Biodiversity of aquatic insect and physicochemical water quality parameters in Mae Tao and Mae Ku watersheds were
assessed bi-monthly from February 2011 to February 2012. A total of 59 families representing 9 orders were recorded.
At order level, Trichoptera was found at the highest frequency in total abundance (45.75%) followed by Ephemeroptera
(18.06%), Hemiptera (13.45%), Odonata (9.62%), Diptera (8.17%), Coleoptera (4.6%), Megaloptera (0.17%),
Lepidoptera (0.11%) and Plecoptera (0.07%). The family Hydropsychidae was the most prominent and the most abundant
aquatic insect taxa followed by Chironomidae. Water temperature, dissolved oxygen and ammonia-nitrogen were similar
at all sampling stations. Significant variations in pH, electrical conductivity, total dissolved solids, sulfate, nitrate-nitrogen
and alkalinity were found at all sampling stations. Taxa richness and diversity index significantly correlated with dissolved
oxygen, sulfate, nitrate-nitrogen and ammonia-nitrogen (p<0.05, p<0.01). Physicochemical data and biological data
showed that mostly the surface water quality in Mae Tao and Mae Ku watersheds were within Type III of The Surface
Water Standard for Agriculture and Water Quality for Protection of Aquatic Resources in Thailand.
Malaysia is a tropical country that is highly dependent on surface water for its raw water supply. Unfortunately, surface water is vulnerable to pollution, especially in developed and dense urban catchments. Therefore, in this study, a methodology was developed for an extensive temporal water quality index (WQI) and classification analysis, simulations of various pollutant discharge scenarios using QUAL2K software, and maps with NH3-N as the core pollutant using an integrated QUAL2K-GIS. It was found that most of the water quality stations are categorized as Class III (slightly polluted to polluted). These stations are surrounded by residential areas, industries, workshops, restaurants and wet markets that contribute to the poor water quality levels. Additionally, low WQI values were reported in 2010 owing to development and agricultural activities. However, the WQI values improved during the wet season. High concentrations of NH3-N were found in the basin, especially during dry weather conditions. Three scenarios were simulated, i.e. 10%, 50% and 70% of pollution discharge into Skudai river using a calibrated and validated QUAL2K model. Model performance was evaluated using the relative percentage difference. An inclusive graph showing the current conditions and pollution reduction scenarios with respect to the distance of Skudai river and its tributaries is developed to determine the WQI classification. Comprehensive water quality maps based on NH3-N as the core pollutant are developed using integrated QUAL2K-GIS to illustrate the overall condition of the Skudai river. High NH3-N in the Skudai River affects water treatment plant operations. Pollution control of more than 90% is required to improve the water quality classification to Class II. The methodology and analysis developed in this study can assist various stakeholders and authorities in identifying problematic areas and determining the required percentage of pollution reduction to improve the Skudai River water quality.
Groundwater resources constitute the main source of clean fresh water for domestic use and it is essential for food production in the agricultural sector. Groundwater has a vital role for water supply in the Campanian Plain in Italy and hence a future sustainability of the resource is essential for the region. In the current paper novel data mining algorithms including Gaussian Process (GP) were used in a large groundwater quality database to predict nitrate (contaminant) and strontium (potential future increasing) concentrations in groundwater. The results were compared with M5P, random forest (RF) and random tree (RT) algorithms as a benchmark to test the robustness of the modeling process. The dataset includes 246 groundwater quality samples originating from different wells, municipals and agricultural. It was divided for the modeling process into two subgroups by using the 10-fold cross validation technique including 173 samples for model building (training dataset) and 73 samples for model validation (testing dataset). Different water quality variables including T, pH, EC, HCO3-, F-, Cl-, SO42-, Na+, K+, Mg2+, and Ca2+ have been used as an input to the models. At first stage, different input combinations have been constructed based on correlation coefficient and thus the optimal combination was chosen for the modeling phase. Different quantitative criteria alongside with visual comparison approach have been used for evaluating the modeling capability. Results revealed that to obtain reliable results also variables with low correlation should be considered as an input to the models together with those variables showing high correlation coefficients. According to the model evaluation criteria, GP algorithm outperforms all the other models in predicting both nitrate and strontium concentrations followed by RF, M5P and RT, respectively. Result also revealed that model's structure together with the accuracy and structure of the data can have a relevant impact on the model's results.
