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A Comprehensive Model for Single Ring Infiltration II: Estimating Field‐Saturated Hydraulic Conductivity
Author(s) -
Stewart Ryan D.,
Abou Najm Majdi R.
Publication year - 2018
Publication title -
soil science society of america journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.836
H-Index - 168
eISSN - 1435-0661
pISSN - 0361-5995
DOI - 10.2136/sssaj2017.09.0314
Subject(s) - hydraulic conductivity , infiltration (hvac) , capillary action , soil science , conductivity , mathematics , soil water , environmental science , chemistry , physics , thermodynamics
Core Ideas Four approaches were tested to estimate K fs from single ring infiltration data. Highest accuracy occurred when capillary length was appropriately constrained. K fs estimates improved if capillary length was overestimated vs. underestimated. Assuming a universal capillary length can also be useful for determining K fs . K fs can be accurately estimated using both early‐time and steady‐state data. In this study, we explored four approaches to infer field‐saturated hydraulic conductivity ( K fs ) from both early‐time and steady‐state infiltration measurements using an explicit expression for three‐dimensional flow. All approaches required an estimate of the soil capillary length, λ. Approach 1 estimated K fs via optimization, in which all other infiltration parameters (9 in total) were known. The remaining approaches constrained λ through different interpretations of coefficients generated by linear regression between infiltration and time. Approach 2 utilized these coefficients plus estimated soil water content to simultaneously quantify both λ and K fs . Approach 3 used an analytical expression in which λ was estimated based on water retention/unsaturated hydraulic conductivity parameters, while Approach 4 adopted a universal λ value of 15 cm. The accuracy of these four approaches were tested using numerical and laboratory infiltration data. Approach 1 had the highest accuracy but also required the most auxiliary data, making it most suitable for laboratory and numerical experiments. Approach 2 was the least consistent, providing negative estimates for λ and K fs under certain conditions. Approach 3 also gave accurate predictions of K fs , but may be inaccurate in instances where the water retention model parameters are uncertain or do not describe soil hydraulic behaviors well. Approach 4 provided reasonable estimates of K fs (within a factor of three from the actual value in most cases), while not requiring additional observational data. The optimal approach for interpreting K fs will thus vary depending on the type and quality of available auxiliary data.