|Ahuja, Laj - GREAT PLAINS SYS RES LAB|
|Pachepsky, Ya - DUKE UNIVERSITY|
|Williams, Robert - GRAZING LANDS RES CENTER|
Submitted to: Soil Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: February 4, 1999
Publication Date: N/A
Interpretive Summary: Understanding of the process of water infiltration into soil is important to be able to predict soil erosion, runoff of water and chemicals from soil, water availability to plants, movement of chemicals to groundwater, salt leaching, and groundwater recharge. An important soil parameter is the conductivity of soil to water, the soil hydraulic conductivity. Researchers and agricultural managers who need to be able to predict infiltration must have estimates of hydraulic conductivity including the range of values they can expect. Unfortunately, soil hydraulic conductivity can be very expensive to measure. This research describes an improved method to estimated saturated hydraulic conductivity using soil porosity, an easily measured soil property, and an index of soil pore size distribution. The soil pore size distribution can be easily estimated from soil survey data. This improved method of estimating soil hydraulic conductivity will make it easier for agricultural managers to obtain realistic values of hydraulic conductivity in order to predict infiltration.
Technical Abstract: Effective porosity (defined here as the difference between satiated total porosity (saturated water content) and water filled porosity at a matric potential of 33 kPa) has been shown to be a good predictor for saturated hydraulic conductivity (Ks) using a modified Kozeny-Carman equation. The purpose of this study was to improve the predictive capability of the modified Kozeny-Carman equation by including information from moisture release curves (soil water content vs matric potential relation). We fitted the Brooks-Corey (B-C) equation parameters to moisture release data from a large database (>500 samples) of soils of data from the Southeastern United States. Values of Ks were also available from the same source. The B-C parameters were the pore size distribution factor and air entry potential. The pore size distribution factor was strongly correlated with effective porosity and with Ks. As a result, inclusion of the pore interaction factor into the Kozeny-Carman equation improved the Ks estimation over using only effective porosity. The improvement came through a better estimation of large values of Ks. Using pore interaction factors and air entry potentials averaged by textural class, and from an equation as a function of these two variables. A constant value of n=2.5 was used for the exponent. Values of Ks calculated using this new independent equation were comparable to values calculated by fitting the slope and exponent of the Kozeny-Carman equation to the Southern Region data. The advantage of the proposed method is that no parameters were fit using the data set from which predicted and measured values were compared.