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DGGV-E-Publikationen

Title: Multi-paprameter monitoring at alpine karst springs to identify suitable early-warning indicators for bacterial contamination

Authors:
Simon Frank, Nadine Goeppert, Nico Goldscheider

Institutions:
Karlsruhe Institute of Technology (KIT), Germany

Event: GeoKarlsruhe 2021

Date: 2021

DOI: 10.48380/dggv-8yhd-na58

Summary:
In alpine regions, karst springs are important sources of drinking water but highly vulnerable to temporary contamination, particularly in response to rainfall events. This variability of water quality requires rapid determination methods of contamination parameters. In this study, we present a multi-parameter approach to determine the dynamics of fecal bacteria, organic carbon and particles at alpine karst springs.

Conventional cultivation-based analysis of fecal bacteria such as E. coli is time-consuming. The measurement of the enzymatic activity of E. coli could prove to be a valuable tool for water-quality monitoring in near real time. We used an automated device (ColiMinder) to measure β-D-glucoronidase (GLUC) at an alpine karst spring. To assess the relations between GLUC activity, discharge dynamics and contamination patterns, multiple hydrochemical, physicochemical and microbiological parameters were measured in high resolution. We observed strong correlations between small particles (1.0 and 2.0 µm), conventional E. coli results, ATP measurements and total organic carbon. These parameters also show strong and significant negative correlations with the electrical conductivity. At high contamination levels, GLUC activity also reveals good correlations with E. coli and small particles.

The results demonstrate that the investigated karst springs showed fast and marked responses of all investigated water-quality parameters to rain events. At high contamination levels, GLUC and particle-size distribution are suitable parameters for the rapid assessment of bacterial contamination in high resolution. While GLUC activity alone cannot substitute conventional determination methods, a combined use of these parameters is a promising approach for an early-warning system regarding bacterial contamination.



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