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Stratégies graduées d’évaluation des risques environnementaux induits par les sédiments fluviaux : revue bibliographique sur la caractérisation des risques et des incertitudes associées

2011· article· en· W3175786701 on OpenAlexaff
Marc Babut, Letícia de Campos Velho Martel, Philippe Ciffroy, J.F. Férard

Bibliographic record

VenueEnvironnement Ingénierie & Développement · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSoil erosion and sediment transport
Canadian institutionsGDG Environnement
Fundersnot available
KeywordsDredgingContext (archaeology)Risk assessmentEnvironmental scienceRisk managementEnvironmental resource managementEnvironmental planningComputer scienceBusinessGeographyGeology

Abstract

fetched live from OpenAlex

Sediments are an essential component of fluvial ecosystems; in the meantime, they can also disturb these systems and their uses. Management of these perturbations, for instance dredging, may also yield adverse effects on the environment; these adverse effects may be increased as sediments are prone to accumulate metals or hydrophobic organic substances. Several industrialized countries have adopted assessment frameworks for sediments; these frameworks have progressively shifted from hazard to ecological risk assessment. Most frameworks are tiered, and involve increasingly sophisticated approaches at higher tiers. In the context of DIESE, a research project granted by the French national research agency (ANR) and aiming to develop a sediment assessment framework for sediments stored upstream dams; we performed a literature survey, with a focus on risk characterization and uncertainty assessment. The sediment assessment frameworks can be grouped in two categories: (i) some derive from the “triad” concept, where the results of the assessment determine the applicable management option; (ii) in the second group, analyses are tuned as a function of the selected management option. Rather few papers cope with risk characterization; in the case of sediments, the very nature of variables contributing to risk leads to qualitative or semi-quantitative methods. Considering that there are other important sources of uncertainty than measurement errors, again qualitative or semi-quantitative methods are more appropriate. Recent developments, in particular in North America, aim to propose comparative risk assessment approaches, allowing to assess and compare several management options (e.g. dredging followed by either water or land disposal), instead of assessing them successively, if the option selected initially is deemed too risky. Another innovative perspective would be to characterize the risks to ecosystems in terms of the services they provide. Les sédiments sont une composante essentielle des écosystèmes fluviaux, en même temps qu’une source de perturbations de leurs usages. Les mesures correctives de ces perturbations, par exemple le dragage, sont également susceptibles d’impacts environnementaux, d’autant plus que les sédiments sont particulièrement susceptibles d’accumuler des substances chimiques dangereuses telles que métaux ou composés organiques hydrophobes. Plusieurs pays industrialisés ont adopté des démarches d’évaluation, d’abord du danger, puis plus récemment des risques environnementaux engendrés par les sédiments. Beaucoup de ces démarches procèdent par étapes successives, mobilisant si nécessaire des moyens de plus en plus sophistiqués. Dans le cadre du projet ANR-PRECODD DIESE (Outils de DIagnostic de l’Ecotoxicité des SEdiments), dont l’un des objectifs est de développer une démarche d’évaluation applicable aux sédiments de retenue, nous avons procédé à une revue bibliographique de démarches d’évaluation existantes, en concentrant plus particulièrement nos efforts sur la caractérisation des risques et des incertitudes associées, qui restent des points délicats actuellement. Ces démarches peuvent être classées en deux catégories, celles relevant de l’approche « triade » où l’on applique une batterie prédéterminée d’analyses, dont les résultats déterminent l’option de gestion applicable, et celles où l’option de gestion est choisie a priori et les analyses adaptées en conséquence. Peu de publications abordent le sujet de la caractérisation des risques, qui dans le cas des sédiments doit combiner des informations de natures différentes, ce qui conduit à des approches qualitatives ou au mieux semi-quantitatives. Dans la mesure où les sources d’incertitude ne se limitent pas aux erreurs de mesure, une approche semi-quantitative apparaît là aussi plus adaptée. Les développements en cours notamment en Amérique du Nord visent des démarches comparatives d’évaluation des risques, ce qui permettrait de comparer directement plusieurs options de gestion (dragage puis dépôt en eau ou mise à terre par exemple) plutôt que de procéder successivement. Une autre perspective innovante serait de caractériser les risques en termes de « services rendus » par les écosystèmes.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.101
GPT teacher head0.270
Teacher spread0.169 · 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 teacher head, not a consensus.

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

Citations1
Published2011
Admission routes1
Has abstractyes

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