Department Water Resources and Drinking Water

Manganese (Mn) is an essential element for human nutrition with the bulk of intake typically coming from food. However, Mn concentrations in drinking water can be substantial, and high levels of overall Mn consumption may be toxic. Recognizing detrimental health effects particularly for infants, the World Health Organization lowered its guideline for Mn in drinking water from 400 µg l⁻¹ to 80 µg l⁻¹ in 2021. Here, to assess the implications of this change on affected regions and populations, machine learning was used with a large dataset of groundwater Mn concentrations and relevant environmental parameters to generate global prediction maps of manganese. Considering populations reliant on untreated groundwater, we estimate that about 180–220 million people are at risk to Mn contamination >80 µg l⁻¹ in drinking water, a four to fivefold increase from about 45 million people at the previous guideline of 400 µg l⁻¹. The number of people potentially impacted by high Mn is comparable to that for geogenic arsenic (As) and fluoride, though Mn receives much less attention. Despite Mn and As accumulating under reducing geochemical conditions, the occurrence of high concentrations of Mn and As generally does not overlap. Since groundwater buffers climate impacts and supports half the world’s population, the presented novel risk maps help locate and secure safe sources.

The formation of toxicologically relevant nitro compounds has been observed during ozonation of nitrite-containing secondary wastewater effluents, but their formation mechanism remains unknown. To identify key nitrating species, three reaction systems were investigated: ozonation of nitrite (O₃/NO₂^–), peroxynitrite (ONOOH/ONOO^–), and hydroxyl radical oxidation of nitrite with γ-radiolysis (γ/NO₂^–). Nitrite ozonation (O₃/NO₂^–) yielded significant amounts of the nitrating agent nitrogen dioxide ^•NO₂ (9.4% at pH 7 to 22% at pH 12) besides the main product nitrate. No peroxynitrite formation was detected during ozonation of nitrite-containing waters, suggesting that ^•NO₂ is the key nitrating species. A comparison of nitro compound formation from 20 aromatic compounds in the three reaction systems showed a consistent formation of nitro compounds with minor differences. Furthermore, the pH-dependence patterns of nitration for two micropollutants (diuron and carbendazim) revealed similarities between the O₃/NO₂^– and γ-radiolysis (γ/NO₂^–) systems, unlike peroxynitrite. These trends, combined with the lack of detection of peroxynitrite during ozonation, a fast reaction of peroxynitrite with ozone (k_pH=9 = (4.96 ± 0.40) × 10⁶ M^–1s^–1), suggest that a significant contribution of peroxynitrite is highly unlikely. Overall, nitration during ozonation involves nitrite oxidation to ^•NO₂, mostly by hydroxyl radical and to a minor extent by ozone.

Groundwater recharge patterns are expected to shift due to climate change; however, the impact on recharge temperature remains an open question. This study investigates the combined impact of climate change on groundwater recharge rates and temperature in a pre-alpine region of Switzerland. By applying a 1D numerical model calibrated with unique lysimeter data, daily recharge rates and temperature dynamics were simulated under 47 climate model projections for three greenhouse gas scenarios (RCP2.6, 4.5 and 8.5) from 1981 to 2099. Results project an annual increase in recharge of 7% (RCP2.6) to 20% (RCP8.5), with rates expected to increase from approximately 702 mm a⁻¹ to a maximum of 770 mm a⁻¹ (RCP2.6), 785 mm a⁻¹ (RCP4.5) and 842 mm a⁻¹ (RCP8.5) by the end of the century, driven primarily by higher winter recharge. Although low recharge rates in summer show minimal change, analysis of the drivers indicates that increased evapotranspiration and decreasing rainfall will extend the periods of low recharge rates into autumn, intensifying potential water stress during warmer months. Moreover, groundwater temperatures are projected to increase together with air temperature, increasing from 10.8°C to 11.6°C (RCP2.6), 12.2°C (RCP4.5) and 13.6°C (RCP8.5) by the end of the century, representing an increase of between 7.5% (RCP2.6) and 26% (RCP8.5). Changes in air temperature mainly drive groundwater warming, whereas changes in recharge rates have minor effects. This study highlights the need for adaptive water management to address shifting seasonal groundwater recharge rates and rising temperatures in pre-alpine regions.

Alluvial systems are dynamic, structurally complex environments. Groundwater that is extracted from these systems is widely used for domestic consumption. Numerical models play an important role in the management of this extraction. To provide support for decision-making, models must assimilate data that inform the spatial and temporal dynamics of the interactions between alluvial surface water (SW) and groundwater (GW). In theory, assimilation of noble gas tracer data into numerical models that solve the advection-dispersion equation as it pertains to gas tracer concentrations can reduce the uncertainties of management-salient predictions made by these models. To date, however, this has not been undertaken; nor has its decision-support efficacy been tested. A modeling framework is introduced whereby data space inversion, a highly efficient method for evaluation of post-data-assimilation uncertainties of complex simulators, is used to evaluate benefits accrued through assimilation of noble gas tracer concentrations (i.e., ²²²Rn; ³⁷Ar; ⁴He) along with more classical observations. The ability of noble gas concentrations to reduce the uncertainties of predictions made using an integrated surface-subsurface hydrological model is rigorously evaluated in simulation experiments that span a range of plausible hydraulic and hydrological conditions. Outcomes of these experiments demonstrate that measurements of ²²²Rn and ⁴He concentrations are able to constrain temporally-variable predictions, such as the magnitudes of SW-GW exchange fluxes, as well as solute breakthrough curves that reflect the residence times of potential pollutants following an aquifer contamination event. ³⁷Ar concentrations can also provide important information on SW-GW interactions, especially the residence times of bank filtrate.