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Record W2133402795 · doi:10.5539/jgg.v5n3p216

Impact of the 2012 Flood on Water Quality and Rural Livelihood in the Orashi Province of the Niger Delta, Nigeria

2013· article· en· W2133402795 on OpenAlexvenueno aff
Prince Chinedu Mmom, Pedro E. Aifesehi

Bibliographic record

VenueJournal of Geography and Geology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicFlood Risk Assessment and Management
Canadian institutionsnot available
Fundersnot available
KeywordsLivelihoodFlood mythNiger deltaWater resource managementFloodplainWater qualityDamagesGeographyAgricultureEnvironmental planningDeltaEnvironmental scienceEngineeringCartographyPolitical scienceEcology

Abstract

fetched live from OpenAlex

Flood event is not considered to be a natural hazard unless there is a threat to human life and/or property as the case of the 2012 flood incident in most parts of the Niger Delta, Nigeria. Thus, this paper aims at assessing the impact of the flood on groundwater quality of the affected areas, as well as the livelihood of the affected rural people. With a focus on six communities in the ORASHI province of the Niger Delta, which is one of the worst hit by the flood, the authors generated and analysed data that was used to draw conclusion for this study. A total of 2 water boreholes and 3 open artisan wells in each of the six (6) communities were sampled. These samples were subjected to both physico-chemical and microbial analysis against WHO standards. The result shows that the various water samples came short of the WHO Standards for safe water. Thus it could be deduced that the 2012 flood triggered damages not only to the life of individuals, properties/ infrastructure, but also most of the drinking water sources, especially, streams and the dug-out wells which were submerged in the event of the flood. The paper discovered that the flood incident seriously devastated the rural economy; farming, the major source of livelihood. The flood has made livelihood support difficult for the people of the area. Thus, community initiated mitigation measures should be promoted so as to strengthen community resilience.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.254

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 head0.006
GPT teacher head0.243
Teacher spread0.237 · 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

Citations21
Published2013
Admission routes1
Has abstractyes

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