2021_Development of Improved Water Quality Modeling For Sungai Beranang Using Multivariate Techniques
| Format: | General Document |
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| _version_ | 1860797989115658240 |
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| building | INTELEK Repository |
| collection | Online Access |
| collectionurl | https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection3 |
| copyright | Copyright©PWB2025 |
| country | Malaysia |
| date | 2021-05-10 16:21 |
| format | General Document |
| id | 15304 |
| institution | UniSZA |
| originalfilename | DEVELOPMENT OF IMPROVED WATER QUALITY MODELING FOR SUNGAI BERANANG USING MULTIVARIATE TECHNIQUES |
| person | PDFsam Basic v4.2.10 Alabyad Laila Omar Mohammed |
| recordtype | oai_dc |
| resourceurl | https://intelek.unisza.edu.my/intelek/pages/view.php?ref=15304 |
| sourcemedia | Server storage Scanned document |
| spelling | 15304 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=15304 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection3 General Document Malaysia Library Staff (Top Management) Library Staff (Management) Library Staff (Support) Terengganu English UniSZA East Coast Environmental Research Institute application/pdf 1.5 PDFsam Basic v4.2.10 337 Server storage Scanned document Universiti Sultan Zainal Abidin UniSZA Private Access Universiti Sultan Zainal Abidin SAMBox 2.3.4; modified using iTextSharp™ 5.5.10 ©2000-2016 iText Group NV (AGPL-version) DEVELOPMENT OF IMPROVED WATER QUALITY MODELING FOR SUNGAI BERANANG USING MULTIVARIATE TECHNIQUES 2021_Development of Improved Water Quality Modeling For Sungai Beranang Using Multivariate Techniques Multivariate Techniques Copyright©PWB2025 Environmental monitoring—Malaysia Multivariate analysis Watershed management—Malaysia Alabyad Laila Omar Mohammed 2021-05-10 16:21 Water Quality Modeling Sungai Beranang Water quality—Malaysia—Sungai Beranang Water quality management—Malaysia Water—Pollution—Malaysia—Sungai Beranang Hydrological modeling—Malaysia River water—Quality—Malaysia—Sungai Beranang Pollution—Mathematical models Water chemistry—Malaysia—Sungai Beranang Sungai Beranang is one of the main reaches of the Langat River, and one of the main sources of water supply in Selangor. It is subjected to pressure due to rapid urbanization and other anthropogenic activities within its proximity areas such as agricultural, residential, recreational and industrialization. All of these activities have altered the land use pattern and deteriorated the water quality of the Sungai Beranang. This study was conducted to assess the spatialtemporal variations of water quality in Sungai Beranang, identify the possible water pollution source and develop Multivariate Water Quality Index (MWQI). Water quality of Sungai Beranang (physical and biological parameters) was measured based on the National Water Quality Standards (NWQS). Multivariate statistical techniques, such as Hierarchical Agglomerative Clustering Analysis (HACA), Principal Component Analysis (PCA), Discriminant Analysis (DA), Multiple Linear Regression (MLR), and Artificial Neural Networks (ANN) were used to assess the spatial/temporal differences in the water quality of Sungai Beranang covering a one-year period of September (2017) to November (2018) for the wet and the dry seasons at nine different locations. Multivariate water quality index (MWQI) using the varimax rotation of PCA was developed to categorize the water pollution levels, which are low, moderate and high. The analysis output clearly indicated that the Sungai Beranang Basin was classified under Class III of Malaysia river water quality standard as resulted from multi-point sources of pollution. The Water Quality Index WQI trend analysis revealed that the upstream water quality of Sungai Beranang was relatively good. HACA yielded three different clusters according to the level of pollution; which are High Pollution Area (HPA), Moderate Pollution Area (MPA) and Low Pollution Area (LPA). The output of DA backward mode revealed that the source apportionment discrimination was achieved with the classification matrix accuracy of 87.74 % with pH, Salinity, COD, TSS, NH3N, NO2, NO3, SO4, EC, Cd, Mg, Zn and Cr. Those significant parameters have a high variation of spatial distribution. While, variation of temporal distribution was achieved with the classification matrix accuracy of 94.44 % with Temperature, Salinity, TSS, NH3-N, Turbidity, EC, O&G, E. coli, Fe, Zn, Pb, Cu. PCA varimax factors (VFs) are responsible for 87.15%, 80.05% and 77.78% of the total variance for LPA, MPA and HPA, respectively. Furthermore, five pollutants (organic, nutrient, chemical, mineral and natural) were the factors aggravating the quality of Sungai Beranang. ANN prediction model was to predict the most significant variables that contaminated Sungai Beranang. MLP-FF-ANN Model B was the best prediction model with the R2 and RMSE values of 0.969 and1.33, respectively. MWQI yielded three categories of water quality pollution level which are low, moderate and high. DA-MLR model gave a good accuracy model performance for forecasting the WQI. The R2 value was 0.90 and the model exhibited 90% variability of WQI. The multivariate techniques in this study was the most effective and reliable in solving the source apportionment of pollution in Sungai Beranang with time and cost savings. The policy maker and relevant government agencies should adopt this approach for monitoring program of the Sungai Beranang as part of the water resources management. Dissertations, Academic Thesis |
