Reliable and continuous measurement of sediment load in rivers is essential for understanding and managing sediment transport dynamics. However, traditional sediment load monitoring methods depend on labor-intensive field sampling techniques, leading to limitations in spatiotemporal coverage. This study introduces a novel approach for machine learning-aided real-time suspended sediment concentration monitoring using a horizontal acoustic Doppler current profiler. Support vector regression models for suspended sediment concentration estimation are derived from eight flow monitoring stations with sediment sampling data. A new model selection framework is proposed, integrating a global optimization algorithm in order to calibrate input variables and hyperparameters simultaneously. The three-fold cross-validation score is utilized to enhance the generalization accuracy and reliability of sediment load estimation. This work assessed the impact of considering additional input variables in addition to the backscattering signal. The findings confirm that incorporating flowrate, water level, and their time derivatives during model training improves predictability. Spatial differences between flow monitoring and sediment sampling locations significantly influence the model accuracy. This study also discusses the potential application of the H-ADCP-based monitoring system to obtain suspended and total sediment loads at an arbitrary flow monitoring station. By offering real-time monitoring capabilities and reduced reliance on labor-intensive field sampling, this work contributes to the advancement of sediment transport data acquisition methods.

中文翻译：

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基于H-ADCP的全局优化支持向量回归实时泥沙量监测系统及其应用

可靠、连续地测量河流中的沉积物负荷对于了解和管理沉积物输送动态至关重要。然而，传统的泥沙负荷监测方法依赖于劳动密集型的现场采样技术，导致时空覆盖范围受到限制。本研究介绍了一种使用水平声多普勒电流剖面仪进行机器学习辅助实时悬浮沉积物浓度监测的新方法。悬浮泥沙浓度估算的支持向量回归模型源自八个流量监测站的泥沙采样数据。提出了一种新的模型选择框架，集成了全局优化算法，以便同时校准输入变量和超参数。利用三重交叉验证分数来提高泥沙负荷估算的泛化精度和可靠性。这项工作评估了除了反向散射信号之外考虑其他输入变量的影响。研究结果证实，在模型训练过程中结合流量、水位及其时间导数可以提高可预测性。流量监测和沉积物采样位置之间的空间差异显着影响模型的准确性。本研究还讨论了基于 H-ADCP 的监测系统在任意流量监测站获取悬浮泥沙量和总泥沙量的潜在应用。通过提供实时监测功能并减少对劳动密集型现场采样的依赖，这项工作有助于沉积物输送数据采集方法的进步。