Evaluating a rapid approach for estimating soil hydraulic conductivity function from near-surface infiltration measurements

Accurate estimation of the soil hydraulic conductivity function (SHCF), which describes the relationship between hydraulic conductivity and matric suction in soil, is essential for modeling flow and transport processes in the vadose zone. Traditional steady-state methods for directly determining SHCF are often laborious, time-consuming, and sometimes inadequate for capturing transient-state flow conditions. This study aims to propose a simple, quick, and accurate method for estimating SHCF that facilitates transient-state flow analysis during vadose zone modeling. The proposed method involves inverse numerical modeling using cumulative infiltration and final moisture content data from surface infiltration tests conducted with a handy mini disc infiltrometer (MDI). To validate this approach, the MDI-inverse modeling results were compared with SHCF results from another transient-state method, the instantaneous profile method (IPM), under similar initial soil conditions. The MDI infiltration tests were performed in homogeneously packed soil columns for two soils (identified as loam and silty clay loam textures) collected from nearby field sites. For each soil, separate IPM tests were conducted in soil columns equipped with soil moisture and matric suction sensors at various depths to facilitate calculation of reference SHCF. A comparison between the MDI and reference IPM results revealed a good agreement, with a low normalized RMSE (under 15%) for the estimated SHCFs and a low relative error (under 35%) for the optimized van Genuchten parameters α and n. The findings indicate that MDI-based cumulative infiltration measurements can reliably estimate SHCF via inverse simulation, providing a practical solution for field applications where traditional sensor deployment is challenging. Moreover, the results also establish MDI as a rapid, convenient, and non-invasive tool for determining SHCF for transient-state flow scenarios.