Comparison of three models fitting the soil water retention curves in a degraded alpine meadow region

Soil water retention curve (SWRC) plays an important role in simulating soil water movement and assessing soil water holding capacity and availability. Comparison of fitness between different models to determine the best SWRC model of specific regions is required. In this study, three popular models, van Genuchten, Brooks Corey and Gardner model, were selected for comparing in a degraded alpine meadow region on the eastern Tibetan Plateau. Fitness, error distribution along with key parameters were compared. For each soil horizon, the soil moisture content at all soil water potentials decreased consistently with degradation, thereby integrally moving the SWRCs of all soil depths downward with degradation. The differences in SWRCs across various degradation degrees diminished along with soil depth and soil water potential. The Adj.r2 values of van Genuchten, Brooks Corey and Gardner models ranged in 0.971–0.995, 0.958–0.997, and 0.688–0.909, respectively. The van Genuchten and Brooks Corey models significantly (p < 0.05) outperformed the Gardner model, and have no significant differences in fitness. The fitness of all three models showed no significant changes with degradation. Regardless of degradation degree and soil depth, the fitting error of van Genuchten and Brooks Corey models was mainly distributed in the higher (from –100 hPa to –500 hPa) and lower (below –10000 hPa) potential sections. With regard to the parameters of van Genuchten and Brooks Corey models, the field capacity (θs), and permanent wilting moisture were highly coherent with Adj.r2 values of higher than 0.98, while the curve shape parameter (θr), and air entry pressure of the Brooks Corey model were much lower than those of the van Genuchten model with Adj.r2 values of lower than 0.91. The SWRCs with varying degrees of degradation are best fitted by both van Genuchten and Brooks Corey models but cannot be fitted by Gardner model. Soil water holding capacity decreased with degradation especially in the top soil (0 cm to 30 cm), but the curve shape of all SWRCs did not change significantly with degradation.

Predicting the drying shrinkage behavior of high strength portland cement mortar under the combined influence of fine aggregate and steel micro fiber

The workability, 28-day compressive strength and free drying shrinkage of a very high strength (121-142 MPa) steel micro fiber reinforced portland cement mortar were studied under a combined influence of fine aggregate content and fiber content. The test results showed that an increase in the fine aggregate content resulted in decreases in the workability, 28-day compressive strength and drying shrinkage of mortar at a fixed fiber content. An increase in the fiber content resulted in decreases in the workability and drying shrinkage of mortar, but an increase in the 28-day compressive strength of mortar at a fixed fine aggregate content. The modified Gardner model most accurately predicted the drying shrinkage development of the high strength mortars, followed by the Ross model and the ACI 209R-92 model. The Gardner model gave the least accurate prediction for it was developed based on a database of normal strength concrete.

Effects of various input levels and different soil water retention curve models on water content estimation using different statistical methods

This study investigated the impact of different input variables on the predictability of the water content using soil water retention curve (SWRC) models. The particle and aggregate size distribution model parameters were calculated by fitting the Perrier model to the related distributions for 75 soil samples. Nine SWRC models were fitted to the experimental data and their coefficients were obtained. The regression method was used to estimate the coefficients for nine SWRC models at three input levels. Cluster analysis classified the SWRC models into more homogeneous groups according to the accuracy of their predictions. The SWRC estimated using the Gardner model had the highest accuracy, but it was not an appropriate model for the soils because of its low fitting accuracy. Boltzman, Campbell, and Fermi models obtained the highest accuracy after the Gardner model. The Durner model yielded the lowest prediction accuracy due to the lack of correlation between the input variables and coefficients in this model. Thus, the water content predictions obtained using different SWRC models varied because different input variables were employed.

The Development of a One-Parameter Model for the Soil-Water Characteristic Curve in Loess Gully Regions

It is important to understand soil hydraulic properties in order to predict the movement of water and solutes such as pollutants. To this end, 55 soil samples were collected from different areas of the Nanxiaohegou basin and used to generate soil-water characteristic curves. These were then fitted using the power-, exponential-, and logarithmic versions of the Gardner model; the logarithmic model yielded the best fit overall. The logarithmic model was further simplified to yield a one-parameter model for estimating the soil-water characteristic curve within the basin, and it was demonstrated that the value of the single parameter is dependent on the topography and usage of the land.