Soil texture affects the conversion factor of electrical conductivity from 1:5 soil-water to saturated paste extracts

Electrical conductivity (EC) of soil-water extracts is commonly used to assess soil salinity. However, its conversion to the EC of saturated soil paste extracts (ECe), the standard measure of soil salinity, is currently required for practical applications. Although many regression models can be used to obtain ECe from the EC of soil-water extracts, the application of a site-specific model to different sites is not straightforward due to confounding soil factors such as soil texture. This study was conducted to develop a universal regression model to estimate a conversion factor (CF) for predicting ECe from EC of soil-water extracts at a 1:5 ratio (EC1:5), by employing a site-specific soil texture (i.e., sand content). A regression model, CF = 8.910 5e(0.010 6sand)/1.298 4 (r(2) = 0.97, P < 0.001), was developed based on the results of coastal saline soil surveys (n = 173) and laboratory experiments using artificial saline soils with different textures (n = 6, sand content = 10%-65%) and salinity levels (n = 7, salinity = 1-24 dS m(-1)). Model performance was validated using an independent dataset and demonstrated that EC(e )prediction using the developed model is more suitable for highly saline soils than for low saline soils. The feasibility of the regression model should be tested at other sites. Other soil factors affecting EC conversion factor also need to be explored to revise and improve the model through further studies.

Automated summary

This study developed a universal regression model to predict ECe from EC of soil-water extracts, using artificial saline soils with different textures and salinity levels. Model validation showed that the prediction of EC(e) using the developed model is more suitable for highly saline soils.