Malaysia depends heavily on rivers as a source for water supply, irrigation, and sustaining the livelihood of local communities. The evolution of land use in urban areas due to rapid development and the continuous problem of illegal discharge have had a serious adverse impact on the health of the country's waterways. Klang River requires extensive rehabilitation and remediation before its water could be utilised for a variety of purposes. A reliable and rigorous remediation work plan is needed to identify the sources and locations of streams that are constantly polluted. This study attempts to investigate the feasibility of utilising a temporal and spatial risk quotient (RQ) based analysis to make an accurate assessment of the current condition of the tributaries in the Klang River catchment area. The study relies on existing data sets on Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Suspended Solids (TSS), and Ammonia (NH3) to evaluate the water quality at thirty strategic locations. Analysis of ammonia pollution is not only based on the limit established for river health but was expanded to include the feasibility of using the water for water intake, recreational activities, and sustaining fish population. The temporal health of Klang River was evaluated using the Risk Matrix Approach (RMA) based on the frequency of RQ > 1 and associated colour-coded hazard impacts. By using the developed RMA, the hazard level for each parameter at each location was assessed and individually mapped using Geographic Information System (GIS). The developed risk hazard mapping has high potential as one of the essential tools in making decisions for a cost-effective river restoration and rehabilitation.
A set of methodological tools was tested to assess the sensitivity of several ecological and biological indices to eutrophication while at the same time attempting to explore a linkage among pressures, classification assessment and drivers. Industrial discharges, harbor activities, natural interactions and river discharges are the pressures most related to the eutrophication process in tropical coastal water bodies. Among the eutrophication indices used, TRIX and operational indicators overestimated the eutrophication status in the study area, but EI and chl-a seems to be a rather responsive index to reflect the first stage of eutrophication. It is noteworthy that EI and chl-a showed better overall agreement with the ecological quality status (EcoQ) showing that probably it reflects the indirect relation of macrobenthic with water eutrophication in a better way. An ecological boundary of EI and chl-a from moderate to poor may be needed in order to explain the poor status of relatively eutrophic Klang Strait coastal sites.
This study has applied the concept of the hybrid PAC-UF process in the treatment of the final effluent of the palm oil industry for reuse as feedwater for low-pressure boilers. In a bench-scale set-up, a low-cost empty fruit bunch-based powdered activated carbon (PAC) was employed for upstream adsorption of biotreated palm oil mill effluent (BPOME) with the process conditions: 60 g/L dose of PAC, 68 min of mixing time and 200 rpm of mixing speed, to reduce the feedwater strength, alleviate probable fouling of the membranes and thus improve the process flux (productivity). Three polyethersulfone ultrafiltration membranes of molecular weight cut-off (MWCO) of 1, 5 and 10 kDa were investigated in a cross-flow filtration mode, and under constant transmembrane pressures of 40, 80, and 120 kPa. The permeate qualities of the hybrid processes were evaluated, and it was found that the integrated process with the 1 kDa MWCO UF membrane yielded the best water quality that falls within the US EPA reuse standard for boiler-feed and cooling water. It was also observed that the permeate quality is fit for extended reuse as process water in the cement, petroleum and coal industries. In addition, the hybrid system's operation consumed 37.13 Wh m(-3) of energy at the highest applied pressure of 120 kPa, which is far lesser than the typical energy requirement range (0.8-1.0 kWh m(-3)) for such wastewater reclamation.
Multiple interactions of geogenic and anthropogenic activities can trigger groundwater pollution in the tropical savanna watershed. These interactions and resultant contamination have been studied using applied geochemical modeling, conventional hydrochemical plots, and multivariate geochemometric methods, and the results are presented in this paper. The high alkalinity values recorded for the studied groundwater samples might emanate from the leaching of carbonate soil derived from limestone coupled with low rainfall and high temperature in the area. The principal component analysis (PCA) unveils three components with an eigenvalue > 1 and a total dataset variance of 67.37%; this implies that the temporary hardness of the groundwater and water-rock interaction with evaporite minerals (gypsum, halite, calcite, and trona) is the dominant factor affecting groundwater geochemistry. Likewise, the PCA revealed anthropogenic contamination by discharging [Formula: see text] [Formula: see text][Formula: see text] and [Formula: see text] from agricultural activities and probable sewage leakages. Hierarchical cluster analysis (HCA) also revealed three clusters; cluster I reflects the dissolution of gypsum and halite with a high elevated load of [Formula: see text] released by anthropogenic activities. However, cluster II exhibited high [Formula: see text] and [Formula: see text] loading in the groundwater from weathering of bicarbonate and sylvite minerals. Sulfate ([Formula: see text]) dominated cluster III mineralogy resulting from weathering of anhydrite. The three clusters in the Maiganga watershed indicated anhydrite, gypsum, and halite undersaturation. These results suggest that combined anthropogenic and natural processes in the study area are linked with saturation indexes that regulate the modification of groundwater quality.
