MétaCan
Menu
Back to cohort
Record W7114765137 · doi:10.3390/hydrology12120329

Development of an Adapted Water Quality Index for the Danube River Using Objective Weighting Methods

2025· article· en· W7114765137 on OpenAlexaboutno aff

Bibliographic record

VenueHydrology · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
FundersHORIZON EUROPE Framework ProgrammeEuropean Commission
KeywordsWater qualityWeightingHydrology (agriculture)Index (typography)Robustness (evolution)Index methodBiochemical oxygen demandNitrate

Abstract

fetched live from OpenAlex

The Danube River is one of Europe’s largest transboundary rivers, characterized by substantial spatial heterogeneity in environmental conditions, monitoring practices, and water management frameworks. Developing a harmonized approach for basin-wide surface-water quality assessment is therefore essential. This study presents the development and application of an adapted Water Quality Index (Danube WQI) for assessing and monitoring water quality along the Danube River, one of Europe’s largest and most complex transboundary systems. The Danube WQI is based on established WQI methodologies and integrates two objective weighting approaches—the Entropy Weight Method (EWM) and the CRITIC (Criteria Importance Through Inter-Criteria Correlation) method—to minimize subjectivity and improve the robustness of parameter weighting. Long-term water quality data from the TransNational Monitoring Network (TNMN) of the International Commission for the Protection of the Danube River (ICPDR) were used, covering 42 stations across nine countries (1996–2022). Nine parameters were selected: dissolved oxygen (DO), biochemical oxygen demand (BOD5), total nitrogen (TN), nitrate (NO3), ammonium (NH4), total phosphorus (TP), orthophosphate (PO4), electrical conductivity (EC), and pH. During the formation of sub-indices and rating curves, national water quality standards from the Danube countries were harmonized to ensure consistent parameter classification. Results indicate that the Danube River generally exhibits very good water quality, with most sections belonging to the first and second quality classes. Comparison with the Canadian Water Quality Index (CWQI) confirmed similar results but demonstrated higher seasonal sensitivity of the Danube WQI. Additionally, rankings obtained using the PROMETHEE II multicriteria method showed strong agreement with the Danube WQI classifications, further confirming the robustness of the proposed index. The proposed index provides a harmonized and transferable framework that can support integrated water management and policy evaluation across the Danube River Basin and within the EU Water Framework Directive context.

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)0.003
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.074
GPT teacher head0.405
Teacher spread0.331 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueHydrologySame topicWater Quality and Pollution AssessmentFrench-language works237,207