Applying high-frequency surrogate measurements and a wavelet-ANN model to provide early warnings of rapid surface water quality anomalies.

@article{Shi2018ApplyingHS,
  title={Applying high-frequency surrogate measurements and a wavelet-ANN model to provide early warnings of rapid surface water quality anomalies.},
  author={Bin Shi and Peng Wang and Jiping Jiang and Rentao Liu},
  journal={The Science of the total environment},
  year={2018},
  volume={610-611},
  pages={1390-1399}
}
It is critical for surface water management systems to provide early warnings of abrupt, large variations in water quality, which likely indicate the occurrence of spill incidents. In this study, a combined approach integrating a wavelet artificial neural network (wavelet-ANN) model and high-frequency surrogate measurements is proposed as a method of water quality anomaly detection and warning provision. High-frequency time series of major water quality indexes (TN, TP, COD, etc.) were produced… CONTINUE READING