Estimation of Macropore Properties for No-till Soils

Abstract

Macropores contribute to rapid movement of water and solutes through the soil. Determining the size and distribution of macropore requires laborious field and/or laboratory procedures. The objective of this study was to develop methods for estimating macropore size and distribution based on more easily obtained data such as soil texture, one set of pore size, and count and/or macropore saturated hydraulic conductivity. Algorithms based on fractal geometry were developed to estimate the soil macropore properties of macropore sizes/counts, areal porosity, and/or saturated hydraulic conductivity. A database representing five soil textures under a no-till farming practice was used to develop empirical equations to calculate macropore size/count, areal porosity, and macropore conductivity based on three levels of available data. The three levels of input data are soil texture and (1) an arbitrary size (Rx) and pore count above that size (Nx); (2) a measured macropore saturated hydraulic conductivity (Kmacro); or (3) an estimated largest macropore radius (R1). The form of all regression equations were shown to be consistent with equations from fractal geometry. The developed equations were tested with independent, published macropore data and their reported variances. The verifications indicated that satisfactory estimates of macropore size/counts, areal porosity, and saturated conductivity can be made from more readily available macropore data.