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Castrignanò, A., Buttafuoco, G., & Giasi, C. (2008). Assessment of groundwater salinisation risk using multivariate geostatistics. In S. A., P. M.J., & D. R. (Eds.), geoENV VI – Geostatistics for Environmental Applications (Vol. 15, pp. 191–202). Springer, Dordrecht.
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Schmittner, K. - E., & Giresse, P. (1999). The impact of atmospheric sodium on erodibility of clay in a coastal Mediterranean region. Environmental Geology, 37(3), 195–206.
Abstract: Heavy rainfalls, between 25 and 100 mm·h–1, were simulated on Pliocene/Quaternary sediments. To reproduce the heterogeneity of natural environments, 231 small plots of various sizes (between 2.5 and 3.5 m2; mean: about 3 m2) were used. The duration of all simulations was 1 h. We used water that had been collected during natural rainfall. The concentration of clay particles in the sheet wash depended upon the concentration of dissolved sodium in the wash (for about 42%) and of the sheet wash quantity (for about 37%). Under natural water conditions colloidal matter, like clay minerals, is charged negatively and therefore is destabilized by metal cations such as in the case of Na+. Results suggest that relatively higher concentrations of montmorrillonite were related to higher concentrations of sodium as opposed to illite and kaolinite. Microflakes of up to 25 μ were observed to vary between face-to-edge and face-to-face modes (competition between protons and other cations). The concentration of dissolved sodium (Na+) in the runoff water depends on water and sodium balances such as atmospheric input, infiltration, evaporation and surface water runoff. The reduction of vegetation cover increases the amount of salt and amorphous matter in/on the topsoil between heavy rainfall generations. The best predictor to explain montmorillonite, illite and kaolinite in % of mineral clay-sized matter in the surface water runoff (sheet wash) is the percentage of each clay mineral in the topsoil. As opposed to illite and kaolinite, more sheet wash indicate for montmorillonite relatively higher concentrations in the wash. The results of model simulations were confirmed on different field plots of about 1 ha and small catchments during natural heavy rainfall events. Models can also be used to understand and to better simulate sheet, rill and gully erosion, micropedimentation; and pedimentation.
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Johnson, J. S., Baker, L. A., & Fox, P. (1999). Geochemical transformations during artificial groundwater recharge: soil–water interactions of inorganic constituents. Water research, 33(1), 196–206.
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Carrera*, J., Alcolea, A., Medina, A., Hidalgo, J., & Slooten, L. J. (2005). Inverse problem in hydrogeology. Hydrogeol. J., 13, 206–222.
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Stamatakis, M. G., Tziritis, E. P., & Evelpidou, N. (2009). The geochemistry of boron-rich groundwater of the Karlovassi Basin, Samos Island, Greece. Central European Journal of Geosciences, 1(2), 207–218.
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