Salt Transport to Saturated Porous Media under Unstable Conditions: Experimental, Analytical, and Numerical Studies
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There are three main transport mechanisms that occur under unstable flow conditions: a) The transport of saltwater from the overlying salt source to the underlying porous media, b) the transport of an equivalent volume of displaced groundwater from the porous media into the source, and c) the transport of the saltwater through the porous media. In many situations; such as, estuaries, salt lakes, and landfills, it may be necessary to determine the rate of saltwater transport from an overlying unstable salt source that has heavier saline water overlying porous media fully saturated by lighter saline water. Studies of unstable density stratification have shown a rapid and erratic redistribution of salt. The phenomenon of saltwater transport through a porous media under unstable conditions has been studied extensively via laboratory and/or numerical studies. In comparison, the phenomenon of saltwater transport from the saltwater source to a less dense underlying porous media under unstable conditions has received very little attention. Therefore, this research will address this saltwater transport under unstable conditions. Goals of this research were to measure and model the salt mass transport from the source to underlying porous media under unstable conditions. The basic steps followed were: 1) To measure salt mass transport from the source to porous media with time called a source depletion curve (SDC) as well as salt mass transport through the porous media called a break through curve (BTC), 2)to be able to verify the measured SDC of all experiments with analytical equations, and 3) to create a numerical simulation that will predict the experimental and analytical results. To achieve this, the independent parameters measured were column size, porous media depth, initial source concentration, initial porous media concentration, source height, and hydraulic conductivity. Thirty-seven experiments were conducted on five different plexiglass models of different dimensions which were filled with saturated F40 sand. The cross-section of the models ranged from 10 cm by 10 cm to 61 cm by 61 cm, while the depth of models ranged between 13.6 cm and 170 cm, the saline water layer on top of the sand was termed the source layer. Thirty-four experiments had finite mass source and were conducted over 15 days with initial source concentration that ranged between 4.5 g/l and 72 g/l and source depth that ranged from 4.5 cm to 11.70 cm. The salt transport through the porous media was studied using the sand column with a finite mass source and constant mass source experiments lasting between 5 to 29 days. Salt concentrations were measured at five different depths within the porous media from the porous media interface. There was no hydraulic gradient across the porous media at any time of the experiments run. The finite source mass experiment results, using mass analysis, showed that the salt transport from the source to porous media was deterministic. All experiments that had the same conditions produced identical rates of mass transport from the source to porous media. In contrast, the salt transport through the porous media was stochastic, since the observed breakthrough curves at the five depths were considerably different. The analytical equations used to predict the SDC of all experiments that were run under different parameters visually matched the measured SDCs. Additionally, it showed that the salt transport from source to porous media SDC is independent from column size, porous media depth, initial source concentration, initial porous media concentration, source height, and hydraulic conductivity until the salt reaches the sand column bottom. The results presented in this research can be used to predict source depletion curves accurately. The mass transport from source to porous media was examined numerically and showed that the measured and predicted of SDC was well matched. Therefore, the SDC can be simulated accurately by using a coupled numerical model. The conclusions include:1-SDC is deterministic and can be modeled analytically and numerically2-BTC is stochastic and could not be modelled accurately 3-The SDC can be predicted numerically for any size models4-A numerical model to predict SDC of real-world situations such as estuaries can be modelled.