An optical sensor for in-stream monitoring of suspended sediment concentration

Abstract

Suspended sediment concentration (SSC) in water is one of the most important parameters to evaluate water quality. Monitoring SSC provides important information on determining sediment transport for soil erosion research and soil/water conservation practices. Sediment mass transported at a given time can be assessed by simultaneous SSC and water flow velocity measurements. Fouling, including bio-fouling, has damaging impact on optical SSC measurements over the long term. In this study, an inexpensive, real-time, self-cleaning, optical sediment and flow velocity sensor was developed. Laboratory experiments were conducted on a previously designed SSC sensor. A light modulation algorithm was designed to reduce the influence of ambient light, especially sunlight, on measurement accuracy. Statistical models to predict SSC based on measured light intensities were established and compared with neural network models. The statistical analysis showed that soil texture played an important role in SSC measurement accuracy while the designed sensor was capable of reducing the effect of water color on sensor performance. Neural-network models can further remove the influence of soil texture type on SSC measurement. The sensor design was simplified based on a stepwise selection analysis. Long-term field experiments were conducted in Kansas and Georgia to evaluate the sensor performance, the effect of fouling, including bio-fouling, on sensor lenses, and the effect of temperature on the measurement. Methods of removing the fouling effect through data correction were developed. Results indicated that the designed optical SSC sensor was capable of providing rapid response to SSC fluctuations in water flow. Temperature of the water body has an insignificant impact on SSC measurement. In order to reduce fouling, an air-blast cleaning mechanism was integrated into the optical sediment sensor. Laboratory experiments in a manually created fouling environment were conducted to observe the fouling process on sensor cases made of different materials, and to verify the effectiveness of air-blast cleaning in reducing fouling. Results indicated that air-blast cleaning mechanism was capable of reducing clay/silt fouling on sensor signals. The duration and frequency of air-blast cleaning can be determined and adjusted depending on actual field conditions. An air pressure drop test was conducted on the hose carrying pressurized air. Results showed negligible pressure drop.A flow velocity measurement function based on the cross-correlation principle was integrated into the optical sediment sensor. An experiment was conducted in laboratory to examine the sensor performance on velocity measurement using a closed circulation system. A solution of blue colorant, Brilliant Blue FCF, was used as an artificial source to absorb light emitted by LEDs in the sensor and the signal variation patterns were measured. The results indicated that the cross-correlation-based velocity sensor was capable of measuring water flow velocity within in a certain velocity range using the dye injection method.