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Record W2946648909 · doi:10.2495/sdp-v14-n2-141-151

Factors of uncertainty in the integrated management of water resources: The case of water reuse

2019· article· en· W2946648909 on OpenAlexvenueno aff
Pablo Aznar-Crespo, Antonio Aledo, Joaquín Melgarejo

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicWastewater Treatment and Reuse
Canadian institutionsnot available
FundersEuropean Commission
KeywordsReuseEnvironmental scienceWater resourcesWater resource managementWater conservationIntegrated water resources managementEnvironmental planningEnvironmental resource managementBusinessEnvironmental economicsWaste managementEngineering

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.364
Threshold uncertainty score0.159

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.230
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2019
Admission routes1
Has abstractyes

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Same venueInternational Journal of Sustainable Development and PlanningSame topicWastewater Treatment and ReuseFrench-language works237,207