Evaluating groundwater salinity patterns and spatiotemporal dynamics in complex endorheic aquifer systems
Bibliographic record
Abstract
Understanding salinity dynamics in endorheic aquifer systems is crucial for effective water resource management in arid regions. These environments, often characterized by intense agriculture and limited freshwater availability, are particularly vulnerable to water scarcity and salinity. The Bahira plain in central Morocco exemplifies such conditions, where groundwater salinity threatens both water quality and agricultural productivity. This research provides a comprehensive geochemical and isotopic assessment of salinity sources and evolution in both unconfined and confined aquifers within an endorheic basin. 213 groundwater samples from two aquifers were analyzed for major ions and stable isotopes. The findings reveal contrasting salinity levels, with the unconfined aquifer exhibiting hyper-salinity (EC up to 60,000 μS.cm −1 ) attributed to excessive evaporation and soil leaching, whereas the confined aquifer displays comparatively lower EC levels (500 to 3000 μS.cm −1 ). The spatial distribution of salinity reflects underlying variability in recharge and hydrogeological connectivity across the basin. To evaluate salinity variation and ionic imbalances, a binary mixing model was applied, providing insights into dominant hydrogeochemical processes. Geochemical observations emphasize the importance of water-rock interactions in controlling groundwater salinity, further intensified by high evaporation rates. Stable isotopic studies corroborate these observations, demonstrating evaporative enrichment and distinguishing between local recharge sources for the unconfined aquifer and regional input from high-elevation precipitation in the confined aquifer. These observations sharpen notions of hydrogeochemical processes in endorheic basins, emphasizing the array of climatic, geologic, and anthropogenic factors that control groundwater quality. The findings have broader implications for sustainable water management in similar dryland ecosystems worldwide.
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.
How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".