Sediment color as a predictor of the subsurface redox conditions at large scale

The redox conditions of the subsurface are critical for predicting nitrate transport and fate in groundwater. Groundwater chemistry of redox-sensitive parameters can be used to infer subsurface redox conditions; however, it typically provides only point-scale information and requires significant time and effort to acquire large datasets. In soil science, soil/sediment colors have been used to qualitatively infer redox status in different soil horizons. In this study, we quantitatively assessed the potential of sediment color as a proxy for subsurface redox conditions at a national scale in Denmark. We did so by comparing sediment color classifications with groundwater redox conditions from approximately 4000 groundwater screens across the country. The sediment color dataset included seven base colors i.e., red, yellow, black, blue, green (olive), gray, and brown, encompassing a total of 89 variations, accounting for nuances (e.g., yellowish, grayish) and lightness (light vs dark). Our results revealed that, overall, qualitative redox interpretations based on sediment color aligned well with the oxic groundwater fraction. Gray and brown groups were the predominant colors, and within each group, the oxic water fraction increased with oxic-associated nuances (e.g., yellowish gray) and lighter shades (e.g., light yellowish gray) compared to their respective base color (i.e., gray). Most brown colors and gray shades with oxic (e.g., yellowish gray) and brownish nuances (e.g., brownish gray) showed oxic water fractions that decreased exponentially with increasing depth, suggesting hydrological controls on the redox conditions. Based on these findings, sediment color data from more than 27,000 boreholes across the country were quantitatively translated into oxic probability, enabling more precise delineation of the redox interface. Since sediment color data can be collected rapidly and at large scales, it provides a reliable and cost-effective means of assessing subsurface redox conditions. Therefore, sediment colors data have great potential to enhance large-scale modelling of redox-sensitive contaminant transport and fate.