Issue |
E3S Web of Conf.
Volume 415, 2023
8th International Conference on Debris Flow Hazard Mitigation (DFHM8)
|
|
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Article Number | 02019 | |
Number of page(s) | 4 | |
Section | Experiments and Modeling | |
DOI | https://doi.org/10.1051/e3sconf/202341502019 | |
Published online | 18 August 2023 |
Testing applicability of image analysis for measurements of sediment concentration in laboratory experiments
1 Master’s Program in Environmental Sciences, University of Tsukuba, Japan
2 Faculty of Life and Environmental Sciences, University of Tsukuba, Japan
* Corresponding author: uchida.taro.fw@u.tsukuba.ac.jp
Flume experiments are typically conducted to reveal the detailed behavior of debris flows. Direct sampling at the lower end of a flume has been used to measure sediment concentrations in flume experiments; however, direct sampling measurements under non-steady or non-equilibrium conditions are difficult. In contrast, image analysis methods can acquire spatiotemporal high-resolution data in a non-contact manner. In this study, we conducted experiments in which a homogenous sediment concentration field of 0 ~ 20 % was prepared in a water tank with a depth of 10 cm using coarse and fine sediments. We filmed the experiments and verified the relationships between sediment concentrations and image features in a fixed area. As a result, the mean of pixel values for coarse sediments depends on the sediment concentration of up to 10 % and the number of mode pixels for fine sediments depends on the sediment concentration of up to 20 %. We then analyzed factors influencing image features and identified three processes. Furthermore, we analyzed the effects of the sediment grain size on image features, and the results show that both the brightness index and brightness uniformity index of images are affected. In conclusion, these findings indicate that image analysis can be used to clarify both sediment concentration and grain size.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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