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A feature-based framework for detecting technical outliers in water-quality data from in situ sensors
Priyanga Dilini Talagala, Rob J. Hyndman, Catherine Leigh +2
Outliers due to technical errors in water-quality data from in situ sensors can reduce data quality and have a direct impact on inference drawn from subsequent data analysis. Howev…
Predicting Sediment and Nutrient Concentrations in Rivers Using High Frequency Water Quality Surrogates
Catherine Leigh, Sevvandi Kandanaarachchi, James M. McGree +4
A particular focus of water-quality monitoring is the concentrations of sediments and nutrients in rivers, constituents that can smother biota and cause eutrophication. However, th…
A framework for automated anomaly detection in high frequency water-quality data from in situ sensors
Catherine Leigh, Omar Alsibai, Rob J. Hyndman +9
River water-quality monitoring is increasingly conducted using automated in situ sensors, enabling timelier identification of unexpected values. However, anomalies caused by techni…