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Record W4212982199 · doi:10.1002/ird.2694

Water reuse to free up freshwater for higher‐value use and increase climate resilience and water productivity

2022· article· en· W4212982199 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIrrigation and Drainage · 2022
Typearticle
Languageen
FieldEngineering
TopicWater resources management and optimization
Canadian institutionsUnited Nations University Institute for Water, Environment, and Health
FundersConsortium of International Agricultural Research CentersGlobal Affairs CanadaGovernment of CanadaWorld Bank Group
KeywordsWater scarcityReuseWater conservationEnvironmental scienceWater useWater resourcesProductivityFarm waterDesalinationBusinessWater resource managementNatural resource economicsEconomicsEngineeringEcology

Abstract

fetched live from OpenAlex

Abstract The impact of climate change on the availability of water affects all types of land use and sectors. This complexity calls for integrated water resources management and negotiations between sectors on the most important, cost‐effective, and productive allocation of water where it is a limited resource. This reflection paper shows examples of adaptation efforts to water scarcity at a scale where gains in water productivity can be derived from inter‐sectoral water reuse and wastewater–freshwater swaps, complementing other water scarcity coping strategies (water savings, long‐distance transfer, and desalination). Wastewater treatment for reuse offers opportunities across scales as it allows, for example, donor regions to be compensated with reclaimed water for the release of freshwater for higher‐value use, increasing overall economic water productivity in this way. In such water swaps, farmers are compensated with higher water volumes in exchange for higher quality. The reuse of water between sectors offers opportunities to (i) expand the traditional (agricultural) water productivity concept and (ii) significantly increase water productivity at the system level. While rural–urban water reallocation can help mitigate the impacts of climate change, compensating farmers with reclaimed water remains limited for the reasons discussed in the paper.

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.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.515
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.012
GPT teacher head0.201
Teacher spread0.189 · 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