Article Details

Abstract

In order to improve the accuracy and adaptability of online measurement of suspended sediment concentration in complex water environments using light absorption method, this paper systematically studies the influence of multiple environmental factors such as temperature, flow velocity, and sensor depth on the output characteristics of transmissive photoelectric sensors, and proposes a multivariate linear compensation model. Firstly, the impact mechanism of various factors on sensor output is quantitatively analyzed through controlled variable experiments, confirming a good linear correlation between sediment concentration, temperature, flow velocity, and sensor output. On this basis, multiple linear regression method is introduced to construct a sediment concentration compensation model based on multi-factor coupling. The experimental results show that the proposed model significantly improves measurement accuracy, with an average relative error reduced from 10.63% to 5.52%, which is superior to single factor correction and some machine learning models. Research has shown that the multivariate linear compensation model can effectively suppress environmental interference and provide a feasible technical solution for online high-precision monitoring of suspended sediment concentration.

Keywords

suspended sediment concentration; light absorption method; online measurement; environmental influence; error analysis

References

1. [1] Wang Chi, Huo Xiaoyan Research on ultra-low sediment concentration measurement technology based on photoelectric method [C]//The 10th National Symposium on Basic Theoretical Research of Sediments Wuhan: Nanjing Institute of Water Resources Science, 2017: 849-852
2. [2] Yang Huadong, Zhu Hao, Wang Zichao, etc Research on online monitoring technology for sediment concentration in water based on transmission spectroscopy [J]. Spectroscopy and Spectral Analysis, 2022, 42 (12): 3817-3822
3. [3] Zeng Rui, Wei Lixin, Wan Sicheng, etc Online monitoring of sediment in tidal river sections based on optical turbidity meter [J]. Water Resources and Hydropower Express, 2024, 45 (S2): 4-8
4. [4] Zheng Yuhang Analysis of the applicability of OBS-3A turbidity meter in the determination line of sediment concentration ratio in Liaohe River [J]. Water Conservancy Technical Supervision, 2024 (11): 39-42, 78
5. [5] Wang Nimin, Hong Meiling, Dan Shuai, etc Research progress on runoff and sediment monitoring methods [J]. Subtropical Soil and Water Conservation, 2023, 35 (2): 21-24, 30
6. [6] Andualem G T，Hewa A G，Myers R B，et al. Predicting Suspended Sediment Transport in Urbanised Streams: A Case Study of Dry Creek, South Australia [J].Hydrology，2024，11（11）：196-196.
7. [7] Xu D F，Sun Y N，Chen W L，et al. Development and Experimental Study of an Experimental Setup for an Online Vibrating Tube Liquid Densitometer [J/OL].Applied Sciences，2024，14（21）：9905.https://doi.org/10.3390/app14219905.
8. [8] Chen H G，Pan J，Xie D L，et al. A Portable Device for On-Site Measurement of Sediment Concentration by Vibrating Tube Method [EB/OL].[2025-11-28].https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4987340.
9. [9] Liu Mingtang, Qin Zening, Qi Huiqin, etc Research on the Optimal Fusion Model of Kalman GORBF Multi source Data for Suspended Sediment Concentration Detection [J]. Chinese Journal of Applied Basic and Engineering Sciences, 2020, 28 (3): 680-690
10. [10] Lei Tingwu, Zhao Jun, Yuan Jianping, etc Measurement of runoff sediment concentration using gamma ray transmission method and its algorithm [J]. Journal of Agricultural Engineering, 2002 (1): 18-21, 13
11. [11] Li Degui, Zhang Guanghai, Ye Fan, etc Development of Isotope Sand Analyzer Based on C8051F350 Microcontroller [J]. Electronic Products World, 2017, 24 (8): 61-64
12. [12] Francisco P，Rodrigo M. Acoustic Backscatter and Attenuation of A Flocculated Cohesive Sediment Suspension [J].Continental Shelf Research，2022，240.