| spellingShingle | 2021_Development of Improved Water Quality Modeling For Sungai Beranang Using Multivariate Techniques |
| state | Terengganu |
| subject | Environmental monitoring—Malaysia Multivariate analysis Watershed management—Malaysia Water quality—Malaysia—Sungai Beranang Water quality management—Malaysia Water—Pollution—Malaysia—Sungai Beranang Hydrological modeling—Malaysia River water—Quality—Malaysia—Sungai Beranang Pollution—Mathematical models Water chemistry—Malaysia—Sungai Beranang Dissertations, Academic |
| summary | Sungai Beranang is one of the main reaches of the Langat River, and one of the main sources of water supply in Selangor. It is subjected to pressure due to rapid urbanization and other anthropogenic activities within its proximity areas such as agricultural, residential, recreational and industrialization. All of these activities have altered the land use pattern and deteriorated the water quality of the Sungai Beranang. This study was conducted to assess the spatialtemporal variations of water quality in Sungai Beranang, identify the possible water pollution source and develop Multivariate Water Quality Index (MWQI). Water quality of Sungai Beranang (physical and biological parameters) was measured based on the National Water Quality Standards (NWQS). Multivariate statistical techniques, such as Hierarchical Agglomerative Clustering Analysis (HACA), Principal Component Analysis (PCA), Discriminant Analysis (DA), Multiple Linear Regression (MLR), and Artificial Neural Networks (ANN) were used to assess the spatial/temporal differences in the water quality of Sungai Beranang covering a one-year period of September (2017) to November (2018) for the wet and the dry seasons at nine different locations. Multivariate water quality index (MWQI) using the varimax rotation of PCA was developed to categorize the water pollution levels, which are low, moderate and high. The analysis output clearly indicated that the Sungai Beranang Basin was classified under Class III of Malaysia river water quality standard as resulted from multi-point sources of pollution. The Water Quality Index WQI trend analysis revealed that the upstream water quality of Sungai Beranang was relatively good. HACA yielded three different clusters according to the level of pollution; which are High Pollution Area (HPA), Moderate Pollution Area (MPA) and Low Pollution Area (LPA). The output of DA backward mode revealed that the source apportionment discrimination was achieved with the classification matrix accuracy of 87.74 % with pH, Salinity, COD, TSS, NH3N, NO2, NO3, SO4, EC, Cd, Mg, Zn and Cr. Those significant parameters have a high variation of spatial distribution. While, variation of temporal distribution was achieved with the classification matrix accuracy of 94.44 % with Temperature, Salinity, TSS, NH3-N, Turbidity, EC, O&G, E. coli, Fe, Zn, Pb, Cu. PCA varimax factors (VFs) are responsible for 87.15%, 80.05% and 77.78% of the total variance for LPA, MPA and HPA, respectively. Furthermore, five pollutants (organic, nutrient, chemical, mineral and natural) were the factors aggravating the quality of Sungai Beranang. ANN prediction model was to predict the most significant variables that contaminated Sungai Beranang. MLP-FF-ANN Model B was the best prediction model with the R2 and RMSE values of 0.969 and1.33, respectively. MWQI yielded three categories of water quality pollution level which are low, moderate and high. DA-MLR model gave a good accuracy model performance for forecasting the WQI. The R2 value was 0.90 and the model exhibited 90% variability of WQI. The multivariate techniques in this study was the most effective and reliable in solving the source apportionment of pollution in Sungai Beranang with time and cost savings. The policy maker and relevant government agencies should adopt this approach for monitoring program of the Sungai Beranang as part of the water resources management. |
| title | 2021_Development of Improved Water Quality Modeling For Sungai Beranang Using Multivariate Techniques |
| title_full | 2021_Development of Improved Water Quality Modeling For Sungai Beranang Using Multivariate Techniques |
| title_fullStr | 2021_Development of Improved Water Quality Modeling For Sungai Beranang Using Multivariate Techniques |
| title_full_unstemmed | 2021_Development of Improved Water Quality Modeling For Sungai Beranang Using Multivariate Techniques |
| title_short | 2021_Development of Improved Water Quality Modeling For Sungai Beranang Using Multivariate Techniques |
| title_sort | 2021_development of improved water quality modeling for sungai beranang using multivariate techniques |