Temporal Aspects of Surface Water Quality Variation Using Robust Statistical Tools
Robust statistical tools were applied on the water quality datasets with the aim of determining the most significance parameters and their contribution towards temporal water quality variation. Surface water samples were collected from four different sampling points during dry and wet seasons and an...
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1100/2012/294540 |
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| author | Adamu Mustapha Ahmad Zaharin Aris Mohammad Firuz Ramli Hafizan Juahir |
| author_facet | Adamu Mustapha Ahmad Zaharin Aris Mohammad Firuz Ramli Hafizan Juahir |
| author_sort | Adamu Mustapha |
| collection | DOAJ |
| description | Robust statistical tools were applied on the water quality datasets with the aim of determining the most significance parameters and their contribution towards temporal water quality variation. Surface water samples were collected from four different sampling points during dry and wet seasons and analyzed for their physicochemical constituents. Discriminant analysis (DA) provided better results with great discriminatory ability by using five parameters with (P<0.05) for dry season affording more than 96% correct assignation and used five and six parameters for forward and backward stepwise in wet season data with P-value (P<0.05) affording 68.20% and 82%, respectively. Partial correlation results revealed that there are strong (rp=0.829) and moderate (rp=0.614) relationships between five-day biochemical oxygen demand (BOD5) and chemical oxygen demand (COD), total solids (TS) and dissolved solids (DS) controlling for the linear effect of nitrogen in the form of ammonia (NH3) and conductivity for dry and wet seasons, respectively. Multiple linear regression identified the contribution of each variable with significant values r = 0.988, R2 = 0.976 and r = 0.970, R2 = 0.942 (P<0.05) for dry and wet seasons, respectively. Repeated measure t-test confirmed that the surface water quality varies significantly between the seasons with significant value P<0.05. |
| format | Article |
| id | doaj-art-2163079118fb4f0bab4676ce35ffc8c7 |
| institution | Kabale University |
| issn | 1537-744X |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-2163079118fb4f0bab4676ce35ffc8c72025-02-03T05:44:16ZengWileyThe Scientific World Journal1537-744X2012-01-01201210.1100/2012/294540294540Temporal Aspects of Surface Water Quality Variation Using Robust Statistical ToolsAdamu Mustapha0Ahmad Zaharin Aris1Mohammad Firuz Ramli2Hafizan Juahir3Centre of Excellence for Environmental Forensics, Faculty of Environmental Studies, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, MalaysiaCentre of Excellence for Environmental Forensics, Faculty of Environmental Studies, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, MalaysiaCentre of Excellence for Environmental Forensics, Faculty of Environmental Studies, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, MalaysiaCentre of Excellence for Environmental Forensics, Faculty of Environmental Studies, Universiti Putra Malaysia, 43400 UPM Serdang, Selangor, MalaysiaRobust statistical tools were applied on the water quality datasets with the aim of determining the most significance parameters and their contribution towards temporal water quality variation. Surface water samples were collected from four different sampling points during dry and wet seasons and analyzed for their physicochemical constituents. Discriminant analysis (DA) provided better results with great discriminatory ability by using five parameters with (P<0.05) for dry season affording more than 96% correct assignation and used five and six parameters for forward and backward stepwise in wet season data with P-value (P<0.05) affording 68.20% and 82%, respectively. Partial correlation results revealed that there are strong (rp=0.829) and moderate (rp=0.614) relationships between five-day biochemical oxygen demand (BOD5) and chemical oxygen demand (COD), total solids (TS) and dissolved solids (DS) controlling for the linear effect of nitrogen in the form of ammonia (NH3) and conductivity for dry and wet seasons, respectively. Multiple linear regression identified the contribution of each variable with significant values r = 0.988, R2 = 0.976 and r = 0.970, R2 = 0.942 (P<0.05) for dry and wet seasons, respectively. Repeated measure t-test confirmed that the surface water quality varies significantly between the seasons with significant value P<0.05.http://dx.doi.org/10.1100/2012/294540 |
| spellingShingle | Adamu Mustapha Ahmad Zaharin Aris Mohammad Firuz Ramli Hafizan Juahir Temporal Aspects of Surface Water Quality Variation Using Robust Statistical Tools The Scientific World Journal |
| title | Temporal Aspects of Surface Water Quality Variation Using Robust Statistical Tools |
| title_full | Temporal Aspects of Surface Water Quality Variation Using Robust Statistical Tools |
| title_fullStr | Temporal Aspects of Surface Water Quality Variation Using Robust Statistical Tools |
| title_full_unstemmed | Temporal Aspects of Surface Water Quality Variation Using Robust Statistical Tools |
| title_short | Temporal Aspects of Surface Water Quality Variation Using Robust Statistical Tools |
| title_sort | temporal aspects of surface water quality variation using robust statistical tools |
| url | http://dx.doi.org/10.1100/2012/294540 |
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