Groundwater metabolome responds to recharge in fractured sedimentary strata

Understanding the sources, structure and fate of dissolved organic matter (DOM) in groundwater is paramount for the protection and sustainable use of this vital resource. On its passage through the Critical Zone, DOM is subject to biogeochemical conversions. Therefore, it carries valuable cross-habitat information for monitoring and predicting the stability of groundwater ecosystem services and assessing these ecosystems' response to fluctuations caused by external impacts such as climatic extremes. Challenges arise from insufficient knowledge on groundwater metabolite composition and dynamics due to a lack of consistent analytical approaches for long-term monitoring. Our study establishes groundwater metabolomics to decipher the complex biogeochemical transport and conversion of DOM. We explore fractured sedimentary bedrock along a hillslope recharge area by a 5-year untargeted metabolomics monitoring of oxic perched and anoxic phreatic groundwater. A summer with extremely high temperatures and low precipitation was included in the monitoring. Water was accessed by a monitoring well-transect and regularly collected for liquid chromatography-mass spectrometry (LC-MS) investigation. Dimension reduction of the resulting complex data set by principal component analysis revealed that metabolome dissimilarities between distant wells coincide with transient cross-stratal flow indicated by groundwater levels. Time series of the groundwater metabolome data provides detailed insights into subsurface responses to recharge dynamics. We demonstrate that dissimilarity variability between groundwater bodies with contrasting aquifer properties coincides with recharge dynamics. This includes groundwater high- and lowstands as well as recharge and recession phases. Our monitoring approach allows to survey groundwater ecosystems even under extreme conditions. Notably, the metabolome was highly variable lacking seasonal patterns and did not segregate by geographical location of sampling wells, thus ruling out vegetation or (agricultural) land use as a primary driving factor. Patterns that emerge from metabolomics monitoring give insight into subsurface ecosystem functioning and water quality evolution, essential for sustainable groundwater use and climate change-adapted management.