Status of seawater intrusion in Mexico: A review
Bibliographic record
Abstract
Study region: This review examines seawater intrusion in Mexico's coastal aquifers. Study focus: The review synthesizes current knowledge on seawater intrusion in Mexican coastal aquifers, documented since the 1980s. The study shows case studies including the extent of seawater intrusion, driving forces, and mitigation strategies. It reviews the commonly used approaches of seawater intrusion assessment in Mexico. The study discusses how climate change and sea level rise impact coastal groundwater resources. New hydrological insights for the region: Seawater intrusion has been documented in Mexican coastal states since the 1970s. Researchers focused on the Baja California Peninsula, Sonora, and the Yucatán Peninsula. Groundwater analysis reveals diverse intrusion patterns, with below-sea-level water tables extending up to 60 km inland and depths reaching −100 m in Sonora, while the Yucatán Peninsula maintains water tables above sea level. Each region presents distinct research priorities: Baja California faces severe water scarcity due to its arid climate, prompting strategies for water allocation and conservation; Baja California Sur emphasizes climate change impacts on water systems; Sonora's diverse geology necessitates advanced hydrogeological analysis to understand groundwater flow; and Quintana Roo faces heightened vulnerability to sea-level rise, particularly in tourist and ecological zones. This synthesis of seawater intrusion highlights the role of climate change, which directly links to human-induced pressures. The findings offer insights into coastal regions worldwide grappling with similar challenges from climate change and increasing water demand.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".