Noise reduction in chaotic hydrologic time series: facts and doubts

The issues of noise reduction and the reliability of its application to hydrologic time series are discussed. First, the concepts of noise, its effect, and noise reduction are briefly presented. Second, a few published articles in hydrology are critically reviewed with regard to the application of noise reduction to hydrologic data. Third, a case study of the English River, Ontario, Canada, is used to support the conclusions. It is found that the commonly used algorithm for noise reduction in hydrologic data might also remove a significant part of the original signal and introduce an artificial chaoticity to the data. It is recommended that current noise reduction algorithms should be applied with caution and used only for better estimation of chaotic invariants. The raw data should always be the basis for any further hydrologic analysis.