It is not easy to state clearly to the public for quality of groundwater bodies, even if there are a large number of effective water quality data, it is still hard to combine and induct,and it often occurs in different units have each put forward to explain on the test results.Multivariate statistical analysis method can simplify high complex data into a representative function of the small number of factors, clearly explained to a group of inter-relationship of the original variables, or to be clustered and identified according to the similarity between the data to understand the reason behind the formation of certain phenomena, so this study utilize it to explore the groundwater characteristics.
In this study, monitoring data come from the Kaohsiung city 48 groundwater monitoring wells of the EPA National Water Quality Monitoring Information website database, apply SPSS12.0 package software to execute multivariate statistical analysis, including factor analysis ,cluster analysis and discriminant analysis, and thus induction, sorting and classification of water quality characteristics, evaluating the causes of pollution and local area characteristics. The results of factor analysis to obtain the groundwater quality of the Kaohsiung region 4 representative factors: the factor of salinization, organic pollution factor, the factor of ore melting and acid-base factor. Four principal component factors instead of the 17 analysis projects of the regional groundwater quality in Kaohsiung city, the variance amounted to 78.3%. Use of cluster analysis of the 48 monitoring wells in the region is divided into four groups, according to the different nature of the monitoring data and the nature of similarity and group, to investigate the correlation between the monitoring well water quality within each cluster and the main factor, and by monitoring wells position to distinguish between the average underground water quality of inland area than the coastal area, we can get the results of seawater intrusion and salinization phenomena in coastal area, and monitoring wells located in the Cijin district are polluted by the pH factor. Kaohsiung regional groundwater quality is generally in the case of hard water to very hard water.
In order to understand the difference of the multivariate statistical analysis method and the general groundwater pollution index analysis, draw Piper water quality diamond cluster analysis diagram to compare the similarities and differences,the results show that the multivariate statistical analysis can supply a systematic analysis of variable data and the overall variations of the water quality, and objective clustering, while the general composite index analytcial method such as Piper, by the characteristic position to get the type of pollution, but difficult to explain the overall pollution characteristics. At last, in this study, the hope to recommend the pollution control assessment and prevention strategies of Kaohsiung city underground water.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0824112-152131 |
| Date | 24 August 2012 |
| Creators | Wang, Mei-hsueh |
| Contributors | Ting-Yu Chen, Ping-Chih Huang, Chin-Ming Kao, Chi-Tsan Lin |
| 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-0824112-152131 |
| Rights | user_define, Copyright information available at source archive |
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