Sustainable Water Management for Azraq Geopark: Enhancing Environmental Sustainability and Geotourism
Bibliographic record
Abstract
This research is centered on the development of sustainable water resources, vital for facilitating the inauguration of Jordan's premier geopark in Azraq.The region's geological formations, educational and aesthetic appeal, cultural heritage sites, and the existence of endangered species in its oasis underscore Azraq's significance.In a region grappling with water scarcity, the provision of a sustainable and reliable water supply emerges as a fundamental prerequisite for the geopark's successful functioning.Innovative water management strategies are delved into, with an emphasis on enhancing the recharge volume through Managed Aquifer Recharge (MAR).Simultaneously, the potential of utilizing basalt rock caves as water storage facilities is explored.The high potential of the basalt area as a source of rechargeable water is recognized, which could ameliorate the basin's water situation, yielding favorable environmental and socioeconomic outcomes, and fostering environmental sustainability to augment the national geopark.The implementation of these strategies is projected to confer considerable benefits, including the amplification of the aquifer recharge rate, the augmentation of water storage, and the promotion of environmental sustainability.The integration of MAR and basalt rock cave water storage strategies is posited not only to ensure the geopark's prosperity but also to advocate for natural heritage conservation and stimulate socio-economic growth within Jordan.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| 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".