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  • ddc:551.49  (2)
  • Blackwell Publishing Ltd  (2)
  • Copernicus
  • 2020-2023  (2)
  • 1945-1949
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  • 1
    Publikationsdatum: 2022-09-27
    Beschreibung: Little research attention has been given to validating clusters obtained from the groundwater geochemistry of the waterworks' capture zone with a prevailing lake‐groundwater exchange. To address this knowledge gap, we proposed a new scheme whereby Gaussian finite mixture modeling (GFMM) and Spike‐and‐Slab Bayesian (SSB) algorithms were utilized to cluster the groundwater geochemistry while quantifying the probability of the resulting cluster membership against each other. We applied GFMM and SSB to 13 geochemical parameters collected during different sampling periods at 13 observation points across the Barnim Highlands plateau located in the northeast of Berlin, Germany; this included 10 observation wells, two lakes, and a gallery of drinking production wells. The cluster analysis of GFMM yielded nine clusters, either with a probability ≥0.8, while the SSB produced three hierarchical clusters with a probability of cluster membership varying from 〈0.2 to 〉0.8. The findings demonstrated that the clustering results of GFMM were in good agreement with the classification as per the principal component analysis and Piper diagram. By superimposing the parameter clustering onto the observation clustering, we could identify discrepancies that exist among the parameters of a certain cluster. This enables the identification of different factors that may control the geochemistry of a certain cluster, although parameters of that cluster share a strong similarity. The GFMM results have shown that from 2002, there has been active groundwater inflow from the lakes towards the capture zone. This means that it is necessary to adopt appropriate measures to reverse the inflow towards the lakes.
    Beschreibung: Article impact statement: The probability of cluster membership quantified using an algorithm should be validated against another probabilistic‐based classifier.
    Beschreibung: Federal Ministry of Education and Research http://dx.doi.org/10.13039/501100002347
    Schlagwort(e): ddc:551.9 ; ddc:551.49
    Sprache: Englisch
    Materialart: doc-type:article
    Standort Signatur Erwartet Verfügbarkeit
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  • 2
    Publikationsdatum: 2022-04-01
    Beschreibung: We present a workflow to estimate geostatistical aquifer parameters from pumping test data using the Python package welltestpy. The procedure of pumping test analysis is exemplified for two data sets from the Horkheimer Insel site and from the Lauswiesen site, Germany. The analysis is based on a semi‐analytical drawdown solution from the upscaling approach Radial Coarse Graining, which enables to infer log‐transmissivity variance and horizontal correlation length, beside mean transmissivity, and storativity, from pumping test data. We estimate these parameters of aquifer heterogeneity from type‐curve analysis and determine their sensitivity. This procedure, implemented in welltestpy, is a template for analyzing any pumping test. It goes beyond the possibilities of standard methods, for example, based on Theis' equation, which are limited to mean transmissivity and storativity. A sensitivity study showed the impact of observation well positions on the parameter estimation quality. The insights of this study help to optimize future test setups for geostatistical aquifer analysis and provides guidance for investigating pumping tests with regard to aquifer statistics using the open‐source software package welltestpy.
    Beschreibung: Article impact statement: We present a workflow to infer parameters of subsurface heterogeneity from pumping test data exemplified at two sites using welltestpy.
    Beschreibung: German Federal Environmental Foundation (DBU) http://dx.doi.org/10.13039/100007636
    Schlagwort(e): ddc:551.49
    Sprache: Englisch
    Materialart: doc-type:article
    Standort Signatur Erwartet Verfügbarkeit
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