BRIDGE - Integrierte hydrologische Modellierung für operationelle Vorhersage und Entscheidungsfindung
80% des Trinkwassers der Schweiz stammen aus Grundwasser. Durch den Klimawandel bedingte Dürreperioden und eine steigende Nachfrage nach Bewässerungsanlagen setzen das Grundwasser unter erheblichen Druck. Die Grundwassermodellierung spielt eine wichtige Rolle im Umgang mit dieser wertvollen Ressource. Es besteht jedoch ein sehr grosses Potenzial, die derzeitige Modellierungspraxis zu verbessern, vor allem durch eine verbesserte Charakterisierung des Untergrunds und durch eine realistischere Repräsentation der Wechselwirkungen zwischen Oberflächengewässern und Grundwasser.
Dieses Projekt basiert auf folgenden gemeinsamen Entwicklungen der Eawag, der Université de Neuchâtel (UNINE) und der Universität Basel (UNIBAS): (1) Durch den Einsatz modernster Massenspektrometrie ergänzen wir die vorhanden Markierstoffe für Gewässer durch nichttoxische Gase, welche in den Untergrund injiziert werden können. Dadurch erweitern wir die räumliche und zeitliche Skala der verfügbaren Markiermethoden und ermöglichen neue Wege zur Charakterisierung des Untergrunds. (2) Durch den Aufbau von integrierten Modellen ermöglichen wir die gekoppelte Simulation von hydrologischen Prozessen an der Oberfläche, im Untergrund und von betrieblicher Infrastruktur wie Pumpen, Drainagen und Bewässerungssystemen. Durch die explizite Simulation von Markierstofftransport wird die Modellkalibrierung zudem wesentlich robuster. (3) Durch die Entwicklung neuer technischer sowie rechnerischer Methoden für die Echtzeit-Assimilation von Daten gewährleisten wir, dass die hydrologischen Modelle immer nahe am realen Systemzustand sind und somit kontinuierlich zur Unterstützung der operativen Entscheidungsfindung genutzt werden können.
BRIDGE wird es ermöglichen, diese drei neuen Entwicklungen zu kombinieren und auf eine operationelle Ebene zu bringen. In enger Zusammenarbeit mit involvierten Interessensgruppen entwickeln und bewerten wir die Effizienz unserer hydrologischen Dienstleistung anhand zweier Pilotstudien: eine zur Steigerung der Effizienz der Bewässerung im Gemüsebau und eine zur Trinkwasserproduktion in einem komplexen urbanen Umfeld.
Hugo Delottier, Hydrogeological Processes, Centre for Hydrogeology and Geothermics (CHYN), University of Neuchâtel, Switzerland
Qi Tang, Hydrogeology Research Group, Department of Environmental Sciences, University of Basel, Switzerland
Morgan Peel, Environmental Isotopes Group, W+T, Swiss Federal Institute of Aquatic Science and Technology (EAWAG), Switzerland
Annette Affolter Kast, Hydrogeology Research Group, Applied and Environmental Geology Working Group, Department of Environmental Sciences, University of Basel, Switzerland
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title => protected'Assessing the worth of noble gas tracer concentrations in alluvial river-aqu ifer systems using data space inversion' (115 chars)
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description => protected'Alluvial systems are dynamic, structurally complex environments. Groundwater that is extracted from these systems is widely used for domestic consumptio n. Numerical models play an important role in the management of this extract ion. To provide support for decision-making, models must assimilate data tha t inform the spatial and temporal dynamics of the interactions between alluv ial surface water (SW) and groundwater (GW). In theory, assimilation of nobl e gas tracer data into numerical models that solve the advection-dispersion equation as it pertains to gas tracer concentrations can reduce the uncertai nties of management-salient predictions made by these models. To date, howev er, 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 uncertainti es of complex simulators, is used to evaluate benefits accrued through assim ilation of noble gas tracer concentrations (i.e., <sup>222</sup>Rn; <sup>37< /sup>Ar; <sup>4</sup>He) 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 eva luated in simulation experiments that span a range of plausible hydraulic an d hydrological conditions. Outcomes of these experiments demonstrate that me asurements of <sup>222</sup>Rn and <sup>4</sup>He 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 resi dence times of potential pollutants following an aquifer contamination event . <sup>37</sup>Ar concentrations can also provide important information on S W-GW interactions, especially the residence times of bank filtrate.' (1891 chars)
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description => protected'Dissolved noble gases have been recognized for decades as ideal artificial h ydro(geo)logical tracers, as they are chemically inert, invisible, and non-t oxic. However, their widespread adoption has historically been limited by th e difficulty of tracer injection, sampling, and analysis procedures. Develop ments in portable, high-resolution dissolved gas measurement technology over the last two decades have rekindled interest in the use of gas tracer metho ds for routine hydrogeological investigations, such as well-to-well tracer t ests, intra-well tests, or studies of river infiltration towards alluvial aq uifers. The application of gases in aqueous environments still poses unique challenges compared to other tracer methods, as potential exsolution and deg assing need to be accounted for, and, if possible, avoided during tracer inj ection. Here, we present a simple and efficient methodology that addresses t hese challenges and allows the efficient, on-site preparation and injection of highly concentrated tracer solutions with controlled dissolved gas concen trations. We applied the method in a large drinking water wellfield and perf ormed well-to-well tracer tests in an unconfined aquifer using helium-4 (<su p>4</sup>He), neon-20 (<sup>20</sup>Ne) and krypton-84 (<sup>84</sup>Kr). Kn own tracer quantities were injected together with fluorescent dyes into an o bservation well upgradient of a pumping well. Gas tracer breakthrough was mo nitored in the pumping well with a portable mass spectrometer. Breakthrough curves of <sup>4</sup>He and <sup>84</sup>Kr compared favorably with fluores cent dye tracers, and enabled reliable estimates of groundwater flow velocit ies, 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 ra nge of artificial tracer...' (2055 chars)
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Assessing the worth of noble gas tracer concentrations in alluvial river-aquifer systems using data space inversion
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.
Delottier, H.; Peel, M.; Doherty, J.; Schilling, O. S.; Brunner, P. (2026) Assessing the worth of noble gas tracer concentrations in alluvial river-aquifer systems using data space inversion, Water Resources Research, 62(7), e2025WR041730 (37 pp.), doi:10.1029/2025WR041730, Institutional Repository
Fischer, M.; Delottier, H.; Tang, Q.; Schilling, O. S.; Schiavoni, V.; Brunner, P. (2026) An automated IoT-Based infrastructure for real-time soil water deficit prediction, In: Nunes Alonso, A.; Palmieri, R. (Eds.), Distributed applications and interoperable systems. 26th IFIP WG 6.1 international conference, DAIS 2026, held as part of the 21st international federated conference on distributed computing techniques,, 105-120, doi:10.1007/978-3-032-27358-1_7, Institutional Repository
A controlled and scalable noble gas injection method for quantitative tracer tests in hydrogeological 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.
Peel, M.; Solanki, K.; Brunner, P.; Hunkeler, D.; Schilling, O. S.; Kipfer, R. (2026) A controlled and scalable noble gas injection method for quantitative tracer tests in hydrogeological studies, Water Research, 294, 125505 (10 pp.), doi:10.1016/j.watres.2026.125505, Institutional Repository
