From Fragmented to Integrated: Advancing Surface Water Quality Assessment through WQPI in the Upper Medjerda River, Northeastern Algeria.

Abstract

Assessing water quality in semi-arid river systems under intense anthropogenic pressures presents significant challenges for sustainable management. In this study, we evaluated the surface water quality of the upper Medjerda River in northeastern Algeria by integrating traditional indices, the Organic Pollution Index (OPI) and the Weighted Arithmetic Water Quality Index (WA_WQI), with advanced multivariate analyses including Principal Component Analysis (PCA) and Generalized Linear Models (GLMs). To overcome the limitations of conventional methods, we developed a new composite metric, the Water Quality Pollution Index (WQPI), synthesizing both general physicochemical conditions and organic pollution. Results revealed widespread degradation at upstream sites, where 50% of samples exhibited very poor water quality according to WA_WQI and 37.5% were classified as highly organically polluted by OPI. Spatial interpolation highlighted intense pollution near urbanized zones, with a gradual downstream improvement; whereas the GLM analyses identified nitrate (NO₃⁻) as the most critical factor for influencing water quality and its variability, confirming its dominant role in nutrient-driven pollution processes. The results of WQPI provided a clearer classification of water quality, capturing pollution dynamics overlooked by traditional indices. Notably, 12.5% of stations exhibited very poor water quality and 75% showed poor quality. This underscores the value of integrated approaches for monitoring and managing semi-arid basins.