Impacts of Floods on Organic Carbon Concentrations in Alluvial Soils along Hydrological Gradients Using a Digital Elevation Model (DEM)
Bibliographic record
Abstract
This study examines the spatial distribution of the organic carbon found in alluvial soils affected by successive floods. In flood zones, very little is known of the processes associated with the development of soils subjected to frequent flooding, in particular with respect to the accumulation of litter and organic carbon concentrations. The aim of this study is to better understand the distribution of organic carbon based on various hydrological gradients associated with flood recurrence. A digital elevation model was developed from LIDAR data to assess the microtopography of the site, and further delineate floodplains and no-flood zones. Various soil properties were considered in addition to organic carbon, such as pH, soil bulk density, litter, drainage, and topographic levels (elevation). The results show that the soils in the frequent-flood zones (FFz, recurrence of 0–20 years) have significantly less total organic carbon than the soils in the no-flood zones (NFz) and the moderate flood zones (MFz, 20–100 years). Average values obtained for the surface horizons (0–20 cm) vary by 1.74% ± 0.85% (FFz), 3.34% ± 1.09% (MFz) and 3.54% ± 1.77% (NFz), respectively. The absence of ground litter in the frequent flood zones helps decrease the input of organic matter in the surface horizons and progressively results in soil depletion.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".