic group within each taxonomic group by considering similarity in soil hydraulic conductivity, soil available water capacity, soil erosivity, and soil depth. A SWAT model developed using the taxonomic data was shown to show similar nutrient and hydrologic loads when compared with a SWAT model developed using SSURGO. The parameter distribution of both the models were also found to be similar. However, the taxonomic model reduced simulation time by half, as the taxonomic dataset mitigates boundary-based discontinuity issues that arise in soil surveys when compiling the SSURGO dataset.