Distribution and source analysis of bioavailable metals in highland river sediment

Razali, Azlini; Ismail, Sharifah Norkhadijah Syed; Awang, Suriyani; Praveena, Sarva Man­gala; Abidin, Emilia Zainal

doi:10.1080/15275922.2020.1834020

Cited by 3 publications

(2 citation statements)

References 30 publications

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“…2. Situated in the north-west State of Pahang, it bordered by another two states which are Kelantan on the north side and Perak on the west side and also bordered by Lipis district on the South-East side of the Cameron Highlands district (Razali et al, 2020a, Pradhan & Lee, 2010. This unique district has a total area roughly in 69,699 km 2 with a height between 300 m and 2,016 m above sea level.…”

Section: Methodology Study Areamentioning

confidence: 99%

A Performance Comparison of Various Artificial Intelligence Approaches for Estimation of Sediment of River Systems

Hayder¹,

Solihin²,

Kushiar³

2021

J. Ecol. Eng.

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Sediment is a universal issue that is generated in the river catchment and affects the river flow, reservoir capacity, hydropower generation and dam structure. This paper aims to present the result of experimentation in sediment load estimation using various machine learning algorithms as a powerful AI approach. The data was collected from eight locations in upstream area of Ringlet reservoir catchment. The input variables are discharge and suspended solid. It was found that there is strong correlation between sediment and suspended solid with correlation coefficient of R = 0.9. The developed ML model successfully estimated the sediment load with competitive results from ANN, Decision Tree, AdaBoost and SVM. The best result was produced by SVM (v-SVM version) where very low RMSE was generated for both training and testing dataset despite its more complicated hyperparameters setup. The results also show a promising application of machine learning for future prediction in hydro-informatic systems.

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Section: Methodology Study Areamentioning

confidence: 99%

A Performance Comparison of Various Artificial Intelligence Approaches for Estimation of Sediment of River Systems

Hayder¹,

Solihin²,

Kushiar³

2021

J. Ecol. Eng.

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“…2 Hierarchical cluster analysis for Fe, Mn and Pb concentrations from river water comes from natural sources. Metals in C1 could be due to significant agricultural activities nearby via surface runoff (Razali et al 2021;Ghannam 2021;Abdullah et al 2020;Che Nadzir et al 2019). Note that both rivers flow through palm oil plantation areas.…”

Section: Sources Of Metalmentioning

confidence: 99%

Assessment of metal concentrations from recreational rivers in a tropical region (Jengka, Malaysia)

et al. 2022

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A recreational river may be exposed to some extent of metal pollution. Two rivers, namely Sungai Weh and Sungai Jempul, were selected for this study, as both areas offer recreational activities for residents in Jengka, Pahang, Malaysia. This study examines the concentration of selected metals (Fe, Mn, and Pb), elucidates the possible sources, evaluates the toxicity loads, and estimates the potential health risk. Metal concentrations were analysed using inductively coupled plasma optical emission spectrometry (ICP-OES). The concentrations were found in the sequence of Fe > Pb > Mn. Hierarchical cluster analysis (HCA) suggested that the metals’ origins included both anthropogenic activities and natural sources. About 16.66% of Pb should be removed from the river water to ensure safety, based on the heavy metal toxicity load calculation (HMTL). Children are more vulnerable to non-cancer and cancer risks than adults. The findings indicate that comprehensive monitoring of water quality parameters and thorough exposure assessment should be performed.

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Occurrence, origin, and risk assessment of metals in drinking water from a tropical suburban area (Jengka, Malaysia)

2023

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Information about metal contamination in drinking water remains inadequate, especially for semi-urban areas. This study determines the concentrations of metals in drinking water in Jengka, Pahang, Malaysia. It also attempts to assess the potential health risks and to identify the possible sources of metal contamination. Metal concentration was analysed using inductively coupled plasma optical emission spectrometry. The results included the mean concentrations of Zn (1.7 × 10–1 mg/L), Pb (2.4 × 10–2 mg/L), and Cr (1.75 × 10–3 mg/L). In general, the concentration of metals was below the drinking water limitation standards set by the Malaysia Ministry of Health and the World Health Organization, except for Pb. This work estimates low potential non-cancer (HQ < 1) and low cancer risks (LCR < 1) from metal exposure. However, children appear to be more susceptible to metal exposure via drinking water than adults. Based on multivariate analysis, metal in drinking water could come from two sources. The findings suggest comprehensive continuous monitoring of metal concentrations from potable water, especially for semi-urban regions, to minimise health risks.

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Distribution and source analysis of bioavailable metals in highland river sediment

Cited by 3 publications

References 30 publications

A Performance Comparison of Various Artificial Intelligence Approaches for Estimation of Sediment of River Systems

A Performance Comparison of Various Artificial Intelligence Approaches for Estimation of Sediment of River Systems

Assessment of metal concentrations from recreational rivers in a tropical region (Jengka, Malaysia)

Occurrence, origin, and risk assessment of metals in drinking water from a tropical suburban area (Jengka, Malaysia)

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