Abstract
Because Taiwan is a subtropical island, many pleasure beaches are situated on its coast. However, according to long-term monitoring data, fecal contamination at Taiwanese coastal beaches frequently exceeds the U.S. Environmental Protection Agency (EPA) guidelines. To avoid public health hazards, mapping the spatial extent of this contamination is crucial. This study applied indicator kriging (IK) to probabilistically assess the water quality of bathing beaches on the Taiwanese coast. Moreover, because the discontinuity of the traditional Cartesian coordinate established on an island coastline is difficult for geostatistical estimates, this study proposed a novel kriging estimation approach to deal with this problem. First, a one-dimensional (1-D) cyclic coordinate system of the Taiwanese coast was established using primary and secondary coordinates at each beach site. Escherichia coli (E. coli) and enterococci concentrations at coastal beaches were converted into indicator variables according to the U.S. EPA guidelines. IK was then used to spatially model the occurrence probabilities that exceeded the U.S. EPA guidelines for E. coli and enterococci. Finally, the water quality of bathing beaches on the Taiwanese coast was classified on the basis of the estimated probabilities. The study results indicated that bathing on the central western, northeastern, and southeastern Taiwanese coasts poses a potential threat to human health caused by high levels of fecal contamination. Moreover, primary and secondary coordinates established at beach sites were capable of analyzing the spatial variability and kriging estimates of the 1-D cyclic coordinates along the coastline.
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The author would like to thank the Taiwan Environmental Protection Administration generously supporting the data on E. coli and enterococci concentrations at 12 Taiwanese beaches.
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Jang, CS. Probabilistic assessment of the water quality of bathing beaches on the Taiwanese coast using indicator-based geostatistics with one-dimensional cyclic coordinates. Environ Earth Sci 77, 760 (2018). https://doi.org/10.1007/s12665-018-7958-5
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DOI: https://doi.org/10.1007/s12665-018-7958-5