The study compared different models that predict soil moisture levels based on soil texture. They found that the Mironov model was the most accurate overall, especially for L-band microwave remote sensing. However, the Dobson model performed best in soils with high silt content. The study used root mean square error and linear correlation coefficient to evaluate the models' accuracy.