Impacto urbano en la calidad y recarga del agua subterránea utilizando trazadores hidrogeoquímicos y ambientales en el acuífero de San Salvador
Bibliographic record
Abstract
Chemical and isotopic characteristics of the urban aquifer of San Salvador, drinking water (SAP) and wastewater systems (SAR), were evaluated in an area of 362 km2 to detect if leakages in both are recharging the aquifer and modifying its natural quality. An amount of 37 sampling sites that includes deep wells and springs, as well as two water import systems of the Metropolitan Area of San Salvador (AMSS) were sampled in 2007, 2009 and 2017. Samples were analyzed for major ions and stable isotopes of d18O and d2H. While the SAR was characterized by chemical tracers of Cl- and NO3-. Results show the existence of four water groups: Groups A (Ca-Mg-HCO3), B (Mg-Ca-HCO3) and D (Na-Ca-HCO3) have meteoric water as their main source of recharge, hence, they do not evidence urban influence in their quality; group C (Na-Ca-HCO3 and Na-Mg-HCO3) is derived from group A, flows under the AMSS and suggests three sources of recharge: Direct natural recharge due to precipitation along urban recharge from SAP and SAR leakages. An expensive “fictitious sustainability” could be perceived due to the quantitative contribution of the SAP recharge, which would be hiding the effects of the extractions and consequently the decrease of groundwater levels in the aquifer. Meanwhile, SAR recharge forewarn of a potential entry of pollutants into the aquifer that must be monitored and treated in a timely manner to avoid contamination. The study highlights the need of an integrated urban water resources management.
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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 | 0.001 |
| 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".