This study evaluates the performance of the Ain El Houtz wastewater treatment plant (WWTP) in Tlemcen, Algeria, by applying a fuzzy logic-based framework to multi-scale temporal data. A total of 2192 effluent samples collected between 2020 and 2022 were analyzed for Biochemical Oxygen Demand over five days (BOD5), Chemical Oxygen Demand (COD), dissolved oxygen (O-2), pH, nitrate (NO3-), phosphate (PO43-), and temperature. Expert-derived parameter weights were integrated into a Mamdani fuzzy inference system to compute a Fuzzy Water Quality Index (FWQI). Sensitivity analysis was conducted to assess the robustness of the model to variations in weights and membership functions. Results revealed satisfactory performance in 2020 and 2022 (FWQI > 85%), while 2021 showed critical degradation (FWQI approximate to 50%), unrelated to seasonal climate variability. Comparison with raw parameters and regulatory thresholds validated the FWQI's ability to capture operational fluctuations. This work represents the first multi-scale fuzzy logic application to wastewater treatment monitoring in Algeria, highlighting both the potential and limitations of fuzzy indices in semi-arid contexts. The approach provides a transferable decision-support tool for improving effluent quality management and guiding corrective actions in WWTPs.