Assessment and development of optical technology for continuous suspended sediment measurement in aquatic environments

Document Type : Research Article


1 Faculty of Engineering, Payame Noor University, Tehran, Iran

2 Department of Hydraulic Engineering and Hydro-Environment, Water Research Institute, Tehran, Iran

3 Faculty of Natural Resources and Environment, Ferdowsi University of Mashhad, Mashhad, Iran


The monitoring of fluvial suspended sediment transport plays an important role in the assessment of morphological processes, river behavior, identifying erosion and sediment loss zones and better watershed management. In order to eliminate information deficiencies and achieve a suitable database for suspended load, it is necessary to equip hydrometric stations with instruments for continuous and indirect monitoring of suspended sediment. The aim of this research is to construct and validate an optical sensor with a multi-beam ratio technology and artificial intelligence-based modeling (MLP & SVR) for suspended sediment measuring. After the implementation of the new technology, the performance of the device was evaluated in two stages, including calibration and validation. To attain this, various experimental tests were carried out in the hydraulic laboratory of the Water Research Institute of the Ministry of Energy. Reference turbidity meter and total suspended solids (TSS) were used to test the performance of the OBS technology. In the calibration stage, 70% of TSS data were used and the remaining 30% of data were used to validate optical technology. The plotted calibration curves show a very good correlation between the optical voltage recorded by the sensors and the suspended sediment concentration. Also, SVR & MLP models were employed to improve the results of suspended load prediction. The performance of the optical device and also optical device with intelligence models were evaluated through four statistical indices, namely, Mean Absolute Percentage Error (MAPE), Root mean square Error (RMSE), Nash–Sutcliffe coefficient (NSE), correlation coefficient (R) and coefficient of determination (R2). The results of this stage showed that the intelligence modeling could result in improvements in suspended load reported by optical technology. The best improvements were obtained by MLP-optical technology. The results showed that values ​​of validation indicators for MLP model are equal to 0.023, 7.608, 0.99, 0.99 and 0.99, respectively, which indicates the proper performance of the technology.


Main Subjects

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