A study on diversity and distribution of fish communities and water qualities were carried out from January 2009 to December 2010 to cover monsoon and non-monsoon at Kuantan estuary, Pahang, Malaysia. A total of 19 species of primary marine fish belong to 12 families were recorded. Out of 311 individuals the fish fauna was dominated by Ariidae followed by Lutjanidae and Lactaridae. As such Ariidae contributes 50% of the fish caught in the study area and its diversity index (H') was 0.97. A The Ariidae family consist of four (4) species; Arius maculatus, Arius sumatranus, Arius tenuispinis and Arius thalassinus. The Ariidae family can be found in all stations as they are euryhaline (highly tolerant to salinity) and this fish family are known to be a hardy estuarine catfish. Among all species in family Ariidae, Arius thalassinus was the most dominant (23%) among all species. As such collected species showed highest species diversity (0.34) followed by Arius tenuispinis (0.25) compared to other species. Arius tenuispinis alone contributed 11.90% among the samples caught from all stations. The fishes were caught and recorded highest in September-December. Pseudorhombus quinque ocellatus, Nibea soldado, Sardinella fimbriata, Toxotes jaculatrix, Dasyatis ushiei, Setipinna taty were the least dominant in the Kuantan estuary with 9.33% of total abundance. Physico-temperatures, such as temperature (22.03-30 degrees C), Conductivity (10.342.43 mS cm(-1)), TDS (0.06-26.34 mg L(-1)), salinity (0.05-29.09 ppt), DO (6.37-8.38 mg L(-1)), pH (4.97-8.03), Chl a (0.01-1.33 microg L(-1)), nitrite (0.01-0.08 mg L(-1)), nitrate (0.60-0.88 mg L(-1)), phosphate (0.24-0.40 mg L(-1)). Nevertheless, the study envisages that the water quality and fish diversity are still conducive in the Kuantan estuary. The fish diversity of Pahang estuary was high monsoon compared to non-monsoons. The station 4 (LKIM fishing boat jetty and adjacent Hospital Kuantan) is the most polluted area due to the presence of several outskirts could be alarming for the sustainable development of fish and other aquatic organisms in Kuantan estuary in the long run.
This case study uses several univariate and multivariate statistical techniques to evaluate and interpret a water quality data set obtained from the Klang River basin located within the state of Selangor and the Federal Territory of Kuala Lumpur, Malaysia. The river drains an area of 1,288 km(2), from the steep mountain rainforests of the main Central Range along Peninsular Malaysia to the river mouth in Port Klang, into the Straits of Malacca. Water quality was monitored at 20 stations, nine of which are situated along the main river and 11 along six tributaries. Data was collected from 1997 to 2007 for seven parameters used to evaluate the status of the water quality, namely dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, suspended solids, ammoniacal nitrogen, pH, and temperature. The data were first investigated using descriptive statistical tools, followed by two practical multivariate analyses that reduced the data dimensions for better interpretation. The analyses employed were factor analysis and principal component analysis, which explain 60 and 81.6% of the total variation in the data, respectively. We found that the resulting latent variables from the factor analysis are interpretable and beneficial for describing the water quality in the Klang River. This study presents the usefulness of several statistical methods in evaluating and interpreting water quality data for the purpose of monitoring the effectiveness of water resource management. The results should provide more straightforward data interpretation as well as valuable insight for managers to conceive optimum action plans for controlling pollution in river water.
Despite the amount of awareness created, waterborne disease still poses threat, especially in developing countries. Due to the scarcity of reported data on waterborne parasites, the consumption of unsafe water prolongs. Thus, the occurrences of waterborne parasites from various samples were investigated from one of the Southeast Asian country, the Philippines.
