## 4 Discussion  
A previous study [23] predicted turbidity based on color changes in an underwater image that was captured directly (without a specific light-source supply) in a single-case experiment; following this, the direct relationship between turbidity and concentration was used to estimate the suspended-sediment concentration. In the present study, similar results were obtained under constant lighting conditions even when the underwater filming conditions were dynamic. Moreover, the concentration was directly estimated based on color changes, overcoming the limitations associated with the turbidity-concentration relationship. Generally, most turbidity measurement methods utilize scattering rates due to turbid particles; therefore, the obtained results depend on the shapes and sizes of suspended-sediment particles. Additionally, the forms of the equations exert a dominant influence on the indirect methods of concentration estimation based on the turbidity-concentration relationship during the estimation of a section that was not involved in creating the formula. Therefore, the exponent (0.85) of the turbidity-concentration relationship equation proposed in this study was found to be lower than one, and the predicted values were low at high concentrations. In contrast, the underwater-image color change observed in this study was not significantly impacted by the particle size and yielded better predictions compared to the turbidity-concentration relationship. Based on the developed models, the red and green band values could be deemed critical for predicting suspended-sediment concentrations because the models included two of the best band-provided R\({}^{2}\) values between the models with two explanatory variables. These results can be attributed to the following phenomena: The wavelength that can penetrate the deepest in water changes from blue to green because particles tend to mostly absorb blue light, whereas water is known to absorb red light. In addition, coastal waters typically contain mineral or clay particles with a high refractive index, making them very efficient at scattering light [17]. In this study, the underwater-image color was observed to differ under different experimental cases at low concentrations. While the overall range of predicted results demonstrated good predictability, the accuracy of predictions at low concentrations was lower compared to that of the turbidity-concentration  
Figure 7: Suspended-sediment concentration estimated from (**a**) the measured turbidity, (**b**) predicted turbidity, and (**c**) underwater-image color change. relationship. Since coastal regions typically exhibit very low suspended-sediment concentrations, it is recommended to utilize the suggested method in conjunction with existing measurement methods. To enhance predictability at low concentrations, further analysis and experimentation should be conducted. The estimation of sediment concentrations may also be influenced by various filming and image-related conditions, such as lens state and camera performance. The lower predictability at low concentrations suggests the need for improvements in the camera box system to ensure consistent light-source conditions. In future research, the camera box will be redesigned to prevent any refracted light from entering through the water surface, thus maintaining constant lighting conditions. Additionally, a method that considers factors such as contrast and brightness, beyond just the RGB values, will be developed for estimating suspended-sediment concentrations. Moreover, for the application of the proposed method to real estuaries or coastal areas, additional parameters and experiments need to be considered. The experiments conducted in this study were carried out under constant conditions; however, further experiments accounting for different flow conditions and changes in water quality factors such as salinity are necessary. Furthermore, our study solely focused on red clay, and additional research using different types of sand, silt, and clay is warranted.