Multicomponent statistical analysis to identify flow and transport processes in a highly-complex environment

Moeck, Christian; Radny, Dirk; Borer, Paul; Rothardt, Judith; Auckenthaler, Adrian; Berg, Michael; Schirmer, Mario

doi:10.1016/j.jhydrol.2016.09.023

Cited by 32 publications

(46 citation statements)

References 55 publications

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“…Based on previous modeling studies (AUG , ; Moeck et al ) boundary conditions are set in the two aforementioned hydrogeologically relevant units: The Quaternary sand‐gravel, and the Upper Muschelkalk aquifers (Moeck et al ). For the Quaternary aquifer, a constant head boundary condition is set at the southern edge of the model domain between two piezometers (Figure ).…”

Section: Methodsmentioning

confidence: 99%

“…Groundwater flow is from southeast to northwest in the direction of the Rhine River (Figure c). Due to the low hydraulic conductivity of the Middle Muschelkalk ( sulphate zone ) together with a decreasing thickness of the Upper Muschelkalk, upwelling of regional groundwater into the Quaternary aquifer can occur (Figure d) (Moeck et al ). For our study area, Spottke et al () speculated that water extracted by large‐scale industrial pumping must contain water fractions from the deeper Muschelkalk aquifer.…”

Section: Study Area and Hydrogeologymentioning

confidence: 99%

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Pathline Density Distributions in a Null‐Space Monte Carlo Approach to Assess Groundwater Pathways

Moeck¹,

Molson

Schirmer

2019

Groundwater

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A null‐space Monte‐Carlo (NSMC) approach was applied to account for uncertainty in the calibration of the hydraulic conductivity (K) field for a three‐dimensional groundwater flow model of a major water supply system in Switzerland. The approach generates different parameter realizations of the K field using the pilot point methodology. Subsequently, particle tracking (PT) was applied to each calibrated model, and the resulting particles are interpreted as the spatial pathline density distribution of multiple sources. The adopted approach offers advantages over classical PT which does not provide a means for treating uncertainty originating from the incomplete description of subsurface heterogeneity. Uncertainty in the K field is shown to strongly influence the spatial pathline distribution. Pathline spreading is particularly evident in locations where the information content of the head observations does not sufficiently constrain the estimated parameters. Despite the predictive uncertainty, the pumped drinking water at the study site is most likely dominated by artificially‐infiltrated groundwater originating from the local infiltration canals. The model suggests that within the well field, the central pumping wells could be extracting regional groundwater, although the probability is relatively low. Nevertheless, a rigorous uncertainty assessment is still required since only a few realizations resulted in flow paths that support the field observations. Model results should therefore not be based on only one model realization; rather, an uncertainty analysis should be carried out to provide a sufficiently large suite of equally probable simulations that include all potential sources and pathways.

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Section: Methodsmentioning

confidence: 99%

Section: Study Area and Hydrogeologymentioning

confidence: 99%

Pathline Density Distributions in a Null‐Space Monte Carlo Approach to Assess Groundwater Pathways

Moeck¹,

Molson

Schirmer

2019

Groundwater

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“…The isotopic signatures of 115 samples of groundwater in and around the Calera aquifer were analyzed; the data are presented in the Supplementary File. [24][25][26]. Nevertheless, the groundwater samples in this study are clustered into four groups.…”

Section: Isotopic Composition Of Groundwater and Recharge Sitesmentioning

confidence: 98%

“…The d ranged between −0.85‰ and 82.94‰, with a mean of 32.76‰ ± 23.71‰. There are different multivariate methods to group the samples; one widely-used method is the Hierarchical Cluster Analysis (HCA) approach, which has been used in the clustering of groundwater samples by several investigations [24][25][26]. Nevertheless, the groundwater samples in this study are clustered into four groups.…”

Section: Isotopic Composition Of Groundwater and Recharge Sitesmentioning

confidence: 99%

Identifying Groundwater Recharge Sites through Environmental Stable Isotopes in an Alluvial Aquifer

Gonzalez-Trinidad

Pacheco-Guerrero

Júnez-Ferreira

et al. 2017

Water

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“…Traditionally, hydrogeochemical evolution along groundwater flow paths has primarily been identified by graphical methods depicting the concentrations of a limited number of major ions. Two main multivariate statistical techniques, hierarchical cluster analysis (HCA) and principal components analysis (PCA), are very useful in this regard (Moeck et al 2016). Two main multivariate statistical techniques, hierarchical cluster analysis (HCA) and principal components analysis (PCA), are very useful in this regard (Moeck et al 2016).…”

Section: Introductionmentioning

confidence: 99%

Hydrogeochemical Evolution Along Groundwater Flow Paths in the Manas River Basin, Northwest China

et al. 2018

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The impacts of long‐term pumping on groundwater chemistry remain unclear in the Manas River Basin, Northwest China. In this study, major ions within five surface water and 105 groundwater samples were analyzed to identify hydrogeochemical processes affecting groundwater composition and evolution along the regional‐scale groundwater flow paths using the multivariate techniques of hierarchical cluster analysis (HCA) and principal components analysis (PCA) and traditional graphical methods for analyzing groundwater geochemistry. HCA classified the groundwater samples into four clusters (C1 to C4). PCA reduced the dimensionality of geochemical data into three PCs, which explained 86% of the total variance. The results of HCA and PCA were used to identify three zones: “recharge,” “transition,” and “discharge.” In the recharge zone the groundwater type is Ca‐HCO3‐SO4 and is primarily impacted by the dissolution of calcite and silicate weathering. In the transition zone the groundwater type is Ca‐HCO3‐SO4‐Cl and is impacted by rock dissolution and reverse ion exchange. In the discharge zone the groundwater type is Na‐Cl and is impacted by evaporation and reverse ion exchange. In addition, anthropogenic activities impact the groundwater chemistry in the study area. The groundwater type generally changes from Ca‐HCO3‐SO4 in the recharge area to Na‐Cl in the discharge area along the regional‐scale groundwater flow paths. This study provides a process‐based knowledge for understanding the interaction of groundwater flow patterns and geochemical evolution within the Manas River Basin.

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Multicomponent statistical analysis to identify flow and transport processes in a highly-complex environment

Cited by 32 publications

References 55 publications

Pathline Density Distributions in a Null‐Space Monte Carlo Approach to Assess Groundwater Pathways

Pathline Density Distributions in a Null‐Space Monte Carlo Approach to Assess Groundwater Pathways

Identifying Groundwater Recharge Sites through Environmental Stable Isotopes in an Alluvial Aquifer

Hydrogeochemical Evolution Along Groundwater Flow Paths in the Manas River Basin, Northwest China

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