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Particle-size distribution (PSD), especially clay content, is an important physical property of soil because of its large influence on soil hydrological characteristics, salinity, fertility, erodibility, nutrient content, swelling/shrinking, and degradation. The authors present a case study of soil PSD and its relationship with soil-water content (SWC) in a gravel-mulched field in an arid area of northwestern China using a statistical regression model and Pearson correlation coefficients. The SWC was correlated with clay content, and both increased with soil depth, with correlation coefficients ranging from 0.901 to 0.972. The regression analysis of clay content and SWC from various depths used the least-squares method, and the predictive accuracies of the regression models were evaluated with the data for measured clay content. Both the mean error and root mean square error were low and the prediction accuracy was high. The SWCs were significantly positively correlated between soil layers, with all correlation coefficients greater than 0.989, indicating that the SWC in a specific layer could be well estimated by the SWC in the adjacent subsoil. Clay content can thus be predicted from measured SWC, and can be further used to evaluate soil quality and productivity. This study also provides a theoretical reference for the prevention of salinization, the adjustment of land use and agricultural production, and the conservation of soil and water. (C) 2017 American Society of Civil Engineers.