A new study by the Competence Centre for Water Berlin addresses a key problem of water reuse in agricultural irrigation: validating that water treatment plants reliably meet the required performance targets.
The study investigated statistical methods for compliance with EU Regulation 2020/741, which requires that 90% of the calculated Log10 reduction values used to assess removal performance must meet strict criteria. Various statistical approaches, including binomial weighting, tolerance intervals, and Bayesian methods, were examined for their suitability in validating treatment performance. Data from a German wastewater treatment plant were analyzed over a period of more than one year, focusing on three key indicators of water quality: E. coli bacteria, Clostridium perfringens spores , and somatic coliphages (viruses that infect bacteria).
The results highlight the advantages of Bayesian tolerance intervals, which address real-world challenges such as unequal sample sizes, non-normally distributed data, and measurements below the detection limit. At the same time, they enable a more rigorous consideration of statistical uncertainty. This approach allows for reliable and valid results even with smaller datasets. Therefore, the study suggests incorporating the use of tolerance intervals into the development of future water reuse guidelines to increase confidence in water reuse and thus contribute to addressing global water scarcity.
Beyond water reuse, the study highlights the broad applicability of these statistical methods in the fields of environmental monitoring and public health. High percentiles , such as those used in the assessment of bathing water or irrigation water quality, could also benefit from such approaches.
By refining statistical methods for process validation, this study contributes to the discussion on the use of best available methods to ensure microbial safety in water reuse. Thus, it makes an important contribution to promoting sustainable practices and addressing urgent resource conflicts, the authors write.
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