Estimation of soil water characteristic curve parameters in different models in light soils

In addition to soil water content, soil matric potential is also important for plant growth. Soil water characteristic curve (SWCC) or soil moisture characteristic curve describes soil water content and soil matric potential relationship. Many models have been developed to describe the SWCCs and their fitting to the experimental data. However, their fitting accuracies in different soil textures, have been rarely investigated. In this study, matric potential-moisture data of 16 soil sample of forest station in Finland use to fit SWCC models. Nine well known and frequently applied SWCC models were fitted to the measured data. The most accurate models of total soil samples, each textural group and each textural class were estimated using root mean square error (RMSE), coefficient of determination (R2) and mean error (ME). Result showed that van Genuchten-Mualem, van Genuchten, Gardner and Brutsaert models had most accurate and Brooks and Corey model had least accurate to predict SWCC.