Local and Global Sensitivity Analysis of a Reactive Transport Model Simulating Floodplain Redox Cycling. Issue 12 (3rd December 2021) - Perzan, Z.; Babey, T.; Caers, J.; Bargar, J. R.; Maher, K.
Abstract: Reactive transport models (RTMs) are essential tools that simulate the coupling of advective, diffusive, and reactive processes in the subsurface, but their complexity makes them difficult to understand, develop and improve without accompanying statistical analyses. Although global sensitivity analysis (SA) can address these issues, the computational cost associated with most global SA techniques limits their use with RTMs. In this study, we apply distance‐based generalized sensitivity analysis (DGSA), a novel and computationally efficient method of global SA, to a floodplain‐scale RTM and compare DGSA results to those from local SA. Our test case focuses on the impact of 17 uncertain environmental parameters on spatially and temporally variable redox conditions within a floodplain aquifer. The input parameters considered include flow and diffusion rates, geochemical reaction rates, and the spatial distribution of sediment facies. Sensitivity was evaluated for three distinct components of the model response, encompassing both multidimensional and categorical output. Parameter rankings differ between local SA and DGSA, due to nonlinear effects of individual parameters and interaction effects between parameters. DGSA results show that fluid residence time, which is controlled by aquifer permeability, generally exerts a stronger control on redox conditions than do geochemical reaction rates. Sensitivity indices also demonstrate that sulfate reduction is key for establishing and maintaining reducing conditions throughout the aquifer. These results provide insights into the key drivers of heterogeneous redox processes within floodplain aquifers, as well as the main sources of uncertainty when modeling complex subsurface systems. Plain Language Summary: Models that simulate the movement of groundwater and contaminants in aquifers, known as reactive transport models (RTMs), are complex. Multiple competing processes, including the physics of groundwater flow and the chemistry of microbial interactions, make the results of such models difficult to understand without additional statistical analyses. Sensitivity analysis, a technique for calculating the effect of each input variable on model output, is one potential tool for interpreting complex models, but it is rarely performed on RTMs due to the computational resources required. In this paper, we show that distance‐based generalized sensitivity analysis (DGSA) can be used to interpret reactive transport models and has several advantages over other techniques. As a case study, we use DGSA to measure the effect of 17 input variables on a model that simulates iron cycling within a shallow aquifer. Results show that groundwater flow rates control dissolved iron concentrations and are generally more influential than geochemical reaction rates. Though we focus on iron, the findings are relevant for other microbially driven reactions, which can control the mobility of many nutrients, contaminants, and metals in groundwater. Key Points: Global sensitivity analysis is a valuable tool for improving process understanding in subsurface biogeochemical models Parameter rankings from local and global sensitivity analyses can differ when applied to reactive transport models In certain settings, sediment permeability exerts a more dominant control on redox cycling than do geochemical reaction rates