Abstract
Groundwater extracted from alluvial aquifers close to rivers is vulnerable to contamination by infiltrating river water. Infiltration is often increased during high discharge events, when the levels of waterborne pathogens are also increased. Water suppliers with low-level treatment thus rely on alternative measures derived from information on system state to manage the resource and maintain drinking-water quality. In this study, a combination of Self-Organizing Maps and Sammon’s Mapping (SOM-SM) was used as a proxy analysis of a multivariate time-series to detect critical system states whereby contamination of the drinking water extraction wells is imminent. Groundwater head, temperature and electrical conductivity time-series from groundwater observation wells were analysed using the SOM-SM method. Independent measurements (spectral absorption coefficient, turbidity, particle density and river stage) were used. This approach can identify critical system states and can be integrated into an adaptive, online, automated groundwater-management process.
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Acknowledgments
The authors thank Stefan Scheidler from the Applied and Environmental Geology Group, University of Basel, Endress+Hauser Metso AG and the Waterworks Reinach and Surroundings (WWRuU) for their support. This work was funded by the Swiss Innovation Promotion Agency CTI (projects number 8999.1 PFIW-IW and 12611.2 PFIW-IW) and the Freiwillige Akademische Gesellschaft Basel.
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Page, R.M., Huggenberger, P. & Lischeid, G. Multivariate Analysis of Groundwater-Quality Time-Series Using Self-organizing Maps and Sammon’s Mapping. Water Resour Manage 29, 3957–3970 (2015). https://doi.org/10.1007/s11269-015-1039-2
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DOI: https://doi.org/10.1007/s11269-015-1039-2