A Conceptual Socio-Hydrogeological Model Applied to Sustainable Water Management. Case Study of the Valdivia River Basin, Southwestern Ecuador
Bibliographic record
Abstract
The scientific community has a growing interest in understanding the interaction of the human-water system in water resource models. In Santa Elena (Ecuador), Valdivia, San Pedro, Sinchal, Barcelona and Carrizal communities are located in a semi-arid area, making the water supply a critical problem for local communities. In addition to the climatic conditions of the sector, the main problem is the weak participation in the integral management of the groundwater resource by the stakeholders involved. Specifically, there is evidence of a lack of ancestral-technical knowledge in management strategies and the fact that the demand for water for agriculture, tourism, and their basic needs exceed the sustainable supply capacity. The present study assesses the natural and anthropic conditions of the middle and lower basin of the Valdivia river through a socio-hydrogeological conceptual model of the river-aquifer system to develop productive activities in an environment of sustainability. The study methodology consists of four phases: i) river basin data analysis, ii) hydrogeological studies, iii) application of the Participatory Action Research (PAR) and Strengths-Weaknesses-Opportunities-Threats (SWOT) analysis, and iv) conceptual model of the river-aquifer system. The results show that the socio-hydrogeological model of the Valdivia River basin has four systems: hydrogeological, ecological, economic, and social. In addition, the research detected problems present in the systems, such as droughts due to the influence of natural phenomena, aquifer overexploitation, lack of aquifer sustainability techniques, weak management and control of water resources, contamination of water sources and a lack of support from government agencies. The systems identified allow JAAPR-Valdivia to manage strategies to solve the problems detected in search of the sustainability of water resources.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 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".