Estimation of River Pollution Index in a Tidal Stream Using Kriging Analysis

International Journal of Environmental Research and Public Health

Yen-Chang Chen²  Hui-Chung Yeh¹ 

[1] Department of Natural Resources, Chinese Culture University, Taipei 11114, Taiwan;Department of Civil Engineering, National Taipei University of Technology, Taipei 10608, Taiwan;

关键词: geostatistics;    kriging;    river pollution index;    tidal stream;    water quality;   

DOI  :  10.3390/ijerph9093085

来源: mdpi

【 摘 要 】

Tidal streams are complex watercourses that represent a transitional zone between riverine and marine systems; they occur where fresh and marine waters converge. Because tidal circulation processes cause substantial turbulence in these highly dynamic zones, tidal streams are the most productive of water bodies. Their rich biological diversity, combined with the convenience of land and water transports, provide sites for concentrated populations that evolve into large cities. Domestic wastewater is generally discharged directly into tidal streams in Taiwan, necessitating regular evaluation of the water quality of these streams. Given the complex flow dynamics of tidal streams, only a few models can effectively evaluate and identify pollution levels. This study evaluates the river pollution index (RPI) in tidal streams by using kriging analysis. This is a geostatistical method for interpolating random spatial variation to estimate linear grid points in two or three dimensions. A kriging-based method is developed to evaluate RPI in tidal streams, which is typically considered as 1D in hydraulic engineering. The proposed method efficiently evaluates RPI in tidal streams with the minimum amount of water quality data. Data of the Tanshui River downstream reach available from an estuarine area validate the accuracy and reliability of the proposed method. Results of this study demonstrate that this simple yet reliable method can effectively estimate RPI in tidal streams.

【 授权许可】

CC BY   
© 2012 by the authors; licensee MDPI, Basel, Switzerland.