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Record W3038826406 · doi:10.22630/pniks.2020.29.2.14

Assessment of Lower Zab river water quality using both Canadian Water Quality Index Method and NSF Water Quality Index Method

2020· article· en· W3038826406 on OpenAlexaboutno aff
Sarah Ahmed, Omer Muhie Eldeen Taha, Mohamed A. Najemalden, Rehab T. Ahmed, Ali A. Abedulwahab

Bibliographic record

VenueScientific Review Engineering and Environmental Sciences (SREES) · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicWater Quality and Pollution Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsWater qualityTurbidityEnvironmental scienceRaw waterHydrology (agriculture)AlkalinityIndex (typography)Biochemical oxygen demandEnvironmental engineeringSalinitySurface waterChemical oxygen demandWastewaterEngineeringEcologyChemistry

Abstract

fetched live from OpenAlex

Rivers are considered the most important sources of surface water on Earth. They are play a significant role in all human activities and the quality of river water is needed. Therefore, the importance of the water quality index is arising through providing data base about quality of the water source, and explain the change in the water quality over a period of time continually. This study involved determination of physicochemical and biological parameters of Lower Zab river in Kirkuk city at two different points. The objectives of the study are to assess the present water quality, through analysis of some selected water quality parameters like pH, TDS, BOD, dissolved oxygen, turbidity, EC, alkalinity, and salinity etc. and to compare the results with the Canadian Council of Ministers of the Environment and National Sanitation Foundation Water Quality Indices. Raw water samples were collected from the Lower Zab river twice a month by one sample every 15 days from each station. The water quality data include 16 different parameters. Tests were carried out following the American Public Health Association standard methods. The results show that all parameters values were within the standards of drinking water proposed by the CCME standards and Iraqi standards or the World Health Organization standards for drinking purpose, except turbidity, DO, nitrate, calcium, which were mostly higher than the standards and sometimes BOD and potassium. The results of WQI showed that the water quality at LZ3 station is lower than LZ2 station due to the polluting activity of the Lower Zab river. Furthermore, for the years 2014, 2015, and 2016, the water quality was degraded due to the ISIS war. Also, it was noted in the 2013 year that the water quality degraded more in fall and winter seasons due to that the earth has exposed to the long-dried season and then suddenly exposed to a high rainfall season which in turns leads to increase some parameters very high (i.e. turbidity). Finally, the Lower Zab river water cannot be use for drinking directly. However, a pretreatment is needed before the drinking use.

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)0.012
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.706
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.051
GPT teacher head0.342
Teacher spread0.291 · 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 designBench or experimental
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

Citations12
Published2020
Admission routes1
Has abstractyes

Explore more

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