Evaluation and Validation of Estimated Sediment Yield and Transport Model Developed with Model Tree Technique

Prediction of Suspended Sediment Concentration Based on the Turbidity-Concentration Relationship Determined via Underwater Image Analysis

Sediment measurement data are essential for sediment transport analysis and therefore highly important in overall river planning. Extant sediment measurement methods consume considerable manpower and time and are limited by factors including economic reasons and worker risks. This study primarily aimed to predict the changes in SSC (Suspended Sediment Concentration) and turbidity by examining the change in color in underwater images. While maintaining a constant flow in a channel, the turbidity and concentration were measured under different SSC. Multiple regression models were developed using turbidity measurement results, and they exhibited high explanatory powers (adjusted R2 > 0.91). Furthermore, upon verification using the verification dataset of the experimental results, an excellent predictive power (RMSE ≈ 0.4 NTU) was demonstrated. The model with the highest predictive power, which was inclusive of red and green bands and showed no underlying multicollinearity was used to predict turbidity. Finally, the turbidity and suspended sediment concentration relationship determined from the experimental results was used to estimate the sediment concentration from the color changes in the underwater images. The concentrations that were predicted by the model showed satisfactory results, compared to the measurements (RMSE ≈ 21 ppm). This study indicated the feasibility of continuous SSC monitoring using underwater images as a new measurement method.

Expanding the Sediment Transport Tracking Possibilities in a River Basin through the Development of a Digital Platform—DNS/SWAT

Simulation of stochastic and variable sediment transport processes within models still poses a big challenge, especially in mountainous areas. Since sediment transport, including erosion and deposition, remains an unceasing problem in many areas, sediment modeling is perceived as a possible solution. This article combines a review of the selected sediment models with a presentation of the effects of several years of research using the DNS digital platform in the Western Carpathians. The review focuses on the main advantages and gaps in selected modeling tools with particular emphasis on one of the most popular: SWAT. The description of the digital platform—DNS is an example of how to answer these gaps by combining subsequent models, methods, and databases using their best features. To accentuate the benefits of such an approach, the effects of combining subsequent models (AdH/PTM) and methods (fingerprinting) on a common digital DNS space are presented, on the example of the Raba River (basin). In this way, both unique possibilities of estimating the amount of contamination carried with sediment particles and their sources, as well as sequencing of sedimentation in the reservoir, taking into account its subsequent zones, were obtained.