Comparison of water quality index (WQI) between Doe method and Harkin’s index
Water quality index (WQI) provides a convenient means of summarizing large numbers of water quality data, facilitating its communication to a general audience and will aid in establishment of priorities by providing quantitative data on overall water quality in regularly sampled water bodies. Large...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2007
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/11582/1/LimFuiLingMFKKSA2007.pdf |
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| Summary: | Water quality index (WQI) provides a convenient means of summarizing large numbers of water quality data, facilitating its communication to a general audience and will aid in establishment of priorities by providing quantitative data on overall water quality in regularly sampled water bodies. Large volume of continuous time series water quality data can be readily available due to automated continuous water quality monitoring of DOE/ASMA. Raw data obtained from DOE/ASMA for Sungai Rompin, Skudai and Klang from year 1998 to 2002 is analyzed using DOE WQI method and Harkin’s WQI method. Average WQI from the study are: Sungai Rompin DOE 81.65 / Harkins 9.76; Sungai Skudai DOE 67.33 / Harkins 10.80 ; Sungai Klang DOE 51.54 / Harkins 9.63. DOE WQI show that Sungai Rompin is clean river, Sungai Skudai is slightly polluted and Sungai Klang is polluted river. However, Harkin’s WQI is not able to provide the observation as DOE WQI. This indicate that DOE WQI is more sensitive to data changes and provide better insight of river condition compared to Harkin’s WQI. Correlation value, r2 calculated using Microsoft excel obtained for Sungai Rompin is 0.25, Sungai Skudai is 0.59 and Sungai Klang is 0.43. However, weak or marginally significant correlation does not necessary indicate lack of agreement as to what constitutes good or poor water quality because of Harkin’s WQI calculation. Harkin’s WQI dependant on the control vector chosen for the Sn calculation. This is the major hindrance of Harkin’s WQI because the Sn data need to be computed whenever there is new data added to be computed. The control vector chosen also will affect the overall observation because by using different data as the control vector, the whole Harkin’s WQI data will be change. DOE WQI is more dependants on dissolved oxygen (DO) data because it has the highest weighing compared to other parameter. Current DOE WQI method still the preferred simplify method to share data with public. However, there is way to further improve on the water quality information to the authority or public for management. |
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