Managing Global Resources for a Secure Future

2017 Annual Meeting | Oct. 22-25 | Tampa, FL

199-5 Predicting Saturated Hydraulic Conductivity Values in a Soil Profile from Various Estimates of Critical Pore Diameter.

See more from this Division: SSSA Division: Soil Physics and Hydrology
See more from this Session: Estimating Soil Physical Properties

Tuesday, October 24, 2017: 10:30 AM
Tampa Convention Center, Room 21

Mingming Qin, Environmental Sciences, Rutgers University, New Brunswick, NJ, Daniel Gimenez, Department of Environmental Sciences, Rutgers University, New Brunswick, NJ and Daniel Hirmas, 1475 Jayhawk Blvd., Lindley Hall Room 415A, University of Kansas, Lawrence, KS
Abstract:
Percolation theory has been successfully applied to the prediction of saturated hydraulic conductivity (Ks). Critical pore diameter (Rc), defined as the largest constriction or throat diameter among all pores traversing both ends of a sample (connected paths), is a crucial parameter in the theory. Application of percolation models of Ks has been boosted by the availability of Micro-CT instruments, which allows the measurement of Rc. One drawback to the Micro-CT technique is that it often requires ex-situ samples with diameters limited to a few centimeters. However, a recently developed technique known as multistripe laser triangulation (MLT) scanning has been used in-situ to successfully quantify soil structure and macropore networks on vertical excavation walls. This method has the potential to provide Rc values that are more representative of field conditions. The goal of this study was to apply percolation theory to the prediction of Ks in six horizons of a Grundy silt loam soil profile in northeastern Kansas. A 1-m soil profile was scanned with the MLT technique to obtain information on soil structure and macropore networks. Soil samples were collected from each horizon to measure particle-size distribution (PSD), bulk density, and water retention. In addition, water retention curves and Ks values of each horizon within a lysimeter adjacent to the scanned soil profile were optimized by fitting measured water content data using a Markov chain Monte Carlo technique in combination with the mobile-immobile water (MIM) model in HYDRUS-1D. Critical pore diameters (Rc) were calculated from optimized Ks values and estimated from PSD and water retention data, and MLT images. The values of Rc obtained by the different techniques will be discussed in the context of predicting Ks at the field/profile scale with percolation theory.

See more from this Division: SSSA Division: Soil Physics and Hydrology
See more from this Session: Estimating Soil Physical Properties