Variable 222Rn emanation rates in an alluvial aquifer: Limits on using 222Rn as a tracer of surface water – Groundwater interactions

Peel, Morgan; Kipfer, Rolf; Hunkeler, Daniel; Brunner, Philip

doi:10.1016/j.chemgeo.2022.120829

Cited by 14 publications

(4 citation statements)

References 46 publications

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“…In contrast, the radon concentration from the sediment matrix could increase with depth within the hyporheic zone (Gilfedder et al, 2019;Peel et al, 2022). We sampled from the upper first 20 cm of the river et al (2019), radon concentrations of the sediment matrix in this study were slightly higher than groundwater samples of BS1 and BS2 of similar concentration (Table 2).…”

Section: Uncertainties Related To the Detection Of Gaining Stream Con...mentioning

confidence: 63%

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Localizing and quantifying groundwater‐surface water interactions at different scales: A tracer approach at the River Moselle, Germany

Engel,

Mischel,

Quanz

et al. 2024

Hydrological Processes

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Groundwater‐surface water interactions (GSI) connect rivers and streams with riparian areas and the adjacent aquifer. Although these interactions exert a substantial control of quantity and quality of both groundwater and surface water, knowledge on GSI along rivers at the regional scale, particularly for inland waterways, is still limited. We investigated GSI along the river Moselle, an important federal inland waterway in Germany, by using radon and tritium to identify gaining (water flux from the aquifer to the surface water) and losing (water flux from the surface water to the aquifer) stream conditions, respectively. Gaining stream conditions were identified by continuously measuring radon along the river during boat surveys with a high spatial resolution (every 2 km) during intermediate (October 2020) and near low flow conditions (August/September 2021). The tritium concentrations in surface water and groundwater and the resulting tritium inventories were used to characterize losing stream conditions Monthly tritium inventories from 2017 to 2022 revealed a mean loss for the whole period of 20.3 % and a mean gain of 21.8%. Both were probably triggered by a combination of losing stream conditions and flood‐induced mass transfer of water from the aquifer back into the river as well as discharge fluctuations. At the investigated site Lehmen there were direct indications of an influence of surface water due to elevated tritium concentrations in the groundwater (up to 13.3 Bq L−1). Using radon mass balance modelling, good agreements of simulated versus measured radon data with respect to two groundwater end‐member scenarios were obtained during intermediate flow (Spearman's ρ: 0.97 and 0.99; MAE: 10.1 and 3.4 Bq L−1) and near low flow (Spearman's ρ: 0.97 and 0.99; MAE: 11 and 6.5 Bq L−1). Considerable groundwater inflow was limited to the meander of Detzem, where cumulated groundwater inflow of about 19 m3 s−1 (9.5% of total discharge) and 4.2 m3 s−1 (3.8% of total discharge) was simulated during intermediate and near low flow, respectively. However, the groundwater inflow was relatively low compared to alpine streams, for example. The study will help to better identify and quantify GSI at the regional scale and provide methodological guidance for future studies focusing on inland waterways.

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Section: Uncertainties Related To the Detection Of Gaining Stream Con...mentioning

confidence: 63%

“…In contrast, the radon concentration from the sediment matrix could increase with depth within the hyporheic zone (Gilfedder et al, 2019; Peel et al, 2022). We sampled from the upper first 20 cm of the river bed, while Gilfedder et al (2019) used radon concentrations from samples taken at 1 m depth.…”

Section: Discussionmentioning

confidence: 99%

Localizing and quantifying groundwater‐surface water interactions at different scales: A tracer approach at the River Moselle, Germany

Engel,

Mischel,

Quanz

et al. 2024

Hydrological Processes

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“…In previous studies, the geological or hydrogeological conditions were considered a key factor determining the spatial variability of LGD (Peel et al, 2022; Sun et al, 2022). The groundwater around Tangxun Lake correspond to various types with a complex distribution, which may be an important factor for the spatial variability of LGD (Figure 1d).…”

Section: Resultsmentioning

confidence: 99%

Spatial variability of lacustrine groundwater discharge in the largest urban lake in Asia: Coupled influence from land use and hydrogeology

Sun

et al. 2023

Hydrological Processes

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Lacustrine groundwater discharge (LGD) has a profound impact on the status of lake ecosystems. The distinct spatial variability of LGD has been acknowledged, but corresponding research has rarely been conducted, especially in urban lakes with changing land use. In this study, the spatial variability of LGD in Tangxun Lake, the largest urban lake in Asia, was quantitatively estimated using the 222 Rn mass balance model.Catchments with different land use and hydrogeological conditions within the study area are divided into five regions. The results revealed three ranges of the LGD rate in five regions: the first range of 25 mm/day (region II: 27.25 ± 8.38 mm/day and region IV: 23.04 ± 7.51 mm/day), the second range of 15 mm/day (region III: 14.16 ± 5.64 mm/day), and the third range of 10 mm/day (region I: 10.61 ± 4.31 mm/day, region V: 9.05 ± 3.60 mm/day). Here, we found that the LGD rate of urban lakes was

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“…The study site at the outlet of the upper Emme valley, a 194 km 2 alluvial headwater catchment in the Swiss Pre‐Alps (Figure 1a), has already served for multiple hydrogeological studies and is equipped with an extensive monitoring network (Figura et al., 2011, 2013; Käser & Hunkeler, 2015; Kropf et al., 2014; Lapin et al., 2014; Moeck et al., 2022; Peel et al., 2022; Popp et al., 2021; Schilling, Gerber, et al., 2017; Tang et al., 2018). GW is abstracted on a floodplain from 8 wells located 150–250 m away from the Emme river (Figure 1a).…”

Section: Methodsmentioning

confidence: 99%

Buried Paleo‐Channel Detection With a Groundwater Model, Tracer‐Based Observations, and Spatially Varying, Preferred Anisotropy Pilot Point Calibration

Schilling

Partington

Doherty

et al. 2022

Geophysical Research Letters

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Alluvial sand and gravel (ASG) aquifers are highly heterogeneous and exhibit strong, spatially variable anisotropy, often interspersed by buried paleo‐channels of increased hydraulic conductivity. Groundwater flow and solute transport is often characterized by preferential flow caused by anisotropic properties in ASG aquifers. Connected ASG subsurface structures such as buried paleo‐channels, however, are difficult to reproduce with commonly used techniques, and anisotropy is rarely considered in applied groundwater models. To ease the notoriously difficult problem of how to consider anisotropy, we propose a novel modeling framework based on calibration of an integrated surface‐subsurface hydrological model via spatially varying, preferred anisotropy pilot point inversion. The inversion leverages hydraulic and tracer‐based observations representing multiple spatial and temporal scales. We demonstrate the applicability of the framework on a real‐world ASG site used for drinking water production, and we quantify the information content of observations to identify connected paleo‐channels and provide guidance for optimal field‐data acquisition.

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Variable 222Rn emanation rates in an alluvial aquifer: Limits on using 222Rn as a tracer of surface water – Groundwater interactions

Cited by 14 publications

References 46 publications

Localizing and quantifying groundwater‐surface water interactions at different scales: A tracer approach at the River Moselle, Germany

Localizing and quantifying groundwater‐surface water interactions at different scales: A tracer approach at the River Moselle, Germany

Spatial variability of lacustrine groundwater discharge in the largest urban lake in Asia: Coupled influence from land use and hydrogeology

Buried Paleo‐Channel Detection With a Groundwater Model, Tracer‐Based Observations, and Spatially Varying, Preferred Anisotropy Pilot Point Calibration

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