The study presents a baseline variability and climatology study of measured hydrodynamic, water properties and some water quality parameters of West Johor Strait, Singapore at hourly-to-seasonal scales to uncover their dependency and correlation to one or more drivers. The considered parameters include, but not limited by sea surface elevation, current magnitude and direction, solar radiation and air temperature, water temperature, salinity, chlorophyll-a and turbidity. FFT (Fast Fourier Transform) analysis is carried out for the parameters to delineate relative effect of tidal and weather drivers. The group and individual correlations between the parameters are obtained by principal component analysis (PCA) and cross-correlation (CC) technique, respectively. The CC technique also identifies the dependency and time lag between driving natural forces and dependent water property and water quality parameters. The temporal variability and climatology of the driving forces and the dependent parameters are established at the hourly, daily, fortnightly and seasonal scales.
Groundwater chemistry of small tropical islands is influenced by many factors, such as recharge, weathering and seawater intrusion, among others, which interact with each other in a very complex way. In this work, multivariate statistical analysis was used to evaluate the factors controlling the groundwater chemistry of Kapas Island (Malaysia). Principal component analysis (PCA) was applied to 17 hydrochemical parameters from 108 groundwater samples obtained from 18 sampling sites. PCA extracted four PCs, namely seawater intrusion, redox reaction, anthropogenic pollution and weather factors, which collectively were responsible for more than 87% of the total variance of the island's hydrochemistry. The cluster analysis indicated that three factors (weather, redox reaction and seawater intrusion) controlled the hydrochemistry of the area, and the variables were allocated to three groups based on similarity. A Piper diagram classified the island's water types into Ca-HCO3 water type, Na-HCO3 water type, Na-SO4-Cl water type and Na-Cl water type, indicating recharge, mixed, weathering and leached from sewage and seawater intrusion, respectively. This work will provide policy makers and land managers with knowledge of the precise water quality problems affecting the island and can also serve as a guide for hydrochemistry assessments of other islands that share similar characteristics with the island in question.
Rivers play a significant role in providing water resources for human and ecosystem survival and health. Hence, river water quality is an important parameter that must be preserved and monitored. As the state of Selangor and the city of Kuala Lumpur, Malaysia, are undergoing tremendous development, the river is subjected to pollution from point and non-point sources. The water quality of the Klang River basin, one of the most densely populated areas within the region, is significantly degraded due to human activities as well as urbanization. Evaluation of the overall river water quality status is normally represented by a water quality index (WQI), which consists of six parameters, namely dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, suspended solids, ammoniacal nitrogen and pH. The objectives of this study are to assess the water quality status for this tropical, urban river and to establish the WQI trend. Using monthly WQI data from 1997 to 2007, time series were plotted and trend analysis was performed by employing the first-order autocorrelated trend model on the moving average values for every station. The initial and final values of either the moving average or the trend model were used as the estimates of the initial and final WQI at the stations. It was found that Klang River water quality has shown some improvement between 1997 and 2007. Water quality remains good in the upper stream area, which provides vital water sources for water treatment plants in the Klang valley. Meanwhile, the water quality has also improved in other stations. Results of the current study suggest that the present policy on managing river quality in the Klang River has produced encouraging results; the policy should, however, be further improved alongside more vigorous monitoring of pollution discharge from various point sources such as industrial wastewater, municipal sewers, wet markets, sand mining and landfills, as well as non-point sources such as agricultural or urban runoff and commercial activity.
This article describes design and application of feed-forward, fully-connected, three-layer perceptron neural network model for computing the water quality index (WQI)(1) for Kinta River (Malaysia). The modeling efforts showed that the optimal network architecture was 23-34-1 and that the best WQI predictions were associated with the quick propagation (QP) training algorithm; a learning rate of 0.06; and a QP coefficient of 1.75. The WQI predictions of this model had significant, positive, very high correlation (r=0.977, p<0.01) with the measured WQI values, implying that the model predictions explain around 95.4% of the variation in the measured WQI values. The approach presented in this article offers useful and powerful alternative to WQI computation and prediction, especially in the case of WQI calculation methods which involve lengthy computations and use of various sub-index formulae for each value, or range of values, of the constituent water quality variables.
The study was to determine the concentration of aluminium (Al) and study the physicochemical parameters (pH, total dissolved solids (TDS), turbidity, and residual chlorine) in drinking water supply in selected palm oil estates in Kota Tinggi, Johor. Water samples were collected from the estates with the private and the public water supplies. The sampling points were at the water source (S), the treatment plant outlet (TPO), and at the nearest houses (H1) and the furthest houses (H2) from the TPO. All estates with private water supply failed to meet the NSDWQ for Al with mean concentration of 0.99 ± 1.52 mg/L. However, Al concentrations in all public water supply estates were well within the limit except for one estate. The pH for all samples complied with the NSDWQ except from the private estates for the drinking water supply with an acidic pH (5.50 ± 0.90). The private water supply showed violated turbidity value in the drinking water samples (14.2 ± 24.1 NTU). Insufficient amount of chlorination was observed in the private water supply estates (0.09 ± 0.30 mg/L). Private water supplies with inefficient water treatment served unsatisfactory drinking water quality to the community which may lead to major health problems.
