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Record W4297619630 · doi:10.9734/bpi/ecees/v5/2865a

Assessment of Water Quality of River Salandi by using Modified Canadian Council of Ministers of the Environmental Water Quality Index Method in Bhadrak, Odisha, India

2022· book-chapter· en· W4297619630 on OpenAlexaboutno aff
Pratap Kumar Panda, Prasant Kumar Dash, Rahas Bihari Panda

Bibliographic record

VenueBook Publisher International (a part of SCIENCEDOMAIN International) · 2022
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsWater qualityWet seasonEnvironmental sciencePollutionHydrology (agriculture)PollutantDry seasonEnvironmental engineeringWater resource managementToxicologyGeographyEngineeringBiologyEcology

Abstract

fetched live from OpenAlex

The present Study highlights Water Quality of the River Salandi by using Modified Canadian Council of Ministers of the Environment Water Quality Index Method, Bhadrak, Odisha, India. The selection of nine sampling stations along the bank of the river has been done on the basis of availability of more expected pollutants to satisfy the aim and objective of this work. Water samples collected from nine different places during summer, rainy, post-rainy and winter seasons in the year 2015 and 2016 have been analysed to study the sixteen physico-chemical parameters by using standard procedures, prescribed by APHA-2012 and out of which mean and standard deviations (SD) of twelve parameters have been calculated and computed to study Water Quality Index (WQI) through Canadian Council of Ministers of Environment (CCME) method in a modified manner for the year 2015 and 2016. The study reveals that water quality of both the years is marginal and belongs to class-D. Further, it is concluded that comparatively poorer water quality of the year 2016 than the year 2015 is due the higher amplitude (F3). Besides, analysis of physico-chemical parameters confirms that the river Salandi is polluted with respect to Cr(VI), iron, chloride, fluoride and pathogenic bacteria and gravity of pollution is more during rainy, post-rainy than the summer and winter seasons and pollution follows a decreasing trend from upstream to downstream. In addition to using contemporary techniques like electrodialysis, disinfection, and reduction of Cr (VI) with SO2 in acidic medium followed by lime treatment to turn Cr (VI) into Cr(III) as chromium hydroxide, along with phytoremediation and bioremediation for the treatment of toxic substances and pathogenic bacteria, and concurrently increasing DO value through photosynthesis.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.564
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0160.000

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 head0.063
GPT teacher head0.309
Teacher spread0.247 · 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.

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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

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