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Record W4410757125 · doi:10.15292/acta.hydro.2025.02

Comparative Hydrological Analysis at Two Stations on the Boundary River Sotla/Sutla (Slovenia–Croatia)

2025· article· en· W4410757125 on OpenAlexaff
Ognjen Bonacci, Ana Žaknić‐Ćatović, Tanja Roje-Bonacci

Bibliographic record

VenueActa hydrotechnica · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersEuropean Regional Development FundEuropean Commission
KeywordsBoundary (topology)Hydrology (agriculture)GeographyWater resource managementEnvironmental scienceGeologyMathematicsGeotechnical engineering

Abstract

fetched live from OpenAlex

This study examines hydrological processes at the Zelenjak (1958–2023) and Rakovec (1926–2022) stations on the Sotla/Sutla River, analyzed on an annual time scale. The analysis includes time series of annual minimum and maximum mean daily flows and mean annual flows. Additionally, data on annual precipitation and mean annual temperatures measured at the climatological station Bizeljsko in the period 1951 to 2024 were used to calculate annual runoff coefficients at the Zelenjak and Rakovec stations. The New Drought Index (NDI) was calculated using precipitation and air temperature data measured at the Bizeljsko climatological station. All analyses indicated a strong variability of the analyzed parameters over the available data period. A clear downward trend in mean annual flows is observed. In the recent period, from 2000 onward, there has been a sharp increase in mean annual air temperatures and a decline in all other analyzed hydrological and climatological parameters. Particularly concerning is the notable rise in the frequency and intensity of droughts in the 2000–2024 period. The causes of these trends could not be reliably determined through an analysis conducted on an annual time scale. It appears that natural factors, particularly the sharp rise in air temperatures, have played a significant role. However, it is important to emphasize that the natural characteristics of the Sotla/Sutla River basin have, to date, remained largely unaffected by human interventions. Furthermore, the insufficient accuracy in defining peak flows must be considered, as the rating curves used to define maximum flows may not have been reliable in certain periods.

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 score0.064
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.275
Teacher spread0.256 · 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

Citations3
Published2025
Admission routes1
Has abstractyes

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