Sediment deposition in riparian zones exacerbates saltwater intrusion
Bibliographic record
Abstract
Coastal farmland is becoming increasingly exposed to flooding due to climate change. Inundation can lead to groundwater and soil degradation through saltwater intrusion. Much of the research investigating saltwater intrusion is focused along the marine coast; however, as storm intensity and sea levels rise, transitional coastal areas not previously susceptible to salinization may be at risk. Flood-derived sediment deposits may provide an overlooked salinity source in estuarine and upriver areas, even where floodwater salinity is relatively low. This study was conducted to evaluate the impact of subaerial flood deposits on underlying soil and porewater. A parcel of agricultural land in an estuarine floodplain in Nova Scotia, Canada, was selected to assess the subsurface response to repeated, low-salinity flooding. The site experienced inundation by fortnightly tidal floodwater following a managed dike realignment, resulting in dynamic surficial alteration. A three-year field campaign, including soil and water monitoring, geophysical surveying, and drone-based LiDAR surveying, was conducted to monitor changes to the site geomorphology and water and sediment chemistry. A one-dimensional numerical solute transport and vertical water flow model informed by field data was applied to investigate the hypothesis that saline sediment deposits can drive downward saltwater intrusion in areas experiencing brackish or low-salinity flooding. Results revealed that the soil concentrations exceeded that of the brackish floodwater by up to 50 times, with the highest salinization occurring preferentially in areas experiencing persistent deposition. Model results showed that soil salinization may persist for decades longer than the duration of flooding; however, removing these deposits through erosion resulted in soil and groundwater recovery. This study highlights the potential importance of flood-derived sediments for exacerbating saltwater intrusion in riparian areas along estuaries, which were not previously thought to be at risk of saline flooding.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".