Field quantification of wetting–drying cycles to predict temporal changes of soil pore size distribution()

Wetting–drying (WD) cycles substantially influence structure related soil properties and processes. Most studies on WD effects are based on controlled cycles under laboratory conditions. Our objective was the quantification of WD cycles from field water content measurements and the analysis of their relation to the temporal drift in the soil pore size distribution. Parameters of the Kosugi hydraulic property model (r(m,Kosugi), σ(Kosugi)) were derived by inverse optimization from tension infiltrometer measurements. Spectral analysis was used to calculate WD cycle intensity, number and duration from water content time series. WD cycle intensity was the best predictor (r(2) = 0.53–0.57) for the temporal drift in median pore radius (r(m,Kosugi)) and pore radius standard deviation (σ(Kosugi)). At lower soil moisture conditions the effect of cycle intensity was reduced. A bivariate regression model was derived with WD intensity and a meteorological indicator for drying periods (ET(0), climatic water balance deficit) as predictor variables. This model showed that WD enhanced macroporosity (higher r(m,Kosugi)) while decreasing pore heterogeneity (lower σ(Kosugi)). A drying period with high cumulative values of ET(0) or a strong climatic water balance deficit on the contrary reduced r(m,Kosugi) while slightly increasing σ(Kosugi) due to higher frequency at small pore radius classes. The two parameter regression model was applied to predict the time course of soil pore size distribution parameters. The observed system dynamics was captured substantially better by the calculated values compared to a static representation with averaged hydraulic parameters. The study showed that spectral analysis is an adequate approach for the quantification of field WD pattern and that WD intensity is a key factor for the temporal dynamics of the soil pore size distribution.