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Russak, A., Sivan, O., & Yechieli, Y. (2016). Trace elements (Li, B, Mn and Ba) as sensitive indicators for salinization and freshening events in coastal aquifers. Chemical Geology, 441, 35–46.
Abstract: The current global intrusion of seawater into coastal aquifers causes salinization of groundwater and thus significant degradation of its quality. This study quantified the effect of seawater intrusion and freshening events in coastal aquifers on trace elements (Li, B, Mn and Ba) across the fresh-saline water interface (FSI) and their possible use as indicators for these events. This was done by combining field data and column experiments simulating these events. The experiments enabled quantification of the processes affecting the trace element composition and examination of whether salinization and freshening events are geochemically reversible, which has been seldom investigated. The dominant process affecting trace element composition during salinization and freshening is ion exchange. The results of the experiments show that the concentrations of major cations and Li+ were reversible during salinization and freshening, whereas B, Mn2+ and Ba2+ were not. During salinization, Li+ and B were depleted due to sorption by 10 and 100μmol·L−1, respectively, to about half of their expected conservative concentrations. The relative depletion of Li+ increased with distance from the shore, representing the propagation of salinization. Ba2+ and Mn2+ were desorbed from the sediment during salinization and enriched by tenfold in the aqueous phase compared to their concentration in seawater ( 0.1 μeq·L−1). During freshening both were depleted by almost tenfold compared to their concentration in fresh groundwater ( 0.7 μeq·L−1). The depletion of Mn2+ is a sensitive marker for freshening because Mn2+ has a strong affinity to the solid phase. Moreover, this study shows that both Mn2+ and Ba2+ can be used as sensitive hydrogeochemical tools to distinguish between salinization and freshening events in the FSI zone in coastal aquifers.
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Satrio, S., Prasetio, R., Hadian, M., Syafri, I. (2016). Stable Isotopes and Hydrochemistry Approach for Determining the Salinization Pattern of Shallow Groundwater in Alluvium Deposit Semarang, Central Java. Indonesian Journal on Geoscience, 4.
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Seyedmohammadi*, J., Esmaeelnejad, L., & Shabanpour, M. (2016). Spatial variation modeling of groundwater electrical conductivity using geostatistics and GIS. Model. Earth Syst. Environ., 2, 169.
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Siarkos, I., & Latinopoulos, P. (2016). Modeling seawater intrusion in overexploited aquifers in the absence of sufficient data: application to the aquifer of Nea Moudania, northern Greece. Hydrogeology J., 24, 2123–2141.
Abstract: In many coastal areas, overexploitation of groundwater resources has led both to the quantitative degradation of local aquifers and the deterioration of groundwater quality due to seawater intrusion. To investigate the behavior of coastal aquifers under these conditions, numerical modeling is usually implemented; however, the proper implementation of numerical models requires a large amount of data, which are often not available due to the time-consuming and costly process of obtaining them. In the present study, the investigation of the behavior of coastal aquifers under the lack of adequate data is
attempted by developing a methodological framework consisting of a series of numerical simulations: a steady-state, a false-transient and a transient simulation. The sequence and the connection between these simulations constitute the backbone of the whole procedure aimed at adjusting the various
model parameters, as well as obtaining the initial conditions for the transient simulation. The validity of the proposed methodology is tested through evaluation of the model calibration procedure and the estimation of the simulation errors (mean error, mean absolute error, root mean square error, mean relative error) using the case of Nea Moudania basin, northern Greece. Furthermore, a sensitivity analysis is performed in order to minimize the error estimates and thus to maximize the reliability of the models. The results of the whole procedure affirm the proper implementation of the developed methodology under specific conditions and assumptions due to the lack of sufficient data, while they give a clear picture of the aquifer’s quantitative and qualitative status.
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