Soil Water Characteristic Estimates by Texture and Organic Matter for Hydrologic Solutions

Abstract

Hydrologic analyses often involve the evaluation of soil water infiltration, conductivity, storage, and plant-water relationships. To define the hydrologic soil water effects requires estimating soil water characteristics for water potential and hydraulic conductivity using soil variables such as texture, organic matter (OM), and structure. Field or laboratory measurements are difficult, costly, and often impractical for many hydrologic analyses. Statistical correlations between soil texture, soil water potential, and hydraulic conductivity can provide estimates sufficiently accurate for many analyses and decisions. This study developed new soil water characteristic equations from the currently available USDA soil database using only the readily available variables of soil texture and OM. These equations are similar to those previously reported by Saxton et al. but include more variables and application range. They were combined with previously reported relationships for tensions and conductivities and the effects of density, gravel, and salinity to form a comprehensive predictive system of soil water characteristics for agricultural water management and hydrologic analyses. Verification was performed using independent data sets for a wide range of soil textures. The predictive system was programmed for a graphical computerized model to provide easy application and rapid solutions and is available at http://hydrolab.arsusda. gov/soilwater/Index.htm.

Modeling soil organic carbon in corn ( Zea mays L.)-based systems in Ohio under climate change

“…These expectations held true for Wooster, but not for Hoytville. Clay affects both the water holding capacity (Williams et al 1983;Saxton and Rawls 2006) and the proportion of CO 2 evolved to biomass and humus formed (Jenkinson et al 1987;Coleman and Jenkinson 2014). In general, soils with higher clay build up slightly more SOC than those with lower clay, and this could explain the overall difference in TOC content between the sites.…”

Visual drainage assessment: A standardised visual soil assessment method for use in land drainage design in Ireland

“…The topsoil was not sampled. From this soil texture data, saturated hydraulic conductivity (k s ) equivalents were determined (Saxton and Rawls, 2006), assuming a soil organic matter content of 2.5 % (by weight). The pits were then photographed before backfilling.…”

“…The pits were then photographed before backfilling. In order to assess the validity of the VDA permeability classification, VDA assigned permeability classes were compared with the estimated k s (Saxton and Rawls, 2006) of soil samples collected at a comparable depth. Data were analysed using ANOVA with VDA permeability classification as a fixed effect.…”

Improving soil organic carbon parameterization of land surface model for cold regions in the Northeastern Tibetan Plateau, China

“…Because of the thermal and hydraulic properties of SOC are very different from mineral soil, the influences of SOC on LSMs soil moisture simulation should be well considered in this area (Yang et al, 2009). On the one hand, increased organic content generally produces a soil with increased water holding capacity and conductivity, largely as a result of its influence on soil water content (Manns and Berg, 2014;Saxton and Rawls, 2006). On the other hand, organic material acts as an insulator, with low thermal conductivity and relatively high heat capacity modulating the transfer of energy down into the soil during spring and summer and out of the soil during fall and winter, further effecting soil temperature and water properties (Bonan, 1989;Lawrence et al, 2012).…”