Relating Quantitative Soil Structure Metrics to Saturated Hydraulic Conductivity

Abstract

Core Ideas Soil structure quantified in the field using a 3D laser scanning technique (MLT). MLT data and coefficient of linear extensibility combined into a structure metric. Soil water contents recorded at four depths in a field lysimeter and used in HYDRUS‐1D. Saturated conductivity (Ks) estimated with a Markov chain Monte Carlo approach. New metric better correlated to Ks in horizons with strong soil structure. Soil structure affects saturated hydraulic conductivity (Ks) by creating highly conductive macropores that preferentially transmit soil water. In this study, we explored the relationship between Ks and macropores in an Oxyaquic Vertic Argiudoll in northeastern Kansas. Macropores were quantified from an excavation wall using multistripe laser triangulation (MLT) scanning. Soil water contents were measured at four depths within a soil lysimeter installed within 2 m of the MLT‐scanned soil profile and adjacent to an Ameriflux tower monitoring precipitation, air temperature, and solar radiation. Selected hydraulic properties of soil horizons within the lysimeter were optimized to water content data using a Markov chain Monte Carlo technique in combination with the mobile–immobile water (MIM) model in HYDRUS‐1D. Estimates of Ks varied between 4198 cm d−1 in the A horizon and 0.6 cm d−1 in a 2Btss2 horizon with strongly expressed wedge structure. Approximately 87% of the variation in Ks was explained by the geometric mean of the widths of pores quantified with the MLT technique and modified by the coefficient of linear extensibility (COLE). The use of the COLE allows the widths of the macropores obtained under dry conditions to be approximated at saturation. Two models that predict Ks from either texture or water retention data resulted in Ks estimates that were similar to each other but significantly lower than Ks values predicted with MIM in horizons where structural pores dominate water flow. This technique shows a great deal of promise in better understanding and predicting the relationship of soil structure to water flow.