International Journal of Environment and Climate Change

Background: Surface waters in urban agricultural areas are increasingly exposed to contamination from farming practices, domestic activities, and rapid urbanization, which can alter their physicochemical quality. In Daloa (Côte d’Ivoire), the expansion of lettuce and rice cultivation around lowland water bodies highlights the need to assess water quality and identify the main factors influencing physicochemical variability.

Aims: This study aimed to characterize the physicochemical quality of surface waters under lettuce and rice cultivation in the city of Daloa (Côte d’Ivoire) using physicochemical parameters and multivariate statistical approaches to identify the main factors influencing water quality and assess the potential impact of agricultural activities on these aquatic environments the major factors affecting water quality.

Study Design: This study was carried out on surface waters from 30 sampling points located in lettuce and rice cultivation areas in the city of Daloa.

Place and Duration of Study: Surface water sampling and physicochemical analyses were carried out from January 2024 to January 2025.

Methodology: The selected sampling points were georeferenced prior to each collection. In situ parameters, including temperature, pH, electrical conductivity, dissolved oxygen, and redox potential, were measured using a calibrated portable multiparameter device. R software was used for descriptive analysis of the data, assessment of factorability through correlation matrix computation, and multivariate analyses, including Principal Component Analysis followed by Hierarchical Ascending Classification

Results: The physicochemical analyses showed spatial variability in water quality parameters across the study area. Temperature, pH, electrical conductivity, dissolved oxygen, and redox potential exhibited marked fluctuations between sites influenced by agricultural activities. Correlation analysis revealed significant relationships among key parameters, indicating strong interdependence of water quality variables. Principal Component Analysis identified the main factors controlling water quality, with the first principal components explaining a substantial proportion of the total variance. Hierarchical Ascending Classification grouped sampling sites into distinct clusters reflecting different levels of anthropogenic influence.

Conclusion: These results emphasize the importance of managing environmental conditions of surface waters under agricultural pressure to ensure the sustainability of lettuce and rice production systems in the city of Daloa.