An Integrated Approach for Deciphering Hydrogeochemical Processes during Seawater Intrusion in Coastal Aquifers
Bibliographic record
Abstract
For managing the freshwater in the worldwide coastal aquifers, it is imperative to understand the hydrogeochemical processes and flow patterns in the mixing freshwater/saltwater zone. The Egyptian Nile Delta aquifer is a typical example. The management of seawater intrusion (SWI) requires detailed investigations of the intrusion wedge and the dynamic processes in the mixing zone. Thus, a multidisciplinary approach was applied based on holistic hydrogeochemical, statistical analysis, and DC resistivity measurements to investigate the lateral and vertical changes in groundwater characteristics undergoing salinization stressor. The results of cross plots and ionic deviations of major ions, hydrochemical facies evolution diagram (HFE-D), and seawater mixing index (SMI) were integrated with the resistivity results to show the status of the SWI where the intrusion phase predominates in ~2/3 of the study are (~70 km radius) and the compositional thresholds of Na, Mg, Cl, and SO4 are 600, 145, 1200, and 600 mg/L, respectively, indicating that the wells with higher concentrations than these thresholds are affected by SWI. Moreover, the results demonstrate the efficiency of combining hydrogeochemical facies from heatmap and resistivity investigations to provide a large-scale characterization of natural and anthropogenic activities controlling aquifer salinization to support decision-makers for the long-term management of coastal groundwater.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".