A synthesis of worldwide sediment source tracing research including fallout radiocesium (Cs-137)
Bibliographic record
Abstract
Quantifying the main sources delivering harmful sediment loads to river systems is required to improve our knowledge of soil erosion processes. Among these potential sources, quantifying the contributions of surface (e.g. cultivated topsoil) and subsurface (e.g. channel bank, gully, landslide) material to sediment transiting river systems is of particular interest. Radiocesium (137Cs) that was emitted during the atmospheric bomb tests that took mainly place in the 1960s and nuclear accidents provides an effective tracer to distinguish between topsoil material exposed to the fallout and subsoil sheltered from this fallout. A global synthesis of research articles (n=123) that used radiocesium to fingerprint sediment sources indicated that the largest number of publications (~55% of the total) were found in the United Kingdom, Australia and the United States. On the contrary, very few studies (~9% of the total) were published for catchments located in Africa or South America. Given the low proportion of fallout recorded in regions located between 0-20°N and 0-20°S, the potential of this technique for quantifying sediment source contributions may be limited in this part of the world. A similar conclusion may be drawn for applying this method in agricultural areas exposed to several soil erosion during the last several decades, such as Chinese Loess Plateau and South Africa. Overall, 94% of studies incorporating 137Cs as a potential tracer included this property in mixing models. In the future, given the continuous decay of the initial radiocesium fallout that peaked in the 1960s, the access to ultra-low background gamma-ray spectrometry facilities will be increasingly necessary to measure this important sediment tracing property. In addition, more research should be devoted to develop surrogate tracers providing discrimination between surface and subsurface material. Based on this extensive study review, researchers are also recommended to systematically include basic catchment information, details on the soil/sediment sampling design and access to raw data to facilitate the dissemination of this information among the communities of scientists and catchment managers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.037 | 0.038 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.004 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".