A New Efficient Approach to Model Stiff Biogeochemical Reactive Transport Scenarios Across Groundwater Systems.

Biogeochemical reactive transport models (RTMs) are key for understanding the evolution of the quality of groundwater systems and their interaction with anthropogenic activities. The inherent stiffness of these models, within which bio‐geochemical reactions and transport processes take place simultaneously across diverse time scales, poses significant computational challenges. The development of current RTMs is characterized by a tradeoff between accuracy and computational efficiency. Our study introduces a novel approach grounded on Computational Singular Perturbation (CSP) with the aim of efficiently solving stiff biogeochemical RTMs in groundwater systems. We integrate the CSP concept and algorithm with a reactive transport model associated with a groundwater system. Our results document that this yields a significant improvement in terms of efficiency while maintaining accuracy. For demonstration and evaluation purposes, we apply the approach to a collection of typical groundwater biogeochemical RTMs including H2O2 production/consumption, Cr(VI) adsorption‐desorption equilibrium, and denitrification processes within riparian aquifers. The new approach is then evaluated against traditional apparent rate (AR) and Equilibrium‐kinetic (EK) methods. Our results reveal that the new approach effectively identifies fast species and simplifies reaction networks, thus significantly reducing stiffness and computational costs while maintaining remarkable accuracy. Overall, our approach offers a robust and efficient solution for modeling stiff biogeochemical processes in groundwater systems. Its successful application to diverse reaction networks highlights its potential for broad implementation in environmental and engineering contexts, paving the way for accurate and computationally feasible groundwater quality assessments. Key Points: We develop a new approach to solve stiff biogeochemical reactive transport models efficiently and accurately in groundwaterOur new approach rests on a time scale analysis of modeled species through computational singular perturbationThe approach enables one to simplify the model by reducing the number of species associated with its formulation [ABSTRACT FROM AUTHOR]