Abteilung Wasserressourcen und Trinkwasser

Hydrological models are calibrated on specific periods based on how well simulations match streamflow observations by selecting the parameter vector(s) that provide the highest accuracy. This accuracy can decrease significantly during extrapolation to periods not seen during calibration, especially when they are characterized by different climate conditions. Here, we develop a novel calibration objective that relies on the joint calibration of model accuracy and time-invariance of residuals, hypothesizing that such invariance can improve the temporal generalizability of hydrological models. We test this approach using a hydrological model and 208 catchments in Western Germany. We evaluate it based on (a) the accuracy loss between calibration and evaluation, (b) the compromise between accuracy and residual invariance, (c) the dependence of residuals on variations in forcings, and (d) the instability of parameters between two calibration periods. We find that our approach reduces the loss in accuracy between calibration and extrapolation as compared to calibration approaches solely based on accuracy. Furthermore, our method combined with the Boxcox streamflow transformation weakens the dependence of residuals on variations in the forcing. However, we find that invariant residuals do not necessarily imply improved parameter stability between different calibration periods. Furthermore, the gain in temporal generalizability comes at the cost of a decrease in accuracy, which should be considered based on the application. Our results highlight that the new RESIdual STability (RESIST) calibration objective has the potential to improve the temporal generalizability of hydrological models for climate-impact studies.

Dissolved noble gases have been recognized for decades as ideal artificial hydro(geo)logical tracers, as they are chemically inert, invisible, and non-toxic. However, their widespread adoption has historically been limited by the difficulty of tracer injection, sampling, and analysis procedures. Developments in portable, high-resolution dissolved gas measurement technology over the last two decades have rekindled interest in the use of gas tracer methods for routine hydrogeological investigations, such as well-to-well tracer tests, intra-well tests, or studies of river infiltration towards alluvial aquifers. The application of gases in aqueous environments still poses unique challenges compared to other tracer methods, as potential exsolution and degassing need to be accounted for, and, if possible, avoided during tracer injection. Here, we present a simple and efficient methodology that addresses these challenges and allows the efficient, on-site preparation and injection of highly concentrated tracer solutions with controlled dissolved gas concentrations. We applied the method in a large drinking water wellfield and performed well-to-well tracer tests in an unconfined aquifer using helium-4 (⁴He), neon-20 (²⁰Ne) and krypton-84 (⁸⁴Kr). Known tracer quantities were injected together with fluorescent dyes into an observation well upgradient of a pumping well. Gas tracer breakthrough was monitored in the pumping well with a portable mass spectrometer. Breakthrough curves of ⁴He and ⁸⁴Kr compared favorably with fluorescent dye tracers, and enabled reliable estimates of groundwater flow velocities, travel times, and tracer recovery. These findings illustrate how noble gases can substitute or complement other artificial tracer methods, even in large-scale settings. The methodology can be extended to other gases (e.g., neon-22, xenon isotopes, light hydrocarbons), significantly expanding the range of artificial tracers available for routine hydrogeological investigations.

Groundwater is a crucial drinking water source, and maintaining its quality becomes increasingly important as global demand rises. This study examines the spatial distribution and controlling factors of five geogenic groundwater contaminants—arsenic (As), manganese (Mn), iron (Fe), ammonium (NH₄), and total phosphorus (P)—across Denmark using classification machine learning models. We trained the models using data from over 7100 well intakes and 34 spatial covariates related to soil, geology, groundwater level, and recharge. The models achieved area under the curve scores ranging from 0.85 to 0.90. Predicted areas exceeding guideline thresholds for drinking water (As, Mn, Fe, NH₄) or ecological ecosystem status (P) cover 14% (As), 78% (Mn), 74% (Fe), 80% (NH₄), and 49% (P) of Denmark's area; more than 60% are classified with high confidence, with uncertainty varying by monitoring density, among other factors. The 2D spatial predictions integrate multi-depth observations and reflect geological and hydrogeological controls. Elevated As levels were mainly associated with glacial meltwater sand and clay aquifers overlying pre-Quaternary marine clays. Feature importance analysis confirms that complex Quaternary layering, confining clay units, and redox-sensitive conditions—particularly in the presence of reactive Fe/Mn oxides and organic matter—drive As mobilization. All five contaminants tend to co-occur spatially under reducing conditions, indicating shared redox-driven release mechanisms. This study shows how national-scale, high-resolution datasets combined with machine learning can predict groundwater quality, aiding well siting and water treatment decisions, and provides transferable insights for regions with similar hydrogeological conditions.

Dissolved organic matter (DOM) acts as an inducer as well as an inhibitor in the photodegradation of 4-(N,N-dimethylamino)benzonitrile (DMABN), which undergoes both photodegradation by the excited triplet states of chromophoric DOM (³CDOM*), and inhibition upon back reduction by the antioxidant moieties of DOM itself. On average, water with dissolved organic carbon (DOC) > 2.3 mgC L⁻¹ would inhibit DMABN photodegradation by over 50 %. From the available data of [³CDOM*] steady-state concentrations and the levels of DOC in lake water on a quasi-global scale (60°S-60°N latitude range), we were able to numerically assess the photochemical lifetimes of DMABN, here reported as year averages. Lifetimes of DMABN in lake water would amount to a couple of months or longer, and they would be the shortest in the tropical belt. Results of numerical calculations were interpolated using a suitable model function, with which an analytical equation was derived that relates DMABN lifetimes with lake depth, DOC, and latitude. For the first time to our knowledge, a general equation is here proposed to assess the photodegradation kinetics of a pollutant on a (quasi–)global scale.