DUGi

A validation workflow for treatment wetland performance data

http://dugi.udg.edu/item/http:@@@@hdl.handle.net@@10256@@26619

Treatment wetlands (TWs) effectively remove target pollutants and enhance urban water circularity and resilience. They constitute a prominent solution for urban wastewater treatment, thanks to their adaptability across various types of wastewater, scales and climatic conditions. However, the disparity in TW designs and the focus on a restricted set of variables applicable to research studies impede any comprehensive evaluation and comparison of TW performance. Our study introduces a methodology for data validation, in concurrently establishing a workflow specific to TW. This approach is aimed at defining the scope and relationships within the data, implementing checks and concatenating them into a quality flag, as an initial step towards building reliable statistical models. We underscore the importance of both mobilising comprehensive knowledge and identifying customary, yet implicit, choices intertwined in data processing. As for the application workflow, we collected and analysed data sourced from peer-reviewed papers on horizontal and vertical flow TW. Deficiencies were noted in key data elements like dimensions, concentrations and operational conditions. For the data analysis, relationships are highlighted between variables introduced for modelling purposes. These methodologies and workflows assess the quality of the data, in paving the way towards more dependable statistical models for TW design and implementation

This project is part of the MULTISOURCE European project, which has received funding from the European Union’s Horizon H2020 innovation action programme under grant agreement 101003527. This particular research, as a joint venture between INRAE and ICRA, has also received funding from H2O’Lyon University’s School of Research on Water and Hydrosystems Sciences as well as from the Economy and Knowledge Department of the Catalan Government through Consolidated Research Groups ICRA tech (2021-SGR-01283) and LEQUIA (2021-SGR-01352)

IWA Publishing