Advancing Water Quality Monitoring and Mapping: Calibration and Validation of the HydroColor and Citclops Smartphone Applications

Water quality monitoring and mapping is crucial for protecting ecosystems and human health, and it has become increasingly significant as societies worldwide prioritize environmental awareness and sustainable practices. This study focuses on advancing water quality monitoring by evaluating the performance of two smartphone applications (APPs) (HydroColor and Citclops, now EyeOnWater), in estimating key parameters such as turbidity, the concentration of suspended particulate matter ([SPM]), and color. Methodologies included field testing and comparing the water quality parameters estimated from smartphone images with those obtained using laboratory and hyperspectral sensors to assess their reliability and accuracy. As a measure of transparency to assess the water types that were used for the studies, colour saturation and dominant wavelength were determined to range from 0.08 to 0.73 and 497 to 582 respectively. The findings of the APPs revealed varying degrees of accuracy, with HydroColor achieving R2 value of 0.36 and RMSE of 4.13 for turbidity and R2 value of 0.83 and RMSE of 3.44 for SPM. Also, the Citclops attained an R2 value of 0.7 and RMSE of 1.32 for color estimation. Additionally, the study highlighted limitations in both APPs, particularly regarding their applicability across different water systems. These insights emphasize the need for proper calibration and validation procedures for smartphone-based water quality monitoring APPs. In conclusion, the study underscores the growing significance of these APPs in enabling accessible, real-time water quality monitoring and their potential to revolutionize environmental monitoring practices through citizen science. By leveraging the potential of smartphone technology, we can achieve more comprehensive and sustainable management of water resources, ultimately benefiting both ecosystems and human communities. Ultimately, this research contributes to advancing smartphone-based monitoring initiatives, informing decision-making in environmental management, and enhancing our understanding of water quality dynamics in diverse environments.