Saltwater Intrusion Vulnerability of Soil and Groundwater Near Estuaries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT Estuaries and the soil and groundwater surrounding them are increasingly vulnerable to the compounding effects of climate change. Despite their societal and ecological importance, surprisingly little consideration has been given to the vulnerability of soil and groundwater systems adjacent to estuaries. Here, we use global datasets to identify the spatial extent of at‐risk land near estuaries and present a literature review on how changing estuarine surface water may impact soil and groundwater in these areas. Approximately 150,000 km 2 of agricultural land and 23 of the world's megacities are located in low‐elevation coastal zones close to an estuary. Future sea‐level rise, storm surges, drought, and increased evaporation will increase the surface water salinity in many estuaries, while oceanic and fluvial drivers will likely result in more flooding in these low‐elevation zones. The spatial and temporal variations in surface water dynamics and conditions of individual estuaries (e.g., geology, bathymetry, tidal range) result in complex and highly variable groundwater‐surface water interactions in these settings. Field and modeling studies have indicated that increased exposure to saline or brackish water during estuarine flood events will result in soil salinization and vertical saltwater intrusion into underlying aquifers. Increased surface water levels and salinity can also lead to the lateral, subsurface migration of saline water into estuary bank sediments, potentially contaminating groundwater used for irrigation and human consumption. The salinization of soil and groundwater near estuaries may result in food and water insecurity in areas not previously considered at risk of coastal climate impacts.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.003 | 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 it