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Record W7015976616

Water and Sediment Quality of Rajang River Downstream of Bakun Dam, Sarawak.

2019· other· en· W7015976616 on OpenAlexaboutno aff

Bibliographic record

VenueUnimas Institutional Repository (Universiti Malaysia Sarawak) · 2019
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsSpillwayHydroelectricityHydrology (agriculture)Water qualitySedimentDownstream (manufacturing)Water level
DOInot available

Abstract

fetched live from OpenAlex

Water and sediment quality in the downstream river may be affected by the of the Bakun Hydroelectric dam. Knowledge on water and sediment quality in the regulated Rajang River, downstream of the Bakun Hydroelectric Dam is still scarce, especially for a longer distance up to Kapit. As more hydroelectric dams are to be built in the future, it is important to collect baseline data for future references. The main concerns in Rajang River are the differences of water quality between two operations, which are, during the opened spillway (water discharged through turbine and spillway) and the closed spillway (water discharged through turbine only). The water quality potentially changes with the discharge from the spillway. Therefore, in this study, the water and sediment quality were conducted along the Rajang River up to 210 km long. A total of 15 stations were selected for this study for a distance of 210 km, and six sampling trips were conducted from April 2016 to May 2018, covering the opened and closed spillway of the Bakun Hydroelectric Dam. Results show that pH is significantly lower at stations nearer to the dam, regardless of spillway operations, and gradually increasing as distance from the dam increases. At station 1, nearest to the dam during closed spillway, pH was less than 6.0, significantly lower than opened spillway. The DO concentration in the river deteriorated when there was no spillway discharge. Multiple regression modelling was applied to determine the minimum discharge required to raise DO and pH at station 1 to comply with Class II NWQS. Rainfall event before and during sampling increased turbidity and TSS; and decreased transparency. The means of COD, NO2-N, NO3-N, OKN, PO4-P, TS and H2S were significantly higher during opened spillway, especially at the stations nearer to the dam. The TP concentration in the river was mainly affected by the wastes from longhouses, logging camps and agricultural activities. In terms of water quality index (WQI), the classification ranged from Class II to III, and the status is either Slightly Polluted (94.4%) or Polluted (5.6%). Compared to the condition prior to impoundment, parameters such as temperature, pH, DO, NO3-N, PO4-P and TP declined with the impoundment of Bakun Dam. The heavy metals in water were mainly affected by the surrounding activities. The range of heavy metals for Al were from undetected to 0.651 mg/L; Cu, 0.008 mg/L to 0.015 mg/L; Fe, 1.070 mg/L to 3.417 mg/L; Mn, 0.007 mg/L to 0.113 and Zn, from undetected to 0.626 mg/L. The NWQS classifications for heavy metals in water ranged from Class II to III. Sediment quality analysis showed that the percentage of sand was 6.24% to 99.53%; silt, 0.22% to 93.55%; and clay, 0.21% to 20.88%. The textural classes in Rajang River were sand, loam, sandy loam, loamy sand and silt. The sediment quality results for pH, OM, TOC, TP and TKN were 6.06 to 6.43, 0.73% to 4.07%, 0.02% to 0.21%, 145 mg/kg to 381 mg/kg and 1099 mg/kg to 2289 mg/kg respectively. Based on sediment guideline for the protection and management of aquatic sediment quality in Ontario, the TOC and TP were categorized as below the lowest effect level, while TKN was categorized as exceeding the lowest effect level. Meanwhile, the distribution of TOC, OM, TP and heavy metals in sediments were significantly correlated with clay. The range of heavy metals in sediments for Al were 299.4 mg/kg to 1326.0 mg/kg; Cu, 3.933 mg/kg to 17.267 mg/kg; Fe, 4333.0 mg/kg to 16807.3 mg/kg; Mn, 61.0 mg/kg to 410.7 mg/kg; and Zn, 14.4 mg/kg to 41.4 mg/kg. Overall, most parameters were influenced by land-use activities besides spillway and turbine discharge; and large tributaries inflow. The concentration of DO should be raised during closed spillway in order to ensure the healthy growth of sensitive aquatic organisms.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.719
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.000
Science and technology studies0.0000.003
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.012
GPT teacher head0.229
Teacher spread0.217 · 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 designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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