Rethinking Tracer Interpretation in Alpine Karst: Comparing Physically Plausible Models for Comprehensive Transport Assessment

Tracer tests in alpine karst aquifers often produce characteristic breakthrough curves, but turning them into reliable transport information remains difficult. Multiple peaks, strong asymmetry, and persistent tailing challenge many routinely applied models. We present a long-term tracer dataset from a karst spring in the Eisenerz Alps (Austria), comprising 15 tracer experiments conducted with the same setup over more than a decade. This exceptional consistency allows us to evaluate tracer transport across a wide range of hydrologic conditions and to systematically test how different modeling concepts respond to changing flow states. We examine the performance of commonly used approaches, from classical moment-based analyses and advection–dispersion models to mobile–immobile and multi-dispersion formulations. While more complex models offer greater flexibility, they also introduce issues of non-uniqueness, overfitting, and limited physical interpretability—especially when attempting to reproduce both peak structure and long-term tailing. Instead of favoring model simplicity or complexity, we focus on aligning model structure with the information content of the tracer data. Tracer transport is interpreted within a physically informed conceptual framework that integrates modeling results with independent evidence from local geology, hydrogeology, and speleological observations. This combination allows transport models to be constrained by system-specific knowledge, providing a more defensible basis for interpreting breakthrough curves across contrasting hydrologic conditions. By combining long-term tracer observations with physically constrained modeling and explicit uncertainty considerations, this contribution outlines a robust framework for interpreting alpine karst tracer tests—an essential step toward conservative assessments of contaminant persistence and risk at alpine karst springs.