In arid and semiarid areas, the availability of reliable data for water retention in relation to soil type, texture, and soil carbonate content is low. It is therefore desirable to explore the interaction between soil hydraulic properties and other physical and chemical properties to estimate the soil water retention curve (SWRC) from easily measured soil parameters. In this study, 72 soil samples were collected from rural areas throughout northwest Syria, covering most of its agroclimatic zones and soil types. Soil water content at different matric potentials and 11 chemical and physical soil properties were determined. A Pearson correlation matrix was computed on which principal component analysis was applied to three soil water contents, −1, −33, and −1500 kPa, and the 11 soil properties. Four principal components (PCs) explained 77% of the variation in the data set. The three soil water contents were highly linked to PC1, which was correlated with the plastic limit, texture, soil carbonate content, and specific surface area. In addition, the soil water content at −1 kPa was also linked to PC4, which was correlated with bulk density. Therefore, from the initial 11 soil properties, seven contributed to the three soil water contents (plastic limit, texture, soil carbonate, specific surface area, and bulk density); the remaining four (organic matter, gravel, cation exchange capacity, and hygroscopic water content) had a negligible influence. Consequently, pedotransfer functions might be estimated using the original seven, from the initial 11, soil properties or their corresponding PCs to estimate the SWRC.

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