Rivers are the main sources of freshwater supply for the world population. However, many economic activities contribute to river water pollution. River water quality can be monitored using various parameters, such as the pH level, dissolved oxygen, total suspended solids, and the chemical properties. Analyzing the trend and pattern of these parameters enables the prediction of the water quality so that proactive measures can be made by relevant authorities to prevent water pollution and predict the effectiveness of water restoration measures. Machine learning regression algorithms can be applied for this purpose. Here, eight machine learning regression techniques, including decision tree regression, linear regression, ridge, Lasso, support vector regression, random forest regression, extra tree regression, and the artificial neural network, are applied for the purpose of water quality index prediction. Historical data from Indian rivers are adopted for this study. The data refer to six water parameters. Twelve other features are then derived from the original six parameters. The performances of the models using different algorithms and sets of features are compared. The derived water quality rating scale features are identified to contribute toward the development of better regression models, while the linear regression and ridge offer the best performance. The best mean square error achieved is 0 and the correlation coefficient is 1.
The concentration, distribution, and risk assessment of parabens were determined in the surface water of the Terengganu River, Malaysia. Target chemicals were extracted via solid-phase extraction, followed by high-performance liquid chromatography analysis. Method optimization produced a high percentage recovery for methylparaben (MeP, 84.69 %), ethylparaben (EtP, 76.60 %), and propylparaben (PrP, 76.33 %). Results showed that higher concentrations were observed for MeP (3.60 μg/L) as compared with EtP (1.21 μg/L) and PrP (1.00 μg/L). Parabens are ubiquitously present in all sampling stations, with >99 % of detection. Salinity and conductivity were the major factors influencing the level of parabens in the surface water. Overall, we found no potential risk of parabens in the Terengganu River ecosystem due to low calculated risk assessment values (risk quotient
As an inland dryland lake basin, the rivers and lakes within the Lake Bosten basin provide scarce but valuable water resources for a fragile environment and play a vital role in the development and sustainability of the local societies. Based on the Google Earth Engine (GEE) platform, combined with the geographic information system (GIS) and remote sensing (RS) technology, we used the index WI2019 to extract and analyze the water body area changes of the Bosten Lake basin from 2000 to 2021 when the threshold value is -0.25 and the slope mask is 8°. The driving factors of water body area changes were also analyzed using the partial least squares-structural equation model (PLS-SEM). The result shows that in the last 20 years, the area of water bodies in the Bosten Lake basin generally fluctuated during the dry, wet, and permanent seasons, with a decreasing trend from 2000 to 2015 and an increasing trend between 2015 and 2019 followed by a steadily decreasing trend afterward. The main driver of the change in wet season water bodies in the Bosten Lake basin is the climatic factors, with anthropogenic factors having a greater influence on the water body area of dry season and permanent season than that of wet season. Our study achieved an accurate and convenient extraction of water body area and drivers, providing up-to-date information to fully understand the spatial and temporal variation of surface water body area and its drivers in the basin, which can be used to effectively manage water resources.
This study investigated relationships of a water quality index (WQI) with multiple water quality variables (WQVs), explored variability in water quality over time and space, and established linear and non-linear models predictive of WQI from raw WQVs. Data were processed using Spearman's rank correlation analysis, multiple linear regression, and artificial neural network modeling. Correlation analysis indicated that from a temporal perspective, the WQI, temperature, and zinc, arsenic, chemical oxygen demand, sodium, and dissolved oxygen concentrations increased, whereas turbidity and suspended solids, total solids, nitrate nitrogen (NO3-N), and biochemical oxygen demand concentrations decreased with year. From a spatial perspective, an increase with distance of the sampling station from the headwater was exhibited by 10 WQVs: magnesium, calcium, dissolved solids, electrical conductivity, temperature, NO3-N, arsenic, chloride, potassium, and sodium. At the same time, the WQI; Escherichia coli bacteria counts; and suspended solids, total solids, and dissolved oxygen concentrations decreased with distance from the headwater. Lastly, regression and artificial neural network models with high prediction powers (81.2% and 91.4%, respectively) were developed and are discussed.
Alkylphenols and most pesticides, especially organochlorine pesticides are endocrine-disrupting chemicals and they usually mimic the female hormone, estrogen. Using these chemicals in our environment would eventually lead us to consume them somehow in the food web. Several rivers in the State of Selangor, Malaysia were selected to monitor the level of alkylphenols and pesticides contamination for several months. The compounds were extracted from the water samples using liquid-liquid extraction method with dichloromethane and ethyl acetate as the extracting solvents. The alkylphenols and pesticides were analyzed by selected ion monitoring (SIM) mode using the quadrapole detector in Shimadzu QP-5000 gas chromatograph-mass spectrometer (GCMS). Recovery of most alkylphenols and pesticides were in the range of 50% to 120%. Trace amounts of the compounds were detected in the river water samples, mainly in the range of parts per trillion. This technique of monitoring the levels of endocrine-disruptors in river water is consistent and cost effective.
