In recent years, many construct wetlands in Taiwan have been built for the purposes of wastewater treatment, river water purification, and ecology conservation. To evaluate the effectiveness of constructed wetlands on water purification, frequent water quality monitoring is needed. In this study, the multivariate statistical analysis was applied to evaluate the contaminant removal efficiency in a constructed wetland, and the time series method was then used to predict the trend of the indicative pollutant concentration in the wetland.
Multivariate statistical analysis simplifies the original data into representative factors, or hive off the similarity between data to cluster, and then identify clustering outcomes. In this study, an artificial wetlands at the site around an old bridge locates at the Kaoping River Basin was used as the study site. The statistical software SPSS 12.0 was used to perform the multivariate statistical analysis to evaluate water quality characteristics of its. Results from this study show that the removal efficiency for the total coliforms (TC) of System A and B was 98%, 55% for biochemical oxygen demand (BOD), 53% for chemical Oxygen demand (COD), 55% for ammonia nitrogen (NH3-N), and 39% for total nitrogen (TN). Moreover, suspended solids (SS) couldn¡¦t be removed in both A and B systems. The box-and-whisker plot indicates that the water quality of inflow was unstable and variable; however, outflow was turning stable with its flow direction. The major pollutant indicators, except SS, were all in a decreasing tendency. The paired t-test shows p value of each item were lower than 0.05, except total phosphorus (TP) in System A, nitrate nitrogen (NO3-N) and Chlorophyll a (Chl-a) in System B. The correlation parameters from TN, nitrogen oxides (NOx), NO3-N and nitrite nitrogen (NO2-N) and so on were all higher than 0.7.
The factor analysis of SPSS shows that 17 water-quality items of the study site could obtain four to six principal components, including nitrate nutrition factor, phosphorus nutrition factor, eutrophication factor, organic factor, and environmental background factor, the major influencing components are nutrition factor and eutrophication factor. The ponds of the study site were classified into two or three clusters depend on in-and-out flow location. This study attempted to establish a forecasting model of wetland pollutants concentration through the time series (ARIMA), results show that the outcome of the B7 pond was better than others. Results indicate that the ARIMA model can be used to simulate the trend of treatment efficiency using the wetland system. Experience and results obtained from this study would provide solutions for water quality control.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0830110-021108 |
| Date | 30 August 2010 |
| Creators | Wu, Fang-Ling |
| Contributors | C.S. Yu, C. M. Kao, T. Y. Yeh, Ting-Nien Wu |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | Cholon |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0830110-021108 |
| Rights | not_available, Copyright information available at source archive |
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