Prediction of Peak Velocity of Pollutant Transport in Rivers Using Group Method Data Handling (GMDH) and Intelligent Hybrid Method GMDH-HS

Document Type : Research Paper

Authors

1 MSc Student of Water Structure, Department of Water Engineering, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran

2 Assist. Prof., Department of Water Engineering, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran

3 Assoc. Prof., Department of Water Engineering, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran

Abstract

Estimating of the peak velocity of pollutant in a flow using hydraulic and geometrical parameters is very important in predicting the pollution transport in rivers. Suitable empirical equations are developed, none of which is reliable enough in estimating the peak velocity of pollutant before a thorough calibration. So, in this research artificial intelligence methods are used for this purpose. The objective of this research was to predict the peak velocity of pollutant by Group Method Data Handling (GMDH) methods and an intelligent hybrid method (GMDH-HS). The result of these methods were compared to the best regression equation. The dimensionless relative discharge (Q'a), dimensionless drainage area, the ratio of discharge at the section at the time of  measurement to drainage area (Q/Da) and the reached slope (S) were taken as input parameters to these models. These data were collected from several different rivers in the United States. Mackey-Glass standard function was used to evaluate the performance of the GMDH and GMDH-HS models. The results indicated that the proposed models predicted the peak velocity of pollutant precisely (CE GMDH =0.9328, CE GMDH-HS =0.9038 & CE Vp Equation=0.3802) and these models are more accurate compared to the best nonlinear regression equation..

Keywords

Main Subjects

References

Alikhani, K., Qaderi, K. & Ahmadi, M.M. 2012. Predicting the distribution of deposited sediment in Karaj reservoir using various improved harmony search algorithms. Journal of Soil and Water Conservation Research, 21(3), 165-184. (In Persian)
Faramarz, M., Ayubzadeh, S. & Mohammadi, K. 2005. Numerical simulation of distribution and transmission levels of pollution in the river floodplain. The 5th Iranian Hydraulic Conference. Shahid Bahonar University of Kerman, Kerman, Iran. (In Persian)
Harvey, E. & Jobson, H. E. 1996. Prediction of traveltime and longitudinal dispersion in rivers and streams. U.S. Geological Survey Water-Resources Investigations Report 84-4203, USA.
Hoseinzadeh, M., Qaderi, K. & Ahmadi, M. M. 2013. Stage-discharge relationship modeling in the river using intelligent methods (GMDH, NF-GMDH). National Conference Optimization of Water Use, Gorgan, Iran. (In Persian)
Ivakhnenko, A.G. 1968. Group method of data handling-rival of method of stochastic approximation. Sov. Autom. Control, 13(1), 43-55.
Jabson, H. E. 1995. Prediction of traveltime and longitudinal dispersion in rivers and streams. U.S. Geological Survey Open-File Report 71-0096, USA.
Julínek, T. & Říha, M. 2017. Longitudinal dispersion in an open channel determined from a tracer study. Environmental Earth Science, 76:592.http://doi.org/10.1007/s12665-017-6913-1
Razek, M. & Abouelnour, A. 1972. A statistical methodology for predicting pollutants in a river. Water Resources Bulletin, 8(1), 15-23.
Sanchez, E., Shibata T. & Zadeh, L. A. 1997. Genetic algorithms and fuzzy logic systems. World Scientific Publishing Co., Inc. River Edge, N.J., USA.
Sattar, A. M. A. & Gharabaghi, B. 2015. Gene expression models for prediction of longitudinal dispersion coefficient in streams. Journal of Hydrology, 524, 587-596.
Tsai, T. & Yen, T. 2017. GMDH algorithms applied to turbidity forecasting. Appl. Water Sci., 7 (3), 1151-1160.
Wiley, J. B. & Messinger, T. 2013. Estimation of traveltime and longitudinal dispersion in streams in West Virginia, West Virginia Bureau for Public Health, Office of Environmental Health Services, Scientific Investigations Report 2013-5182, Virginia, USA.
ZelenaKov, M., Carnogurska, M. & Gargar, I., 2012. Prediction of pollutant concentration in laborec river station, Slovak Republic. Procedia Engineering, 42, 1474-1473.
Journal of Water and Wastewater; Ab va Fazilab ( in persian )
Volume 30, Issue 1 - Serial Number 119
March and April 2019
Pages 64-76

Files

Share

How to cite

Statistics