Contamination of water systems with endocrine disrupting chemicals (EDCs) is becoming a major public health concern due to their toxicity and ubiquity. The intrusion of EDCs into water sources and drinking water has been associated with various adverse health effects on humans. However, there is no comprehensive overview of the occurrence of EDCs in Malaysia's water systems. This report aims to describe the occurrence of EDCs and their locations. Literature search was conducted electronically in two databases (PubMed and Scopus). A total of 41 peer-reviewed articles published between January 2000 and May 2021 were selected. Most of the articles dealt with pharmaceuticals (16), followed by pesticides (7), hormones (7), mixed compounds (7), and plasticisers (4). Most studies (40/41) were conducted in Peninsular Malaysia, with 60.9% in the central region and almost half (48.8%) in the Selangor State. Only one study was conducted in the northern region and East Malaysia. The Langat River, the Klang River, and the Selangor River were among the most frequently studied EDC-contaminated surface waters, while the Pahang River and the Skudai River had the highest concentrations of some of the listed compounds. Most of the risk assessments resulted in a hazard quotient (HQ) and a risk quotient (RQ) 1 in the Selangor River. An RQ > 1 for combined pharmaceuticals was found in Putrajaya tap water. Overall, this work provides a comprehensive overview of the occurrence of EDCs in Malaysia's water systems. The findings from this review can be used to mitigate risks and strengthen legislation and policies for safer drinking water.
Several research efforts have been conducted to monitor and analyze the impact of environmental factors on the heavy metal concentrations and physicochemical properties of water bodies (lakes and rivers) in different countries worldwide. This article provides a general overview of the previous works that have been completed in monitoring and analyzing heavy metals. The intention of this review is to introduce the historical studies to distinguish and understand the previous challenges faced by researchers in analyzing heavy metal accumulation. In addition, this review introduces a survey on the importance of time increment sampling (monthly and/or seasonally) to comprehend and determine the rate of change of different parameters on a monthly and seasonal basis. Furthermore, suggestions are made for future research to achieve more understandable figures on heavy metal accumulation by considering climate conditions. Thus, the intent of the current study is the provision of reliable models for predicting future heavy metal accumulation in water bodies in different climates and pollution conditions so that water management can be achieved using intelligent proactive strategies and artificial neural network (ANN) techniques.
The concentrations were ranged from 1.35 ± 0.16 to 2.22 ± 0.34 µg/g (dry weight) and 2.65 ± 0.34 to 4.36 ± 0.53 µg/g (dry weight) for Cd and Pb, respectively, in blood cockle Anadara granosa from four sites of Sabang River, namely, Kampung Sambir, Kampung Tambirat, Beliong Temple, and Kampung Tanjung Apong, which are located at Asajaya, Sarawak, Malaysia. All values exceeded safety limits set by Malaysian Food Regulation (1985). It may be the cause of serious human health problems after long term consumption. Thus, consumer should have consciousness about such type of seafood from mentioned sites and need further investigation.
This study aims to determine the concentration of sterols used as biomarkers in the surface microlayer (SML) in estuarine areas of the Selangor River, Malaysia. Samples were collected during different seasons through the use of a rotation drum. The analysis of sterols was performed using gas chromatography equipped with a flame ionisation detector (GC-FID). The results showed that the concentrations of total sterols in the SML ranged from 107.06 to 505.55 ng L(-1). The total sterol concentration was found to be higher in the wet season. Cholesterol was found to be the most abundant sterols component in the SML. The diagnostic ratios of sterols show the influence of natural sources and waste on the contribution of sterols in the SML. Further analysis, using principal component analysis (PCA), showed distinct inputs of sterols derived from human activity (40.58%), terrigenous and plant inputs (22.59%) as well as phytoplankton and marine inputs (17.35%).
This study examined the concentration of heavy metals in 13 fish species. The results indicated that shellfish species (clams) have the highest metal concentrations, followed by demersal and pelagic fishes. The mean concentration of metals in clams are Zn 88.74 ± 11.98 µg/g, Cu 4.96 ± 1.06 µg/g, Pb 1.22 ± 0.19 µg/g, Cd 0.34 ± 0.04 µg/g dry wt. basis, whereas the same measure in fish tissues was 58.04 ± 18.51, 2.47 ± 1.21, 0.58 ± 0.27 and 0.17 ± 0.08 µg/g dry wt. basis. The concentrations of heavy metals in clams and fish tissues were still lower than the maximum allowable concentrations as suggested by the Malaysian Food Act (1983) and are considered safe for local human consumption.
