The use of optical camera for river turbidity monitoring

Improving river monitoring techniques is critical given the concomitant impact of climate change, population growth, and pollution over the last years. Turbidity is one of the most significant metrics for water quality characteristics. In river basins, high turbidity values can be indicative of both organic and inorganic materials. Turbidity is often used as a proxy for transport of suspended particles and associated fluxes of hydrophobic pollutants in a wide range of hydrological conditions. However, it is demanding to estimate suspended sediment yields in rivers because of the high variability along stream of suspended sediment concentrations. Traditional methods, such as gravimetric analysis, are time-consuming, expensive, often discontinuous in space and time and influenced by human errors or instrumental limitations.

Remote sensing techniques are a suitable alternative to point measurements. Satellite remote sensing allows to study the spatial and temporal variations of water status parameters, but it is limited by the spatial and temporal resolution of the satellites considered. Low range systems can help increase the resolution of the imagery used for this purpose. In particular, the use of optical cameras can significantly reduce the monitoring cost and exponentially increase the information on water bodies health and hydrological dynamics, offering a large amount of data distributed in time and space. Nonetheless, all optical sensing methods are strongly affected by many environmental constraints (light, good optical transmission, visibility, etc.), which make them currently not always suitable for regular long-term monitoring of turbidity in rivers. 

The main goal of the monitoring procedure identified in this work is to avoid all these constraints, by processing the camera image to use it as a real measurement data. In this work, an image processing procedure has been identified by exploiting the water surface reflectance properties to estimate water turbidity spectral indices related to red and green bands of the light visible spectrum (Miglino et al., 2022). This river monitoring system is under development in different cross sections of the Bode River, one of the best-instrumented catchments in Central Germany.managed by UFZ Helmholtz Centre for Environmental Research. They gather a wide range of environmental data including a long-term time series on water quantity and quality. Preliminary results highlighted interesting similarities between the chromatic variation of the water surface captured by the RGB camera and the real data. 

 

Keywords: turbidity, sediment transport, image processing, spectral indices, remote sensing, camera, water quality assessment.

 

References:

Miglino, D., Jomaa, S., Rode, M., Isgro, F., & Manfreda, S. (2022). Monitoring Water Turbidity Using Remote Sensing Techniques. Environmental Sciences Proceedings, 21(1), 63.