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Record W1978585043 · doi:10.5539/sar.v3n3p16

Status of Groundwater Table Depth Under Long-Term Irrigation in Wonji Plain: Concerns for Sustainability of Wonji-Shoa Sugar Estate, Upper Awash Valley, Ethiopia

2014· article· en· W1978585043 on OpenAlexvenueno aff
Megersa Olumana Dinka, Willibald Loiskandl, Julius Musyoka Ndambuki

Bibliographic record

VenueSustainable Agriculture Research · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicIrrigation Practices and Water Management
Canadian institutionsnot available
Fundersnot available
KeywordsWaterlogging (archaeology)Water tableSustainabilityGroundwater rechargeGroundwaterHydrology (agriculture)Environmental scienceWater resource managementIrrigationGeographyGeologyAquifer

Abstract

fetched live from OpenAlex

<p>The present study attempted to highlight the concerns of shallow groundwater table depth (GWTD) to the sustainability of Wonji-Shoa Sugar Estate (WSSE), Upper Awash Valley of Ethiopia. The recent magnitude and fluctuation of GWTD is mapped in ArcView GIS (using universal kriging technique) from the monthly GWTD monitoring data (2007-2009) using piezometer tubes. The study result clearly showed that the GWTD at WSSE was extremely shallow, showed great spatio-seasonal variability and rising trend; thus, threatening the sustainability of WSSE significantly. About 90% of the plantation fields have GWTD above the critical depth of 1.5 m below the soil surface and, hence, critically waterlogged. As a result, the estate is recently achieving only 55% of the production potential realized in the 1960s. Past trends indicate that the GW has the potential to inundate Wonji plain and is anticipated to devastate production during the next 10-15 years. Therefore, in order to sustain production system in the region, there is an urgent need to identify the possible causes of waterlogging and investigate the feasible remedial measures to combat its problems. The spatial mapping of GWTD with identified problematic areas, indicated in the current study, is believed to provide a tool for water management and, hence, crucial for the decision making and actions taking processes.</p>

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.291
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.045
GPT teacher head0.337
Teacher spread0.293 · 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 designObservational
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

Citations4
Published2014
Admission routes1
Has abstractyes

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