Estimation of soil moisture using confined compression curve parameters

Abstract

The confined compression curve (CCC) represents the relationship between the logarithm of the applied stress and the void ratio. There are several similarities between the soil water retention curve (SWRC) and the CCC. The aim of this study was to modify the Dexter SWRC model to fit the experimental CCC data by replacing the matric suction and water content in the Dexter model with the normal stress and void ratio, respectively, as well as using the CCC parameters and characteristics (pre-compression stress, compression, and swelling indices) as predictors to estimate the SWRC. We collected 150 soil samples from five provinces of Iran. The SWRC, CCC, and basic properties of the soil samples (clay, silt/sand, and bulk density) were measured. The Dexter model was applied to the experimental data for both the CCC and SWRC, and their parameters were calculated. The CCC parameters and basic soil properties were used to estimate the soil moisture at five input levels with the Dexter model. The best results were obtained using the basic properties of soil as predictors, as well as with the parameters of the Dexter model obtained by its fitting to the CCC data. The integral root mean squared error was reduced from 0.059 and 0.061 (in the first step) to 0.053 and 0.056gg−1 in the training and testing steps, respectively. The relative improvements in the SWRC estimates showed that improvements of 4.9% to 11.9% were obtained by using the CCC parameters as predictors. These improved estimates can be attributed to the apparent similarities between the two curves as well as the impacts of similar factors on these curves and the correlation between them.