Geoscientific Model Development
We introduce a time-dependent, one-dimensional model of early diagenesis that we term RADI, an acronym accounting for the main processes included in the model: chemical reactions, advection, molecular and bio-diffusion, and bio-irrigation. RADI is targeted for study of deep-sea sediments, in particular those containing calcium carbonates (CaCO3). RADI combines CaCO3 dissolution driven by organic matter degradation with a diffusive boundary layer and integrates state-of-the-art parameterizations of CaCO3 dissolution kinetics in seawater, thus serving as a link between mechanistic surface reaction modeling and global-scale biogeochemical models. RADI also includes CaCO3 precipitation, providing a continuum between CaCO3 dissolution and precipitation. RADI integrates components rather than individual chemical species for accessibility and is straightforward to compare against measurements. RADI is the first diagenetic model implemented in Julia, a high-performance programming language that is free and open source, and it is also available in MATLAB/GNU Octave. Here, we first describe the scientific background behind RADI and its implementations. Following this, we evaluate its performance in three selected locations and explore other potential applications, such as the influence of tides and seasonality on early diagenesis in the deep ocean. RADI is a powerful tool to study the time-transient and steady-state response of the sedimentary system to environmental perturbation, such as deep-sea mining, deoxygenation, or acidification events.
National Aeronautics and Space Administration
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Moss Landing Marine Laboratories
Olivier Sulpis, Matthew P. Humphreys, Monica M. Wilhelmus, Dustin Carroll, William M. Berelson, Dimitris Menemenlis, Jack J. Middelburg, and Jess F. Adkins. "RADIv1: a non-steady-state early diagenetic model for ocean sediments in Julia and MATLAB/GNU Octave" Geoscientific Model Development (2022): 2105-2131. https://doi.org/10.5194/gmd-15-2105-2022