- Thesis topic: Study on the Impact of River Pollution Index(RPI) by River Flowrate

- Doi: https://doi.org/10.6840/cycu202301080

- Abstract: 

       The water resources are the essential resource in human society, which affects the daily life of everyone. The major freshwater resource of Taiwan mainly come from reservoir and river. Due to Taiwan is an island, it does have enough land for the densely populated. Thus , no matter whether it is in the plains or on the high mountains, there still have human activities exist. However, some area of reservoir or the catchment of river are suffering from excessive land development or pollution of land and water sources, and there often occurs heavy rainfall due to the variably climate and weather of Taiwan. With this conditions, in the state of incomplete water and soil conservation and contaminated soil and water sources, pollutants are often brought into natural water bodies, causing pollution of freshwater resources. Therefore, It is necessary to pay attention to contaminated fresh water sources. The indicators commonly used to indicate water quality standards include RPI and WQI. At present, in the research on water resources, correlation analysis, regression analysis and multivariate analysis are often used to study the causes of water pollution and water quality characteristics. This study uses narrative statistics, correlation analysis, regression analysis and principal component analysis to explore the impact of river runoff in Taiwan on the nature of river pollution
       The research results show that the river runoff is most correlated with the concentration of suspended solids in the water, whether it is analyzed in different time periods or in different regions, showing a moderate correlation or above, and the highest correlation coefficient r is 0.577. The most relevant river pollution index. In the single regression analysis results of different time periods and different regions, ammonia nitrogen is always the water quality parameter with the highest explanatory power. The results of multiple regression analysis show that when the analysis time is prolonged, the water quality parameters that can be explained by the river pollution index increase. However, since the explanatory power of each water quality parameter for the river pollution index is different, the explanatory power of the regression full model for the river pollution index is reduced from 71.8% to 67.7%. In the results of multiple regression analysis in different regions, the central river has the highest explanatory ability for river pollution index, which can explain 78.7% of the pollution situation in the central river, followed by the southern river, the coefficient of determination R2 value is 0.706, and the eastern river has the highest explanatory ability. Poor, with an explanatory power of 28.1%. The results of the recalculation of the weights of the water quality parameters of the rivers in each region from the principal component analysis showed that compared with the BOD, the COD obtained a higher weight value, indicating that the COD has a better explanation for the pollution of the river. In addition, when the water quality parameters are analyzed by principal components, the KMO value is the highest in the analysis results of the past five years, reaching 0.614, and the total variance explained is up to 68.26%, and 4 principal components can be extracted; In the PCA/FA analysis, the KMO value of the central river was the highest, reaching 0.679, the total variance explained was 65.63%, and three principal components could be extracted. Among the influencing factors of river pollution properties obtained after factor rotation, the overall factor extraction and rotation axis can describe the river pollution properties above 65%. Among them, river runoff has the most influence on the pollution properties of central and eastern rivers. Remarkably.

Keywords: River Pollution Index, River Runoff, Correlation Analysis, Regression Analysis, Principal Component Analysis, River Water Quality