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Record W1965390037 · doi:10.1002/ird.367

Drainage in the Aral Sea Basin

2007· article· en· W1965390037 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.

Bibliographic record

VenueIrrigation and Drainage · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicTransboundary Water Resource Management
Canadian institutionsMcGill University
Fundersnot available
KeywordsStructural basinDrainageGeologyDrainage basinHydrology (agriculture)Environmental scienceOceanographyGeographyGeomorphologyCartographyBiologyGeotechnical engineeringEcology

Abstract

fetched live from OpenAlex

The intensity of irrigation in Central Asia requires artificial drainage in order to control waterlogging and salinization. There are about 5.35 million ha with a combination of surface drainage, and vertical and horizontal subsurface drainage. Of the five Central Asian republics, Uzbekistan is the country with the most significant artificially drained land, of approximately 1 million ha. There have been several innovations in drainage design in the region, in order to account for seepage from irrigation canals and upstream irrigated lands, percolation from excess irrigation water, groundwater fluxes to the root zone, and the accompanying salts moving into the crop root zone. Deeper subsurface drainage depths are considered essential for the control of waterlogging and salinity. There were significant investments in drainage in the region until the 1990s. However, with the collapse of the Soviet Union and the deterioration of economic conditions in Central Asia, investment in drainage declined. Drainage systems are no longer properly maintained and the areas suffering from salinization and waterlogging have been increasing. The drainage problems are compounded by the weakened institutional structure to successfully operate and maintain the drainage network. This paper addresses the technical and institutional improvements required to improve drainage performance, and stresses the importance of implementation of drainage with irrigation in the context of integrated water resources management. Copyright © 2007 John Wiley & Sons, Ltd. L'intensité de l'irrigation en Asie centrale exige le drainage artificiel pour contrôler l'engorgement et la salinisation des terres. Il y a environ 5,35 millions d'ha traités conjointement par drainage de surface et drainage souterrain, horizontal et vertical. Des cinq républiques d'Asie Centrale, l'Ouzbekistan est le pays le plus traité, avec environ un million d'hectares drainés. Il y a eu plusieurs innovations dans la conception du drainage dans la région, afin de prendre en compte l'infiltration à partir des canaux d'irrigation et des terres irriguées en amont, la percolation de l'irrigation excessive, les afflux d'eaux souterraines aux zones racinaires, et les sels qui les accompagnent. Un drainage plus profond est considéré comme essentiel pour maîtriser l'engorgement et la salinité. Il y a eu des investissements significatifs de drainage dans la région jusqu'aux années 90. Cependant, avec l'effondrement de l'Union Soviétique et la détérioration des conditions économiques en Asie centrale, ces investissements ont diminué. Les systèmes de drainage souterrain ne sont plus entretenus correctement et les surfaces engorgées et salinisées augmentent. Les problèmes de drainage sont aggravés par la faiblesse des structures pour faire fonctionner et maintenir le réseau de drainage. Cet article traite des améliorations techniques et organisationnelles nécessaires pour améliorer les performances de drainage, et souligne l'importance de coupler le drainage et l'irrigation dans un contexte de gestion intégrée des ressources en eau. Copyright © 2007 John Wiley & Sons, Ltd.

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)0.003
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.846
Threshold uncertainty score0.415

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 head0.018
GPT teacher head0.297
Teacher spread0.279 · 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