Factors of uncertainty in the integrated management of water resources: The case of water reuse
Bibliographic record
Abstract
The non-conventional water resources (water reuse (WR) and desalination) are a strategic option to compensate the structural water deficit of the southeast of Spain.In addition to increasing water availability and reducing the pressure on conventional resources, these resources show strategic functions at environmental, social and economic level.However, WR does not experience sufficient acceptance by some water users.Uncertainties regarding the quality of reclaimed water, food safety, price or regulations are factors of rejection or ambiguity.The results of a survey carried out on 114 users belonging to irrigation communities of several river basins in Spain are presented.In general, results show a moderate level of implementation of WR.However, the growth potential of WR is significantly high.This depends on water quality and price, which are the two most important valuation factors of WR.Regulations, food safety or water quality for crops generate uncertainty and concern among the irrigation communities.The effects on the environment or the control of availability are aspects positively valued.Conventional resources (transfers and groundwater) are better valued than non-conventional ones (WR and desalination).This constitutes a factor of vulnerability to consolidate the transformation of the Spanish hydrological model.The information presented can be useful to guide the design of future hydrological policies and reduce the socio-institutional vulnerability related to the integrated management 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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".