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Record W2759229222 · doi:10.2495/sdp-v13-n3-425-435

Sustainable water management in Kuwait: Current situation and possible correctional measures

2018· article· en· W2759229222 on OpenAlexvenueno aff
Amitabha Mukhopadhyay, A. Akber

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicWater management and technologies
Canadian institutionsnot available
FundersKuwait Institute for Scientific Research
KeywordsCurrent (fluid)Environmental planningEnvironmental scienceEnvironmental resource managementBusinessWater resource managementEngineering

Abstract

fetched live from OpenAlex

Kuwait, an arid country, has no surface source of useable water. It mainly depends on desalination plants for its freshwater needs. Brackish groundwater (salinity <5000 ppm) is used for irrigation and mixing with desalinated water. At the current rate of increase in demand for freshwater, large investment is necessary at close intervals to augment the desalination capacity of the country. With very little natural replenishment, the aquifers yielding the brackish water are also under great stress. Management of both supply and demand is necessary to solve these problems. In addition to the increase in desalination capacity, supply may be augmented by the increased use of renovated wastewater, storage of seasonally higher supply of usable water in the aquifers through artificial recharge, establishment of integrated water transport network through the Gulf Cooperation Council (GCC) countries and exploration of new useable groundwater resources both onshore and offshore. Possible new sources of water are harvesting of rainfall runoff in the wadis and depressions and runoff carried by the storm water network within the urban areas, moisture recovery from the vadose zone, and the paleo-groundwater possibly preserved under the Arabian Gulf. Demand may be curbed through maintaining lower pressure in the water network and some form of rationing, reduction of network loss through adoption of appropriate measures, implementation of updated water code that will help in saving water, control of population through tighter immigration measures and reduction in government subsidy. Finally, water authorities should take steps to increase public awareness about all aspects of water management outlined before in real earnest.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.070
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.002
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.022
GPT teacher head0.243
Teacher spread0.221 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations17
Published2018
Admission routes1
Has abstractyes

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