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

Document Type : Research Article

Authors

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

Abstract

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.

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References

[1] J.E. Cloern, P.C. Abreu, J. Carstensen, L. Chauvaud, R. Elmgren, J. Grall, H. Greening, J.O.R. Johansson, M. Kahru, E.T. Sherwood, Human activities and climate variability drive fast‐paced change across the world's estuarine–coastal ecosystems, Global change biology, 22(2) (2016) 513-529.
[2] C.E. Boyd, Water quality: an introduction, Springer Nature, 2019.
[3] N. Hudson, Soil conservation: fully revised and updated, Soil conservation: fully revised and updated., (Ed. 3) (2015).
[4] M. Lenzi, L. Mao, F. Comiti, Interannual variation of suspended sediment load and sediment yield in an alpine catchment, Hydrological Sciences Journal, 48(6) (2003) 899-915.
[5] R. Hostache, C. Hissler, P. Matgen, C. Guignard, P. Bates, Modelling suspended-sediment propagation and related heavy metal contamination in floodplains: a parameter sensitivity analysis, Hydrology and Earth System Sciences, 18(9) (2014) 3539-3551.
[6] D. Walling, A. Collins, The catchment sediment budget as a management tool, Environmental Science & Policy, 11(2) (2008) 136-143.
[7] H. Burchard, H.M. Schuttelaars, D.K. Ralston, Sediment trapping in estuaries, Annual review of marine science, 10 (2018) 371-395.
[8] T. Sahab, Comprehensive plan for Sistan flood control, Sediment studies in Sistan river, 1992.
[9] T.K. Edwards, G.D. Glysson, H.P. Guy, V.W. Norman, Field methods for measurement of fluvial sediment, US Geological Survey Denver, CO, 1999.
[10] J. McHenry, N. Coleman, J. Willis, C. Murphree, G. Bolton, O. Sansom, A. Gill, Performance of nuclear-sediment concentration gauges, in:  Isotopes in hydrology. Proceedings of a symposium, 1967.
[11] J.R. Gray, J.W. Gartner, Technological advances in suspended‐sediment surrogate monitoring, Water resources research, 45(4) (2009).
[12] A.K. Rai, A. Kumar, Continuous measurement of suspended sediment concentration: Technological advancement and future outlook, Measurement, 76 (2015) 209-227.
[13] D. Wren, B. Barkdoll, R. Kuhnle, R. Derrow, Field techniques for suspended-sediment measurement, Journal of Hydraulic Engineering, 126(2) (2000) 97-104.
[14] O. Navratil, M. Esteves, C. Legout, N. Gratiot, J. Nemery, S. Willmore, T. Grangeon, Global uncertainty analysis of suspended sediment monitoring using turbidimeter in a small mountainous river catchment, Journal of Hydrology, 398(3-4) (2011) 246-259.
[15] S. Bian, Z. Hu, Z. Xue, J. Lv, An observational study of the carrying capacity of suspended sediment during a storm event, Environmental monitoring and assessment, 184(10) (2012) 6037-6044.
[16] G.-W. Lin, H. Chen, D.N. Petley, M.-J. Horng, S.-J. Wu, B. Chuang, Impact of rainstorm-triggered landslides on high turbidity in a mountain reservoir, Engineering Geology, 117(1-2) (2011) 97-103.
[17] K. Schwarz, T. Gocht, P. Grathwohl, Transport of polycyclic aromatic hydrocarbons in highly vulnerable karst systems, Environmental Pollution, 159(1) (2011) 133-139.
[18] M. Haimann, M. Liedermann, L. Petra, H. Habersack, An integrated suspended sediment transport monitoring and analysis concept, International Journal of Sediment Research, 29(2) (2014) 135-148.
[19] J.R. Gray, J. Gartner, Overview of selected surrogate technologies for high-temporal resolution suspended sediment monitoring, in:  Proceedings of the 2nd Joint Federal Interagency Conference, Las Vegas, NV, Citeseer, 2010.
[20] S. Haun, N. Rüther, S. Baranya, M. Guerrero, Comparison of real time suspended sediment transport measurements in river environment by LISST instruments in stationary and moving operation mode, Flow Measurement and Instrumentation, 41 (2015) 10-17.
