Hydrological tracers rank among the most important tools in hydrogeology. They improve our conceptual understanding of hydrogeological systems and support quantitative insights into groundwater recharge, flow paths, hydrochemistry, and groundwater-surface water interactions. Recent advances in analytical techniques (e.g., for high-frequency analyses of dissolved noble gases and stable water isotopes directly in the field, or high-throughput sequencing of environmental DNA) allow precise measurement of an unprecedented range of physical, chemical, and biological tracers at spatial and temporal resolutions that were unthinkable just a few years ago. Additionally, modern computing resources finally enable explicit numerical simulation of the transport of hydrological tracers, as well as other relevant processes, from the local to the regional scale. The recent explosion of data assimilation and machine learning techniques complements state-of-the-art physically based numerical modelling and opens up many new possibilities for the interpretation of tracer data. We are undoubtedly in a golden age of tracer hydrogeology.
This Research Topic aims to showcase recent advances, innovations, and emerging methods in measuring, simulating, and interpreting hydrological tracers in groundwater studies. In particular, it seeks to highlight multidisciplinary approaches that provide an improved conceptual and/or quantitative understanding of complex hydrogeological systems. The goal of this Research Topic lies in improving groundwater tracer applications, methods, and our understanding of hydrogeological systems from the local to the regional scale. Because acquisition of hydrological tracers supports the decision-making process, the goal also lies in improving water resources management and making the exploitation of our precious groundwater resources more sustainable and adaptable to future anthropogenic and climatic perturbations.
For this Research Topic, we seek submissions that demonstrate how the measurement, application, modelling and interpretation of hydrological tracers provide us with an improved understanding of hydrogeological systems. Studies may employ any hydrogeological, ecohydrological, hydrochemical, hydro-economic, or water resource management perspective and can be based purely on tracer measurements or modelling of tracers, ranging anywhere from the local scale to the regional scale. Nonetheless, we explicitly encourage submissions of studies that integrate both field-based and numerical approaches via model-data fusion techniques. For example, suitable studies may involve advanced analytical tracer techniques, novel tracer applications, innovative tracer combinations, explicit tracer transport modelling, tracer-aided integrated surface-subsurface hydrological modelling, or tracer-model-data fusion techniques and machine learning.
The following types of articles are sought: Original research, Conceptual analysis, Report & Brief research report, Review & Mini review, Methods, Technology and code, Perspective, Opinion.
Hydrological tracers rank among the most important tools in hydrogeology. They improve our conceptual understanding of hydrogeological systems and support quantitative insights into groundwater recharge, flow paths, hydrochemistry, and groundwater-surface water interactions. Recent advances in analytical techniques (e.g., for high-frequency analyses of dissolved noble gases and stable water isotopes directly in the field, or high-throughput sequencing of environmental DNA) allow precise measurement of an unprecedented range of physical, chemical, and biological tracers at spatial and temporal resolutions that were unthinkable just a few years ago. Additionally, modern computing resources finally enable explicit numerical simulation of the transport of hydrological tracers, as well as other relevant processes, from the local to the regional scale. The recent explosion of data assimilation and machine learning techniques complements state-of-the-art physically based numerical modelling and opens up many new possibilities for the interpretation of tracer data. We are undoubtedly in a golden age of tracer hydrogeology.
This Research Topic aims to showcase recent advances, innovations, and emerging methods in measuring, simulating, and interpreting hydrological tracers in groundwater studies. In particular, it seeks to highlight multidisciplinary approaches that provide an improved conceptual and/or quantitative understanding of complex hydrogeological systems. The goal of this Research Topic lies in improving groundwater tracer applications, methods, and our understanding of hydrogeological systems from the local to the regional scale. Because acquisition of hydrological tracers supports the decision-making process, the goal also lies in improving water resources management and making the exploitation of our precious groundwater resources more sustainable and adaptable to future anthropogenic and climatic perturbations.
For this Research Topic, we seek submissions that demonstrate how the measurement, application, modelling and interpretation of hydrological tracers provide us with an improved understanding of hydrogeological systems. Studies may employ any hydrogeological, ecohydrological, hydrochemical, hydro-economic, or water resource management perspective and can be based purely on tracer measurements or modelling of tracers, ranging anywhere from the local scale to the regional scale. Nonetheless, we explicitly encourage submissions of studies that integrate both field-based and numerical approaches via model-data fusion techniques. For example, suitable studies may involve advanced analytical tracer techniques, novel tracer applications, innovative tracer combinations, explicit tracer transport modelling, tracer-aided integrated surface-subsurface hydrological modelling, or tracer-model-data fusion techniques and machine learning.
The following types of articles are sought: Original research, Conceptual analysis, Report & Brief research report, Review & Mini review, Methods, Technology and code, Perspective, Opinion.
