Analysis of hydrological trend for radioactivity content in bore-hole water samples using wavelet based denoising

A wavelet transform based denoising methodology has been applied to detect the presence of any discernable trend in 137Cs and 90Sr activity levels in bore-hole water samples collected four times a year over a period of eight years, from 2002 to 2009, in the vicinity of typical nuclear facilities inside the restricted access zones. The conventional non-parametric methods viz., Mann–Kendall and Spearman rho, along with linear regression when applied for detecting the linear trend in the time series data do not yield results conclusive for trend detection with a confidence of 95% for most of the samples. The stationary wavelet based hard thresholding data pruning method with Haar as the analyzing wavelet was applied to remove the noise present in the same data. Results indicate that confidence interval of the established trend has significantly improved after pre-processing to more than 98% compared to the conventional non-parametric methods when applied to direct measurements.

► Environmental trend analysis with wavelet pre-processing was carried out.
► Removal of local fluctuations to obtain the trend in a time series with various mother wavelets.
► Theoretical validation of the methodology with model outputs.
► Efficient detection of trend for 137Cs, 90Sr in bore-hole water samples improves the associated confidence interval to more than 98%.
► Wavelet based pre-processing reduces the indecisive nature of the detected trend.