Integrating Bayesian Groundwater Mixing Modeling With On‐Site Helium Analysis to Identify Unknown Water Sources. Issue 12 (11th December 2019)

• Record Type: Journal Article
• Authors: Popp, Andrea L.; Scheidegger, Andreas; Moeck, Christian; Brennwald, Matthias S.; Kipfer, Rolf
• Is Part Of: Water resources research. Volume 55:Issue 12(2019)
• Page Start: 10602
• Page End: 10615
• Publication Date: 2019-12-11
• Subjects: groundwater mixing -- Baysian mixing modeling -- new tracer methods -- end‐member mixing -- helium -- conceptual model; Hydrology -- Periodicals; 333.91
• DOI: 10.1029/2019WR025677
• Languages: English
• ISSNs: 0043-1397

Abstract

Abstract: Analyzing groundwater mixing ratios is crucial for many groundwater management tasks such as assessing sources of groundwater recharge and flow paths. However, estimating groundwater mixing ratios is affected by various uncertainties, which are related to analytical and measurement errors of tracers, the selection of end‐members, and finding the most suitable set of tracers. Although these uncertainties are well recognized, it is still not common practice to account for them. We address this issue by using a new set of tracers in combination with a Bayesian modeling approach, which explicitly considers the possibility of unknown end‐members while fully accounting for tracer uncertainties. We apply the Bayesian model we developed to a tracer set, which includes helium ( 4 He) analyzed on site to determine mixing ratios in groundwater. Thereby, we identify an unknown end‐member that contributes up to 84 ± 9% to the water mixture observed at our study site. For the 4 He analysis, we use a newly developed Gas Equilibrium Membrane Inlet Mass Spectrometer (GE‐MIMS), operated in the field. To test the reliability of on‐site 4 He analysis, we compare results obtained with the GE‐MIMS to the conventional lab‐based method, which is comparatively expensive and labor intensive. Our work demonstrates that (i) tracer‐aided Bayesian mixing modeling can detect unknown water sources, thereby revealing valuable insights into the conceptual understanding of the groundwater system studied, and (ii) on‐site 4 He analysis with the GE‐MIMS system is an accurate and reliable alternative to the lab‐based analysis. Key Points: On‐site 4 He analysis reliably substitutes expensive and time‐consuming lab‐based 4 He analysis We present a Bayesian groundwater mixing model explicitly considering unknown end‐members and measurement uncertainty Unknown water sources can be identified by combining the Bayesian mixing model and 4 He analyzed on‐site