13. [13] Livsey N D，Turner R D R ，Grace R P .Combining Optical and Acoustic Backscatter Measurements for Monitoring of Fine Suspended‐Sediment Concentration Under Changes in Particle Size and Density [J/OL].Water Resources Research，2023，59（8）：e2022WR033982.https://doi.org/10.1029/2022WR033982.
14. [14] Zhen K，Yang W J，Lin H L，et al. Research on sediment Concentration Measurement Based on Multi-frequency Ultrasonic Signal Response [J/OL].Measurement，2023，208：112485.https://doi.org/10.1016/j.measurement.2023.112485.
15. [15] Cheng Chong Research on the distribution characteristics of suspended sediment based on oscillation grid experiment and clustering image recognition algorithm [D]. Xi'an: Xi'an University of Technology, 2023
16. [16] Nookala R S，Duan G J，Qi K，et al. Quantification of Suspended Sediment Concentration Using Laboratory Experimental Data and Machine Learning Model [J].Water，2025，17（15）：2301-2301.
17. [17] Song G X，Jiang Y J，Lei X Y，et al. Measurement of Suspended Sediment Concentration at the Outlet of the Yellow River Canyon: Using Sentinel-2 Images and Machine Learning [J].Remote Sensing，2025，17（14）：2424-2424.
18. [18] Deng Luosheng, Che Guolin, Jin Jianhui Measurement of suspended sediment concentration based on Kalman LSTM model [J]. Journal of Electronic Measurement and Instrumentation, 2023, 37 (5): 163-170
19. [19] Deng Luosheng Research on sediment concentration measurement method based on data fusion [D]. Kunming: Kunming University of Science and Technology, 2023
20. [20] Wang Y W，Peng Y，Du Z Y，et al. Calibrations of Suspended Sediment Concentrations in High-Turbidity Waters Using Different In Situ Optical Instruments [J].Water，2020，12（11）：3296-3296.
21. [21] Hou Y Z，Xing Q G，Zheng X Y，et al. Monitoring Suspended Sediment Concentration in the Yellow River Estuary and Its Vicinity Waters on the Basis of SDGSAT-1 Multispectral Imager [J].Water，2023，15（19）：3522.
22. [22] Wang Dandan Application analysis of OBS-3A turbidity meter in sediment concentration measurement of sandy rivers in Fuxin area [J]. Heilongjiang Water Conservancy Science and Technology, 2021, 49 (1): 153-155
23. [23] Pan Renhong Research and Application of Sand Concentration Relationship Model in Guangxi River OBS Turbidity Meter Online Monitoring System [J]. Guangxi Water Resources and Hydropower, 2021 (6): 57-61, 67
24. [24] Li Xinyue, Zhou Shaoyang, Zeng Rui Application of real-time sediment online monitoring system based on photoelectric sand analyzer [J]. Jiangsu Water Resources, 2024 (10): 32-35

Funding

Major Science and Technology Project of the Ministry of Water Resources (SKS-2022142); Guiding Plan for Key Scientific Research Projects of Higher Education Institutions in Henan Province in 2025 (25B510010); Open Fund Project of Key Laboratory of Yellow River Downstream Channel and Estuary Management, Ministry of Water Resources (2025007)

About the authors

Liu Mingtang (1974-), male, Han nationality, from Xinyang, Henan Province, professor, doctoral student, research direction: water conservancy information technology; Lei Shuo (2001-), male, Han ethnicity, from Puyang, Henan Province, currently pursuing a master's degree in sediment monitoring and compensation; Li Shihao (2001-), male, Han ethnicity, from Zhoukou, Henan Province, master's student, research direction: ultrasonic sediment concentration measurement; Wu Shanshan (2000-), female, Han ethnicity, from Xinyang, Henan Province, is currently pursuing a master's degree in knowledge graph; Miao Jiahao (2001-), male, Han ethnicity, from Jiyuan, Henan Province, is currently pursuing a master's degree. His research focuses on measuring the flow velocity of sediment laden water bodies; Yang Quan (2001-), male, Han ethnicity, from Nanyang, Henan Province, is currently pursuing a master's degree in image processing of sediment laden water bodies.