Author/Authors :
Fernando Visconti، نويسنده , , José Miguel de Paz، نويسنده , , José Luis Rubio، نويسنده ,
Abstract :
Calcite equilibrium characterisation of soil solutions is needed in order to provide soil salinity modellers with reliable solubility constants in solutions where the hypothesis of equilibrium can be accepted. A total of 134 soil samples were taken from 39 sites at 2, 3, or 4 depths per site, down to a maximum depth of 95 cm, during a survey in the irrigated agricultural area of the Segura River Lowland (SE Spain). Soil saturation extracts obtained from each sample were analysed for thirteen chemical properties: Na, NH4, K, Mg, Ca, Cl, NO2, NO3, SO4, alkalinity, chemical oxygen demand, and electrical conductivity. A principal component analysis (PCA) was then done on the correlation matrix from the log-transformed data set. Three principal components, accounting for 76% of the variance in the correlation matrix, were retained after eigenvector extraction. These components were interpreted as representing salinisation, soil superficiality as opposed to soil depth, and fertilisation status. Sodium, chloride, magnesium, calcium and sulphate concentrations were highly correlated with the first principal component and were interpreted as explaining the variance in electrical conductivity of the soil saturation extracts, and by proxy soil salinity. Alkalinity, pH, chemical oxygen demand, and nitrite were correlated with the second principal component. Nitrate, potassium and ammonium concentrations were correlated with the third principal component, and their variation in soil was independent of soil saturation extract salt content and soil depth. According to the interpretation of the second principal component, soil saturation extracts are further than the solutions in the saturated pastes from being in equilibrium with calcite. The calcite oversaturation status of soil saturation extracts is related to soil organic matter content.
Keywords :
Soil salinity , Irrigation , Calcite solubility , soil solution , Principal component analysis