Soil hydraulic property maps for the contiguous United States at 100-m resolution and seven depths: Code design and preliminary results

Estimates of the van Genuchten (1980, abbreviated as VG) parameters and saturated hydraulic conductivity (Ks) were made for the contiguous United States at a resolution of 100 m and seven soil depths by combining the SoilGrids+ (SG+) soil property maps of Ramcharan et al. with the R3H3 member of the Rosetta3 hierarchical pedotransfer functions (PTFs) of Zhang et al. To this end, we developed multi-threaded code that significantly speeds up computation (up to a factor 25) depending on the level of parallelism. We verified estimates first by calculating simple summary statistics of estimated basic properties of SG+ with actual measured soil properties for 14,113 pedons in the National Cooperative Soil Survey (NCSS) (2023) labsample database. Next, we computed summary statistics of PTF-estimated moisture contents for NCSS and SG+ data. The results show estimation errors are dominated by intrinsic errors of the PTF, and that (potentially correctable) systematic errors are present in SG+ soil properties and PTF estimates. The resulting hydraulic property maps contain well over 750 million points for each of the seven layers and show considerable horizontal and depth variation for each VG parameter and Ks, except the VG "n" parameter, which is dominated by values between 1.25 and 1.6. The hydraulic property maps are 99.9% complete, and we demonstrate that plausible profiles and uncertainty information can be generated for virtually each point. The maps are available as two multi-channel GeoTIFF maps per SG+ layer: one with the five hydraulic parameters and one with the corresponding covariances. van Genuchten parameters and saturated hydraulic conductivity were estimated for the contiguous United States and seven depths. Retention estimates were verified with National Cooperative Soil Survey soil data and analyzed for systematic errors. Parallelized code was developed to speedup future repeat analyses. Uncertainty in hydraulic characteristics can be expressed individually for every point. Data available as GeoTIFF files at 100-m resolution, two files (parameters and covariances) for each depth. Soil hydraulic properties are needed to calculate the infiltration of water into soils and to estimate flooding potential. Such properties can be measured in the laboratory which is usually an expensive and labor-intensive task. Pedoytransfer functions are statistical methods that can estimate soil hydraulic properties from primary soil properties such as soil texture and bulk density. Recently, maps of primary properties were published for the contiguous United States at a resolution of 100 m. The present work applies artificial neural network pedotransfer functions to these maps and evaluates the accuracy of the estimates by soil depth and other criteria. The results are encouraging with some suggestions for future improvements. The developed code and estimated data are publicly available.