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Record W4415386634 · doi:10.5194/hess-29-5383-2025

Explicit simulation of microbial transport with a dual-permeability, two-site kinetic deposition formulation using the integrated surface–subsurface hydrological model HydroGeoSphere

2025· article· en· W4415386634 on OpenAlexafffund
Friederike Currle, René Therrien, Oliver S. Schilling

Bibliographic record

VenueHydrology and earth system sciences · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicGroundwater flow and contamination studies
Canadian institutionsUniversité Laval
FundersSentinelle Nord, Université LavalSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsHydrology (agriculture)Deposition (geology)TRACERAquiferAdvectionHydraulic conductivitySubsurface flowWellheadHydrological modelling

Abstract

fetched live from OpenAlex

Assessing the transport behaviour of microbes in surface water–groundwater systems is important to prevent contamination of drinking-water resources by pathogens. While wellhead protection area (WHPA) delineation is predominantly based on dye injection tests and advective transport modelling, size exclusion of colloid-sized microbes from the smaller and usually less conductive pore spaces causes a faster breakthrough and thus faster apparent transport of microbes compared to that of solutes. To provide a tool for better assessment of the differences between solute and microbial transport in surface water–groundwater systems, here, we present the implementation of a dual-permeability, two-site kinetic deposition formulation for microbial transport in the integrated surface–subsurface hydrological model HydroGeoSphere (HGS). The implementation considers attachment, detachment, and inactivation of microbes in both permeability regions and allows for multispecies transport. The dual-permeability, two-site kinetic deposition implementation in HGS was verified against an analytical solution for dual-permeability colloid transport. The suitability of the model for microbial transport in integrated surface–subsurface hydrological settings at the wellfield or small headwater catchment scale is demonstrated by two illustrative examples. The first example is a benchmark for integrated rainfall–runoff and streamflow generation modelling to which we added microbial transport from a conceptual manure application, demonstrating the novelty of explicit and coupled microbial and solute transport simulations in an integrated surface–subsurface hydrological scenario. The second example is a multi-tracer flow and transport study of an idealized alluvial riverbank filtration site, in which we simulate in parallel the transport of reactive microbes, conservative 4 He, and reactive 222 Rn, demonstrating the assessment of mixing ratios, tracer breakthrough curves, and travel times in an integrated manner via multiple approaches. The developed simulation tool represents the first integrated surface–subsurface hydrological simulator for reactive solute and microbial transport and marks an important advancement to unlock and quantify governing microbial transport processes in coupled surface water–groundwater settings. It enables meaningful WHPA delineation and risk assessments of riverbank filtration sites with respect to microbial contamination even under situations of extreme hydrological and microbial stress, such as flood events.

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)0.000
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.238
Teacher spread0.222 · 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 designSimulation or modeling
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

Citations4
Published2025
Admission routes2
Has abstractyes

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