Abstract
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.
Highlights
The complex flow of tidal streams is mainly influenced by interactions between river water and seawater
The spatial distribution of river pollution index (RPI) of the Tanshui River and its branches was simulated successfully by combining the 1D ordinary kriging method with water quality data collected in the field
This approach is simpler than simulation through conventional 2D variable hydrological models. This approach solves the problem of determining complex initial conditions necessary for boundary building in models; instead, only the sampled data are used to represent the average water quality of the studied river section
Summary
The complex flow of tidal streams is mainly influenced by interactions between river water and seawater. Waves caused by wind shear alter the circulation patterns and mixing process of river water and seawater Within this process, only a 2% difference in density between river water and sea water results in a horizontal pressure gradient, which affects water flow. Traditional models fail to accurately estimate the flow and water quality of tidal streams. Lo et al (1999) [7] applied a steady-state quality model to simulate the biochemical oxygen demand (BOD) and kriging theory for selecting optimal sampling locations and frequency. Their results indicated a total number of monitoring stations in the Keelung River of 21 and a sampling frequency of approximately 2–3 times per month. Our proposed algorithm is based on 1D kriging and provides a simple and efficient solution for the complexities of boundary conditions encountered in traditional 2D hydrological models
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