[21] I. Cáceres, J.M. Alsina, J. van Der Zanden, J.S. Ribberink, A. Sánchez-Arcilla, The effect of air bubbles on optical backscatter sensor measurements under plunging breaking waves, Coastal engineering, 159 (2020) 103721.
[22] P. Ghaffari, J. Azizpour, M. Noranian, V. Chegini, V. Tavakoli, M. Shah-Hosseini, Estimating suspended sediment concentrations using a broadband ADCP in Mahshahr tidal channel, Ocean Science Discussions, 8(4) (2011) 1601-1630.
[23] D. Felix, I. Albayrak, R.M. Boes, Continuous measurement of suspended sediment concentration: Discussion of four techniques, Measurement, 89 (2016) 44-47.
[24] G.H. Merten, P.D. Capel, J.P. Minella, Effects of suspended sediment concentration and grain size on three optical turbidity sensors, Journal of Soils and Sediments, 14(7) (2014) 1235-1241.
[25] S. Miyata, S. Mizugaki, S. Naito, M. Fujita, Application of time domain reflectometry to high suspended sediment concentration measurements: Laboratory validation and preliminary field observations in a steep mountain stream, Journal of Hydrology, 585 (2020) 124747.
[26] Z. Sirabahenda, A. St-Hilaire, S.C. Courtenay, M.R. Van Den Heuvel, Comparison of acoustic to optical backscatter continuous measurements of suspended sediment concentrations and their characterization in an agriculturally impacted river, Water, 11(5) (2019) 981.
[27] A. D7512, Standard guide for monitoring of suspended sediment concentration in open channel flow using optical instrumentation, 2009.
[28] A. D6698, Standard test method for on-line measurement of turbidity below 5 NTU in water, 2014.
[29] EPA, Methods for the Determination of Inorganic Substances in Environmental Samples (EPA/600/R-93/100) in, USEPA (EPA) Office of Water (OW) 1993.
[30] I. 7027, Water quality determination of turbidity in, ISO/TC 147/SC 2 Physical, chemical and biochemical methods, 1999, pp. 10.
[31] Standard Method 2130B, Available from Standard Methods for the Examination of Water and Wastewater, 21st Edition in: , American Public Health Association, Washington, DC, 2005.
[32] M. Buttmann, Suspended solids measurement as reliable process control, in:  Proceedings of ISA TECH EXPO Technology Update Conference, Houston, TX: Instrument Society of America, 2001, pp. 563-572.
[33] H. Yu, S. Kim, SVM Tutorial-Classification, Regression and Ranking, Handbook of Natural computing, 1 (2012) 479-506.
[34] T. Rajaee, H. Ebrahimi, V. Nourani, A review of the artificial intelligence methods in groundwater level modeling, Journal of hydrology, 572 (2019) 336-351.
[35] M. Alizamir, O. Kisi, M. Zounemat-Kermani, Modelling long-term groundwater fluctuations by extreme learning machine using hydro-climatic data, Hydrological sciences journal, 63(1) (2018) 63-73.
[36] S.M.I. Kabir, H. Ahmari, Sediment Color Effects on the Estimation of Suspended Sediment Concentration from Digital Imagery, in:  World Environmental and Water Resources Congress 2020: Emerging and Innovative Technologies and International Perspectives, American Society of Civil Engineers Reston, VA, 2020, pp. 40-50.
[37] Y. Shao, J.P.-Y. Maa, Comparisons of different instruments for measuring suspended cohesive sediment concentrations, Water, 9(12) (2017) 968.
[38] Y.P. Wang, G. Voulgaris, Y. Li, Y. Yang, J. Gao, J. Chen, S. Gao, Sediment resuspension, flocculation, and settling in a macrotidal estuary, Journal of Geophysical Research: Oceans, 118(10) (2013) 5591-5608.
[39] F. Druine, R. Verney, J. Deloffre, J.-P. Lemoine, M. Chapalain, V. Landemaine, R. Lafite, In situ high frequency long term measurements of suspended sediment concentration in turbid estuarine system (Seine Estuary, France): Optical turbidity sensors response to suspended sediment characteristics, Marine Geology, 400 (2018) 24-37.
Amirkabir Journal of Civil Engineering
Volume 54, Issue 5
August 2022
Pages 2051-2064

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