Prediction of Soil Physical Quality Index by Using Conveniently Measurable Soil Properties in Some Saline and Calcareous Soils



Soil quality has been defined as “the capacity of a soil to function within ecosystem and land use boundaries, to sustain biological productivity, maintain environmental quality, and promote plant as well as animal health”. Its assessment is needed to improve sustainable soil management. Since soil quality can’t be measured directly, it must be inferred from quality related indicators, which are measurable soil properties. The objectives of this research are: I) to identify a factor of quantitative assessment of soil quality, namely soil physical quality index (S) and II) to predict the S index by using, Pedo-transfer functions along with some conveniently measurable soil properties. Some physical and chemical properties of 84 soil samples (27 samples saline and 57 ones calcareous), such as particle size distribution, organic matter, bulk density, carbonates (CaCO3), Electrical Conductivity (EC), and Sodium Adsorption Ratio (SAR) were assessed. Also soils' moisture retention curves were plotted at 0, 2.5, 5.5, 10, 20, 30, 50, 100, 200, 300, 500, 1000 kpa pressure heads. The parameters of Van Genuchten equation (1980), through a use of ROSSETA software, as well as the slope of moisture retention curve, at the inflection point, were determined. The slope of the curve was considered as soil physical quality index (S). Regression was established between this index and the conveniently measurable soil properties through a use of Pedo-transfer functions and an employment of SPSS software. The results showed that there is a significant correlation existing S index and the percentage of clay, silt and carbonates in saline, calcareous as well as in all data set (p=0.01). Also a significant correlation existed between S index and bulk density in saline and calcareous soils shown at 5 and 1% level, respectively. The results finally indicated a strong regression relationship between calculated S obtained from moisture retention curve and S predicted from conveniently measurable properties. Correlation coefficients between the two were 0.855, 0.920, and 0.919 in saline, calcareous, and all data set, respectively.