Eutrophication, driven by nutrient enrichment, represents substantial anthropogenic pressure with harmful consequences for aquatic ecosystems. The Water Framework Directive provides a structured approach to addressing this challenge as it requires European Union Member States to achieve at least good ecological status for their surface waters. The establishment of realistic nutrient boundaries, above which negative effects become pronounced, is essential to guide regulatory intervention aimed at securing long-term water sustainability in Europe. Greece is one of the Member States which should determine nutrient boundaries supporting the good ecological status of lakes. Two statistical approaches, ranged major axis regression and binomial logistic regression, were applied for setting appropriate nutrient boundaries for Greek natural lakes and reservoirs, using datasets of phytoplankton and total phosphorus concentrations, retrieved from the national monitoring program (2016–2023). The predicted boundary values for total phosphorus supporting good ecological status ranged from 32 to 76 μg/L, with stricter boundaries corresponding to deep lakes. Nutrient boundaries that reflect the environmental pressures on Greek natural lakes and reservoirs are fundamental to ensure proper design of lake management strategies.

Water transparency is a simple qualitative feature widely used as a proxy for lake trophic state and eutrophication pressure. The Water Framework Directive (WFD) requires boundaries for physical and chemical supporting elements to ensure good ecological status, yet many Member States lack type-specific transparency boundaries linked to biological responses. Secchi depth represents an ideal indicator for both expert and non-expert monitoring, integrating ecohydrological processes into an accessible, cost-effective measure. This study aims to designate water transparency boundaries supporting good ecological status for three Greek natural lake types: very shallow, shallow and deep lakes, for monitoring and management. Using national monitoring data (2013–2023) from 19 natural lakes, we applied binary logistic regression to establish transparency boundaries calibrated against two biological quality elements (BQEs): phytoplankton and macrophytes. Model performance showed moderate to good predictive capacity with a conservative error balance favoring environmental protection. The analysis yielded type-specific boundaries of 0.6 m for very shallow lakes (phytoplankton), 1.4–1.5 m for shallow lakes (macrophytes and phytoplankton, respectively) and 3.1 m for deep lakes (phytoplankton). These empirically derived, BQE-validated boundaries provide operational targets for WFD compliance, restoration planning and citizen science monitoring programs, supporting adaptive ecohydrological management of Mediterranean lake ecosystems while enabling accessible long-term trend assessment.