Abteilung Wasserressourcen und Trinkwasser

Wasserressourcen & Trinkwasser

Wir untersuchen die massgeblichen physikalischen und chemischen Prozesse in Grund-, Oberflächen- und Trinkwasser. Unsere Grundlagenforschung und angewandte Studien zu Wasserressourcen, ‑verschmutzung sowie ‑aufbereitung tragen wesentlich zur nachhaltigen Wassernutzung im nationalen und internationalen Kontext bei.

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Publikationen

Wu, R., Podgorski, J., Berg, M., & Polya, D. A. (2023). Pseudo contour maps from logistic regression modelling: case study of groundwater arsenic distribution in Gujarat state, India. In A. van der Wal, A. Ahmad, B. Petrusevski, J. Weijma, D. Savic, P. van der Wens, … R. Naidu (Eds.), Arsenic in the environment. Proceedings. Proceedings of the 8th international congress and exhibition on arsenic in the environment (As2021) (pp. 95-96). doi:10.1201/9781003317395-40, Institutional Repository

Logistic regression modelling is a widely used prediction method to generate probability maps
of groundwater arsenic exceeding a selected threshold concentration. In this study, we converted logistic regression modelled probability maps to a pseudo contour map which comprehensively integrated important information of several probability maps of groundwater arsenic concentrations in Gujarat state, India. The pseudo contour map of groundwater arsenic concentrations clearly and intuitively indicates high groundwater arsenic concentrations (>10 mg/L) occurring in Kachchh District and Banas Kantha District and shows groundwater arsenic concentrations in northern and central Gujarat to be slightly higher than near the western
and eastern borders of the state. The cutoffs, where sensitivity equals specificity, is one of the most appropriate criteria of diagnosis of continuous probability results, better ensuring the accuracy of the generation of a pseudo contour map. However, the probability cutoff of each contour is likely different, so that the generated map is pseudo-contour rather than a contour map.
Stopelli, E., Duyen, V. T., Mai, T. T., Trang, P. T. K., Viet, P. H., Lightfoot, A., … Berg, M. (2023). Interplay of As (im)mobilisation processes in groundwater: learning from hydrochemical investigations. In A. van der Wal, A. Ahmad, B. Petrusevski, J. Weijma, D. Savic, P. van der Wens, … R. Naidu (Eds.), Arsenic in the environment. Proceedings. Proceedings of the 8th international congress and exhibition on arsenic in the environment (As2021) (pp. 21-22). doi:10.1201/9781003317395-9, Institutional Repository

Millions of people worldwide are exposed to arsenic (As) contaminated groundwater. Despite decades of research and evidence of As mobilisation in anoxic aquifers being caused by reductive dissolution of iron minerals, the mechanisms behind the local scale variability of dissolved As remains unclear. Therefore, the trans-disciplinary AdvectAs project investigates the environmental behaviour and spatial heterogeneity of dissolved As in groundwater in the Red River delta, Vietnam. Here we present the results from hydrochemical and water isotope investigations. In particular, we will show how the large As variability (0.1–510 mg/L) is related to consecutive As (im)mobilisation steps, depending on site hydrology, geology and the interplay of Fe, Mn, S and organic matter cycles. Such complexity of (im)mobilisation processes can be simplified in 5 major hydro(geo) chemical zones, providing a conceptual tool with potential for application at other sites in Asia affected by geogenic As contamination of groundwater.
Podgorski, J., & Berg, M. (2023). Second-generation global risk map of groundwater arsenic contamination. In A. van der Wal, A. Ahmad, B. Petrusevski, J. Weijma, D. Savic, P. van der Wens, … R. Naidu (Eds.), Arsenic in the environment. Proceedings. Proceedings of the 8th international congress and exhibition on arsenic in the environment (As2021) (pp. 3-4). doi:10.1201/9781003317395-1, Institutional Repository

Naturally occurring arsenic in groundwater affects millions of people around the world. In order to assess the extent of this problem, we have used machine learning to create a global prediction map of groundwater arsenic greater than 10 mg/L. The resulting model includes already known arsenic-affected areas as well as new potentially contaminated areas. Combining the global arsenic prediction model with household groundwater-usage statistics, we estimate that 94–220 million people are potentially exposed to high arsenic concentrations in groundwater. As groundwater is increasingly utilized to support a growing population and buffer against increasing water scarcity due to a changing climate, this model will help raise awareness, identify suitable areas for safe wells and guide where testing for arsenic should be prioritized.
Höge, M., Kauzlaric, M., Siber, R., Schönenberger, U., Horton, P., Schwanbeck, J., … Fenicia, F. (2023). CAMELS-CH: hydro-meteorological time series and landscape attributes for 331 catchments in hydrologic Switzerland. Earth System Science Data, 15(12), 5755-5784. doi:10.5194/essd-15-5755-2023, Institutional Repository

We present CAMELS-CH (Catchment Attributes and MEteorology for Large-sample Studies – Switzerland), a large-sample hydro-meteorological data set for hydrologic Switzerland in central Europe. This domain covers 331 basins within Switzerland and neighboring countries. About one-third of the catchments are located in Austria, France, Germany and Italy. As an Alpine country, Switzerland covers a vast diversity of landscapes, including mountainous environments, karstic regions, and several strongly cultivated regions, along with a wide range of hydrological regimes, i.e., catchments that are glacier-, snow- or rain dominated. Similar to existing data sets, CAMELS-CH comprises dynamic hydro-meteorological variables and static catchment attributes.
CAMELS-CH (Höge et al., 2023; available at https://doi.org/10.5281/zenodo.7784632) encompasses 40 years of data between 1 January 1981 and 31 December 2020, including daily time series of stream flow and water levels, and of meteorological data such as precipitation and air temperature. It also includes daily snow water equivalent data for each catchment starting from 2 September 1998. Additionally, we provide annual time series of land cover change and glacier evolution per catchment. The static catchment attributes cover location and topography, climate, hydrology, soil, hydrogeology, geology, land use, human impact and glaciers. This Swiss data set complements comparable publicly accessible data sets, providing data from the “water tower of Europe”.

News

Lenny Winkel zur ETH-Professorin ernannt

19. September 2024

Lenny Winkel (*1975), zurzeit ausserordentliche Professorin an der ETH Zürich und Gruppenleiterin am Wasserforschungsinstitut Eawag, wurde vom ETH-Rat zur ordentlichen Professorin für Anorganische Umweltgeochemie am Department Umweltsystemwissenschaften ernannt.

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Forschungsprojekte

The project investigates what measures are most effective in influencing a river corridor so that river restoration and groundwater flow systems can help to mitigate the effects of floods and droughts.

Record Catchment
Die „Groundwater Assessment Platform“ (GAP) ermöglicht den einfachen Austausch von Daten und Informationen über geogene Inhaltsstoffe wie Arsen und Fluorid, die zu Verunreinigungen des Trinkwassers führen können

Grundwasser-Assessment Plattform

Weitere Forschungsprojekte