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Record W4392598654 · doi:10.5194/egusphere-egu24-3797

Multivariate statistical analysis of groundwater geochemistry to characterize flow in the Kurikka buried valley aquifer system, Western Finland

2024· preprint· en· W4392598654 on OpenAlexaff
Marie-Amélie Pétré, Niko Putkinen, Timo Ruskeeniemi, René Lefebvre

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsAquiferGroundwaterGeologyGroundwater flowMultivariate statisticsGeochemistryMultivariate analysisAquifer propertiesHydrology (agriculture)GeomorphologyGeotechnical engineeringGroundwater rechargeStatisticsMathematics

Abstract

fetched live from OpenAlex

The Kurikka buried valley aquifer system (Western Finland) contains significant groundwater resources in coarse-grained sediments alternating with till layers. Over the past 10 years, this multilayered aquifer system has been the object of growing interest to increase the water supply to the towns of Vaasa, Kurikka and nearby municipalities. In this context, it is important to understand the groundwater flow system to assess its sustainable exploitation rate and implement sustainable management of this resource. The goal of this study was to assess groundwater quality in the Kurikka aquifer system and interpret the geochemical data to better understand groundwater flow patterns. This goal was achieved through the geochemical characterization of groundwater and the use of multivariate statistical analysis to interpret results. The study area (600 km2) encompasses 4 buried valleys connected to the main Kyrönjoki valley. Compilation of historical geochemical data (56 samples) from 2011-2021 was completed in June-August 2023 by a large groundwater sampling campaign (42 samples) from observation wells, bedrock boreholes, production wells and springs, covering all parts of the study area. Samples were analyzed for major ions, minor and trace elements and tritium analyses were performed on a subset of 25 samples. Multivariate statistical analysis (Hierarchical Clustering and Principal Components) was carried out based on 18 physicochemical parameters for 98 samples.Five water groups emerged from the hierarchical classification. The first three clusters (C1-C2-C3) represent water from sediments, cluster 4 corresponds to water from the bedrock in the upgradient areas and cluster 5 represents water from the bedrock deep beneath the buried valleys. The major recharge area is located to the west of the study area, in the topographic highs where less evolved, tritiated waters were found (C3). From the recharge area, groundwater flows to the north, east and south-east. A similar groundwater evolution from Ca-HCO3 to Na-HCO3 water types was observed in both sediments and bedrock in the recharge area (C4). This suggests there is either an evolution within the buried valleys themselves or the buried valleys act as discharge and mixing feature for the evolved bedrock waters. Groundwater from the northernmost buried valley and the northern part of the Kyrönjoki valley (C1) are geochemically distinct from the rest of the study area and contain tritiated waters, reflecting a different context of modern esker with a shallower system. Bedrock groundwater (C4-C5) are characterized by a lower pCO2 value and higher pH. While one bedrock borehole beneath the central Paloluoma buried valley showed a more evolved water type and was tritium-free, fresh groundwater was still found until 100 m depth, suggesting deep active flow in bedrock.This study will be complemented by an additional dataset of groundwater residence time tracers (3H, 14C) and isotope data (87Sr, 18O/2H) that will provide more information on groundwater origin and support the interpretation of the evolution of the water groups found in the Kurikka aquifer system.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.256
Teacher spread0.238 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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