Characterization of hydrochemistry changes in Johor Straits within 5 years of monitoring works was successfully carried out. Water quality data sets (27 stations and 19 parameters) collected in this area were interpreted subject to multivariate statistical analysis. Cluster analysis grouped all the stations into four clusters ((Dlink/Dmax) × 100<90) and two clusters ((Dlink/Dmax) × 100<80) for site and period similarities. Principal component analysis rendered six significant components (eigenvalue>1) that explained 82.6% of the total variance of the data set. Classification matrix of discriminant analysis assigned 88.9-92.6% and 83.3-100% correctness in spatial and temporal variability, respectively. Times series analysis then confirmed that only four parameters were not significant over time change. Therefore, it is imperative that the environmental impact of reclamation and dredging works, municipal or industrial discharge, marine aquaculture and shipping activities in this area be effectively controlled and managed.
This paper describes the design of an artificial neural network (ANN) model to predict the water quality index (WQI) using land use areas as predictors. Ten-year records of land use statistics and water quality data for Kinta River (Malaysia) were employed in the modeling process. The most accurate WQI predictions were obtained with the network architecture 7-23-1; the back propagation training algorithm; and a learning rate of 0.02. The WQI forecasts of this model had significant (p < 0.01), positive, very high correlation (ρs = 0.882) with the measured WQI values. Sensitivity analysis revealed that the relative importance of the land use classes to WQI predictions followed the order: mining > rubber > forest > logging > urban areas > agriculture > oil palm. These findings show that the ANNs are highly reliable means of relating water quality to land use, thus integrating land use development with river water quality management.
A computer-aided multivariate water quality index is developed based on partial least squares (PLS) regression. The index is termed as the partial least squares water quality index (PLS-WQI). Briefly, a training set was computationally generated based on the guideline of National Water Quality Standards for Malaysia (NWQS) to predict the water quality. The index is benchmarked with the well-established index developed by the Department of Environment, Malaysia (DOE-WQI). The PLS-WQI is a continuous variable with the value closer to I indicating good water quality and closer to V indicating poor water quality. Unlike other conventional indexing methods, the algorithm calculates the index in a multivariate manner. The algorithm allows rapid processing of a large dataset without tedious calculation; it can be an efficient tool for spatial and temporal routine monitoring of water quality. Although the algorithm is designed based on the guideline of NWQS, it can be easily adapted to accommodate other guidelines. The algorithm was evaluated and demonstrated on the simulated and real datasets. Results indicate that the algorithm is robust and reliable. Based on six parameters, the overall ratings derived are inversely correlated to DOE-WQI. When the number of parameter is increased, the overall ratings appear to provide better insights into the water quality.
Studies on the occurrence of pharmaceutical residues in drinking water were conducted especially in developed countries. However, limited studies reported the occurrence of pharmaceutical residues in developing countries. Thus, this study is conducted to fill the knowledge gap of pharmaceutical residue occurrences in developing countries, particularly in Malaysia, along with public awareness level and its potential human health risk. This study investigates public awareness level of drinking water quality and pharmaceutical handling, the occurrence of nine pharmaceutical residues (amoxicillin, caffeine, chloramphenicol, ciprofloxacin, dexamethasone, diclofenac, nitrofurazone, sulfamethoxazole, and triclosan) and potential human health risks in drinking water from Kajang (Malaysia) using commercially competitive enzyme-linked immunosorbent assay kits. In general, the public awareness level of Kajang population showed poor knowledge (82.02%), and less positive attitude (98.88%) with a good practice score (57.3%). Ciprofloxacin was detected at the highest concentration (0.667 ng/L) while amoxicillin was at the lowest concentration (0.001 ng/L) in drinking water from Kajang (Malaysia). Nevertheless, all the reported occurrences were lower than previous studies conducted elsewhere. There was no appreciable potential human health risk for all the pharmaceutical residues as the risk quotient (RQ) values were less than 1 (RQ water risk management and regulation in Malaysia.