Abteilung Wasserressourcen und Trinkwasser

Dense non-aqueous phase liquids (DNAPLs) are characterized by low solubility and high density, leading to extensive groundwater contamination over both spatial and temporal scales. Identification of sources and quantification of residual DNAPL is therefore critical for designing effective remediation strategies. Radon has been widely used as a tracer for DNAPL quantification due to its preferential phase partitioning behavior towards DNAPL. Building on this concept, noble gases have been proposed as potential tracers; however, they have not been generally applied, as the coefficients of Ar, Kr, and Xe between water and DNAPL are not known. Thus, this study aimed to evaluate the use of noble gases, alongside radon, as partitioning tracers for identifying and quantifying residual DNAPL in groundwater. Partition coefficients for Ar, Kr, and Xe were derived, while Xe was found most sensitive, indicating the strongest affinity for DNAPL. Correspondingly, Fe_Xe was most depleted in regions near the highest PCE concentrations. Using the derived partition coefficients, the potential residual PCE zone ("contaminated zone") was quantified within the PCE contaminated study site at the Namdong Industrial Complex, South Korea. The residual PCE inferred from noble gases agreed with radon-based estimates yet yielded a more tightly constrained range, and remained of the same order of magnitude as soil core derived values. Overall, this study demonstrates the potential of using noble gases as a partitioning tracer for DNAPL quantification, and the derived noble gas partition coefficients opens a novel window to apply noble gases in groundwater.

Elemente Seltener Erden gelangen über anthropogene Quellen in Gewässer. Insbesondere Gadolinium-basierte Kontrastmittel aus der Magnetresonanztomographie sowie Lanthan und Cer aus technischen Anwendungen können zu erhöhten Konzentrationen dieser Elemente im Ablauf von Abwasserreinigungsanlagen führen. Die vorliegende Studie fokussiert auf das Vorkommen von Gadolinium, Lanthan und Cer in Zürcher Abwässern und leitet daraus potenzielle ökotoxikologische Risiken für die Gewässer des Kantons Zürich ab.

Taiwan’s mid-20th-century Blackfoot disease epidemic highlighted the public health implications of geogenic arsenic in groundwater and prompted extensive water-supply interventions. Despite these measures, arsenic persists in aquifers, continuing to affect drinking water, irrigation, and aquaculture. This study developed a scalable machine learning model to identify areas across Taiwan at risk of groundwater arsenic concentrations exceeding the WHO guideline of 10 µg/L. The model demonstrated robust performance (mean AUC 0.93, balanced accuracy 0.87). A detailed evaluation and interpretation of the principal predictor variables governing arsenic dissolution provides insights into geochemical and hydrogeological controls on mobilization. Furthermore, the resulting hazard map of Taiwan was used to estimate the human population at risk as well as the locations and types of exposed agriculture and aquaculture. Hotspots are clustered in the Chianan, Pingtung and Lanyang plains, where many rural communities still rely on untreated groundwater. Population exposure is substantial, with an estimated 148,000 people at risk in 2023, which is about half the 303,000 reported in 1998. Agricultural impacts are also considerable: >80 % of aquaculture areas, and 33 % of paddy rice fields occur within high-risk zones. Several high-risk zones lie outside Taiwan's Groundwater Control Areas, revealing regulatory blind spots. By connecting Taiwan's historical arsenic crisis to novel predictive tools, this work supports evidence-based strategies to reduce current exposures and prevent future public arsenic-related health impacts.

Mountainous regions such as Switzerland, which are characterized by highly complex geological and hydrogeological conditions, hold significant geothermal potential linked to tectonic settings and deep hydrothermal flow systems. However, geothermal exploration in such regions is challenged by geological and hydrogeological complexity, data scarcity, high uncertainty, administrative hurdles, as well as environmental and economic risks associated with drilling. Robust quantitative tools that maximize the value of the limited information available on the subsurface are needed to assess geothermal potential, productivity, and sustainability. Here, a step-by-step framework for the assessment of regional hydrothermal flow systems is presented. The framework consists of 3D geological modeling, 3D thermohydraulic modelling (3D-TH-model), and a systematic sensitivity analysis for the identification of the optimal structural model complexity. The framework is demonstrated on the hydrothermal systems of the Upper Aarmassif in the Swiss Alps. Results showed that thermal upwelling in the system is driven by strong topographic gradients and upward flux along more permeable tectonic faults and thrusts. The upwelling results in significantly elevated groundwater temperatures near the surface in the Rhône Valley, with temperatures exceeding 70 °C at depths of 1000 m and reaching ~100 °C at depths of 2000 m. These model outputs were verified by the few available vertical borehole temperature profiles, horizontal tunnel temperature profiles, groundwater recharge rates and hydraulic head distribution, ¹⁴C-based groundwater residence times, and geothermometrically identified hydrothermal-reservoir-temperature estimates. The framework provides the basis for risk-reduced geothermal exploration, thereby supporting sustainable geothermal development—a significant step towards a decarbonized energy future.