Numerical modeling of physical and biochemical processes in the subsurface and their impacts on the self-potential signature

Abstract

Abstract. Subsurface contamination is a significant problem due to excessive fertigation and industrial and domestic wastewater discharge. With numerical modeling and geophysical tool development, subsurface contaminant research has become easier to implement and study. However, there is still a gap in coupling the biochemical processes and geophysical signals. Such a coupling model is needed to facilitate understanding subsurface processes and provide further theoretical basis to practice and field monitoring. Thus, this research aims to simulate the self-potential (SP) signature in response to physical and biochemical dynamics in the subsurface. For the physico-bio-chemical model, the processes of water flow, solute transport, biochemical reactions, microbial dynamics, adsorption, and gas flow are considered. Specifically, the biochemical cycles related to C, N, Mn, Fe, and S are incorporated in the model. The physico-bio-chemical model is then coupled with the SP model. The SP model is addressed by Poisson’s continuity equation, based on streaming and redox potential contribution. The streaming potential is calculated by the effective excess charge density and the water flow velocity, while the Butler-Volmer equation solves the redox potential. The results show that redox processes dominate the SP signals. Oxygen and nitrate concentrations present positive relationships with redox potential and dominate the redox potential in the oxic and anoxic environment, respectively. Nitrification and dissolved organic carbon (DOC) aerobic oxidation rates show positive relationships with redox potential. In contrast, the denitrification rate presents a negative relationship. The higher reaction rates for different redox processes also correspond to their optimal redox potential ranges. The streaming potential affected by water content and flux contributes little to SP, and the negative values along with soil depth become less remarkable. Generally, the SP and redox potential model can better reflect redox species concentrations and reaction rates, while the streaming potential model can reflect the water content and flux dynamics. Thus, the research can guide the detection of redox-sensitive contamination and water leakage in the subsurface.