A Comprehensive Model for Single Ring Infiltration II: Estimating Field‐Saturated Hydraulic Conductivity. Issue 3 (12th April 2018)

• Record Type: Journal Article
• Authors: Stewart, Ryan D.; Abou Najm, Majdi R.
• Is Part Of: Soil Science Society of America Journal. Volume 82:Issue 3(2018)
• Page Start: 558
• Page End: 567
• Publication Date: 2018-04-12
• Subjects: Soils -- United States -- Periodicals; Soil science -- Periodicals; Periodicals; 631.4973
• DOI: 10.2136/sssaj2017.09.0314
• Languages: English
• ISSNs: 0361-5995

Abstract

Abstract : 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.