Prediction of the soil water retention curve for structured soil from saturation to oven‐dryness

Abstract

The soil water retention curve (SWRC) is the most fundamental soil hydraulic function required for modelling soil–plant–atmospheric water flow and transport processes. The SWRC is intimately linked to the distribution of the size of pores, the composition of the solid phase and the soil specific surface area. Detailed measurement of the SWRC is impractical in many cases because of the excessively long equilibration times inherent to most standard methods, especially for fine textured soil. Consequently, it is more efficient to predict the SWRC based on easy‐to‐measure basic soil properties. In this research we evaluated a new two‐stage approach developed recently to predict the SWRC based on measurements for disturbed repacked soil samples. Our study involved undisturbed structured soil and took into account the effects of bulk density, organic matter content and particle‐size distribution. Independently measured SWRCs for 171 undisturbed soil samples with organic matter contents that ranged from 3 to 14% were used for model validation. The results indicate that consideration of the silt and organic matter fractions, in addition to the clay fraction, improved predictions for the dry‐end SWRC. The dry‐end results revealed that the smallest matric potential at hypothetical ‘zero‐water‐content’ varies between −45 000 and −125 000 m (pF 6.65–7.1) even for soils with similar clay mineralogy. The sensitivity analysis of the two‐stage approach indicated that predicted SWRC results are more sensitive to bulk density than to organic matter content or soil texture. For the soils studied, the two‐stage approach showed reasonable agreement with measured data, with a root mean square error of 0.04 cm3 cm−3 for the matric potential range from pF 1 to pF 6.6. Highlights Is a new approach to modelling the soil water retention (SWR) curve applicable to structured soil? The model accurately predicts the full SWR curve with an RMSE of 0.04 cm3 cm−3. Prediction accuracy of the wet part of the SWR curve was sensitive to variation in bulk density. The pF at zero water content, which affects the prediction of dry SWR, ranged from 6.65 to 7.10.

Comparing Visible–Near‐Infrared Spectroscopy and a Pedotransfer Function for Predicting the Dry Region of the Soil‐Water Retention Curve

“…A number of studies used a constant value at pF 0 ( W = 0, pF 0 ) of 6.7 to 7.1 (Ross et al, 1991; Rossi and Nimmo, 1994; Fayer and Simmons, 1995; Webb, 2000; Groenevelt and Grant, 2004; Schneider and Goss, 2012; Arthur et al, 2013). Since studies have shown that pF 0 can be variable depending on the clay mineralogy or cation exchange capacity (Lu and Khorshidi, 2015; Karup et al, 2017), we anchored the CS function instead at the gravimetric soil water content at −10 6 cm H 2 O ( W 6 , pF = 6). Consequently, the two parameters in the CS function became W 6 and α, and therefore, the modified CS function can be expressed as …”

“…During the last decades, many researchers have developed functions to predict the dry‐end SWRC using basic soil properties (e.g., clay content). Karup et al (2017) predicted the water content at −10 6 cm H 2 O (log 10 |−10 6 | = pF 6) using the clay content, organic matter, and silt fraction as well as the bulk density coupled with the assumption of linearity between pF 4.2 and pF 6.9. Schneider and Goss (2012), based on 18 samples, showed that the dry end of the SWRC can be successfully predicted from a PTF based on clay content.…”

Monitoring soil moisture dynamics in multilayered Fluvisols

“…These contradictory results may be rooted in the uncertainties in water dynamics. Water dynamics and water retention curves can be obtained from arduous measurements (Várallyay és Rajkai 1987), pedotransfer functions (Rajkai and Kabos 1999;Makó et al 2010;Tóth et al 2015;Karup et al 2016;Gohardoust et al 2017) or numeric models, e.g. the RETention Curve computer program (RETC) (van Genuchten et al 1991).…”

Multi-scale effects on the hydraulic behaviour of a root-permeated and compacted soil

“…Processes such as roots shrinkage and exudation on drying have been characterised by imaging techniques or soil physical-chemical analyses [6][7][8][9][10] and are inducing counterposed effects on soil:…”