A Data-Driven Simplified Nernst Equation for Estimating Reduction Potentials in Groundwater from pH and Temperature

Abstract

Reduction potentials of redox couples are fundamental for understanding subsurface geochemistry and guiding water resource exploration and management. Reduction potentials are routinely calculated with the Nernst equation, which requires detailed chemical composition data and complex speciation modeling—factors that limit its application in large-scale or data-limited field settings. To address these limitations, we developed a data-driven simplified Nernst equation that estimates the reduction potentials of individual redox couples using only pH and temperature. By integrating geochemical modeling with a global groundwater chemistry dataset, we demonstrate that pH is the dominant control on redox potential, while temperature and redox species activity play secondary roles. The resulting formulation reduces computational demands while maintaining high-predictive accuracy across diverse groundwater environments. This approach enables rapid and scalable estimation of reduction potentials, supporting applications in geochemical modeling, contaminant transport prediction, and groundwater quality assessments. Furthermore, it offers a thermodynamically grounded yet practical framework for interpreting electron transfer dynamics in natural groundwater systems.