As basic information for assessing reactivity and functionality of wetland-associated dissolved organic matter (DOM) based on their composition and structural properties, chemical characteristics of N in ultrafiltered DOM (UDON; >1 kD) isolated from wetland-associated rivers in three climates (cool-temperate, Hokkaido, Japan; sub-tropical, Florida, USA; tropical, Sarawak, Malaysia) were investigated. The UDON was isolated during dry and wet seasons, or during spring, summer, and autumn. The proportion of UDON present as humic substances, which was estimated as the DAX-8 adsorbed fraction, ranged from 47 to 91%, with larger values in the Sarawak than at the other sites. The yield of hydrolyzable amino acid N ranged 1.24 to 7.01 mg g(-1), which correlated positively to the total N content of UDOM and tended to be larger in the order of Florida>Hokkaido>Sarawak samples. X-ray photoelectron N1s spectra of UDON showed a strong negative correlation between the relative abundances of amide/peptide N and primary amine N. The relative abundances of amide/peptide N and primary amine N in the Sarawak samples were smaller (70-76%) and larger (20-23%) respectively compared to those (80-88% and 4-9%) in the Florida and Hokkaido samples. Assuming terminal amino groups and amide N of peptides as major constituents of primary amine N and amide/peptide N, respectively, the average molecular weight of peptides was smaller in the Sarawak samples than that in the Florida and Hokkaido samples. Seasonal variations in UDON composition were scarce in the Sarawak and Florida samples, whereas the distribution of humic substance-N and nonhumic substance-N and compositions of amino acids and N functional groups showed a clear seasonality in the Hokkaido samples. While aromatic N increased from spring to autumn, contributions from fresh proteinaceous materials were also enhanced during autumn, resulting in the highest N content of UDOM for this season.
This study aims to determine the levels of methylene blue active substances (MBAS) and ethyl violet active substances (EVAS) as anionic surfactants and of disulphine blue active substances (DBAS) as cationic surfactants in the surface microlayer (SML) around an estuarine area using colorimetric methods. The results show that the concentrations of surfactants around the estuarine area were dominated by anionic surfactants (MBAS and EVAS) with average concentrations of 0.39 and 0.51 μmol L⁻¹, respectively. There were significant between-station differences in surfactant concentrations (p<0.05) with higher concentrations found at the stations near the sea. The concentration of surfactants was higher during the rainy season than the dry season due to the influence of runoff water. Further investigation using total organic carbon (TOC) and total organic nitrogen (TON) shows that there is a significant correlation (p<0.05) between both anionic and cationic surfactants and the TON concentration.
Influences of river hydrodynamic behaviours on hydrochemistry (salinity, pH, dissolved oxygen saturations and dissolved phosphorus) were evaluated through high spatial and temporal resolution study of a sandbar-regulated coastal river. River hydrodynamic during sandbar-closed event was characterized by minor dependency on tidal fluctuations, very gradual increase of water level and continual low flow velocity. These hydrodynamic behaviours established a hydrochemistry equilibrium, in which water properties generally were characterized by virtual absence of horizontal gradients while vertical stratifications were significant. In addition, the river was in high trophic status as algae blooms were visible. Conversely, river hydrodynamic in sandbar-opened event was tidal-controlled and showed higher flow velocity. Horizontal gradients of water properties became significant while vertically more homogenised and with lower trophic status. In essence, this study reveals that estuarine sandbar directly regulates river hydrodynamic behaviours which in turn influences river hydrochemistry.
The pollution status of the downstream section of the Jakara River was investigated. Dissolved oxygen (DO), 5-day biochemical oxygen demand (BOD(5)), chemical oxygen demand (COD), suspended solids (SS), pH, conductivity, salinity, temperature, nitrogen in the form of ammonia (NH(3)), turbidity, dissolved solids (DS), total solids (TS), nitrates (NO(3)), chloride (Cl) and phosphates (PO(3-)(4)) were evaluated, using both dry and wet season samples, as a measure of variation in surface water quality in the area. The results obtained from the analyses were correlated using Pearson's correlation matrix, principal component analysis (PCA) and paired sample t-tests. Positive correlations were observed for BOD(5), NH(3), COD, and SS, turbidity, conductivity, salinity, DS, TS for dry and wet seasons, respectively. PCA was used to investigate the origin of each water quality parameter, and yielded 5 varimax factors for each of dry and wet seasons, with 70.7 % and 83.1 % total variance, respectively. A paired sample t-test confirmed that the surface water quality varies significantly between dry and wet season samples (P < 0.01). The source of pollution in the area was concluded to be of anthropogenic origin in the dry season and natural origins in the wet season.
