A database of soil physical properties for the Kansas Mesonet. Issue 6 (7th October 2022) - Parker, Nathaniel; Kluitenberg, Gerard J.; Redmond, Christopher; Patrignani, Andres
Abstract: This study developed a comprehensive database of soil physical properties to expand the potential applications of soil moisture observations across the Kansas Mesonet environmental monitoring network. The database comprises 14 site‐ and depth‐specific soil hydraulic properties for 40 stations monitoring soil water content. The measured soil hydraulic properties include sand, clay, and silt contents; bulk density; particle density; total porosity; effective saturation; saturated hydraulic conductivity; and water retention at six matric potentials. The soil database spans eight soil textural classes, with silty clay loam, silt loam, and silty clay soils dominating the fine‐textured soils, and sandy loam and sandy clay loam soils comprising the only coarse‐textured soils. All the measured soil hydraulic properties showed low coefficient of variation (CV ≤10%) within soil textural classes, except for the saturated hydraulic conductivity, which varied from a median of 0.520 ± 308 cm d –1 in the clay soils to 47.1 ± 119 cm d –1 in the sandy loam soils. The uncertainty of the Kansas Mesonet soil water content observations was reduced by at least 29% using laboratory sensor calibration equations instead of the factory default sensor equation. Our soil physical property database offers new prospects to use historical and near real‐time in situ soil water content observations across the Kansas Mesonet for diverse agricultural and hydrological applications, including drought monitoring, wildfire preparedness, and estimating potential drainage and groundwater recharge rates. Core Ideas: This study developed a comprehensive soil physical property database for the Kansas Mesonet. The database comprises 14 site‐ and depth‐specific soil hydraulic properties for 40 stations. The soil database is dominated by fine‐textured soils with 92% of the soils having >20% clay content. Laboratory sensor calibration equations reduced the uncertainty of the water content measurements by at least 29%.