Abstract
The goal of this thesis is to advance the modeling of physical, chemical, and biological transformations that define the early diagenetic processes in sediments. Early diagenetic models encompass the mathematical formulation and numerical solution of complex biogeochemical reaction systems, and thus contribute to and profit from the advances made in
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the broader field of reaction transport models (RTMs). In chapter 2, the available information on individual biogeochemical reactions common to many natural systems (e.g. redox reactions, mineral dissolution/precipitation processes, and acid/base equilibria) is systematically compiled based on the concept of a Knowledge Base (KB), in order to facilitate the assemblage of RTMs. The KB is interfaced with one-dimensional transport descriptions relevant to many compartments of the Earth system (rivers, estuaries, groundwater or sediments) to yield a unified simulation environment. The flexibility of this modeling framework is illustrated in two applications dealing with biogeochemical processes in sediments and groundwater environments. A new approach is proposed in chapter 3 that yields the reaction-specific proton production and consumption rates, since the quantitative interpretation of pH distribution is a diagnostic indicator of biogeochemical processes. This method also provides a means to interpret the saturation state of pore waters with respect to mineral phases. Here, the chemical species participating in equilibrium reactions appear explicitly in the kinetic reaction stoichiometries and are treated as unknowns. The model is applied by simulating continental shelf sediments. Simulations are also used to determine the response of pH to variations in calcite dissolution kinetics and irrigation intensity. The developed RTM is used to interpret pore water oxygen and pH microprofiles in deep-sea sediments. Two pools of degradable organic matter (OM) are necessary and sufficient to reproduce the oxygen profiles. In contrast, the successful simulation of pH profiles is limited, due to the larger number of processes that affect the proton balance. As OM is unstable in early diagenetic environments, fitting the O2 distribution yields estimates of its deposition flux, while it is not possible to constrain the deposition flux of CaCO3 from the pH data, since the pore waters reach equilibrium with respect to calcite. Thus, the depth-integrated calcite dissolution rate is obtained from the best-fit pH profiles. The nonlinear calcite dissolution rate laws yield the best agreement between modeled and measured pH profiles. The last chapter presents a model of physical and chemical compaction for the interpretation of porosity profiles based on the conservation of mass and momentum. It is used to separate the effects of mechanical compaction from mineral dissolution or precipitation reactions. The hydraulic conductivity and elastic response of a set of deep-sea sediments are estimated through an inverse modeling approach. Preliminary results indicate an inverse relationship between the elastic response coefficient and the lithogenic content of the sediment. This highlights the possibility of linking the sediment compaction behavior to its composition. The simulation results indicate a slightly improved porosity fit to available data with the nonlinear calcite dissolution rate laws, and suggest that treating porosity as an unknown enhances the current early diagenetic modeling efforts.
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