39 Understanding Karst Hydrology and Karst Aquifers Using Innovative Tracers and Other Technologies

We welcome submissions applying innovative tracers and other technologies to investigate karst hydrology and karst aquifers, including but not limited to complex interactions between surface water and groundwater, recharge processes, flow pathways, sediment transport, sustainability, and susceptibility to contaminants.

Sunday, 19 October 2025
1:30 PM - 5:30 PM
HBGCC, 211

Deconvoluting Dye Fluorescence for Multi-Dye-Based Quantitative Water Tracing

Paper number: 39-13
Program: Technical Sessions
Time: 4:40 PM – 4:55 PM

Authors

Abstract

Fluorescent dye tracing is an essential tool for studying flow path distribution, networks, and connectivity in complex hydrogeologic systems such as karst environments. The breakthrough curve, derived from high-frequency measurements of dye concentration at a downstream location, provides quantitative insights into water travel time distribution. However, accurately determining dye concentrations can be challenging due to the presence of natural organic materials (NOMs) such as humic acids, fulvic acids, and chlorophylls, all of which contribute background fluorescence that can obscure dye signals. This study presents a robust, automated spectral deconvolution method for precisely quantifying fluorescent dye concentrations during hydrologic tracing.

By employing an automated multi-peak fitting algorithm, equipped with fluorescence peak information for both common NOMs and dye compounds, the framework efficiently separates dye fluorescence from background signals caused by NOMs. It is resilient to NOM interference and can handle the large data sets generated by high-frequency water sampling required for breakthrough curve estimation. To evaluate the method, three field dye tracing campaigns were conducted, comparing the proposed approach with the standard in-situ fluorometer-based method. Results show improvements in both precision and processing speed with the proposed method. The Python-based software and field data are openly available, enabling the research community to adopt and build upon this platform for more effective tracer studies in karst systems.

Geological Society of America Abstracts with Programs. Vol. 57, No. 6

doi: 10.1130/abs/2025AM-414643

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