Regression-based design optimization of French treatment wetlands.

This study presents a novel approach for the automatic optimization of sizing French vertical flow wetlands, a widely used solution in wastewater treatment across France, with over 6,000 operational units. By leveraging a comprehensive database collected by the French National Research Institute for Agriculture, Food and Environment (INRAE), we have developed robust regression models that link total Kjeldahl nitrogen to surface and total chemical oxygen demand to material depth. By integrating these models into a unified optimization framework, our methodology enhances the design of the entire treatment train, particularly addressing how the sizing of the first stage influences the second stage sizing while complying with stringent effluent quality standards. Extensive validation confirms the effectiveness and reliability of our approach, which is tailored to specific influent characteristics and regulatory requirements. Our strategy improves upon traditional sizing methods, which often rely on surface loads, by allowing for refined optimization based on specific performance targets. The findings contribute to improved design practices and suggest potential directions for future developments, including the integration of additional treatment processes and multi-criteria decision analysis for broader applicability in wastewater management.