The aim of this study is to conduct a comprehensive assessment of the water quality of the Sidi Mohammed Ben Taiba (SMBT), one of the largest drinking water reservoirs in northwestern Algeria, by integrating chemical and biological indicators. The assessment combines the Drinking Water Quality Index (DWQI), the Irrigation Water Quality Index (IWQI), the Organic Pollution Index (OPI) and zooplankton-based biological indicators (Zoo-IQ). A total of 23 physicochemical parameters were analyzed and interpreted using multivariate statistical approaches. This study fills an important knowledge gap by evaluating long-term temporal variability (January 2018–May 2025) and recent spatial heterogeneity (June 2023–May 2025), aiming to support sustainable water management. The results indicate that the reservoir water quality is generally suitable for drinking purposes (22.3 < DWQI < 54.0), is deemed excellent for agricultural irrigation (65 < IWQI < 69) and that the reservoir surface waters are slightly polluted to unpolluted (0.3 < OPI < 1.1). However, a deterioration in water quality has been detected in recent years, linked to increasing nutrient concentrations, as confirmed by the TSI–SD index. Despite the early signs of nutrient enrichment, the Zoo-IQ index remained within the moderate to good range, suggesting a certain degree of resilience in the zooplankton community. However, pronounced seasonal fluctuations observed in the Zoo-IQ and species diversity (H′) during periods of environmental stress serve as an early warning signal of emerging problems that may negatively affect water quality indices (WQI, IWQI, OPI). Station S4, located at the confluence of Wadi Belhassen and Wadi Farhat, descending from the Dahra mountain range in Algeria, has been identified as the most sensitive area and a potential hotspot for future pollution. The study provides robust data on the quality of reservoir water, offering a valuable decision-making tool for artificial reservoir managers and contributing to sustainable water management by identifying risk areas and supporting the implementation of preventive measures.
Bokreta et al. (Fri,) studied this question.