|GHANBARIAN, BEHZAD - Kansas State University|
Submitted to: Soil Science Society of America Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/30/2021
Publication Date: 12/11/2021
Citation: Ghanbarian, B., Skaggs, T.H. 2021. Soil water retention curve inflection point: Insight into soil structure from percolation theory. Soil Science Society of America Journal. 86(2):338-344. https://doi.org/10.1002/saj2.20360.
Interpretive Summary: Crop growth and many other ecohydrologic processes are regulated by the amount of water in the soil. A key soil physical property that affects water content is the soil "hydraulic conductivity." Hydraulic conductivity is a measure of the ease with which water flows or drains in a given soil. Knowledge of hydraulic conductivity permits better planning and management of soil-water resources. In this work, we evaluated a model for estimating soil hydraulic conductivity based on the size of certain critical pores within the soil. The model performed well in tests using data for 59 soils. The research will help engineers and scientists understand soil physical properties that affect agricultural productivity, and to identify soil and water management practices that optimize the profitability of agricultural lands.
Technical Abstract: Quantifying soil structure has been a long-standing challenge in soil physics. Among the proposed indices and parameters, slope at the inflection point of soil water retention curve has been widely used. In this short communication, we provide theoretical insights and show that under full saturation conditions, the pore-throat radius at the inflection point (rinf) is equivalent to the critical pore-throat radius within percolation theory. The inflection point, in fact, corresponds to a critical saturation (critical fraction of pore space) at which a sample-spanning cluster forms and a medium starts percolating. We discuss that rinf is theoretically linked to saturated hydraulic conductivity (Ksat), in a power-law form within the critical path analysis framework. Using 59 soil samples from the GRIZZLY database, we show that the Ksat is correlated to the rinf, although there exists scatter in the data. Interestingly, the experimental exponent 2.219 found from the Ksat–rinf data is less than 5% greater than the estimated theoretical value 2.111 determined from the average fractal dimension of the measured soil water retention curves.