Bukit Merah Reservoir is the main potable and irrigation water source for Kerian District, Perak State, Malaysia. For the past two decades, the reservoir has experienced water stress. Land-use activities have been identified as the contributor of the sedimentation. The Soil and Water Assessment Tool (SWAT) was used to simulate and quantify the impacts of land-use change in the reservoir watershed. The SWAT was calibrated and two scenarios were constructed representing projected land use in the year 2015 and hypothetical land use to represent extensive land-use change in the catchment area. The simulation results based on 17 years of rainfall records indicate that average water quantity will not be significantly affected but the ground water storage will decrease and suspended sediment will increase. Ground water decrease and sediment yield increase will exacerbate the Bukit Merah Reservoir operation problem.
The Langat River in Malaysia has been experiencing anthropogenic input from urban, rural and industrial activities for many years. Sewage contamination, possibly originating from the greater than three million inhabitants of the Langat River Basin, were examined. Sediment samples from 22 stations (SL01-SL22) along the Langat River were collected, extracted and analysed by GC-MS. Six different sterols were identified and quantified. The highest sterol concentration was found at station SL02 (618.29 ng/g dry weight), which situated in the Balak River whereas the other sediment samples ranged between 11.60 and 446.52 ng/g dry weight. Sterol ratios were used to identify sources, occurrence and partitioning of faecal matter in sediments and majority of the ratios clearly demonstrated that sewage contamination was occurring at most stations in the Langat River. A multivariate statistical analysis was used in conjunction with a combination of biomarkers to better understand the data that clearly separated the compounds. Most sediments of the Langat River were found to contain low to mid-range sewage contamination with some containing 'significant' levels of contamination. This is the first report on sewage pollution in the Langat River based on a combination of biomarker and multivariate statistical approaches that will establish a new standard for sewage detection using faecal sterols.
This paper presents Gene-Expression Programming (GEP), which is an extension to the genetic programming (GP) approach to predict the total bed material load for three Malaysian rivers. The GEP is employed without any restriction to an extensive database compiled from measurements in the Muda, Langat, and Kurau rivers. The GEP approach demonstrated a superior performance compared to other traditional sediment load methods. The coefficient of determination, R(2) (=0.97) and the mean square error, MSE (=0.057) of the GEP method are higher than those of the traditional method. The performance of the GEP method demonstrates its predictive capability and the possibility of the generalization of the model to nonlinear problems for river engineering applications.
Sediment samples were analyzed for di-(2-ethylhexyl) phthalate (DEHP), an organic endocrine disruptor, in Houjing River in southern Taiwan. The average DEHP concentration at 10 sampling locations, spanning from upper, middle, and lower segments of the stream, was calculated at 3.81+/-6.36mgkg(-1)drywt. Highest concentration was recorded at the Jhongsing Bridge (20.22mgkg(-1)drywt.) near the Dashe Industrial Park, followed by the Renwu Bridge (8.93mgkg(-1)drywt.) near the Renwu Industrial Park. The surface sediment concentration of DEHP was found to be higher in the dry season (October and December), and lower in the wet (flood) season (August), indicating that sources of DEHP remained active and continued to recharge the Houjing River. Vertical sediment core analysis revealed that highest concentration occurred at the depth of 40-60cm, indicating that historical discharges of DEPH may have been higher than recent years. Domestic comparison of DEHP concentrations in sediment from highest to lowest could be categorized as northern, southern, central, and eastern Taiwan, respectively, and seemed to be positively correlated with population density and/or industrial activity. Compared to other countries, DEHP concentration of the Houjing River was relatively higher than rivers studied in Japan, Germany, Italy, and Malaysia, and was relatively lower than the Aire and Trent Rivers in the United Kingdom.
In Malaysia, rivers are the main source of public water supplies. This study was conducted from 2002 to 2003 to determine the levels of selected organochlorine and organophosphate pesticides in the Selangor River in Malaysia. Surface water samples have been collected seasonally from nine sites along the river. A liquid-liquid extraction followed by gas chromatography-mass spectrometry technique was used to determine the trace levels of these pesticide residues. The organochlorine pesticides detected were lindane, heptachlor, endosulfan, dieldrin, endosulfan sulfate, o,p'-DDT, p,p'-DDT, o,p'-DDE and p,p'-DDE whereas for organophosphate pesticides, they were chlorpyrifos and diazinon. At the river upstream where a dam is located for public water supply, incidents of pesticide levels exceeding the European Economic Community Directive of water quality standards have occurred. Furthermore, the wetland ecosystems located at the downstream of the river which houses the fireflies community is being threatened by occasional pesticide levels above EPA limits for freshwater aquatic organisms. The occurrence of these residual pesticides in the Selangor River can be attributed to the intense agriculture and urban activity.